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IEEE International Conference on Cognitive Informatics

作者： Witold Kinsner Experimental Media Research Group Telecommunications Research Laboratories Institute of Industrial Mathematical Sciences Canada Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

Summary form only given. Deoxyribonucleic acid (DNA) has become one of the most examined molecules on the planet. Scientist around the world have been trying to unravel its secrets for many purposes. For example, genetic information is currently used to raise better plants and animals, create enhanced pharmaceuticals for humans, and for gene therapy in medicine. Science as a whole has benefited from the study of genetics because of the increased understanding of biological process that all organisms share. In recent decades, a significant amount of research has been directed towards sequencing and understanding the entire human genome through the Human Genome Project (HGP) launched in 1986. The goal of the HGP was to find the location of the approximately 1×105 human genes, and read all the sequence of human genome (about 3×109 base pairs, bp). An exponential grow rate of that research has resulted in reaching the goal by 2003. Similarly, the speed of finding genes and their locations is also increasing rapidly. On the other hand, the traditional methods of finding genes and their location at chromatosomes through testing their biological function have been inherently slow. Although numerous faster techniques have been developed, there is still a need to augment them with new approaches. Therefore, robust computational solutions to the gene-finding problem could provide a valuable resource for the HGP and for the molecular-biology community. Most of the current research in the deciphering the meaning of DNA sequences is approached from the lowest base-pair level. Its main objective is to search for patterns or correlations existing in the DNA sequence related to codons, amino acids, and proteins. A number of gene-finding systems have been developed in recent decades. These systems use a variety of sophisticated computational data-miming techniques, including neural networks, dynamic programming, rule-based methods, decision trees, probability reasoning, hidden Marko

关键词： DNA Fractals Bioinformatics Cognitive informatics computers Genomics Humans

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Enhancing MPEG-4 CELP by jointly optimized inter/intra-frame LSP predictors

Enhancing MPEG-4 CELP by jointly optimized inter/intra-frame...

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IEEE Workshop on Speech Coding Proceedings

作者： K. Koishida J. Linden V. Cupermann A. Gersho Signal Compression Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara CA USA University of California Santa Barbara Santa Barbara CA US

This paper presents an LSP quantization design method for bandwidth scalable coders such as the MPEG-4 CELP coder. In the enhancement layer of these coders, the LSP parameters are quantized using both interframe and intraframe predictors. The proposed design algorithm enables us to jointly optimize these predictors. Objective and subjective test results show that the quantizer obtained with the proposed algorithm provides better performance than that used in the MPEG-4 CELP.

关键词： MPEG 4 Standard Speech enhancement Wideband Bandwidth Quantization Laboratories Scalability Narrowband Design methodology Testing

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Automatic Detection and Characterization of Human Veins Using Infra-Red Image Processing

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Journal of computer and Communications 2024年第9期12卷 141-159页

作者： Jean Ndoumbe Brice Ekobo Akoa Gaelle Patricia Talotsing Frederic Franck Kounga Samuel Kaissassou Bertin Chouanmo Njo Laboratory of Computer Engineering Data Science and Artificial Intelligence Department of Computer & Telecommunications Engineering National Higher Polytechnic School Douala Cameroon Laboratory of Electrical Engineering Mechatronics and Signal Processing Department of Electrical & Telecommunications Engineering National Advanced School of Engineering Yaound Cameroon Mobile Computing and Networking Research Laboratory Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada DigiPlus SARL Bonamoussadi Douala Cameroon

The detection and characterization of human veins using infrared (IR) image processing have gained significant attention due to its potential applications in biometric identification, medical diagnostics, and vein-based authentication systems. This paper presents a low-cost approach for automatic detection and characterization of human veins from IR images. The proposed method uses image processing techniques including segmentation, feature extraction, and, pattern recognition algorithms. Initially, the IR images are preprocessed to enhance vein structures and reduce noise. Subsequently, a CLAHE algorithm is employed to extract vein regions based on their unique IR absorption properties. Features such as vein thickness, orientation, and branching patterns are extracted using mathematical morphology and directional filters. Finally, a classification framework is implemented to categorize veins and distinguish them from surrounding tissues or artifacts. A setup based on Raspberry Pi was used. Experimental results of IR images demonstrate the effectiveness and robustness of the proposed approach in accurately detecting and characterizing human. The developed system shows promising for integration into applications requiring reliable and secure identification based on vein patterns. Our work provides an effective and low-cost solution for nursing staff in low and middle-income countries to perform a safe and accurate venipuncture.

关键词： Vein Detection Blood Radiation Infrared Image CLAHE Algorithm Raspberry Pi

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Towards Cognitive Machines: Multiscale Measures and Analysis

Towards Cognitive Machines: Multiscale Measures and Analysis

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Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

作者： W. Kinsner Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MB Canada R3T 5V6 and the Institute of Industrial Mathematical Sciences and Telecommunications Research Laboratories TRLabs

Numerous attempts are being made to develop machines that could act not only autonomously, but also in an increasingly intelligent and cognitive manner. Such cognitive machines ought to be aware of their environments which include not only other machines, but also human beings. Such machines ought to understand the meaning of information in more human-like ways by grounding knowledge in the physical wortti and in the machines' own goals. The motivation for developing such machines range from self-evidenced practical reasons such as the expense of computer maintenance, to wearable computing in health care, and gaining a better understanding of the cognitive capabilities of the human brain. To achieve such an ambitious goal requires solutions to many problems, ranging from human perception, attention, concept creation, cognition, consciousness, executive processes guided by emotions and value, and symbiotic conversational human-machine interactions. An important component of this cognitive machine research includes multiscale measures and analysis. This paper presents definitions of cognitive machines, representations of processes, as well as their measurements, measures and analysis. It provides examples from current research, including cognitive radio, cognitive radar, and cognitive monitors.

关键词： Cognitive machines machine perception, learning, cognition intelligent signal processing cognitive informatics.

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Impact of low-rate sampling on the reconstruction of ECG in phase-space

Impact of low-rate sampling on the reconstruction of ECG in ...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： B. Huang W. