https://reunir.unir.net/handle/123456789/10930 2025-10-19T07:35:19Z https://reunir.unir.net/handle/123456789/11707 A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding Kamble, Shailesh; Thakur, Nileshsingh; Bajaj, Preeti Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-08-18T12:21:32Z No. of bitstreams: 1 ijimai20164_2_14_pdf_10496.pdf: 2373672 bytes, checksum: e53e9e5ed2591a416635d72ffd9dc941 (MD5); Made available in DSpace on 2021-08-18T12:21:32Z (GMT). No. of bitstreams: 1 ijimai20164_2_14_pdf_10496.pdf: 2373672 bytes, checksum: e53e9e5ed2591a416635d72ffd9dc941 (MD5) https://reunir.unir.net/handle/123456789/11706 Design and Implementation of a Combinatorial Optimization Multi-population Meta-heuristic for Solving Vehicle Routing Problems Osaba, Eneko; Díaz, Fernando This paper aims to give a presentation of the PhD defended by Eneko Osaba on November 16th, 2015, at the University of Deusto. The thesis can be placed in the field of artificial intelligence. Specifically, it is related with multi- population meta-heuristics for solving vehicle routing problems. The dissertation was held in the main auditorium of the University, in a publicly open presentation. After the presentation, Eneko was awarded with the highest grade (cum laude). Additionally, Eneko obtained the PhD obtaining award granted by the Basque Government through. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-08-18T12:14:06Z No. of bitstreams: 1 ijimai20164_2_13_pdf_59073.pdf: 319910 bytes, checksum: 81d038ea5224138b810baf50dddf886c (MD5); Made available in DSpace on 2021-08-18T12:14:06Z (GMT). No. of bitstreams: 1 ijimai20164_2_13_pdf_59073.pdf: 319910 bytes, checksum: 81d038ea5224138b810baf50dddf886c (MD5) https://reunir.unir.net/handle/123456789/11705 Intelligent e-Learning Systems: An Educational Paradigm Shift Bhattacharya, Suman; Nath, Sayan Learning is the long process of transforming information as well as experience into knowledge, skills, attitude and behaviors. To make up the wide gap between the demand of increasing higher education and comparatively limited resources, more and more educational institutes are looking into instructional technology. Use of online resources not only reduces the cost of education but also meet the needs of society. Intelligent e-learning has become one of the important channels to reach out to students exceeding geographic boundaries. Besides this, the characteristics of e-learning have complicated the process of education, and have brought challenges to both instructors and students. This paper will focus on the discussion of different discipline of intelligent e-learning like scaffolding based e-learning, personalized e-learning, confidence based e-learning, intelligent tutoring system, etc. to illuminate the educational paradigm shift in intelligent e-learning system. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-08-18T12:02:38Z No. of bitstreams: 1 ijimai20164_2_12_pdf_14815.pdf: 338266 bytes, checksum: de197b27d52887839f622c09c08fef86 (MD5); Made available in DSpace on 2021-08-18T12:02:38Z (GMT). No. of bitstreams: 1 ijimai20164_2_12_pdf_14815.pdf: 338266 bytes, checksum: de197b27d52887839f622c09c08fef86 (MD5) https://reunir.unir.net/handle/123456789/11704 Novel Agent Based-approach for Industrial Diagnosis: A Combined use Between Case-based Reasoning and Similarity Measure Taghezout, Noria; Benkaddour, Fatima Zohra; Ascar, Bouabdellah In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agent- based modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis) lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-08-18T11:48:57Z No. of bitstreams: 1 ijimai20164_2_11_pdf_12710.pdf: 814074 bytes, checksum: 9b2ae5aef83afbb1eb8b3039a54fc2a9 (MD5); Made available in DSpace on 2021-08-18T11:48:57Z (GMT). No. of bitstreams: 1 ijimai20164_2_11_pdf_12710.pdf: 814074 bytes, checksum: 9b2ae5aef83afbb1eb8b3039a54fc2a9 (MD5) https://reunir.unir.net/handle/123456789/11703 Integrating Agents into a Collaborative Knowledge-based System for Business Rules Consistency Management Houari, Nawal Sad; Taghezout, Noria Capitalization and reuse of expert knowledge are very important for the survival of an enterprise. This paper presents a collaborative approach that utilizes domain ontology and agents. Thanks to our knowledge formalizing process, we give to domain expert an opportunity to store different forms of retrieved knowledge from experiences, design rules, business rules, decision processes, etc. The ontology is built to support business rules management. The global architecture is mainly composed of agents such as Expert agent, Evaluator agent, Translator agent, Security agent and Supervisor agent. The Evaluator agent is at the heart of our functional architecture, its role is to detect the problems that may arise in the consistency management module and provides a solution to these problems in order to validate the accuracy of business rules. In addition, a Security agent is defined to handle both security aspects in rules modeling and multi-agent system. The proposed approach is different from the others in terms of the number of rule’s inconsistencies which are detected and treated like contradiction, redundancy, invalid rules, domain violation and rules never applicable, the collaboration that is initiated among business experts and the guarantee of security of the business rules and all the agents which constitute our system. The developed collaborative system is applied in an industrial case study.C Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-08-18T11:01:40Z No. of bitstreams: 1 ijimai20164_2_10_pdf_59746.pdf: 912441 bytes, checksum: ba6781da90f413e90b3c4611ee0d8de6 (MD5); Made available in DSpace on 2021-08-18T11:01:40Z (GMT). No. of bitstreams: 1 ijimai20164_2_10_pdf_59746.pdf: 912441 bytes, checksum: ba6781da90f413e90b3c4611ee0d8de6 (MD5) https://reunir.unir.net/handle/123456789/11702 Genetic Algorithm for Restricted Maximum k-Satisfiability in the Hopfield Network Kasihmuddin, Mohd Shareduwan Bin Mohd; Mansor, Mohd Asyraf Bin; Sathasivam, Saratha The restricted Maximum k-Satisfiability MAX- kSAT is an enhanced Boolean satisfiability counterpart that has attracted numerous amount of research. Genetic algorithm has been the prominent optimization heuristic algorithm to solve constraint optimization problem. The core motivation of this paper is to introduce Hopfield network incorporated with genetic algorithm in solving MAX-kSAT problem. Genetic algorithm will be integrated with Hopfield network as a single network. The proposed method will be compared with the conventional Hopfield network. The results demonstrate that Hopfield network with genetic algorithm outperforms conventional Hopfield networks. Furthermore, the outcome had provided a solid evidence of the robustness of our proposed algorithms to be used in other satisfiability problem. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-08-18T10:27:56Z No. of bitstreams: 1 ijimai20164_2_9_pdf_33484.pdf: 569824 bytes, checksum: 82fa89cb20fe45a2cb3f4b41004bcde5 (MD5); Made available in DSpace on 2021-08-18T10:27:56Z (GMT). No. of bitstreams: 1 ijimai20164_2_9_pdf_33484.pdf: 569824 bytes, checksum: 82fa89cb20fe45a2cb3f4b41004bcde5 (MD5) https://reunir.unir.net/handle/123456789/11693 Euclidean Distance Distortion Based Robust and Blind Mesh Watermarking Dey, Nilanjan; Amar, Yesmine Ben; Trabelsi, Imen; Bouhlel, Salim The three-dimensional (3D) polygonal meshes are recently widely used in several domains, which necessitate the realistic visualization of the objects. Moreover, there is an urgent need to protect the 3D data properties for preventing unauthorized reproduction. The 3D digital watermarking technology is one of the best solutions to protect data from piracy during transmission through the internet. The current work proposed a novel robust watermarking scheme of polygonal meshes for copyright protection purposes. The proposed algorithm is based on the characteristics of the mesh geometry to embed a sequence of data bits into the object by slightly adjusting the vertex positions. Furthermore, the proposed method used a blind detection scheme. The watermarked model is perceptually indistinguishable from the original one and the embedded watermark is invariant to affine transformation. Through simulations, the quality of the watermarked object as well as the inserted watermark robustness against various types of attacks were tested and evaluated to prove the validity and the efficiency of our algorithm. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-30T12:19:30Z No. of bitstreams: 1 ijimai20164_2_8_pdf_17392.pdf: 566963 bytes, checksum: dfddc5c92ea1e7ec9754e8fbc61f48bf (MD5); Made available in DSpace on 2021-07-30T12:19:30Z (GMT). No. of bitstreams: 1 ijimai20164_2_8_pdf_17392.pdf: 566963 bytes, checksum: dfddc5c92ea1e7ec9754e8fbc61f48bf (MD5) https://reunir.unir.net/handle/123456789/11692 Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF Choudhary, Saket Kumar; Singh, Karan Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model) in distributed delay framework (DDF) for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI) distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-30T11:51:41Z No. of bitstreams: 1 ijimai20164_2_7_pdf_14081.pdf: 2129610 bytes, checksum: da3f388af06535374024b64a897909ec (MD5); Made available in DSpace on 2021-07-30T11:51:41Z (GMT). No. of bitstreams: 1 ijimai20164_2_7_pdf_14081.pdf: 2129610 bytes, checksum: da3f388af06535374024b64a897909ec (MD5) https://reunir.unir.net/handle/123456789/11691 Erythrocyte Features for Malaria Parasite Detection in Microscopic Images of Thin Blood Smear: A Review Devi, Salam Shuleenda; Sheikh, Shah Alam; Laskar, Rabul Hussain Microscopic image analysis of blood smear plays a very important role in characterization of erythrocytes in screening of malaria parasites. The characteristics feature of erythrocyte changes due to malaria parasite infection. The microscopic features of the erythrocyte include morphology, intensity and texture. In this paper, the different features used to differentiate the non- infected and malaria infected erythrocyte have been reviewed. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-30T11:13:39Z No. of bitstreams: 1 ijimai20164_2_6_pdf_16718.pdf: 322419 bytes, checksum: 6a69637a566b053de70598cbafaf3f31 (MD5); Made available in DSpace on 2021-07-30T11:13:39Z (GMT). No. of bitstreams: 1 ijimai20164_2_6_pdf_16718.pdf: 322419 bytes, checksum: 6a69637a566b053de70598cbafaf3f31 (MD5) https://reunir.unir.net/handle/123456789/11690 Push Recovery for Humanoid Robot in Dynamic Environment and Classifying the Data Using K-Mean Parashar, Anubha; Parashar, Apoorva; Goyal, Somya Push recovery is prime ability that is essential to be incorporated in the process of developing a robust humanoid robot to support bipedalism. In real environment it is very essential for humanoid robot to maintain balance. In this paper we are generating a control system and push recovery controller for humanoid robot walking. We apply different kind of pushes to humanoid robot and the algorithm that can bring a change in the walking stage to sustain walking. The simulation is done in 3D environment using Webots. This paper describes techniques for feature selection to foreshow push recovery for hip, ankle and knee joint. We train the system by K-Mean algorithm and testing is done on crouch data and tested results are reported. Random push data of humanoid robot is collected and classified to see whether push lie in safer region and then tested on given proposed system. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-30T10:31:17Z No. of bitstreams: 1 ijimai20164_2_5_pdf_12005.pdf: 867542 bytes, checksum: 3d709f1ebe08c84a8087013a438ca16c (MD5); Made available in DSpace on 2021-07-30T10:31:17Z (GMT). No. of bitstreams: 1 ijimai20164_2_5_pdf_12005.pdf: 867542 bytes, checksum: 3d709f1ebe08c84a8087013a438ca16c (MD5) https://reunir.unir.net/handle/123456789/11622 Face Detection for Augmented Reality Application Using Boosting-based Techniques Hbali, Youssef; Ballihi, Lahoucine; Sadgal, Mohammed; Abdelaziz, El Fazziki Augmented reality has gained an increasing research interest over the few last years. Customers requirements have become more intense and more demanding, the need of the different industries to re-adapt their products and enhance them by recent advances in the computer vision and more intelligence has become a necessary. In this work we present a marker-less augmented reality application that can be used and expanded in the e-commerce industry. We take benefit of the well known boosting techniques to train and evaluate different face detectors using the multi-block local binary features. The work purpose is to select the more relevant training parameters in order to maximize the classification accuracy. Using the resulted face detector, the position of the face will serve as a marker in the proposed augmented reality. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-15T10:49:44Z No. of bitstreams: 1 ijimai20164_2_4_pdf_92526.pdf: 1689500 bytes, checksum: abda75ffcf1d33d37b4a091413f84ba2 (MD5); Made available in DSpace on 2021-07-15T10:49:44Z (GMT). No. of bitstreams: 1 ijimai20164_2_4_pdf_92526.pdf: 1689500 bytes, checksum: abda75ffcf1d33d37b4a091413f84ba2 (MD5) https://reunir.unir.net/handle/123456789/11621 Feature Selection for Image Retrieval based on Genetic Algorithm Welekar, Rashmi; Kushwaha, Preeti This paper describes the development and implementation of feature selection for content based image retrieval. We are working on CBIR system with new efficient technique. In this system, we use multi feature extraction such as colour, texture and shape. The three techniques are used for feature extraction such as colour moment, gray level co- occurrence matrix and edge histogram descriptor. To reduce curse of dimensionality and find best optimal features from feature set using feature selection based on genetic algorithm. These features are divided into similar image classes using clustering for fast retrieval and improve the execution time. Clustering technique is done by k-means algorithm. The experimental result shows feature selection using GA reduces the time for retrieval and also increases the retrieval precision, thus it gives better and faster results as compared to normal image retrieval system. The result also shows precision and recall of proposed approach compared to previous approach for each image class. The CBIR system is more efficient and better performs using feature selection based on Genetic Algorithm. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-15T10:10:11Z No. of bitstreams: 1 ijimai20164_2_3_pdf_46881.pdf: 643004 bytes, checksum: ca89f2beb5d1858e23721109561e8474 (MD5); Made available in DSpace on 2021-07-15T10:10:11Z (GMT). No. of bitstreams: 1 ijimai20164_2_3_pdf_46881.pdf: 643004 bytes, checksum: ca89f2beb5d1858e23721109561e8474 (MD5) https://reunir.unir.net/handle/123456789/11620 Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks Bacallao-Vidal, Jesús Concepción; Machado-Fernández, José Raúl The main problem faced by naval radars is the elimination of the clutter input which is a distortion signal appearing mixed with target reflections. Recently, the Pareto distribution has been related to sea clutter measurements suggesting that it may provide a better fit than other traditional distributions. The authors propose a new method for estimating the Pareto shape parameter based on artificial neural networks. The solution achieves a precise estimation of the parameter, having a low computational cost, and outperforming the classic method which uses Maximum Likelihood Estimates (MLE). The presented scheme contributes to the development of the NATE detector for Pareto clutter, which uses the knowledge of clutter statistics for improving the stability of the detection, among other applications. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-15T10:03:45Z No. of bitstreams: 1 ijimai20164_2_1_pdf_46986.pdf: 765872 bytes, checksum: 5ff45ba141750ebfea501766cb2441d6 (MD5); Made available in DSpace on 2021-07-15T10:03:45Z (GMT). No. of bitstreams: 1 ijimai20164_2_1_pdf_46986.pdf: 765872 bytes, checksum: 5ff45ba141750ebfea501766cb2441d6 (MD5) https://reunir.unir.net/handle/123456789/11619 IJIMAI Editor's Note - Vol. 4 Issue 2 Verdú, Elena The research works presented in this regular issue cover different fields of application such as medicine, industry or education, proposing solutions based on various topics of interest, as for example: neural networks, neuro-fuzzy systems, case-based reasoning systems, image retrieval, classification, feature selection, meta-heuristics, constraint satisfaction, or knowledge-based systems. The International Journal of Interactive Multimedia and Artificial Intelligence provides an interdisciplinary forum in which scientists and professionals share their research results and report new advances on Artificial Intelligence tools and tools that use Artificial Intelligence with interactive multimedia techniques. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-15T09:48:22Z No. of bitstreams: 1 ijimai20164_2_0_pdf_27843.pdf: 133661 bytes, checksum: e81eb60ad7130c72351735585358d288 (MD5); Made available in DSpace on 2021-07-15T09:48:22Z (GMT). No. of bitstreams: 1 ijimai20164_2_0_pdf_27843.pdf: 133661 bytes, checksum: e81eb60ad7130c72351735585358d288 (MD5) https://reunir.unir.net/handle/123456789/11618 Analyzing the EEG Signals in Order to Estimate the Depth of Anesthesia using Wavelet and Fuzzy Neural Networks Esmaeilpour, Mansour; Mohammadi, Ali Reis Ali Estimating depth of Anesthesia in patients with the objective to administer the right dosage of drug has always attracted the attention of specialists. To study Anesthesia, researchers analyze brain waves since this is the place which is directly affected by the drug. This study aimed to estimate the depth of Anesthesia using electroencephalogram (EGG) signals, wavelet transform, and adaptive Neuro Fuzzy inference system (ANFIS). ANFIS can estimate the depth of Anesthesia with high accuracy. A set of EEG signals regarding consciousness, moderate Anesthesia, deep Anesthesia, and iso-electric point were collected from the American Society of Anesthesiologists (ASA) and PhysioNet. First, the extracted features were combined using wavelet and spectral analysis after which the target features were selected. Later, the features were classified into four categories. The results obtained revealed that the accuracy of the proposed method was 98.45%. Since the visual analysis of EEG signals is difficult, the proposed method can significantly help anesthesiologists estimate the depth of Anesthesia. Further, the results showed that ANFIS could significantly increase the accuracy of Anesthesia depth estimation. Finally, the system was deemed to be advantageous since it was also capable of updating in real-time situations as well. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-15T09:24:44Z No. of bitstreams: 1 ijimai20164_2_2_pdf_16114.pdf: 2759022 bytes, checksum: b004239a3cca81ed2384e043bddb508b (MD5); Made available in DSpace on 2021-07-15T09:24:44Z (GMT). No. of bitstreams: 1 ijimai20164_2_2_pdf_16114.pdf: 2759022 bytes, checksum: b004239a3cca81ed2384e043bddb508b (MD5) https://reunir.unir.net/handle/123456789/11616 Comparison between Famous Game Engines and Eminent Games Mishra, Prerna; Shrawankar, Urmila Nowadays game engines are imperative for building 3D applications and games. This is for the reason that the engines appreciably reduce resources for employing obligatory but intricate utilities. This paper elucidates about a game engine, popular games developed by these engines and its foremost elements. It portrays a number of special kinds of contemporary game developed by engines in the way of their aspects, procedure and deliberates their stipulations with comparison. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-15T09:07:34Z No. of bitstreams: 1 ijimai20164_1_13_pdf_63301.pdf: 1739519 bytes, checksum: 5c2c79aedf439d880ec344e9f946a3d3 (MD5); Made available in DSpace on 2021-07-15T09:07:34Z (GMT). No. of bitstreams: 1 ijimai20164_1_13_pdf_63301.pdf: 1739519 bytes, checksum: 5c2c79aedf439d880ec344e9f946a3d3 (MD5) https://reunir.unir.net/handle/123456789/11614 Correlation Between Coupling Metrics Values and Number of Classes in Multimedia Java Projects: A Case Study Bivde, V S; Sarasu, P Coupling is an interdependence relationship between the modules of object-oriented software. It is a property with the most influence on quality attributes of the object-oriented software. Coupling with high values results in complex software design hence software professionals try to keep the coupling as low as possible. The values of coupling metrics are dependent on the type of input source code. Reusability is the main feature of object-oriented languages, so coupling occurs due to reuse of code modules. This paper investigates a correlation between the values of coupling metrics and the number of classes in the multimedia Java code. Here, a case study of a banking multimedia Java project with its forty different versions is conducted to comments on this correlation. The analysis of the results shows that, if the input source code is with a large number of classes then it results in high coupling values. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-14T12:34:03Z No. of bitstreams: 0; Made available in DSpace on 2021-07-14T12:34:03Z (GMT). No. of bitstreams: 0 https://reunir.unir.net/handle/123456789/11613 Evaluating the Emotional State of a User Using a Webcam Magdin, Martin; Turcani, Milan; Hudec, Lukas In online learning is more difficult for teachers identify to see how individual students behave. Student’s emotions like self-esteem, motivation, commitment, and others that are believed to be determinant in student’s performance can not be ignored, as they are known (affective states and also learning styles) to greatly influence student’s learning. The ability of the computer to evaluate the emotional state of the user is getting bigger attention. By evaluating the emotional state, there is an attempt to overcome the barrier between man and non-emotional machine. Recognition of a real time emotion in e-learning by using webcams is research area in the last decade. Improving learning through webcams and microphones offers relevant feedback based upon learner’s facial expressions and verbalizations. The majority of current software does not work in real time – scans face and progressively evaluates its features. The designed software works by the use neural networks in real time which enable to apply the software into various fields of our lives and thus actively influence its quality. Validation of face emotion recognition software was annotated by using various experts. These expert findings were contrasted with the software results. An overall accuracy of our software based on the requested emotions and the recognized emotions is 78%. Online evaluation of emotions is an appropriate technology for enhancing the quality and efficacy of e-learning by including the learner´s emotional states. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-14T12:24:01Z No. of bitstreams: 1 ijimai20164_1_12_pdf_20682.pdf: 574723 bytes, checksum: 6754097ab397e538598834b8a217dd14 (MD5); Made available in DSpace on 2021-07-14T12:24:01Z (GMT). No. of bitstreams: 1 ijimai20164_1_12_pdf_20682.pdf: 574723 bytes, checksum: 6754097ab397e538598834b8a217dd14 (MD5) https://reunir.unir.net/handle/123456789/11612 IJIMAI Editor's Note - Vol. 4 Issue 1 Bahaj, Mohamed The research works presented in this issue are based on various topics of interest, among which are included: Pattern Recognition, Multimedia Information Retrieval, Knowledge extraction and knowledge mining, Data mining, Intelligent Systems & Artificial Intelligence, Wireless Technology, Network Telecommunication, Security & Network Management, Advanced Network Technologies. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-14T12:09:00Z No. of bitstreams: 1 ijimai20164_1_0_pdf_95835.pdf: 145706 bytes, checksum: 8fafdd96430bbebd399d73497e3fa642 (MD5); Made available in DSpace on 2021-07-14T12:09:00Z (GMT). No. of bitstreams: 1 ijimai20164_1_0_pdf_95835.pdf: 145706 bytes, checksum: 8fafdd96430bbebd399d73497e3fa642 (MD5) https://reunir.unir.net/handle/123456789/11611 Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach Ettaouil, Mohamed; Haddouch, Khalid; Elmoutaoukil, Karim A wide variety of real world optimization problems can be modelled as Weighted Constraint Satisfaction Problems (WCSPs). In this paper, we model this problem in terms of in original 0-1 quadratic programming subject to leaner constraints. View it performance, we use the continuous Hopfield network to solve the obtained model basing on original energy function. To validate our model, we solve several instance of benchmarking WCSP. In this regard, our approach recognizes the optimal solution of the said instances. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-14T11:34:23Z No. of bitstreams: 1 ijimai20164_1_11_pdf_42425.pdf: 1161738 bytes, checksum: a4a814ec90a8a9fa881788f7c869b1d6 (MD5); Made available in DSpace on 2021-07-14T11:34:23Z (GMT). No. of bitstreams: 1 ijimai20164_1_11_pdf_42425.pdf: 1161738 bytes, checksum: a4a814ec90a8a9fa881788f7c869b1d6 (MD5) https://reunir.unir.net/handle/123456789/11610 PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization Chebli, S; El Akkary, Ahmed In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI) based congestion controller in active queue management (AQM) router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-14T10:50:24Z No. of bitstreams: 1 ijimai20164_1_10_pdf_18562.pdf: 2282480 bytes, checksum: f9682b7011573900517e96c73e1a0373 (MD5); Made available in DSpace on 2021-07-14T10:50:24Z (GMT). No. of bitstreams: 1 ijimai20164_1_10_pdf_18562.pdf: 2282480 bytes, checksum: f9682b7011573900517e96c73e1a0373 (MD5) https://reunir.unir.net/handle/123456789/11573 Statistical Comparisons of the Top 10 Algorithms in Data Mining for Classification Task Settouti, Nesma; El Amine Bechar, Mohammed; Amine Chikh, Mohammed This work is builds on the study of the 10 top data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) community in December 2006. We address the same study, but with the application of statistical tests to establish, a more appropriate and justified ranking classifier for classification tasks. Current studies and practices on theoretical and empirical comparison of several methods, approaches, advocated tests that are more appropriate. Thereby, recent studies recommend a set of simple and robust non-parametric tests for statistical comparisons classifiers. In this paper, we propose to perform non-parametric statistical tests by the Friedman test with post-hoc tests corresponding to the comparison of several classifiers on multiple data sets. The tests provide a better judge for the relevance of these algorithms. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T12:30:51Z No. of bitstreams: 1 ijimai20164_1_9_pdf_19943.pdf: 791619 bytes, checksum: 692cbe571e5c46d528cd66fb1a5d2e2b (MD5); Made available in DSpace on 2021-07-07T12:30:51Z (GMT). No. of bitstreams: 1 ijimai20164_1_9_pdf_19943.pdf: 791619 bytes, checksum: 692cbe571e5c46d528cd66fb1a5d2e2b (MD5) https://reunir.unir.net/handle/123456789/11572 A Distributed Intelligent System for Emergency Convoy Benalla, Mohammed; Achchab, Boujemâa; Hrimech, Hamid The general problem that guides this research is the ability to design a distributed intelligent system for guiding the emergency convoys; a solution that will be based on a group of agents and on the analysis of traffic in order to generate collective functional response. It fits into the broader issue of Distributed Artificial System (DAI), which is to operate a cooperatively computer agent into multi-agents system (MAS). This article describes conceptually two fundamental questions of emergency convoys. The first question is dedicated to find a response to the traffic situation (i.e. fluid way), while the second is devoted to the convoy orientation; while putting the point on the distributed and cooperative resolution for the general problem. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T12:02:53Z No. of bitstreams: 1 ijimai20164_1_8_pdf_22976.pdf: 1051032 bytes, checksum: 59275d1c104b9e34ad38f85c61b490ff (MD5); Made available in DSpace on 2021-07-07T12:02:53Z (GMT). No. of bitstreams: 1 ijimai20164_1_8_pdf_22976.pdf: 1051032 bytes, checksum: 59275d1c104b9e34ad38f85c61b490ff (MD5) https://reunir.unir.net/handle/123456789/11571 MaxHopCount: A New Drop Policy to Optimize Messages Delivery Rate in Delay Tolerant Networks Harrati, Youssef; Abdali, Abdelmounaim Communication has become a necessity, not only between every point on the earth, but also on the globe. That includes hard topography, highlands, underwater areas, and also space- crafts on other planets. However, the classic wired internet cannot be implemented in such areas, hence, researchers have invented wireless networks. The big challenge for wireless networking nowadays, is maintaining nodes connected in some difficult conditions, such as intermittent connectivity, power failure, and lot of obstacles for the interplanetary networks. In these challenging circumstances, a new networking model arises; it is Delay Tolerant networking which is based on the Store-Carry-and-Forward mechanism. Thus, a node may keep a message in its buffer for long periods of time; until a delivery or forward chance arises then it transmit it to other nodes. One of the big issues that confront this mechanism is the congestion of nodes buffer due to the big number of messages and the limited buffer size. Here, researchers have proposed buffer management algorithms in order to deal with the buffer overload problem, and they called it Drop Policies. In our present work, we propose a new Drop policy which we have compared to other existing policies in different conditions and with different routing protocols, and it always shows good result in term of number of delivered messages, network overhead and also average of latency. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T11:20:28Z No. of bitstreams: 1 ijimai20164_1_7_pdf_15922.pdf: 1094550 bytes, checksum: 6ebe3e875ad2ec225b61eb3edec39c74 (MD5); Made available in DSpace on 2021-07-07T11:20:28Z (GMT). No. of bitstreams: 1 ijimai20164_1_7_pdf_15922.pdf: 1094550 bytes, checksum: 6ebe3e875ad2ec225b61eb3edec39c74 (MD5) https://reunir.unir.net/handle/123456789/11570 Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes Boulid, Youssef; Souhar, Abdelghani; Elyoussfi Elkettani, Mohamed In a character recognition systems, the segmentation phase is critical since the accuracy of the recognition depend strongly on it. In this paper we present an approach based on Markov Decision Processes to extract text lines from binary images of Arabic handwritten documents. The proposed approach detects the connected components belonging to the same line by making use of knowledge about features and arrangement of those components. The initial results show that the system is promising for extracting Arabic handwritten lines. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T11:02:10Z No. of bitstreams: 1 ijimai20164_1_6_pdf_34205.pdf: 1472159 bytes, checksum: d6ff52a2433f187fb0050fb9d5cfbefe (MD5); Made available in DSpace on 2021-07-07T11:02:10Z (GMT). No. of bitstreams: 1 ijimai20164_1_6_pdf_34205.pdf: 1472159 bytes, checksum: d6ff52a2433f187fb0050fb9d5cfbefe (MD5) https://reunir.unir.net/handle/123456789/11569 Multilayer Perceptron: Architecture Optimization and Training Ramchoun, Hassan; Ghanou, Youssef; Ettaouil, Mohamed; Janati Idrissi, Mohammed Amine The multilayer perceptron has a large wide of classification and regression applications in many fields: pattern recognition, voice and classification problems. But the architecture choice has a great impact on the convergence of these networks. In the present paper we introduce a new approach to optimize the network architecture, for solving the obtained model we use the genetic algorithm and we train the network with a back-propagation algorithm. The numerical results assess the effectiveness of the theoretical results shown in this paper, and the advantages of the new modeling compared to the previous model in the literature. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T10:37:59Z No. of bitstreams: 1 ijimai20164_1_5_pdf_30533.pdf: 1396853 bytes, checksum: 86a1788f74a4d54fa0daf8990c74723b (MD5); Made available in DSpace on 2021-07-07T10:37:59Z (GMT). No. of bitstreams: 1 ijimai20164_1_5_pdf_30533.pdf: 1396853 bytes, checksum: 86a1788f74a4d54fa0daf8990c74723b (MD5) https://reunir.unir.net/handle/123456789/11568 A Self-Calibration Method of Zooming Camera El Batteoui, Ismail; Saaidi, Abderrahim; Satori, Khalid In this article we proposed a novel approach to self- calibrate a camera with variable focal length. We show that the estimation of camera’s intrinsic parameters is possible from only two points of an unknown planar scene. The projection of these points by using the projection matrices in two images only permit us to obtain a system of equations according to the camera’s intrinsic parameters . From this system we formulated a nonlinear cost function which its minimization allows us to estimate the camera’s intrinsic parameters in each view. The results on synthetic and real data justify the robustness of our method in term of reliability and convergence. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T09:48:28Z No. of bitstreams: 1 ijimai20164_1_4_pdf_94156.pdf: 1459478 bytes, checksum: 40f444fd2dbb2363fc3be783e7b98399 (MD5); Made available in DSpace on 2021-07-07T09:48:28Z (GMT). No. of bitstreams: 1 ijimai20164_1_4_pdf_94156.pdf: 1459478 bytes, checksum: 40f444fd2dbb2363fc3be783e7b98399 (MD5) https://reunir.unir.net/handle/123456789/11567 Golden Ball Algorithm for solving Flow Shop Scheduling Problem Sayoti, Fatima; Essaid Riffi, Mohammed The Flow Shop Scheduling Problem (FSSP) is notoriously NP-hard combinatorial optimization problem. The goal is to find a schedule that minimizes the makespan. This paper proposes an adaptation of a new approach called Golden Ball Algorithm (GBA). The proposed algorithm has been never tested with FSSP; it’s based on soccer concept to obtain the optimal solution. Numerical results are presented for 22 instances of OR- Library. The computational results indicate that this approach is practical for small OR-Library instances. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T09:38:36Z No. of bitstreams: 1 ijimai20164_1_3_pdf_32338.pdf: 776822 bytes, checksum: 58fdd873a689174d44ca4486a8b45861 (MD5); Made available in DSpace on 2021-07-07T09:38:36Z (GMT). No. of bitstreams: 1 ijimai20164_1_3_pdf_32338.pdf: 776822 bytes, checksum: 58fdd873a689174d44ca4486a8b45861 (MD5) https://reunir.unir.net/handle/123456789/11566 Offline Face Recognition System Based on GaborFisher Descriptors and Hidden Markov Models Elgarrai, Zineb; Elmeslouhi, Othmane; Kardouchi, Mustapha; Allali, Hakim; Selouani, Sid-Ahmed This paper presents a new offline face recognition system. The proposed system is built on one dimensional left-to- right Hidden Markov Models (1D-HMMs). Facial image features are extracted using Gabor wavelets. The dimensionality of these features is reduced using the Fisher’s Discriminant Analysis method to keep only the most relevant information. Unlike existing techniques using 1D-HMMs, in classification step, the proposed system employs 1D-HMMs to find the relationship between reduced features components directly without any additional segmentation step of interest regions in the face image. The performance evaluation of the proposed method was performed with AR database and the proposed method showed a high recognition rate for this database. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T09:29:22Z No. of bitstreams: 1 ijimai20164_1_2_pdf_27472.pdf: 1109380 bytes, checksum: 103a2581b15386f95d5275d2dc31ae67 (MD5); Made available in DSpace on 2021-07-07T09:29:22Z (GMT). No. of bitstreams: 1 ijimai20164_1_2_pdf_27472.pdf: 1109380 bytes, checksum: 103a2581b15386f95d5275d2dc31ae67 (MD5) https://reunir.unir.net/handle/123456789/11565 Segmentation-free Word Spotting for Handwritten Arabic Documents Khaissidi, Ghizlane; Elfakir, Youssef; Mrabti, Mostafa; El Yacoubi, Mounîm; Chenouni, Driss In this paper we present an unsupervised segmentation-free method for spotting and searching query, especially, for images documents in handwritten Arabic, for this, Histograms of Oriented Gradients (HOGs) are used as the feature vectors to represent the query and documents image. Then, we compress the descriptors with the product quantization method. Finally, a better representation of the query is obtained by using the Support Vector Machines (SVM). Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-07-07T09:18:45Z No. of bitstreams: 1 ijimai20164_1_1_pdf_95245.pdf: 1694903 bytes, checksum: 08127b4ffd49d73236de8faf6cc1fa9d (MD5); Made available in DSpace on 2021-07-07T09:18:45Z (GMT). No. of bitstreams: 1 ijimai20164_1_1_pdf_95245.pdf: 1694903 bytes, checksum: 08127b4ffd49d73236de8faf6cc1fa9d (MD5) https://reunir.unir.net/handle/123456789/11447 IJIMAI Editor's Note - Vol. 3 Issue 7 Sanjuán Martínez, Óscar The research works presented in this issue are based on various topics of interest, among which are included: SVM and ANN Based Classification, Security in Android, Semantic Data, Planning and Software Agents, Mission Planning, Clustering in Text Mining, Mobile Networks, Weather Radars, Human Activity Recognition, LIF Neurons and DDF, Theft Prevention, Constraint Programming, Measuring Meditations Effects, Neural Networks and Deep Learning. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2021-06-03T12:25:15Z No. of bitstreams: 0; Made available in DSpace on 2021-06-03T12:25:15Z (GMT). No. of bitstreams: 0 https://reunir.unir.net/handle/123456789/11236 Improved Shape Parameter Estimation in K Clutter with Neural Networks and Deep Learning Machado Fernández, José Raúl; Bacallao Vidal, Jesús de la Concepción The discrimination of the clutter interfering signal is a current problem in modern radars’ design, especially in coastal or offshore environments where the histogram of the background signal often displays heavy tails. The statistical characterization of this signal is very important for the cancellation of sea clutter, whose behavior obeys a K distribution according to the commonly accepted criterion. By using neural networks, the authors propose a new method for estimating the K shape parameter, demonstrating its superiority over the classic alternative based on the Method of Moments. Whereas both solutions have a similar performance when the entire range of possible values of the shape parameter is evaluated, the neuronal alternative achieves a much more accurate estimation for the lower Fig.s of the parameter. This is exactly the desired behavior because the best estimate occurs for the most aggressive states of sea clutter. The final design, reached by processing three different sets of computer generated K samples, used a total of nine neural networks whose contribution is synthesized in the final estimate, thus the solution can be interpreted as a deep learning approximation. The results are to be applied in the improvement of radar detectors, particularly for maintaining the operational false alarm probability close to the one conceived in the design. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:41:13Z No. of bitstreams: 1 ijimai20163_7_14_pdf_14393.pdf: 7630656 bytes, checksum: 884a2afc180871cd0d8014c23667008e (MD5); Made available in DSpace on 2021-04-21T14:41:13Z (GMT). No. of bitstreams: 1 ijimai20163_7_14_pdf_14393.pdf: 7630656 bytes, checksum: 884a2afc180871cd0d8014c23667008e (MD5) https://reunir.unir.net/handle/123456789/11235 Chinese-chi and Kundalini yoga Meditations Effects on the Autonomic Nervous System: Comparative Study Dey, Anilesh; Bhattacharya, D. K.; Tibarewala, D.N.; Dey, Nilanjan; Ashour, Amira S.; Le, Dac-Nhuong; Gospodinova, Evgeniya; Gospodinov, Mitko Cardiac disease is one of the major causes for death all over the world. Heart rate variability (HRV) is a significant parameter that used in assessing Autonomous Nervous System (ANS) activity. Generally, the 2D Poincare′ plot and 3D Poincaré plot of the HRV signals reflect the effect of different external stimuli on the ANS. Meditation is one of such external stimulus, which has different techniques with different types of effects on the ANS. Chinese Chi-meditation and Kundalini yoga are two different effective meditation techniques. The current work is interested with the analysis of the HRV signals under the effect of these two based on meditation techniques. The 2D and 3D Poincare′ plots are generally plotted by fitting respectively an ellipse/ellipsoid to the dense region of the constructed Poincare′ plot of HRV signals. However, the 2D and 3D Poincaré plots sometimes fail to describe the proper behaviour of the system. Thus in this study, a three-dimensional frequency-delay plot is proposed to properly distinguish these two famous meditation techniques by analyzing their effects on ANS. This proposed 3D frequency-delay plot is applied on HRV signals of eight persons practicing same Chi-meditation and four other persons practising same Kundalini yoga. To substantiate the result for larger sample of data, statistical Student t-test is applied, which shows a satisfactory result in this context. The experimental results established that the Chi-meditation has large impact on the HRV compared to the Kundalini yoga. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:36:50Z No. of bitstreams: 1 ijimai20163_7_13_pdf_34001.pdf: 512858 bytes, checksum: 21e0b3b1b8cf23d3f522581ff37366a4 (MD5); Made available in DSpace on 2021-04-21T14:36:50Z (GMT). No. of bitstreams: 1 ijimai20163_7_13_pdf_34001.pdf: 512858 bytes, checksum: 21e0b3b1b8cf23d3f522581ff37366a4 (MD5) https://reunir.unir.net/handle/123456789/11234 An Extensive Evaluation of Portfolio Approaches for Constraint Satisfaction Problems Amadini, Roberto; Gabbrielli, Maurizio; Mauro, Jacopo In the context of Constraint Programming, a portfolio approach exploits the complementary strengths of a portfolio of different constraint solvers. The goal is to predict and run the best solver(s) of the portfolio for solving a new, unseen problem. In this work we reproduce, simulate, and evaluate the performance of different portfolio approaches on extensive benchmarks of Constraint Satisfaction Problems. Empirical results clearly show the benefits of portfolio solvers in terms of both solved instances and solving time. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:27:00Z No. of bitstreams: 1 ijimai20163_7_12_pdf_13932.pdf: 959307 bytes, checksum: ecf386323b85b967802feb9f5e188d0b (MD5); Made available in DSpace on 2021-04-21T14:27:00Z (GMT). No. of bitstreams: 1 ijimai20163_7_12_pdf_13932.pdf: 959307 bytes, checksum: ecf386323b85b967802feb9f5e188d0b (MD5) https://reunir.unir.net/handle/123456789/11233 A Real Time Approach to Theft Prevention in the field of Transportation System Mehta, Vartika; Punetha, Deepak; Bijalwan, Vishwanath This paper report discusses a theft prevention system, which can prevent the theft and also can be track the object. This system is capable to tracking the vehicle as well as theft prevention. An R.F. module is use to exchange the information regarding vehicle and owner of the vehicle with police control room or SOS services. The vehicle can be track with the help of R.F. receiver. A DTMF based fuel lock has been attached in this system. A cell phone with SIM card has been attached with DTMF IC. The fuel flow in the vehicle can be controlled by give a call to this cell phone. This system has been controlled by a microcontroller which can make the system cost effective, low power consumption, effective and reliable. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:22:39Z No. of bitstreams: 1 ijimai20163_7_11_pdf_18075.pdf: 802544 bytes, checksum: 8b627fa29f0458fd51cf708e90650d7a (MD5); Made available in DSpace on 2021-04-21T14:22:39Z (GMT). No. of bitstreams: 1 ijimai20163_7_11_pdf_18075.pdf: 802544 bytes, checksum: 8b627fa29f0458fd51cf708e90650d7a (MD5) https://reunir.unir.net/handle/123456789/11232 Spiking Activity of a LIF Neuron in Distributed Delay Framework Kumar Choudhary, Saket; Singh, Karan; Kumar Solanki, Vijender Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF) neuron in distributed delay framework (DDF) is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel) function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD). Stationary state probability distribution of membrane potential (SPDV) for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:16:57Z No. of bitstreams: 1 ijimai20163_7_10_pdf_21051.pdf: 1315867 bytes, checksum: fb6aaf06642d190b25dfd2c65ed94ea3 (MD5); Made available in DSpace on 2021-04-21T14:16:57Z (GMT). No. of bitstreams: 1 ijimai20163_7_10_pdf_21051.pdf: 1315867 bytes, checksum: fb6aaf06642d190b25dfd2c65ed94ea3 (MD5) https://reunir.unir.net/handle/123456789/11231 Human Activity Recognition in Real-Times Environments using Skeleton Joints Kumar, Ajay; Kumar, Anil; Kumar Singh, Satish; Kala, Rahul In this research work, we proposed a most effective noble approach for Human activity recognition in real-time environments. We recognize several distinct dynamic human activity actions using kinect. A 3D skeleton data is processed from real-time video gesture to sequence of frames and getter skeleton joints (Energy Joints, orientation, rotations of joint angles) from selected setof frames. We are using joint angle and orientations, rotations information from Kinect therefore less computation required. However, after extracting the set of frames we implemented several classification techniques Principal Component Analysis (PCA) with several distance based classifiers and Artificial Neural Network (ANN) respectively with some variants for classify our all different gesture models. However, we conclude that use very less number of frame (10-15%) for train our system efficiently from the entire set of gesture frames. Moreover, after successfully completion of our classification methods we clinch an excellent overall accuracy 94%, 96% and 98% respectively. We finally observe that our proposed system is more useful than comparing to other existing system, therefore our model is best suitable for real-time application such as in video games for player action/gesture recognition. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:09:54Z No. of bitstreams: 1 ijimai20163_7_9_pdf_20470.pdf: 1379754 bytes, checksum: ab6eac94c29a79337157250a26aaac90 (MD5); Made available in DSpace on 2021-04-21T14:09:54Z (GMT). No. of bitstreams: 1 ijimai20163_7_9_pdf_20470.pdf: 1379754 bytes, checksum: ab6eac94c29a79337157250a26aaac90 (MD5) https://reunir.unir.net/handle/123456789/11229 Uncertainty Model For Quantitative Precipitation Estimation Using Weather Radars Gómez Vargas, A. Ernesto; Obregón N., Nelson; Álvarez Pomar, C. Lindsay This paper introduces an uncertainty model for the quantitatively estimate precipitation using weather radars. The model considers various key aspects associated to radar calibration, attenuation, and the tradeoff between accuracy and radar coverage. An S-band-radar case study is presented to illustrate particular fractional-uncertainty calculations obtained to adjust various typical radar-calibration elements such as antenna, transmitter, receiver, and some other general elements included in the radar equation. This paper is based in “Guide to the expression of Uncertainty in measurement” [1] and the results show that the fractional uncertainty calculated by the model was 40 % for the reflectivity and 30% for the precipitation using the Marshall Palmer Z-R relationship. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T14:03:15Z No. of bitstreams: 1 ijimai20163_7_8_pdf_38293.pdf: 9330025 bytes, checksum: a37e62275a5154b9111a93edf0936a4f (MD5); Made available in DSpace on 2021-04-21T14:03:15Z (GMT). No. of bitstreams: 1 ijimai20163_7_8_pdf_38293.pdf: 9330025 bytes, checksum: a37e62275a5154b9111a93edf0936a4f (MD5) https://reunir.unir.net/handle/123456789/11228 Design Methodology for Self-organized Mobile Networks Based Anzola, John; Bolaños Castro, Sandro Javier; Tarazona Bermúdez, Giovanny Mauricio The methodology proposed in this article enables a systematic design of routing algorithms based on schemes of biclustering, which allows you to respond with timely techniques, clustering heuristics proposed by a researcher, and a focused approach to routing in the choice of clusterhead nodes. This process uses heuristics aimed at improving the different costs in communication surface groups called biclusters. This methodology globally enables a variety of techniques and heuristics of clustering that have been addressed in routing algorithms, but we have not explored all possible alternatives and their different assessments. Therefore, the methodology oriented design research of routing algorithms based on biclustering schemes will allow new concepts of evolutionary routing along with the ability to adapt the topological changes that occur in self-organized data networks. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T13:55:35Z No. of bitstreams: 1 ijimai20163_7_7_pdf_10406.pdf: 1445296 bytes, checksum: d04da4743687f67d9c83712bd03bcf69 (MD5); Made available in DSpace on 2021-04-21T13:55:35Z (GMT). No. of bitstreams: 1 ijimai20163_7_7_pdf_10406.pdf: 1445296 bytes, checksum: d04da4743687f67d9c83712bd03bcf69 (MD5) https://reunir.unir.net/handle/123456789/11227 Comparative Study of Clustering Algorithms in Text Mining Context JALIL, Abdennour Mohamed; HAFIDI, Imad; ALAMI, Lamiae; ENSA, Khouribga The spectacular increasing of Data is due to the appearance of networks and smartphones. Amount 42% of world population using internet [1]; have created a problem related of the processing of the data exchanged, which is rising exponentially and that should be automatically treated. This paper presents a classical process of knowledge discovery databases, in order to treat textual data. This process is divided into three parts: preprocessing, processing and postprocessing. In the processing step, we present a comparative study between several clustering algorithms such as KMeans, Global KMeans, Fast Global KMeans, Two Level KMeans and FWKmeans. The comparison between these algorithms is made on real textual data from the web using RSS feeds. Experimental results identified two problems: the first one quality results which remain for algorithms, which rapidly converge. The second problem is due to the execution time that needs to decrease for some algorithms. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T13:50:44Z No. of bitstreams: 1 ijimai20163_7_6_pdf_27159.pdf: 2390043 bytes, checksum: 8617cf316deab2187e36bf96ca08d1b7 (MD5); Made available in DSpace on 2021-04-21T13:50:44Z (GMT). No. of bitstreams: 1 ijimai20163_7_6_pdf_27159.pdf: 2390043 bytes, checksum: 8617cf316deab2187e36bf96ca08d1b7 (MD5) https://reunir.unir.net/handle/123456789/11225 Linear Temporal Logic-based Mission Planning Kumar, Anil; Kala, Rahul In this paper, we describe the Linear Temporal Logic-based reactive motion planning. We address the problem of motion planning for mobile robots, wherein the goal specification of planning is given in complex environments. The desired task specification may consist of complex behaviors of the robot, including specifications for environment constraints, need of task optimality, obstacle avoidance, rescue specifications, surveillance specifications, safety specifications, etc. We use Linear Temporal Logic to give a representation for such complex task specification and constraints. The specifications are used by a verification engine to judge the feasibility and suitability of plans. The planner gives a motion strategy as output. Finally a controller is used to generate the desired trajectory to achieve such a goal. The approach is tested using simulations on the LTLMoP mission planning tool, operating over the Robot Operating System. Simulation results generated using high level planners and low level controllers work simultaneously for mission planning and controlling the physical behavior of the robot. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T13:42:09Z No. of bitstreams: 1 ijimai20163_7_5_pdf_16569.pdf: 9919883 bytes, checksum: 52531a5b73c0e5d02a08a6101e72c8b5 (MD5); Made available in DSpace on 2021-04-21T13:42:09Z (GMT). No. of bitstreams: 1 ijimai20163_7_5_pdf_16569.pdf: 9919883 bytes, checksum: 52531a5b73c0e5d02a08a6101e72c8b5 (MD5) https://reunir.unir.net/handle/123456789/11222 The Silver Lining Methodology Castillo Chamorro, José Miguel The way in which Strategic planning is designed is different depending on the organization. For that reason, no standard procedures can be given to develop Strategic planning. However, the scenarios analysis method is used in any field or organization. We could define a scenario as a set of variables or events that describes a future situation. Additionally, the continuous irruption of new technologies invites us to carry out a revision of the old methodologies and procedures with the intention of starting an innovation process to make them more efficient. The challenge presented in this article consists of the use of the agents technology within a new methodological approach to envision future possible scenarios more quickly and more accurately than the classical methods we currently use. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T12:01:47Z No. of bitstreams: 1 ijimai20163_7_4_pdf_36802.pdf: 822662 bytes, checksum: 72681da991ac08f9ec1edeb702004029 (MD5); Made available in DSpace on 2021-04-21T12:01:47Z (GMT). No. of bitstreams: 1 ijimai20163_7_4_pdf_36802.pdf: 822662 bytes, checksum: 72681da991ac08f9ec1edeb702004029 (MD5) https://reunir.unir.net/handle/123456789/11221 Query Migration from Object Oriented World to Semantic World SOUSSI, Nassima; BAHAJ, Mohamed — In the last decades, object-oriented approach was able to take a large share of databases market aiming to design and implement structured and reusable software through the composition of independent elements in order to have programs with a high performance. On the other hand, the mass of information stored in the web is increasing day after day with a vertiginous speed, exposing the currently web faced with the problem of creating a bridge so as to facilitate access to data between different applications and systems as well as to look for relevant and exact information wished by users. In addition, all existing approach of rewriting object oriented languages to SPARQL language rely on models transformation process to guarantee this mapping. All the previous raisons has prompted us to write this paper in order to bridge an important gap between these two heterogeneous worlds (object oriented and semantic web world) by proposing the first provably semantics preserving OQLto-SPARQL translation algorithm for each element of OQL Query (SELECT clause, FROM clause, FILTER constraint, implicit/ explicit join and union/intersection SELECT queries). Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T11:55:24Z No. of bitstreams: 1 ijimai20163_7_3_pdf_20232.pdf: 479196 bytes, checksum: 690ea97178136a909e868a0bb9aec212 (MD5); Made available in DSpace on 2021-04-21T11:55:24Z (GMT). No. of bitstreams: 1 ijimai20163_7_3_pdf_20232.pdf: 479196 bytes, checksum: 690ea97178136a909e868a0bb9aec212 (MD5) https://reunir.unir.net/handle/123456789/11220 A New Protection for Android Applications ER-RAJY, Latifa; El kiram, My Ahmed Today, Smartphones are very powerful, and many of its applications use wireless multimedia communications. Prevention from the external dangers (threats) has become a big concern for the experts these days. Android security has become a very important issue because of the free application it provides and the feature which make it very easy for anyone to develop and published it on Play store. Some work has already been done on the android security model, including several analyses of the model and frameworks aimed at enforcing security standards. In this article, we introduce a tool called PermisSecure that is able to perform both static and dynamic analysis on Android programs to automatically detect suspicious applications that request unnecessary or dangerous permissions. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T11:51:03Z No. of bitstreams: 1 ijimai20163_7_2_pdf_15309.pdf: 484497 bytes, checksum: 885e61b8d1cd487fa3f8e64f937f726b (MD5); Made available in DSpace on 2021-04-21T11:51:03Z (GMT). No. of bitstreams: 1 ijimai20163_7_2_pdf_15309.pdf: 484497 bytes, checksum: 885e61b8d1cd487fa3f8e64f937f726b (MD5) https://reunir.unir.net/handle/123456789/11219 SVM and ANN Based Classification of Plant Diseases Using Feature Reduction Technique D. Pujari, Jagadeesh; Yakkundimath, Rajesh; Syedhusain Byadgi, Abdulmunaf Computers have been used for mechanization and automation in different applications of agriculture/horticulture. The critical decision on the agricultural yield and plant protection is done with the development of expert system (decision support system) using computer vision techniques. One of the areas considered in the present work is the processing of images of plant diseases affecting agriculture/horticulture crops. The first symptoms of plant disease have to be correctly detected, identified, and quantified in the initial stages. The color and texture features have been used in order to work with the sample images of plant diseases. Algorithms for extraction of color and texture features have been developed, which are in turn used to train support vector machine (SVM) and artificial neural network (ANN) classifiers. The study has presented a reduced feature set based approach for recognition and classification of images of plant diseases. The results reveal that SVM classifier is more suitable for identification and classification of plant diseases affecting agriculture/horticulture crops. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T11:43:40Z No. of bitstreams: 1 ijimai20163_7_1_pdf_75740.pdf: 1496497 bytes, checksum: ae2e63598f787536f9bb2bdebb0aea7f (MD5); Made available in DSpace on 2021-04-21T11:43:40Z (GMT). No. of bitstreams: 1 ijimai20163_7_1_pdf_75740.pdf: 1496497 bytes, checksum: ae2e63598f787536f9bb2bdebb0aea7f (MD5) https://reunir.unir.net/handle/123456789/11218 Text Analytics: the convergence of Big Data and Artificial Intelligence Moreno, Antonio; Redondo, Teófilo The analysis of the text content in emails, blogs, tweets, forums and other forms of textual communication constitutes what we call text analytics. Text analytics is applicable to most industries: it can help analyze millions of emails; you can analyze customers’ comments and questions in forums; you can perform sentiment analysis using text analytics by measuring positive or negative perceptions of a company, brand, or product. Text Analytics has also been called text mining, and is a subcategory of the Natural Language Processing (NLP) field, which is one of the founding branches of Artificial Intelligence, back in the 1950s, when an interest in understanding text originally developed. Currently Text Analytics is often considered as the next step in Big Data analysis. Text Analytics has a number of subdivisions: Information Extraction, Named Entity Recognition, Semantic Web annotated domain’s representation, and many more. Several techniques are currently used and some of them have gained a lot of attention, such as Machine Learning, to show a semisupervised enhancement of systems, but they also present a number of limitations which make them not always the only or the best choice. We conclude with current and near future applications of Text Analytics. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-04-21T10:45:28Z No. of bitstreams: 1 ijimai20163_6_9_pdf_38545.pdf: 1031480 bytes, checksum: a726d724412337b545d5f2c20ebee8ae (MD5); Made available in DSpace on 2021-04-21T10:45:28Z (GMT). No. of bitstreams: 1 ijimai20163_6_9_pdf_38545.pdf: 1031480 bytes, checksum: a726d724412337b545d5f2c20ebee8ae (MD5) https://reunir.unir.net/handle/123456789/11166 Editor’s Note Mochón, Francisco; Gonzálvez, Juan Carlos Digital information has redefined the way in which both public and private organizations are faced with the use of data to improve decision making. The importance of Big Data lies in the huge amount of data generated every day, especially following the emergence of online social networks (Facebook, Twitter, Google Plus, etc.) and the exponential growth of devices such as smartphones, smartwatches and other wearables, sensor networks, etc. as well as the possibility of taking into account increasingly updated and more varied information for decision making. [1] With proper Big Data analysis we can spot trends, get models from historical data for predicting future events or extract patterns from user behaviour, and thus be able to tailor services to the needs of users in a better way. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-03-31T14:43:26Z No. of bitstreams: 1 ijimai20163_6_0_pdf_37905.pdf: 569978 bytes, checksum: 5bae1c0b5501b8ba6b1e3271bdfd4465 (MD5); Made available in DSpace on 2021-03-31T14:43:27Z (GMT). No. of bitstreams: 1 ijimai20163_6_0_pdf_37905.pdf: 569978 bytes, checksum: 5bae1c0b5501b8ba6b1e3271bdfd4465 (MD5) https://reunir.unir.net/handle/123456789/11165 Real-Time Prediction of Gamers Behavior Using Variable Order Markov and Big Data Technology: A Case of Study Baldominos, Alejandro; Albacete, Esperanza; Marrero, Ignacio; Saez, Yago This paper presents the results and conclusions found when predicting the behavior of gamers in commercial videogames datasets. In particular, it uses Variable-Order Markov (VOM) to build a probabilistic model that is able to use the historic behavior of gamers and to infer what will be their next actions. Being able to predict with accuracy the next user’s actions can be of special interest to learn from the behavior of gamers, to make them more engaged and to reduce churn rate. In order to support a big volume and velocity of data, the system is built on top of the Hadoop ecosystem, using HBase for real-time processing; and the prediction tool is provided as a service (SaaS) and accessible through a RESTful API. The prediction system is evaluated using a case of study with two commercial videogames, attaining promising results with high prediction accuracies. Submitted by Ana María Ampudia Alonso (ana.ampudia@unir.net) on 2021-03-31T14:37:10Z No. of bitstreams: 1 ijimai20163_6_7_pdf_23096.pdf: 1621083 bytes, checksum: c62e8b559c291576e59538de895bbec3 (MD5); Made available in DSpace on 2021-03-31T14:37:10Z (GMT). No. of bitstreams: 1 ijimai20163_6_7_pdf_23096.pdf: 1621083 bytes, checksum: c62e8b559c291576e59538de895bbec3 (MD5) https://reunir.unir.net/handle/123456789/10962 Using GDELT Data to Evaluate the Confidence on the Spanish Government Energy Policy Bodas-Sagi, Diego; Labeaga, José The growing demand for affordable, reliable, domestically sourced, and low-carbon electricity is a matter of concern and it is driven by several causes including public policy priorities. Policy objectives and new technologies are changing wholesale market design. The analysis of different aspects of energy markets is increasingly on the agendas of academics, firms’ managers or policy makers. Some concerns are global and are related to the evolution of climate change phenomena. Others are regional or national and they strongly appear in countries like Spain with a high dependence on foreign energy sources and high potential of domestic renewable energy sources. We can find a relevant case in Spanish solar energy policy. A series of regulatory reforms since 2010 reduce revenues to existing renewable power generators and they end up the previous system of support to new renewable generation. This policy change has altered the composition of the energy market affecting investment decisions. In this paper, we analyze the public opinion about energy policy of the Spanish Government using the Global Database of Events, Language, and Tone (GDELT). The GDELT Project consists of over a quarter-billion event records in over 300 categories covering the entire world from 1979 to present, along with a massive network diagram connecting every person, organization, location, and theme to this event database. Our aim is to build sentiment indicators arising from this source of information and, in a final step, evaluate if positive and