https://reunir.unir.net/handle/123456789/11617 2024-11-04T19:08:20Z 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)