https://reunir.unir.net/handle/123456789/11901 2024-11-07T08:51:49Z 2024-11-07T08:51:49Z González-Crespo, Rubén https://reunir.unir.net/handle/123456789/12418 2022-02-09T10:46:34Z

IJIMAI Editor's Note - Vol. 5 Issue 3 - 10th Anniversary González-Crespo, Rubén The International Journal of Interactive Multimedia and Artificial Intelligence - IJIMAI (ISSN 1989 - 1660) provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances on AI tools or tools that use AI with interactive multimedia techniques. This was the first phrase that appeared into the website of the journal, whose launching had several motivations. First, IJIMAI was established on December 2008 in response to several agents, such as students, teachers, researchers, primarily in Spain and Colombia, who wanted to increase the impact of science in their environment. Second, IJIMAI was established to increase the number of scientific journals developed in Spain into the scope of Artificial Intelligence and Interactive Multimedia; there are very few journals about these topics in our country. Third, since the beginning we believed into an open access project, open for the whole stakeholders. Currently no money is needed to public a contribution in IJIMAI, and no money is needed to read all papers in IJIMAI as well; science should be open to achieve the maximum dissemination of knowledge. Finally, IJIMAI was established with the hope of being a long-term project; this 10th anniversary allows us to affirm that this goal is getting closer. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-09T10:46:34Z No. of bitstreams: 1 ijimai_5_3_0_pdf_26965.pdf: 596339 bytes, checksum: 25d97b9795c2fd2fe53032acc8a94a73 (MD5); Made available in DSpace on 2022-02-09T10:46:34Z (GMT). No. of bitstreams: 1 ijimai_5_3_0_pdf_26965.pdf: 596339 bytes, checksum: 25d97b9795c2fd2fe53032acc8a94a73 (MD5)

Mochón, Francisco https://reunir.unir.net/handle/123456789/12417 2022-02-09T10:43:03Z

Happiness and Technology: Special Consideration of Digital Technology and Internet Mochón, Francisco This research paper can be considered a survey about the impact of technology in happiness. The article points out that the scientific approach of happiness states that happiness can be measured and explanatory factors of well-being must be searched empirically. The analysis of technology impact on happiness starts with the opinion of philosophers and social thinkers, and then focus on the revision of empirical research works. The paper concludes highlighting that technology, being the motor of economic well-being, has positive and negative effects on the subjective well-being of individuals. Therefore it is essential to undertake an adequate regulation that promotes positive effects and mitigates the possible harm. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-09T10:43:03Z No. of bitstreams: 1 ijimai_5_3_17_pdf_20180.pdf: 338634 bytes, checksum: 88e818f346a2150a5f65465f1458f6c6 (MD5); Made available in DSpace on 2022-02-09T10:43:03Z (GMT). No. of bitstreams: 1 ijimai_5_3_17_pdf_20180.pdf: 338634 bytes, checksum: 88e818f346a2150a5f65465f1458f6c6 (MD5)

Siirtola, Pekka Röning, Juha https://reunir.unir.net/handle/123456789/12416 2022-02-09T09:41:13Z

Revisiting “Recognizing Human Activities User- Independently on Smartphones Based on Accelerometer Data” – What Has Happened Since 2012? Siirtola, Pekka; Röning, Juha Our article “Recognizing human activities user-independently on smartphones based on accelerometer data” was published in the International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) in 2012. In 2018, it was selected as the most outstanding article published in the 10 years of IJIMAI life. To celebrate the 10th anniversary of IJIMAI, in this article we will introduce what has happened in the field of human activity recognition and wearable sensor-based recognition since 2012, and especially, this article concentrates on introducing our work since 2012. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-09T09:41:13Z No. of bitstreams: 1 ijimai_5_3_2_pdf_84569.pdf: 328418 bytes, checksum: a2a55465ccb2a7260218d5aa73016f97 (MD5); Made available in DSpace on 2022-02-09T09:41:13Z (GMT). No. of bitstreams: 1 ijimai_5_3_2_pdf_84569.pdf: 328418 bytes, checksum: a2a55465ccb2a7260218d5aa73016f97 (MD5)

Herrera-Viedma, Enrique Baier-Fuentes, Hugo Cascón-Katchadourian, Jesús Merigó, José Martínez, M A https://reunir.unir.net/handle/123456789/12415 2022-02-09T09:36:10Z

A Bibliometric Overview of the International Journal of Interactive Multimedia and Artificial Intelligence Herrera-Viedma, Enrique; Baier-Fuentes, Hugo; Cascón-Katchadourian, Jesús; Merigó, José; Martínez, M A The International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) published its first issue ten years ago. Currently, IJIMAI is indexed in the important database Emerging Sources Citation Index. This paper aims to identify, through a mapping of science, those most relevant aspects of the structure of publications made during the first 10 years of IJIMAI. Using VOSviewer software, the structural maps of the IJIMAI publications are analysed according to techniques such as bibliographic coupling, co-citations and cooccurrence of keywords. In addition, the evolution of the publications, citations and an analysis of the most cited papers of the journal are presented. The results show that IJIMAI has experienced a remarkable growth of both publications and citations in the last five years. We also observe that IJIMAI does not only capture the attention of the Spanish scientific community, but also of emerging countries such as India and Iran and emerging Latin American countries such as Colombia. With a such increasing behaviour, it is expected in the coming years that IJIMAI will position itself among the best journals with similar scientific scope. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-09T09:36:10Z No. of bitstreams: 1 ijimai_5_3_1_pdf_85989.pdf: 1061000 bytes, checksum: 2c17bdcc203f05d2e3abe995878dd013 (MD5); Made available in DSpace on 2022-02-09T09:36:10Z (GMT). No. of bitstreams: 1 ijimai_5_3_1_pdf_85989.pdf: 1061000 bytes, checksum: 2c17bdcc203f05d2e3abe995878dd013 (MD5)

Saez, Yago Mochón, Asunción Rada, Fernando https://reunir.unir.net/handle/123456789/12414 2022-02-09T09:18:20Z

TV Series and Social Media: Powerful Engagement Factors in Mobile Video Games Saez, Yago; Mochón, Asunción; Rada, Fernando The free-to-play business model has become hegemonic in the mobile video game industry, displacing the traditional paid content model that was the norm until the appearance of manufacturers’ app stores. Companies attempt to monetize these games by means of in-game micro-transactions and in-game advertising; thus, it is essential to acquire an enormous number of users because only a small percentage will ultimately make any purchases. To keep players engaged, companies typically put in place marketing and design strategies derived from behavioral telemetry, to maintain a grip on players. We propose an innovative approach, focusing our attention on the impact of having a video game based on a famous TV series. Furthermore, we analyze the effect of social networks on game metrics. The outcome indicates that developing a game based on a TV series and integrating social media with the gameplay improve and reinforce the user’s activation, retention and monetization. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-09T09:18:20Z No. of bitstreams: 1 ijimai_5_3_5_pdf_14724.pdf: 1297779 bytes, checksum: cad83f8812d4beeeea0d7e9933cbc79f (MD5); Made available in DSpace on 2022-02-09T09:18:20Z (GMT). No. of bitstreams: 1 ijimai_5_3_5_pdf_14724.pdf: 1297779 bytes, checksum: cad83f8812d4beeeea0d7e9933cbc79f (MD5)

Ahmed, Walaa Selim, Ali Kamel, Salah Yu, Juan Jurado, Francisco https://reunir.unir.net/handle/123456789/12412 2022-02-08T12:40:16Z

Probabilistic Load Flow Solution Considering Optimal Allocation of SVC in Radial Distribution System Ahmed, Walaa; Selim, Ali; Kamel, Salah; Yu, Juan; Jurado, Francisco This paper proposes a solution procedure for probabilistic load flow problem considering the optimal allocation of Static Var Compensator (SVC) in radial distribution systems. Pareto Envelope-based Selection Algorithm II (PESA-II) with fuzzy logic decision maker is developed to determine the optimal location and size of SVC based on the minimum total power losses and Voltage Deviation (VD). Combined cumulants and gram-chalier expansion are used for solving the probabilistic load flow problem. The proposed algorithm is tested on 33-bus and 69-bus distribution systems. The developed algorithm gives an acceptable solution with low number of iterations and less computation cost compared with the Monte Carlo method. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-08T12:40:16Z No. of bitstreams: 1 ijimai_5_3_16_pdf_17977.pdf: 3057266 bytes, checksum: 8c56d7eb3ab2aaed0fe88cfab17ff4d6 (MD5); Made available in DSpace on 2022-02-08T12:40:16Z (GMT). No. of bitstreams: 1 ijimai_5_3_16_pdf_17977.pdf: 3057266 bytes, checksum: 8c56d7eb3ab2aaed0fe88cfab17ff4d6 (MD5)

Montenegro-Marin, Carlos Enrique Gaona-García, Paulo Alonso Gaona-García, Elvis Gómez-Acosta, Adriana Hassan-Montero, Yusef https://reunir.unir.net/handle/123456789/12411 2022-02-08T12:06:20Z

Issues of Visual Search Methods in Digital Repositories Montenegro-Marin, Carlos Enrique; Gaona-García, Paulo Alonso; Gaona-García, Elvis; Gómez-Acosta, Adriana; Hassan-Montero, Yusef Repositories are important infrastructures which allow the dissemination of large collections of digital resources hosted in museums, libraries, academic institutions or specialized documentation centers. However, there are nowadays several limitations associated with irrelevant search results based on a knowledge area. Some studies have highlighted the major role of information visualization strategies based on Simple Knowledge Organization Systems (SKOS) so as to mitigate such difficulties. The main goal of this article is to present recommendations using information visualization based on SKOS for the development of navigational search interfaces in digital repositories focused on learning process. We use card sorting as methodology in order to obtain qualitative results in our study. As preliminary results we found that taxonomies in visual search engines improve the access to large collections of digital resources based on SKOS, but it depends on the design of taxonomy concepts defined in digital repositories. Finally, it is recommended that the creators of repositories focus their efforts on define levels of relationship and partnership between digital resources using knowledge representation structures like thesauri or ontologies; work with usable visualization interfaces like tree, radial or icicle; and link relevant metadata fields with the navigation structure. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-08T12:06:20Z No. of bitstreams: 1 ijimai_5_3_10_pdf_37318.pdf: 674709 bytes, checksum: 1b9ac59164b0d5f68754361767d2d031 (MD5); Made available in DSpace on 2022-02-08T12:06:20Z (GMT). No. of bitstreams: 1 ijimai_5_3_10_pdf_37318.pdf: 674709 bytes, checksum: 1b9ac59164b0d5f68754361767d2d031 (MD5)

Dehkharghani, Rahim https://reunir.unir.net/handle/123456789/12410 2022-02-08T11:54:17Z

Building Phrase Polarity Lexicons for Sentiment Analysis Dehkharghani, Rahim Many approaches to sentiment analysis benefit from polarity lexicons. Most polarity lexicons include a list of polar (positive/negative) words, and sentiment analysis systems attempt to capture the occurrence of those words in text using polarity lexicons. Although there exist some polarity lexicons in many natural languages, most languages suffer from the lack of phrase polarity lexicons. Phrases play an important role in sentiment analysis because the polarity of a phrase cannot always be estimated based on the polarity of its parts. In this work, a hybrid approach is proposed for building phrase polarity lexicons which is experimented on Turkish as a low-resource language. The obtained classification accuracies in extracting and classifying phrases as positive, negative, or neutral, approve the effectiveness of the proposed methodology. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-08T11:54:17Z No. of bitstreams: 1 ijimai_5_3_11_pdf_18912.pdf: 485408 bytes, checksum: b1fbd19c77ee48985d4581e5deb4f0a5 (MD5); Made available in DSpace on 2022-02-08T11:54:17Z (GMT). No. of bitstreams: 1 ijimai_5_3_11_pdf_18912.pdf: 485408 bytes, checksum: b1fbd19c77ee48985d4581e5deb4f0a5 (MD5)

Mack, Stephen https://reunir.unir.net/handle/123456789/12409 2022-02-08T11:47:34Z

Removing Unclassified Hand Tremor Motion from Computer Mouse Input with Neural Networks Mack, Stephen An artificial neural network based filter to remove unwanted tremor-induced motion in computer mouse input is presented and tested. A method to efficiently capture appropriate training data is shown to be important in the operation and training of the neural network filter. The architecture of the neural network as well as the numerous design choices are presented and explained. A simulation study proves the artificial neural network is successful at removing a simulated Parkinson’s tremor from computer mouse movements even with minimal training data. Resulting tremor-free motion estimated by the artificial neural network is shown to be similar to normal tremor free computer mouse movements. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-08T11:47:34Z No. of bitstreams: 1 ijimai_5_3_6_pdf_59445.pdf: 684059 bytes, checksum: c2a118308d8a9c0ba653511a2c51e4a4 (MD5); Made available in DSpace on 2022-02-08T11:47:34Z (GMT). No. of bitstreams: 1 ijimai_5_3_6_pdf_59445.pdf: 684059 bytes, checksum: c2a118308d8a9c0ba653511a2c51e4a4 (MD5)

Padilla, Victor Conklin, Darrell https://reunir.unir.net/handle/123456789/12408 2022-02-08T09:57:27Z

Generation of Two-Voice Imitative Counterpoint from Statistical Models Padilla, Victor; Conklin, Darrell Generating new music based on rules of counterpoint has been deeply studied in music informatics. In this article, we try to go further, exploring a method for generating new music based on the style of Palestrina, based on combining statistical generation and pattern discovery. A template piece is used for pattern discovery, and the patterns are selected and organized according to a probabilistic distribution, using horizontal viewpoints to describe melodic properties of events. Once the template is covered with patterns, two-voice counterpoint in a florid style is generated into those patterns using a first-order Markov model. The template method solves the problem of coherence and imitation never addressed before in previous research in counterpoint music generation. For constructing the Markov model, vertical slices of pitch and rhythm are compiled over a large corpus of dyads from Palestrina masses. The template enforces different restrictions that filter the possible paths through the generation process. A double backtracking algorithm is implemented to handle cases where no solutions are found at some point within a generation path. Results are evaluated by both information content and listener evaluation, and the paper concludes with a proposed relationship between musical quality and information content. Part of this research has been presented at SMC 2016 in Hamburg, Germany. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-08T09:57:27Z No. of bitstreams: 1 ijimai_5_3_3_pdf_45204.pdf: 1410400 bytes, checksum: a0040082304e458d158f5b9e8ca4d839 (MD5); Made available in DSpace on 2022-02-08T09:57:27Z (GMT). No. of bitstreams: 1 ijimai_5_3_3_pdf_45204.pdf: 1410400 bytes, checksum: a0040082304e458d158f5b9e8ca4d839 (MD5)

Arun, Vanishri Krishna, Murali Arunkumar, B V Padma, S K Shyam https://reunir.unir.net/handle/123456789/12407 2022-02-08T09:49:26Z

Exploratory Boosted Feature Selection and Neural Network Framework for Depression Classification Arun, Vanishri; Krishna, Murali; Arunkumar, B V; Padma, S K; Shyam Depression is a burdensome psychiatric disease common in low and middle income countries causing disability, morbidity and mortality in late life. In this study, we demonstrate a novel approach for detection of depression using clinical data obtained from the on-going Mysore Studies of Natal effects on Ageing and Health (MYNAH), in South India where the members have undergone a comprehensive assessment for cognitive function, mental health and cardiometabolic disorders. The proposed model is developed using machine learning approach for classification of depression using Meta-Cognitive Neural Network (McNN) classifier with Projection-based learning (PBL) to address the self-regulating principles like how, what and when to learn. XGBoost is used for feature selection on the available data of assessments with improved confidence. To improve the efficiency of McNN-PBL classifier the best parameters are found using Particle Swarm Optimization (PSO) algorithm. The results indicate that the McNNPBL classifier selects appropriate records to learn and remove repetitive records which improve the generalization performance. The study helps the clinician to identify the best parameters to analyze the patient. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-08T09:49:25Z No. of bitstreams: 1 ijimai_5_3_7_pdf_21185.pdf: 1282461 bytes, checksum: ffe57e53c76199c50e41d46785f307dd (MD5); Made available in DSpace on 2022-02-08T09:49:25Z (GMT). No. of bitstreams: 1 ijimai_5_3_7_pdf_21185.pdf: 1282461 bytes, checksum: ffe57e53c76199c50e41d46785f307dd (MD5)

Ullah, S Raees, M https://reunir.unir.net/handle/123456789/12406 2022-02-07T12:47:53Z

EVEN-VE: Eyes Visibility Based Egocentric Navigation for Virtual Environments Ullah, S; Raees, M Navigation is one of the 3D interactions often needed to interact with a synthetic world. The latest advancements in image processing have made possible gesture based interaction with a virtual world. However, the speed with which a 3D virtual world responds to a user’s gesture is far greater than posing of the gesture itself. To incorporate faster and natural postures in the realm of Virtual Environment (VE), this paper presents a novel eyes-based interaction technique for navigation and panning. Dynamic wavering and positioning of eyes are deemed as interaction instructions by the system. The opening of eyes preceded by closing for a distinct time-threshold, activates forward or backward navigation. Supporting 2-Degree of Freedom head’s gestures (Rolling and Pitching) panning is performed over the xy-plane. The proposed technique was implemented in a case-study project; EWI (Eyes Wavering based Interaction). With EWI, real time detection and tracking of eyes are performed by the libraries of OpenCV at the backend. To interactively follow trajectory of both the eyes, dynamic mapping is performed in OpenGL. The technique was evaluated in two separate sessions by a total of 28 users to assess accuracy, speed and suitability of the system in Virtual Reality (VR). Using an ordinary camera, an average accuracy of 91% was achieved. However, assessment made by using a high quality camera testified that accuracy of the system could be raised to a higher level besides increase in navigation speed. Results of the unbiased statistical evaluations suggest/demonstrate applicability of the system in the emerging domains of virtual and augmented realities. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-07T12:47:53Z No. of bitstreams: 1 ijimai_5_3_15_pdf_15422.pdf: 2933417 bytes, checksum: f84208a4e51cfc13b5d6ad91bff34889 (MD5); Made available in DSpace on 2022-02-07T12:47:53Z (GMT). No. of bitstreams: 1 ijimai_5_3_15_pdf_15422.pdf: 2933417 bytes, checksum: f84208a4e51cfc13b5d6ad91bff34889 (MD5)

Ayachi, R Bouhani, H Amor, Ben https://reunir.unir.net/handle/123456789/12405 2022-02-07T12:32:12Z

An Evolutionary Approach for Learning Opponent's Deadline and Reserve Points in Multi-Issue Negotiation Ayachi, R; Bouhani, H; Amor, Ben The efficiency of automated multi-issue negotiation depends on the available information about the opponent. In a competitive negotiation environment, agents do not reveal their parameters to their opponents in order to avoid exploitation. Several researchers have argued that an agent's optimal strategy can be determined using the opponent's deadline and reserve points. In this paper, we propose a new learning agent, so-called Evolutionary Learning Agent (ELA), able to estimate its opponent's deadline and reserve points in bilateral multi-issue negotiation based on opponent's counter-offers (without any additional extra information). ELA reduces the learning problem to a system of non-linear equations and uses an evolutionary algorithm based on the elitism aspect to solve it. Experimental study shows that our learning agent outperforms others agents by improving its outcome in term of average and joint utility. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-07T12:32:12Z No. of bitstreams: 1 ijimai_5_3_14_pdf_17519.pdf: 3829818 bytes, checksum: 715108699f04338d7f5a1c69bd265bb0 (MD5); Made available in DSpace on 2022-02-07T12:32:12Z (GMT). No. of bitstreams: 1 ijimai_5_3_14_pdf_17519.pdf: 3829818 bytes, checksum: 715108699f04338d7f5a1c69bd265bb0 (MD5)

Taghezout, Noria Benkaddour, Fatima Zohra Kaddour-Ahmed, Fatima Zahra Hammadi, Ilyes-Ahmed https://reunir.unir.net/handle/123456789/12404 2022-02-07T12:14:44Z

An Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis Taghezout, Noria; Benkaddour, Fatima Zohra; Kaddour-Ahmed, Fatima Zahra; Hammadi, Ilyes-Ahmed In this paper, we propose a global architecture of a recommender tool, which represents a part of an existing collaborative platform. This tool provides diagnostic documents for industrial operators. The recommendation process considered here is composed of three steps: Collecting and filtering information; Prediction or recommendation step; evaluating and improvement. In this work, we focus on collecting and filtering step. We mainly use information result from collaborative sessions and documents describing solutions that are attributed to the complex diagnostic problems. The developed tool is based on collaborative filtering that operates on users' preferences and similar responses. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-07T12:14:44Z No. of bitstreams: 1 ijimai_5_3_13_pdf_15716.pdf: 1421174 bytes, checksum: 0d4769f6e02af7d97de27c05050ed29c (MD5); Made available in DSpace on 2022-02-07T12:14:44Z (GMT). No. of bitstreams: 1 ijimai_5_3_13_pdf_15716.pdf: 1421174 bytes, checksum: 0d4769f6e02af7d97de27c05050ed29c (MD5)

Lakka, Eftychia Malamos, Athanasios Pavlakis, K G Ware, J A https://reunir.unir.net/handle/123456789/12403 2022-02-07T11:47:35Z

Spatial Sound Rendering – A Survey Lakka, Eftychia; Malamos, Athanasios; Pavlakis, K G; Ware, J A Simulating propagation of sound and audio rendering can improve the sense of realism and the immersion both in complex acoustic environments and dynamic virtual scenes. In studies of sound auralization, the focus has always been on room acoustics modeling, but most of the same methods are also applicable in the construction of virtual environments such as those developed to facilitate computer gaming, cognitive research, and simulated training scenarios. This paper is a review of state-of-the-art techniques that are based on acoustic principles that apply not only to real rooms but also in 3D virtual environments. The paper also highlights the need to expand the field of immersive sound in a web based browsing environment, because, despite the interest and many benefits, few developments seem to have taken place within this context. Moreover, the paper includes a list of the most effective algorithms used for modelling spatial sound propagation and reports their advantages and disadvantages. Finally, the paper emphasizes in the evaluation of these proposed works. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-07T11:47:35Z No. of bitstreams: 1 ijimai_5_3_4_pdf_11151.pdf: 786507 bytes, checksum: a753ff8f45ce544461f19ee7253b0d24 (MD5); Made available in DSpace on 2022-02-07T11:47:35Z (GMT). No. of bitstreams: 1 ijimai_5_3_4_pdf_11151.pdf: 786507 bytes, checksum: a753ff8f45ce544461f19ee7253b0d24 (MD5)

Harish, B S Revanasiddappa, M B https://reunir.unir.net/handle/123456789/12400 2022-02-04T11:40:18Z

A New Feature Selection Method based on Intuitionistic Fuzzy Entropy to Categorize Text Documents Harish, B S; Revanasiddappa, M B Selection of highly discriminative feature in text document plays a major challenging role in categorization. Feature selection is an important task that involves dimensionality reduction of feature matrix, which in turn enhances the performance of categorization. This article presents a new feature selection method based on Intuitionistic Fuzzy Entropy (IFE) for Text Categorization. Firstly, Intuitionistic Fuzzy C-Means (IFCM) clustering method is employed to compute the intuitionistic membership values. The computed intuitionistic membership values are used to estimate intuitionistic fuzzy entropy via Match degree. Further, features with lower entropy values are selected to categorize the text documents. To find the efficacy of the proposed method, experiments are conducted on three standard benchmark datasets using three classifiers. F-measure is used to assess the performance of the classifiers. The proposed method shows impressive results as compared to other well known feature selection methods. Moreover, Intuitionistic Fuzzy Set (IFS) property addresses the uncertainty limitations of traditional fuzzy set. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-04T11:40:18Z No. of bitstreams: 1 ijimai_5_3_12_pdf_16348.pdf: 800936 bytes, checksum: d27513b5348efe9f252502b1eec83fc8 (MD5); Made available in DSpace on 2022-02-04T11:40:18Z (GMT). No. of bitstreams: 1 ijimai_5_3_12_pdf_16348.pdf: 800936 bytes, checksum: d27513b5348efe9f252502b1eec83fc8 (MD5)

Atmani, Baghdad Benamina, Mohammed Benbelkacem, Sofia https://reunir.unir.net/handle/123456789/12399 2022-02-04T11:22:41Z

Diabetes Diagnosis by Case-Based Reasoning and Fuzzy Logic Atmani, Baghdad; Benamina, Mohammed; Benbelkacem, Sofia In the medical field, experts’ knowledge is based on experience, theoretical knowledge and rules. Case-based reasoning is a problem-solving paradigm which is based on past experiences. For this purpose, a large number of decision support applications based on CBR have been developed. Cases retrieval is often considered as the most important step of case-based reasoning. In this article, we integrate fuzzy logic and data mining to improve the response time and the accuracy of the retrieval of similar cases. The proposed Fuzzy CBR is composed of two complementary parts; the part of classification by fuzzy decision tree realized by Fispro and the part of case-based reasoning realized by the platform JColibri. The use of fuzzy logic aims to reduce the complexity of calculating the degree of similarity that can exist between diabetic patients who require different monitoring plans. The results of the proposed approach are compared with earlier methods using accuracy as metrics. The experimental results indicate that the fuzzy decision tree is very effective in improving the accuracy for diabetes classification and hence improving the retrieval step of CBR reasoning. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-02-04T11:22:40Z No. of bitstreams: 1 ijimai_5_3_8_pdf_20127.pdf: 1373431 bytes, checksum: da8ff945f19d64fe5b50f5816dc868f5 (MD5); Made available in DSpace on 2022-02-04T11:22:41Z (GMT). No. of bitstreams: 1 ijimai_5_3_8_pdf_20127.pdf: 1373431 bytes, checksum: da8ff945f19d64fe5b50f5816dc868f5 (MD5)

Ayad, Habib Khalil, Mohammed https://reunir.unir.net/handle/123456789/12387 2022-01-31T11:04:36Z

QAM-DWT-SVD Based Watermarking Scheme for Medical Images Ayad, Habib; Khalil, Mohammed This paper presents a new semi-blind image watermarking system for medical applications. The new scheme utilizes Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) to embed a textual data into original medical images. In particular, text characters are encoded by a Quadrature Amplitude Modulation (QAM-16). In order to increase the security of the system and protect then the watermark from several attacks, the embedded data is submitted to Arnold Transform before inserting it into the host medical image. To evaluate the performances of the scheme, several medical images have been used in the experiments. Simulation results show that the proposed watermarking system ensures good imperceptibility and high robustness against several attacks. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T11:04:36Z No. of bitstreams: 1 ijimai_5_3_9_pdf_17617.pdf: 2102769 bytes, checksum: 065afc9e109abe3935779078ed90b8cd (MD5); Made available in DSpace on 2022-01-31T11:04:36Z (GMT). No. of bitstreams: 1 ijimai_5_3_9_pdf_17617.pdf: 2102769 bytes, checksum: 065afc9e109abe3935779078ed90b8cd (MD5)

Burgos, Daniel Nikolov, Roumen Stracke, Christian M. https://reunir.unir.net/handle/123456789/12384 2023-06-26T09:37:34Z

IJIMAI Editor's Note - Vol. 5 Issue 2 Burgos, Daniel; Nikolov, Roumen; Stracke, Christian M. The International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) provides an interdisciplinary forum in which scientists and professionals share their research results and report new advances on tools that use AI with interactive multimedia techniques. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T10:31:16Z No. of bitstreams: 1 ijimai_5_2_0_pdf_14729.pdf: 117631 bytes, checksum: 906383d4577baa3b12802d1a7857a2dd (MD5); Made available in DSpace on 2022-01-31T10:31:16Z (GMT). No. of bitstreams: 1 ijimai_5_2_0_pdf_14729.pdf: 117631 bytes, checksum: 906383d4577baa3b12802d1a7857a2dd (MD5)

González-González, Carina Gómez del Río, Nazaret Navarro-Adelantado, Vicente https://reunir.unir.net/handle/123456789/12382 2022-01-31T10:26:29Z

