https://reunir.unir.net/handle/123456789/12386 2024-11-08T11:33:34Z https://reunir.unir.net/handle/123456789/12418 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) https://reunir.unir.net/handle/123456789/12417 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) https://reunir.unir.net/handle/123456789/12416 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) https://reunir.unir.net/handle/123456789/12415 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) https://reunir.unir.net/handle/123456789/12414 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) https://reunir.unir.net/handle/123456789/12412 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) https://reunir.unir.net/handle/123456789/12411 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) https://reunir.unir.net/handle/123456789/12410 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) https://reunir.unir.net/handle/123456789/12409 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) https://reunir.unir.net/handle/123456789/12408 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) https://reunir.unir.net/handle/123456789/12407 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) https://reunir.unir.net/handle/123456789/12406 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) https://reunir.unir.net/handle/123456789/12405 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) https://reunir.unir.net/handle/123456789/12404 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) https://reunir.unir.net/handle/123456789/12403 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) https://reunir.unir.net/handle/123456789/12400 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) https://reunir.unir.net/handle/123456789/12399 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) https://reunir.unir.net/handle/123456789/12387 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)