negative indexes have any effect on the evolution of key market variables as prices and demand. Submitted by Pedro Cotillas (pedro.cotillas@unir.net) on 2021-02-03T12:42:50Z No. of bitstreams: 1 ijimai20163_6_6_pdf_24130.pdf: 1789873 bytes, checksum: f3947cd24c47b2e15d088763bcba1d83 (MD5); Made available in DSpace on 2021-02-03T12:42:50Z (GMT). No. of bitstreams: 1 ijimai20163_6_6_pdf_24130.pdf: 1789873 bytes, checksum: f3947cd24c47b2e15d088763bcba1d83 (MD5) https://reunir.unir.net/handle/123456789/10211 Social Network Analysis and Big Data tools applied to the Systemic Risk supervision Mochón, Mari-Carmen After the financial crisis initiated in 2008, international market supervisors of the G20 agreed to reinforce their systemic risk supervisory duties. For this purpose, several regulatory reporting obligations were imposed to the market participants. As a consequence, millions of trade details are now available to National Competent Authorities on a daily basis. Traditional monitoring tools may not be capable of analyzing such volumes of data and extracting the relevant information, in order to identify the potential risks hidden behind the market. Big Data solutions currently applied to the Social Network Analysis (SNA), can be successfully applied the systemic risk supervision. This case of study proposes how relations established between the financial market participants could be analyzed, in order to identify risk of propagation and market behavior, without the necessity of expensive and demanding technical architectures. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2020-06-24T11:35:11Z No. of bitstreams: 1 ijimai20163_6_5_pdf_14449.pdf: 1567937 bytes, checksum: 8c19f6197f0288b94ff5642b4560f14a (MD5); Made available in DSpace on 2020-06-24T11:35:11Z (GMT). No. of bitstreams: 1 ijimai20163_6_5_pdf_14449.pdf: 1567937 bytes, checksum: 8c19f6197f0288b94ff5642b4560f14a (MD5) https://reunir.unir.net/handle/123456789/10210 Big Data & eLearning: A Binomial to the Future of the Knowledge Society Alonso Secades, Vidal; Arranz, Olga There is no doubt that in what refers to the educational area, technology is producing a series of changes that will greatly affect our near future. The increase of students experiences in the new educational systems in distance learning makes possible to have information related to the students ‘activities and how these can be dealt with automatic procedures. The implementation of these analytical methods is possible through the use of powerful new technologies such as Data Mining or Big Data. Relevant information is obtained of the use made by the students of the technological tools in a Learning Management System, thus, allowing us to infer a pattern of behavior of the students, to be used in the future. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2020-06-24T10:53:22Z No. of bitstreams: 1 ijimai20163_6_4_pdf_19453.pdf: 737597 bytes, checksum: ebc22f4becd2d764e142448d322e04cd (MD5); Made available in DSpace on 2020-06-24T10:53:22Z (GMT). No. of bitstreams: 1 ijimai20163_6_4_pdf_19453.pdf: 737597 bytes, checksum: ebc22f4becd2d764e142448d322e04cd (MD5) https://reunir.unir.net/handle/123456789/10209 A Fine Grain Sentiment Analysis with Semantics in Tweets Navas-Delgado, Ismael; Aldana-Montes, Jose F.; Barba Gonzalez, Cristobal; García-Nieto, José Social networking is nowadays a major source of new information in the world. Microblogging sites like Twitter have millions of active users (320 million active users on Twitter on the 30th September 2015) who share their opinions in real time, generating huge amounts of data. These data are, in most cases, available to any network user. The opinions of Twitter users have become something that companies and other organisations study to see whether or not their users like the products or services they offer. One way to assess opinions on Twitter is classifying the sentiment of the tweets as positive or negative. However, this process is usually done at a coarse grain level and the tweets are classified as positive or negative. However, tweets can be partially positive and negative at the same time, referring to different entities. As a result, general approaches usually classify these tweets as “neutral”. In this paper, we propose a semantic analysis of tweets, using Natural Language Processing to classify the sentiment with regards to the entities mentioned in each tweet. We offer a combination of Big Data tools (under the Apache Hadoop framework) and sentiment analysis using RDF graphs supporting the study of the tweet’s lexicon. This work has been empirically validated using a sporting event, the 2014 Phillips 66 Big 12 Men’s Basketball Championship. The experimental results show a clear correlation between the predicted sentiments with specific events during the championship. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2020-06-24T09:27:02Z No. of bitstreams: 1 ijimai20163_6_3_pdf_14247.pdf: 1229376 bytes, checksum: eb1c79f224aab1acf6f5b1290b088b82 (MD5); Made available in DSpace on 2020-06-24T09:27:02Z (GMT). No. of bitstreams: 1 ijimai20163_6_3_pdf_14247.pdf: 1229376 bytes, checksum: eb1c79f224aab1acf6f5b1290b088b82 (MD5) https://reunir.unir.net/handle/123456789/10208 PInCom project: SaaS Big Data Platform for and Communication Channels Lombardo, Juan Manuel; López, Miguel Ángel; Mirón, Felipe; Velasco, Susana; Sevilla, Juan Pablo; Mellado, Juan The problem of optimization will be addressed in this article, based on the premise that the successful implementation of Big Data solutions requires as a determining factor not only effective -it is assumed- but the efficiency of the responsiveness of management information get the best value offered by the digital and technological environment for gaining knowledge. In adopting Big Data strategies should be identified storage technologies and appropriate extraction to enable professionals and companies from different sectors to realize the full potential of the data. A success story is the solution PInCom: Intelligent-Communications Platform that aims customer loyalty by sending multimedia communications across heterogeneous transmission channels. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2020-06-24T08:30:00Z No. of bitstreams: 1 ijimai20163_6_2_pdf_29854.pdf: 1482915 bytes, checksum: 49b9ea3359f9781c15f6227cbea8c602 (MD5); Made available in DSpace on 2020-06-24T08:30:00Z (GMT). No. of bitstreams: 1 ijimai20163_6_2_pdf_29854.pdf: 1482915 bytes, checksum: 49b9ea3359f9781c15f6227cbea8c602 (MD5) https://reunir.unir.net/handle/123456789/10199 Operating an Advertising Programmatic Buying Platform: A Case Study Mochón, Francisco; Gonzalvez-Cabañas, J.C. This paper analyses how new technological developments and the possibilities generated by the internet are shaping the online advertising market. More specifically it focuses on a programmatic advertising case study. The origin of the problem is how publishers resort to automated buying and selling when trying to shift unsold inventory. To carry out our case study, we will use a programmatic online advertising sales platform, which identifies the optimal way of promoting a given product. The platform executes, evaluates, manages and optimizes display advertising campaigns, all in real-time. The empirical analysis carried out in the case study reveals that the platform and its exclusion algorithms are suitable mechanisms for analysing the performance and efficiency of the various segments that might be used to promote products. Thanks to Big Data tools and artificial intelligence the platform performs automatically, providing information in a user-friendly and simple manner. Submitted by Susana Figueroa Navarro (susana.figueroa.n@unir.net) on 2020-06-22T08:13:09Z No. of bitstreams: 1 ijimai20163_6_1_pdf_29476.pdf: 1470590 bytes, checksum: 1df7f252b978d019f53ae215d923dda2 (MD5); Made available in DSpace on 2020-06-22T08:13:09Z (GMT). No. of bitstreams: 1 ijimai20163_6_1_pdf_29476.pdf: 1470590 bytes, checksum: 1df7f252b978d019f53ae215d923dda2 (MD5) https://reunir.unir.net/handle/123456789/5817 Detection of Adverse Reaction to Drugs in Elderly Patients through Predictive Modeling San Miguel Carrasco, Rafael Geriatrics Medicine constitutes a clinical research field in which data analytics, particularly predictive modeling, can deliver compelling, reliable and long-lasting benefits, as well as non-intuitive clinical insights and net new knowledge. The research work described in this paper leverages predictive modeling to uncover new insights related to adverse reaction to drugs in elderly patients. The differentiation factor that sets this research exercise apart from traditional clinical research is the fact that it was not designed by formulating a particular hypothesis to be validated. Instead, it was data-centric, with data being mined to discover relationships or correlations among variables. Regression techniques were systematically applied to data through multiple iterations and under different configurations. The obtained results after the process was completed are explained and discussed next. Submitted by Pedro Cotillas (pedro.cotillas@unir.net) on 2017-10-23T16:13:43Z No. of bitstreams: 0; Made available in DSpace on 2017-10-23T16:13:43Z (GMT). No. of bitstreams: 0