Exploring the Benefits of Using Gamification and Videogames for Physical Exercise: a Review of State of Art González-González, Carina; Gómez del Río, Nazaret; Navarro-Adelantado, Vicente There is a lack of motivation in children and adolescents to do physical exercise and at the same time a worldwide obesity epidemic. Gamification and active videogames can be used to increase the motivation of young people, promoting healthy habits. In this work we explore different studies on active videogames, eSports and gamification applied to physical exercise and health promotion. Main findings include positive effects in a reduction in body weight and in the promotion to continue performing of physical exercise. It also contributes to increase the motivation in children and adolescents to practice exercise. The personalization of user experience and emerging technologies (big data, wearables, smart technologies, etc.) are presented as promising opportunities to keep the engagement in game-based program and gamification of physical exercise. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T10:26:29Z No. of bitstreams: 1 ijimai_5_2_6_pdf_43532.pdf: 701313 bytes, checksum: d9387fa0d6151500d16c462f5347898a (MD5); Made available in DSpace on 2022-01-31T10:26:29Z (GMT). No. of bitstreams: 1 ijimai_5_2_6_pdf_43532.pdf: 701313 bytes, checksum: d9387fa0d6151500d16c462f5347898a (MD5)

Jain, Shikha Lodhi, Pooja Mishra, Omji Bajaj, Vasvi https://reunir.unir.net/handle/123456789/12380 2022-01-31T09:58:22Z

StuA: An Intelligent Student Assistant Jain, Shikha; Lodhi, Pooja; Mishra, Omji; Bajaj, Vasvi With advanced innovation in digital technology, demand for virtual assistants is arising which can assist a person and at the same time, minimize the need for interaction with the human. Acknowledging the requirement, we propose an interactive and intelligent student assistant, StuA, which can help new-comer in a college who are hesitant in interacting with the seniors as they fear of being ragged. StuA is capable of answering all types of queries of a new-comer related to academics, examinations, library, hostel and extra curriculum activities. The model is designed using CLIPS which allows inferring using forward chaining. Nevertheless, a generalized algorithm for backward chaining for CLIPS is also implemented. Validation of the proposed model is presented in five steps which show that the model is complete and consistent with 99.16% accuracy of the knowledge model. Moreover, the backward chaining algorithm is found to be 100% accurate. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T09:58:22Z No. of bitstreams: 1 ijimai_5_2_2_pdf_57769.pdf: 864490 bytes, checksum: e4a1813aac9bb2873fb6c4b8266d9c92 (MD5); Made available in DSpace on 2022-01-31T09:58:22Z (GMT). No. of bitstreams: 1 ijimai_5_2_2_pdf_57769.pdf: 864490 bytes, checksum: e4a1813aac9bb2873fb6c4b8266d9c92 (MD5)

Margoum, Sofia Bendaoud, Rachid Berrada, Khalid Idrissi Jouicha, Abdellah https://reunir.unir.net/handle/123456789/12379 2023-01-26T09:29:14Z

UC@MOOC's Effectiveness by Producing Open Educational Resources Margoum, Sofia; Bendaoud, Rachid; Berrada, Khalid; Idrissi Jouicha, Abdellah Open education is one of the most important settings in every society. It grants everyone the right to learn freely. Today, technology is helping to make learning even more open by providing an environment of online education, which plays a remarkable role in shortening distances and encouraging students to learn. At Cadi Ayyad University (UCA) the new-enrolled students are facing linguistics barriers as well as overcrowding in classrooms, in particular for those in open access institutions. Subsequently, they cannot have an easy access to their face-to-face courses. To help students to overcome these problems, the university has decided to design an online environment for all courses and programmes. The most innovative project adopted at UCA to face massification was inspired from the massive open online courses and was designed as an open Educational platform entitled UC@MOOC. More than 120 scripted courses have been posted online so far. In this paper we will describe and discuss an analytics research on geometrical optics course designed for around 2000 students at UCA. Through out this research we will explain how this initiative has been considered as a source of producing open educational resources. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T09:51:19Z No. of bitstreams: 1 ijimai_5_2_8_pdf_53982.pdf: 613254 bytes, checksum: 760bb9fd0ca870c755b574203a8a8995 (MD5); Made available in DSpace on 2022-01-31T09:51:19Z (GMT). No. of bitstreams: 1 ijimai_5_2_8_pdf_53982.pdf: 613254 bytes, checksum: 760bb9fd0ca870c755b574203a8a8995 (MD5)

Klamma, Ralf Lange, de Peter Neumann, Alexander Tobias Nicolaescu, Petru https://reunir.unir.net/handle/123456789/12378 2022-01-31T09:28:22Z

An Integrated Learning Analytics Approach for Virtual Vocational Training Centers Klamma, Ralf; Lange, de Peter; Neumann, Alexander Tobias; Nicolaescu, Petru Virtual training centers are hosted solutions for the implementation of training courses in the form of e.g. Webinars. Many existing centers neglect the informal and social dimension of vocational training as well as the legitimate business interests of training providers and companies sending their employees. In this paper, we present the virtual training center platform V3C that blends formal, certified virtual training courses with self-regulated and social learning in synchronous and asynchronous learning phases. We have developed an integrated learning analytics approach to collect, store, analyze and visualize data for different purposes like certification, interventions and gradual improvement of the platform. The results given here demonstrate the ability of the platform to deliver data for key performance indicators like learning outcomes and drop-out rates as well as the interplay between synchronous and asynchronous learning phases on a very large scale. Since the platform implementation is open source, results can be easily transferred and exploited in many contexts. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T09:28:21Z No. of bitstreams: 1 ijimai_5_2_4_pdf_97157.pdf: 1099837 bytes, checksum: 8104a29d3244961644a8cf16486c8dba (MD5); Made available in DSpace on 2022-01-31T09:28:22Z (GMT). No. of bitstreams: 1 ijimai_5_2_4_pdf_97157.pdf: 1099837 bytes, checksum: 8104a29d3244961644a8cf16486c8dba (MD5)

Medina, Mireles García, Carrillo Olguín, Montes https://reunir.unir.net/handle/123456789/12377 2022-01-31T08:45:17Z

Planning and Allocation of Digital Learning Objects with Augmented Reality to Higher Education Students According to the VARK Model Medina, Mireles; García, Carrillo; Olguín, Montes In the present research, the authors propose the planning, assignment and use of digital learning objects with augmented reality according to the learning style of students in higher education, according to the VARK Model. It is found that students with treatment have had better results in their final grades than students who have not undergone the treatment of having used digital learning objects with augmented reality. The digital objects of learning (DLO’s) with augmented reality designed according to the learning style of the students are an attractive and adequate option so that the teachers who are the main responsible for the didactic planning can spread the knowledge in the students. So that traditional forms of education are put aside and as a result of taking advantage of Information and Communication Technologies that have come to break with the paradigms that have prevailed for years in the teaching - learning process. On the other hand, education based on e-learning platforms facilitates the training of students at a distance allowing them to build and self-manage learning, as well as facilitate the dissemination of digital learning objects with augmented reality according to the learning style according to the VARK Model. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T08:45:17Z No. of bitstreams: 1 ijimai_5_2_7_pdf_10900.pdf: 533229 bytes, checksum: 6c883c7cda3cd3549a2b8a1923402006 (MD5); Made available in DSpace on 2022-01-31T08:45:17Z (GMT). No. of bitstreams: 1 ijimai_5_2_7_pdf_10900.pdf: 533229 bytes, checksum: 6c883c7cda3cd3549a2b8a1923402006 (MD5)

Hamoud, Alaa Khalaf Hashim, Ali Salah Awadh, Wid Aqeel https://reunir.unir.net/handle/123456789/12376 2022-01-31T08:29:11Z

Predicting Student Performance in Higher Education Institutions Using Decision Tree Analysis Hamoud, Alaa Khalaf; Hashim, Ali Salah; Awadh, Wid Aqeel The overall success of educational institutions can be measured by the success of its students. Providing factors that increase success rate and reduce the failure of students is profoundly helpful to educational organizations. Data mining is the best solution to finding hidden patterns and giving suggestions that enhance the performance of students. This paper presents a model based on decision tree algorithms and suggests the best algorithm based on performance. Three built classifiers (J48, Random Tree and REPTree) were used in this model with the questionnaires filled in by students. The survey consists of 60 questions that cover the fields, such as health, social activity, relationships, and academic performance, most related to and affect the performance of students. A total of 161 questionnaires were collected. The Weka 3.8 tool was used to construct this model. Finally, the J48 algorithm was considered as the best algorithm based on its performance compared with the Random Tree and RepTree algorithms. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-31T08:29:11Z No. of bitstreams: 1 ijimai_5_2_3_pdf_30196.pdf: 397209 bytes, checksum: 5691b1fcdb7dbf433b3fa10c20227739 (MD5); Made available in DSpace on 2022-01-31T08:29:11Z (GMT). No. of bitstreams: 1 ijimai_5_2_3_pdf_30196.pdf: 397209 bytes, checksum: 5691b1fcdb7dbf433b3fa10c20227739 (MD5)

Martínez Navarro, Álvaro Moreno-Ger, Pablo https://reunir.unir.net/handle/123456789/12370 2024-02-15T14:33:20Z

Comparison of Clustering Algorithms for Learning Analytics with Educational Datasets Martínez Navarro, Álvaro; Moreno-Ger, Pablo Learning Analytics is becoming a key tool for the analysis and improvement of digital education processes, and its potential benefit grows with the size of the student cohorts generating data. In the context of Open Education, the potentially massive student cohorts and the global audience represent a great opportunity for significant analyses and breakthroughs in the field of learning analytics. However, these potentially huge datasets require proper analysis techniques, and different algorithms, tools and approaches may perform better in this specific context. In this work, we compare different clustering algorithms using an educational dataset. We start by identifying the most relevant algorithms in Learning Analytics and benchmark them to determine, according to internal validation and stability measurements, which algorithms perform better. We analyzed seven algorithms, and determined that K-means and PAM were the best performers among partition algorithms, and DIANA was the best performer among hierarchical algorithms. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T09:45:52Z No. of bitstreams: 1 ijimai_5_2_1_pdf_84728.pdf: 1574330 bytes, checksum: 54be7ed138da258c12b58a9453092bec (MD5); Made available in DSpace on 2022-01-27T09:45:52Z (GMT). No. of bitstreams: 1 ijimai_5_2_1_pdf_84728.pdf: 1574330 bytes, checksum: 54be7ed138da258c12b58a9453092bec (MD5)

García-Peñalvo, Francisco Cruz-Benito, Juan Martín-González, Martín Vázquez-Ingelmo, Andrea Sánchez-Prieto, José Carlos Therón, Roberto https://reunir.unir.net/handle/123456789/12369 2023-01-25T10:32:40Z

Proposing a Machine Learning Approach to Analyze and Predict Employment and its Factors García-Peñalvo, Francisco; Cruz-Benito, Juan; Martín-González, Martín; Vázquez-Ingelmo, Andrea; Sánchez-Prieto, José Carlos; Therón, Roberto This paper presents an original study with the aim of propose and test a machine learning approach to research about employability and employment. To understand how the graduates get employed, researchers propose to build predictive models using machine learning algorithms, extracting after that the most relevant factors that describe the model and employing further analysis techniques like clustering to get deeper insights. To test the proposal, is presented a case study that involves data from the Spanish Observatory for Employability and Employment (OEEU). Using data from this project (information about 3000 students), has been built predictive models that define how these students get a job after finalizing their degrees. The results obtained in this case study are very promising, and encourage authors to refine the process and validate it in further research. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T09:35:30Z No. of bitstreams: 1 ijimai_5_2_5_pdf_12552.pdf: 445862 bytes, checksum: 0db264e24b64c55e8111aeb77e3a7cf6 (MD5); Made available in DSpace on 2022-01-27T09:35:30Z (GMT). No. of bitstreams: 1 ijimai_5_2_5_pdf_12552.pdf: 445862 bytes, checksum: 0db264e24b64c55e8111aeb77e3a7cf6 (MD5)

Khari, Manju https://reunir.unir.net/handle/123456789/12367 2022-01-27T08:46:13Z

IJIMAI Editor's Note - Vol. 5 Issue 1 Khari, Manju The International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) provides an interdisciplinary forum in which scientists and professionals share their research results and report new advances on tools that use AI with interactive multimedia techniques. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T08:46:13Z No. of bitstreams: 1 ijimai_5_1_0_pdf_13503.pdf: 170828 bytes, checksum: 7a816025c5da6bc51e3ba54cc2735c0e (MD5); Made available in DSpace on 2022-01-27T08:46:13Z (GMT). No. of bitstreams: 1 ijimai_5_1_0_pdf_13503.pdf: 170828 bytes, checksum: 7a816025c5da6bc51e3ba54cc2735c0e (MD5)

Mohamed, Emad Mohamed, Al-Attar Ali Mitani, Yasunori https://reunir.unir.net/handle/123456789/12366 2022-01-27T08:42:39Z

MSA for Optimal Reconfiguration and Capacitor Allocation in Radial/Ring Distribution Networks Mohamed, Emad; Mohamed, Al-Attar Ali; Mitani, Yasunori This work presents a hybrid heuristic search algorithm called Moth Swarm Algorithm (MSA) in the context of power loss minimization of radial distribution networks (RDN) through optimal allocation and rating of shunt capacitors for enhancing the performance of distribution networks. With MSA, different optimization operators are used to mimic a set of behavioral patterns of moths in nature, which allows for flexible and powerful optimizer. Hence, a new dynamic selection strategy of crossover points is proposed based on population diversity to handle the difference vectors Lévy-mutation to force MSA jump out of stagnation and enhance its exploration ability. In addition, a spiral motion, adaptive Gaussian walks, and a novel associative learning mechanism with immediate memory are implemented to exploit the promising areas in the search space. In this article, the MSA is tested to adapt the objective function to reduce the system power losses, reduce total system cost and consequently increase the annual net saving with inequity constrains on capacitor size and voltage limits. The validation of the proposed algorithm has been tested and verified through small, medium and large scales of standard RDN of IEEE (33, 69, 85-bus) systems and also on ring main systems of 33 and 69-bus. In addition, the obtained results are compared with other algorithms to highlight the advantages of the proposed approach. Numerical results stated that the MSA can achieve optimal solutions for losses reduction and capacitor locations with finest performance compared with many existing algorithms. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T08:42:39Z No. of bitstreams: 1 ijimai_5_1_14_pdf_75537.pdf: 2952774 bytes, checksum: 15abbd0a4a638e1080a3a712c78fedbd (MD5); Made available in DSpace on 2022-01-27T08:42:39Z (GMT). No. of bitstreams: 1 ijimai_5_1_14_pdf_75537.pdf: 2952774 bytes, checksum: 15abbd0a4a638e1080a3a712c78fedbd (MD5)

Perera, Perera, Harshani Harshani Shiratuddin, Mohd Fairuz Wong, Kok Wai Fullarton, Kelly https://reunir.unir.net/handle/123456789/12365 2022-01-27T08:36:05Z

EEG Signal Analysis of Writing and Typing between Adults with Dyslexia and Normal Controls Perera, Perera, Harshani Harshani; Shiratuddin, Mohd Fairuz; Wong, Kok Wai; Fullarton, Kelly EEG is one of the most useful techniques used to represent behaviours of the brain and helps explore valuable insights through the measurement of brain electrical activity. Hence, plays a vital role in detecting neurological conditions. In this paper, we identify some unique EEG patterns pertaining to dyslexia, which is a learning disability with a neurological origin. Although EEG signals hold important insights of brain behaviours, uncovering these insights are not always straightforward due to its complexity. We tackle this using machine learning and uncover unique EEG signals generated in adults with dyslexia during writing and typing as well as optimal EEG electrodes and brain regions for classification. This study revealed that the greater level of difficulties seen in individuals with dyslexia during writing and typing compared to normal controls are reflected in the brainwave signal patterns. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T08:36:05Z No. of bitstreams: 1 ijimai_5_1_8_pdf_17747.pdf: 1445633 bytes, checksum: 3ac9512ea438440d1f3c88d45adc48ad (MD5); Made available in DSpace on 2022-01-27T08:36:05Z (GMT). No. of bitstreams: 1 ijimai_5_1_8_pdf_17747.pdf: 1445633 bytes, checksum: 3ac9512ea438440d1f3c88d45adc48ad (MD5)

Suliman, Azizah Omarov, Batyrkhan https://reunir.unir.net/handle/123456789/12364 2022-01-27T08:28:30Z

Applying Bayesian Regularization for Acceleration of Levenberg-Marquardt based Neural Network Training Suliman, Azizah; Omarov, Batyrkhan Neural network is widely used for image classification problems, and is proven to be effective with high successful rate. However one of its main challenges is the significant amount of time it takes to train the network. The goal of this research is to improve the neural network training algorithms and apply and test them in classification and recognition problems. In this paper, we describe a method of applying Bayesian regularization to improve Levenberg-Marquardt (LM) algorithm and make it better usable in training neural networks. In the experimental part, we qualify the modified LM algorithm using Bayesian regularization and use it to determine an appropriate number of hidden layers in the network to avoid overtraining. The result of the experiment was very encouraging with a 98.8% correct classification when run on test samples. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T08:28:30Z No. of bitstreams: 1 ijimai_5_1_9_pdf_32121.pdf: 687098 bytes, checksum: 0ece36f7c9507e56324e1207a046025d (MD5); Made available in DSpace on 2022-01-27T08:28:30Z (GMT). No. of bitstreams: 1 ijimai_5_1_9_pdf_32121.pdf: 687098 bytes, checksum: 0ece36f7c9507e56324e1207a046025d (MD5)

Adrian, Cecilia Abdullah, Rusli Atan, Rodziah Jusoh, Yusmadi Yah https://reunir.unir.net/handle/123456789/12363 2022-01-27T08:13:13Z

Conceptual Model Development of Big Data Analytics Implementation Assessment Effect on Decision-Making Adrian, Cecilia; Abdullah, Rusli; Atan, Rodziah; Jusoh, Yusmadi Yah The significance of big data advancement has benefited various organizations to leverage the potential insights and capabilities of big data in organizational performance and decision-making. However, the analytics outcome and quality of big data analytics (BDA) implementation has yet to be addressed. Therefore the aims of this paper are to identify and analyze the affecting factors and elements of BDA implementation and to propose a conceptual model for effective decision-making through BDA implementation assessment. The model is developed based on three dimensions such as performing data strategy (organization), collaborative knowledge worker (people) and executing data analytics (technology). The findings of this ongoing study proceeds with designing a proposed conceptual model with the research hypothesis and may provide a better assessment model for effective decision-making in the long run. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T08:13:13Z No. of bitstreams: 1 ijimai_5_1_13_pdf_81158.pdf: 487442 bytes, checksum: 52e42f27aa17f01834a104976bc364a2 (MD5); Made available in DSpace on 2022-01-27T08:13:13Z (GMT). No. of bitstreams: 1 ijimai_5_1_13_pdf_81158.pdf: 487442 bytes, checksum: 52e42f27aa17f01834a104976bc364a2 (MD5)

Ahmad, Wan Nooraishya Wan Ali, Nazlena Mohamad https://reunir.unir.net/handle/123456789/12362 2022-01-27T07:58:49Z

A Study on Persuasive Technologies: The Relationship between User Emotions, Trust and Persuasion Ahmad, Wan Nooraishya Wan; Ali, Nazlena Mohamad A successful persuasive technology is able to persuade people to change from one state to a more well known state. Therefore, to allow for a change, persuasive technology must be able to affect users’ emotion and make the user trust the technology so that they will adopt the persuasive technology into their daily life routine, as well as continue to use the technology for long period. This paper is aimed to study the relation between users’ emotion with trust and persuasion and how they may contribute to the success of changing a person attitude or behavior towards a certain context or issue. Twenty five participants have completed the study in 6 weeks by using two types of persuasive technology that were assessed at three different interaction stages: pre, during and post. Result shows that emotions have a significant effect on trust, whereas the effect of emotions on persuasion using the persuasive technology was mediated by trust. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-27T07:58:49Z No. of bitstreams: 1 ijimai_5_1_7_pdf_14509.pdf: 372681 bytes, checksum: df5fb93cf1b9580e8b37412c5f4b0911 (MD5); Made available in DSpace on 2022-01-27T07:58:49Z (GMT). No. of bitstreams: 1 ijimai_5_1_7_pdf_14509.pdf: 372681 bytes, checksum: df5fb93cf1b9580e8b37412c5f4b0911 (MD5)

Abdel-Nasser, Mohamed Mahmoud, Karar Kashef, Heba https://reunir.unir.net/handle/123456789/12361 2022-01-26T13:26:31Z

A Novel Smart Grid State Estimation Method Based on Neural Networks Abdel-Nasser, Mohamed; Mahmoud, Karar; Kashef, Heba The rapid development in smart grids needs efficient state estimation methods. This paper presents a novel method for smart grid state estimation (e.g., voltages, active and reactive power loss) using artificial neural networks (ANNs). The proposed method which is called SE-NN (state estimation using neural network) can evaluate the state at any point of smart grid systems considering fluctuated loads. To demonstrate the effectiveness of the proposed method, it has been applied on IEEE 33-bus distribution system with different data resolutions. The accuracy of the proposed method is validated by comparing the results with an exact power flow method. The proposed SE-NN method is a very fast tool to estimate voltages and re/active power loss with a high accuracy compared to the traditional methods. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-26T13:26:31Z No. of bitstreams: 1 ijimai_5_1_12_pdf_18312.pdf: 980918 bytes, checksum: b29143ba71e0d61592542210c26c4ead (MD5); Made available in DSpace on 2022-01-26T13:26:31Z (GMT). No. of bitstreams: 1 ijimai_5_1_12_pdf_18312.pdf: 980918 bytes, checksum: b29143ba71e0d61592542210c26c4ead (MD5)

Charef, Abdallah Bensalloua Djamila, Hamdadou https://reunir.unir.net/handle/123456789/12360 2022-01-26T13:15:19Z

Users Integrity Constraints in SOLAP Systems. Application in Agroforestry Charef, Abdallah Bensalloua; Djamila, Hamdadou SpatialData Warehouse and Spatial On-Line Analytical Processing are decision support technologies which offer the spatial and multidimensional analysis of data stored in multidimensional structure. They are aimed also at supporting geographic knowledge discovery to help decision-maker in his job related to make the appropriate decision . However, if we don’t consider data quality in the spatial hypercubes and how it is explored, it may provide unreliable results. In this paper, we propose a system for the implementation of user integrity constraints in SOLAP namely “UIC-SOLAP”. It corresponds to a methodology for guaranteeing results quality in an analytical process effectuated by different users exploiting several facts tables within the same hypercube. We integrate users Integrity Constraints (IC) by specifying visualization ICs according to their preferences and we define inter-facts ICs in this case. In order to validate our proposition, we propose the multidimensional modeling by UML profile to support constellation schema of a hypercube with several fact tables related to subjects of analysis in forestry management. Then, we propose implementation of some ICs related to users of such a system. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-26T13:15:19Z No. of bitstreams: 1 ijimai_5_1_6_pdf_24536.pdf: 2042302 bytes, checksum: 02a7329e6a5c358002e74e27dd226dd2 (MD5); Made available in DSpace on 2022-01-26T13:15:19Z (GMT). No. of bitstreams: 1 ijimai_5_1_6_pdf_24536.pdf: 2042302 bytes, checksum: 02a7329e6a5c358002e74e27dd226dd2 (MD5)

Saleem, Nasir Tareen, Tayyaba Gul https://reunir.unir.net/handle/123456789/12359 2022-01-26T13:07:47Z

Spectral Restoration Based Speech Enhancement for Robust Speaker Identification Saleem, Nasir; Tareen, Tayyaba Gul Spectral restoration based speech enhancement algorithms are used to enhance quality of noise masked speech for robust speaker identification. In presence of background noise, the performance of speaker identification systems can be severely deteriorated. The present study employed and evaluated the Minimum Mean-Square-Error Short-Time Spectral Amplitude Estimators with modified a priori SNR estimate prior to speaker identification to improve performance of the speaker identification systems in presence of background noise. For speaker identification, Mel Frequency Cepstral coefficient and Vector Quantization is used to extract the speech features and to model the extracted features respectively. The experimental results showed significant improvement in speaker identification rates when spectral restoration based speech enhancement algorithms are used as a pre-processing step. The identification rates are found to be higher after employing the speech enhancement algorithms. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-26T13:07:47Z No. of bitstreams: 1 ijimai_5_1_4_pdf_16417.pdf: 1957139 bytes, checksum: 3b9701b41dca56086367fdaf9a829b94 (MD5); Made available in DSpace on 2022-01-26T13:07:47Z (GMT). No. of bitstreams: 1 ijimai_5_1_4_pdf_16417.pdf: 1957139 bytes, checksum: 3b9701b41dca56086367fdaf9a829b94 (MD5)

Boulid, Youssef Souhar, Abdelghani Ouagague, Mly. https://reunir.unir.net/handle/123456789/12358 2022-01-26T13:00:17Z

Spatial and Textural Aspects for Arabic Handwritten Characters Recognition Boulid, Youssef; Souhar, Abdelghani; Ouagague, Mly. The purpose of the present paper is the recognition of handwritten Arabic characters in their isolated form. The specificity of Arabic characters is taken into consideration, each of the proposed feature extraction method integrates one of the two aspects: spatial and textural. In the first step, a modified Bitmap Sampling method is proposed, which converts the character’s images into a binary Matrix and then constructs a Mask for each class. A matching rate is used between the input binary matrix and the masks to determinate the corresponding class. In the second step we investigate the use of an Artificial Neural Network as classifier with the binary matrices as features and then the histograms of Local Binary Patterns to capture the texture aspect of the characters. Finally, the results of these two methods are combined to take into consideration both aspects at the same time. Tested on the Arabic set of the Isolated Farsi Handwritten Character Database, the proposed method has 2.82% error rate. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-26T13:00:17Z No. of bitstreams: 1 ijimai_5_1_11_pdf_70968.pdf: 923665 bytes, checksum: 57bbc905e4dbac48be784f4a5b0c78e9 (MD5); Made available in DSpace on 2022-01-26T13:00:17Z (GMT). No. of bitstreams: 1 ijimai_5_1_11_pdf_70968.pdf: 923665 bytes, checksum: 57bbc905e4dbac48be784f4a5b0c78e9 (MD5)

Magdin, Martin Prikler, F https://reunir.unir.net/handle/123456789/12357 2022-01-25T10:54:44Z

Real Time Facial Expression Recognition Using Webcam and SDK Affectiva Magdin, Martin; Prikler, F Facial expression is an essential part of communication. For this reason, the issue of human emotions evaluation using a computer is a very interesting topic, which has gained more and more attention in recent years. It is mainly related to the possibility of applying facial expression recognition in many fields such as HCI, video games, virtual reality, and analysing customer satisfaction etc. Emotions determination (recognition process) is often performed in 3 basic phases: face detection, facial features extraction, and last stage - expression classification. Most often you can meet the so-called Ekman’s classification of 6 emotional expressions (or 7 - neutral expression) as well as other types of classification - the Russell circular model, which contains up to 24 or the Plutchik’s Wheel of Emotions. The methods used in the three phases of the recognition process have not only improved over the last 60 years, but new methods and algorithms have also emerged that can determine the ViolaJones detector with greater accuracy and lower computational demands. Therefore, there are currently various solutions in the form of the Software Development Kit (SDK). In this publication, we point to the proposition and creation of our system for real-time emotion classification. Our intention was to create a system that would use all three phases of the recognition process, work fast and stable in real time. That’s why we’ve decided to take advantage of existing Affectiva SDKs. By using the classic webcamera we can detect facial landmarks on the image automatically using the Software Development Kit (SDK) from Affectiva. Geometric feature based approach is used for feature extraction. The distance between landmarks is used as a feature, and for selecting an optimal set of features, the brute force method is used. The proposed system uses neural network algorithm for classification. The proposed system recognizes 6 (respectively 7) facial expressions, namely anger, disgust, fear, happiness, sadness, surprise and neutral. We do not want to point only to the percentage of success of our solution. We want to point out the way we have determined this measurements and the results we have achieved and how these results have significantly influenced our future research direction. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-25T10:54:44Z No. of bitstreams: 1 ijimai_5_1_1_pdf_82035.pdf: 1222831 bytes, checksum: be0c3502763a7b93fc0f6eb2d0b16408 (MD5); Made available in DSpace on 2022-01-25T10:54:44Z (GMT). No. of bitstreams: 1 ijimai_5_1_1_pdf_82035.pdf: 1222831 bytes, checksum: be0c3502763a7b93fc0f6eb2d0b16408 (MD5)

Hamzaoui, Y Amnai, M Choukri, A Fakhri, Y https://reunir.unir.net/handle/123456789/12356 2022-01-25T10:29:55Z

Novel Clustering Method Based on K-Medoids and Mobility Metric Hamzaoui, Y; Amnai, M; Choukri, A; Fakhri, Y The structure and constraint of MANETS influence negatively the performance of QoS, moreover the main routing protocols proposed generally operate in flat routing. Hence, this structure gives the bad results of QoS when the network becomes larger and denser. To solve this problem we use one of the most popular methods named clustering. The present paper comes within the frameworks of research to improve the QoS in MANETs. In this paper we propose a new algorithm of clustering based on the new mobility metric and K-Medoid to distribute the nodes into several clusters. Intuitively our algorithm can give good results in terms of stability of the cluster, and can also extend life time of cluster head. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-25T10:29:55Z No. of bitstreams: 1 ijimai_5_1_3_pdf_41024.pdf: 785747 bytes, checksum: 12a58e3d9212a360c0165802e94d744e (MD5); Made available in DSpace on 2022-01-25T10:29:55Z (GMT). No. of bitstreams: 1 ijimai_5_1_3_pdf_41024.pdf: 785747 bytes, checksum: 12a58e3d9212a360c0165802e94d744e (MD5)

Kamble, Shailesh Thakur, Nileshsingh Samdurkar, Apurva Patharkar, Akshay https://reunir.unir.net/handle/123456789/12355 2022-01-25T10:15:07Z

Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm Kamble, Shailesh; Thakur, Nileshsingh; Samdurkar, Apurva; Patharkar, Akshay Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS) and cross diamond search algorithms (CDS) are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS) algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS) in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-25T10:15:07Z No. of bitstreams: 1 ijimai_5_1_10_pdf_12412.pdf: 1985614 bytes, checksum: 7b67fc33ccfae0a04afc9d3bf450af57 (MD5); Made available in DSpace on 2022-01-25T10:15:07Z (GMT). No. of bitstreams: 1 ijimai_5_1_10_pdf_12412.pdf: 1985614 bytes, checksum: 7b67fc33ccfae0a04afc9d3bf450af57 (MD5)

Bhaskar-Semwal, Vijay Raj, Manish Nandi, G C https://reunir.unir.net/handle/123456789/12354 2022-01-25T09:46:34Z

Hybrid Model for Passive Locomotion Control of a Biped Humanoid:The Artificial Neural Network Approach Bhaskar-Semwal, Vijay; Raj, Manish; Nandi, G C Developing a correct model for a biped robot locomotion is extremely challenging due to its inherently unstable structure because of the passive joint located at the unilateral foot-ground contact and varying configurations throughout the gait cycle, resulting variation of dynamic descriptions and control laws from phase to phase. The present research describes the development of a hybrid biped model using an Open Dynamics Engine (ODE) based analytical three link leg model as a base model and, on top of it, an Artificial Neural Network based learning model which ensures better adaptability, better limits cycle behaviors and better generalization while negotiating along a down slope. The base model has been configured according to the individual subjects and data have been collected using a novel technique through an android app from those subjects while walking down a slope. The pattern between the deviation of the actual trajectories and the base model generated trajectories has been found using a back propagation based artificial neural network architecture. It has been observed that this base model with learning based compensation enables the biped to better adapt in a real walking environment, showing better limit cycle behaviors. We also observed the bounded nature of deviation which led us to conclude that the strategy for biped locomotion control is generic in nature and largely dominated by learning. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-25T09:46:34Z No. of bitstreams: 1 ijimai_5_1_5_pdf_20509.pdf: 1122752 bytes, checksum: 35d27cb4355b571f07b82e8ee741f9ee (MD5); Made available in DSpace on 2022-01-25T09:46:34Z (GMT). No. of bitstreams: 1 ijimai_5_1_5_pdf_20509.pdf: 1122752 bytes, checksum: 35d27cb4355b571f07b82e8ee741f9ee (MD5)

Nighot, Mininath Ghatol, Ashok Thakare, Vilas https://reunir.unir.net/handle/123456789/12353 2022-01-25T09:19:29Z

Self-Organized Hybrid Wireless Sensor Network for Finding Randomly Moving Target in Unknown Environment Nighot, Mininath; Ghatol, Ashok; Thakare, Vilas Unknown target search, in an unknown environment, is a complex problem in Wireless Sensor Network (WSN). It does not have a linear solution when target’s location and searching space is unknown. For the past few years, many researchers have invented novel techniques for finding a target using either Static Sensor Node (SSN) or Mobile Sensor Node (MSN) in WSN i.e. Hybrid WSN. But there is a lack of research to find a solution using hybrid WSN. In the current research, the problem has been addressed mostly using non-biological techniques. Due to its complexity and having a non-linear solution, Bio-inspired techniques are most suited to solve the problem. This paper proposes a solution for searching of randomly moving target in unknown area using only Mobile sensor nodes and combination of both Static and Mobile sensor nodes. In proposed technique coverage area is determined and compared. To perform the work, novel algorithms like MSNs Movement Prediction Algorithm (MMPA), Leader Selection Algorithm (LSA), Leader’s Movement Prediction Algorithm (LMPA) and follower algorithm are implemented. Simulation results validate the effectiveness of proposed work. Through the result, it is shown that proposed hybrid WSN approach with less number of sensor nodes (combination of Static and Mobile sensor nodes) finds target faster than only MSN approach. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2022-01-25T09:19:28Z No. of bitstreams: 1 ijimai_5_1_2_pdf_19352.pdf: 3409132 bytes, checksum: c031351811b430c938336ec2b69ea658 (MD5); Made available in DSpace on 2022-01-25T09:19:29Z (GMT). No. of bitstreams: 1 ijimai_5_1_2_pdf_19352.pdf: 3409132 bytes, checksum: c031351811b430c938336ec2b69ea658 (MD5)

Mochón, Francisco Elvira, Carlos https://reunir.unir.net/handle/123456789/11911 2021-09-27T12:11:58Z

IJIMAI Editor's Note - Vol. 4 Issue 7 Mochón, Francisco; Elvira, Carlos The International Journal of Interactive Multimedia and Artificial Intelligence - IJIMAI (ISSN 1989 - 1660) provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances on AI tools or tools that use AI with interactive multimedia techniques. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T12:11:58Z No. of bitstreams: 1 ijimai_4_7_0_pdf_71516.pdf: 142423 bytes, checksum: 1dec9e26c34da0454ce5922653438c52 (MD5); Made available in DSpace on 2021-09-27T12:11:58Z (GMT). No. of bitstreams: 1 ijimai_4_7_0_pdf_71516.pdf: 142423 bytes, checksum: 1dec9e26c34da0454ce5922653438c52 (MD5)

Rojas, David Carnicero, Javier https://reunir.unir.net/handle/123456789/11910 2021-09-27T11:56:12Z

Big Data and Public Health Systems: Issues and Opportunities Rojas, David; Carnicero, Javier Over the last years, the need for changing the current model of European public health systems has been repeatedly addressed, in order to ensure their sustainability. Following this line, IT has always been referred to as one of the key instruments for enhancing the information management processes of healthcare organizations, thus contributing to the improvement and evolution of health systems. On the IT field, Big Data solutions are expected to play a main role, since they are designed for handling huge amounts of information in a fast and efficient way, allowing users to make important decisions quickly. This article reviews the main features of the European public health system model and the corresponding healthcare and management-related information systems, the challenges that these health systems are currently facing, and the possible contributions of Big Data solutions to this field. To that end, the authors share their professional experience on the Spanish public health system, and review the existing literature related to this topic. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T11:56:12Z No. of bitstreams: 1 ijimai_4_7_8_pdf_16011.pdf: 354882 bytes, checksum: c8b0581f35bddbebaf3c8623c0061f25 (MD5); Made available in DSpace on 2021-09-27T11:56:12Z (GMT). No. of bitstreams: 1 ijimai_4_7_8_pdf_16011.pdf: 354882 bytes, checksum: c8b0581f35bddbebaf3c8623c0061f25 (MD5)

Bodas-Sagi, Diego Labeaga, José https://reunir.unir.net/handle/123456789/11909 2021-09-27T11:43:48Z

Big Data and Health Economics: Opportunities, Challenges and Risks Bodas-Sagi, Diego; Labeaga, José Big Data offers opportunities in many fields. Healthcare is not an exception. In this paper we summarize the possibilities of Big Data and Big Data technologies to offer useful information to policy makers. In a world with tight public budgets and ageing populations we feel necessary to save costs in any production process. The use of outcomes from Big Data could be in the future a way to improve decisions at a lower cost than today. In addition to list the advantages of properly using data and technologies from Big Data, we also show some challenges and risks that analysts could face. We also present an hypothetical example of the use of administrative records with health information both for diagnoses and patients. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T11:43:48Z No. of bitstreams: 1 ijimai_4_7_7_pdf_86496.pdf: 519132 bytes, checksum: 61dfe095796c20f114246608ebd6ba8d (MD5); Made available in DSpace on 2021-09-27T11:43:48Z (GMT). No. of bitstreams: 1 ijimai_4_7_7_pdf_86496.pdf: 519132 bytes, checksum: 61dfe095796c20f114246608ebd6ba8d (MD5)

González-Ferrer, Arturo Seara, Germán Cháfer, Joan Mayol, Julio https://reunir.unir.net/handle/123456789/11908 2021-09-27T11:21:49Z

Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare González-Ferrer, Arturo; Seara, Germán; Cháfer, Joan; Mayol, Julio Talking about Big Data in healthcare we usually refer to how to use data collected from current electronic medical records, either structured or unstructured, to answer clinically relevant questions. This operation is typically carried out by means of analytics tools (e.g. machine learning) or by extracting relevant data from patient summaries through natural language processing techniques. From other perspective of research in medical informatics, powerful initiatives have emerged to help physicians taking decisions, in both diagnostics and therapeutics, built from the existing medical evidence (i.e. knowledge-based decision support systems). Much of the problems these tools have shown, when used in real clinical settings, are related to their implementation and deployment, more than failing in its support, but, technology is slowly overcoming interoperability and integration issues. Beyond the point-of-care decision support these tools can provide, the data generated when using them, even in controlled trials, could be used to further analyze facts that are traditionally ignored in the current clinical practice. In this paper, we reflect on the technologies available to make the leap and how they could help driving healthcare organizations shifting to a value-based healthcare philosophy. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T11:21:49Z No. of bitstreams: 1 ijimai_4_7_6_pdf_12585.pdf: 652666 bytes, checksum: 59b3a20d850628e9bffcea67d4417319 (MD5); Made available in DSpace on 2021-09-27T11:21:49Z (GMT). No. of bitstreams: 1 ijimai_4_7_6_pdf_12585.pdf: 652666 bytes, checksum: 59b3a20d850628e9bffcea67d4417319 (MD5)

Cantón Croda, Rosa María Gibaja Romero, Damián Emilio https://reunir.unir.net/handle/123456789/11907 2021-09-27T10:59:26Z

Development of Injuries Prevention Policies in Mexico: A Big Data Approach Cantón Croda, Rosa María; Gibaja Romero, Damián Emilio Considering that Mexican injuries prevention strategies have been focused on injuries caused by car accidents and gender violence, a whole analysis of the injuries registered are performed in this paper to have a wider overview of those agents that can cause injuries around the country. Taking into account the amount of information from both public and private sources, obtained from dynamic cubes reported by the Minister of Health, Big Data strategies are used with the objective of finding an appropriate extraction such as to identify the real correlations between the different variables registered by the Health Sector. The results of the analysis show areas of opportunity to improve the public policies on the subject, particularly in diminishing wounds at living place, public road (pedestrians) and work. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T10:59:26Z No. of bitstreams: 1 ijimai_4_7_5_pdf_14121.pdf: 509507 bytes, checksum: 776e0ad36e2a0376639079d8b58e9bba (MD5); Made available in DSpace on 2021-09-27T10:59:26Z (GMT). No. of bitstreams: 1 ijimai_4_7_5_pdf_14121.pdf: 509507 bytes, checksum: 776e0ad36e2a0376639079d8b58e9bba (MD5)

Mochón, Francisco Elvira, Carlos Ochoa, Alberto Gonzalvez, Juan Carlos https://reunir.unir.net/handle/123456789/11906 2021-09-27T10:46:55Z

Machine-Learning-Based No Show Prediction in Outpatient Visits Mochón, Francisco; Elvira, Carlos; Ochoa, Alberto; Gonzalvez, Juan Carlos A recurring problem in healthcare is the high percentage of patients who miss their appointment, be it a consultation or a hospital test. The present study seeks patient’s behavioural patterns that allow predicting the probability of no- shows. We explore the convenience of using Big Data Machine Learning models to accomplish this task. To begin with, a predictive model based only on variables associated with the target appointment is built. Then the model is improved by considering the patient’s history of appointments. In both cases, the Gradient Boosting algorithm was the predictor of choice. Our numerical results are considered promising given the small amount of information available. However, there seems to be plenty of room to improve the model if we manage to collect additional data for both patients and appointments. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T10:46:55Z No. of bitstreams: 1 ijimai_4_7_4_pdf_11885.pdf: 326853 bytes, checksum: 7660a249f6c0e17f88867c5837d3b718 (MD5); Made available in DSpace on 2021-09-27T10:46:55Z (GMT). No. of bitstreams: 1 ijimai_4_7_4_pdf_11885.pdf: 326853 bytes, checksum: 7660a249f6c0e17f88867c5837d3b718 (MD5)

Pruenza, Cristina Teurón, María Lechuga, Luis Díaz, Julia González, Ana https://reunir.unir.net/handle/123456789/11905 2021-09-27T10:20:59Z

Development of a Predictive Model for Induction Success of Labour Pruenza, Cristina; Teurón, María; Lechuga, Luis; Díaz, Julia; González, Ana Induction of the labour process is an extraordinarily common procedure used in some pregnancies. Obstetricians face the need to end a pregnancy, for medical reasons usually (maternal or fetal requirements) or less frequently, social (elective inductions for convenience). The success of induction procedure is conditioned by a multitude of maternal and fetal variables that appear before or during pregnancy or birth process, with a low predictive value. The failure of the induction process involves performing a caesarean section. This project arises from the clinical need to resolve a situation of uncertainty that occurs frequently in our clinical practice. Since the weight of clinical variables is not adequately weighted, we consider very interesting to know a priori the possibility of success of induction to dismiss those inductions with high probability of failure, avoiding unnecessary procedures or postponing end if possible. We developed a predictive model of induced labour success as a support tool in clinical decision making. Improve the predictability of a successful induction is one of the current challenges of Obstetrics because of its negative impact. The identification of those patients with high chances of failure, will allow us to offer them better care improving their health outcomes (adverse perinatal outcomes for mother and newborn), costs (medication, hospitalization, qualified staff) and patient perceived quality. Therefore a Clinical Decision Support System was developed to give support to the Obstetricians. In this article, we had proposed a robust method to explore and model a source of clinical information with the purpose of obtaining all possible knowledge. Generally, in classification models are difficult to know the contribution that each attribute provides to the model. We had worked in this direction to offer transparency to models that may be considered as black boxes. The positive results obtained from both the information recovery system and the predictions and explanations of the classification show the effectiveness and strength of this tool. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T10:20:59Z No. of bitstreams: 1 ijimai_4_7_3_pdf_17377.pdf: 692348 bytes, checksum: 1994c566195b8d3e37ef9673c6a1852a (MD5); Made available in DSpace on 2021-09-27T10:20:59Z (GMT). No. of bitstreams: 1 ijimai_4_7_3_pdf_17377.pdf: 692348 bytes, checksum: 1994c566195b8d3e37ef9673c6a1852a (MD5)

Saez, Yago Baldominos Gómez, Alejandro Rada, Fernando https://reunir.unir.net/handle/123456789/11904 2021-09-27T09:37:40Z

DataCare: Big Data Analytics Solution for Intelligent Healthcare Management Saez, Yago; Baldominos Gómez, Alejandro; Rada, Fernando This paper presents DataCare, a solution for intelligent healthcare management. This product is able not only to retrieve and aggregate data from different key performance indicators in healthcare centers, but also to estimate future values for these key performance indicators and, as a result, fire early alerts when undesirable values are about to occur or provide recommendations to improve the quality of service. DataCare’s core processes are built over a free and open-source cross-platform document-oriented database (MongoDB), and Apache Spark, an open-source cluster-computing framework. This architecture ensures high scalability capable of processing very high data volumes coming at fast speed from a large set of sources. This article describes the architecture designed for this project and the results obtained after conducting a pilot in a healthcare center. Useful conclusions have been drawn regarding how key performance indicators change based on different situations, and how they affect patients’ satisfaction. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T09:37:40Z No. of bitstreams: 1 ijimai_4_7_2_pdf_16566.pdf: 784802 bytes, checksum: 14d2bb079d5b214a21c2acf687d97687 (MD5); Made available in DSpace on 2021-09-27T09:37:40Z (GMT). No. of bitstreams: 1 ijimai_4_7_2_pdf_16566.pdf: 784802 bytes, checksum: 14d2bb079d5b214a21c2acf687d97687 (MD5)

Hernández Medrano, Ignacio Tello Guijarro, Jorge Belda, Cristóbal Ureña, Alberto Salcedo, Ignacio Espinosa-Anke, Luis Saggion, Horacio https://reunir.unir.net/handle/123456789/11903 2021-09-27T09:09:25Z

Savana: Re-using Electronic Health Records with Artificial Intelligence Hernández Medrano, Ignacio; Tello Guijarro, Jorge; Belda, Cristóbal; Ureña, Alberto; Salcedo, Ignacio; Espinosa-Anke, Luis; Saggion, Horacio Health information grows exponentially (doubling every 5 years), thus generating a sort of inflation of science, i.e. the generation of more knowledge than we can leverage. In an unprecedented data-driven shift, today doctors have no longer time to keep updated. This fact explains why only one in every five medical decisions is based strictly on evidence, which inevitably leads to variability. A good solution lies on clinical decision support systems, based on big data analysis. As the processing of large amounts of information gains relevance, automatic approaches become increasingly capable to see and correlate information further and better than the human mind can. In this context, healthcare professionals are increasingly counting on a new set of tools in order to deal with the growing information that becomes available to them on a daily basis. By allowing the grouping of collective knowledge and prioritizing “mindlines” against “guidelines”, these support systems are among the most promising applications of big data in health. In this demo paper we introduce Savana, an AI-enabled system based on Natural Language Processing (NLP) and Neural Networks, capable of, for instance, the automatic expansion of medical terminologies, thus enabling the re-use of information expressed in natural language in clinical reports. This automatized and precise digital extraction allows the generation of a real time information engine, which is currently being deployed in healthcare institutions, as well as clinical research and management. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-09-27T09:09:25Z No. of bitstreams: 1 ijimai_4_7_1_pdf_22755.pdf: 935126 bytes, checksum: 8b6c3a77baefcab321a6826593d81f2e (MD5); Made available in DSpace on 2021-09-27T09:09:25Z (GMT). No. of bitstreams: 1 ijimai_4_7_1_pdf_22755.pdf: 935126 bytes, checksum: 8b6c3a77baefcab321a6826593d81f2e (MD5)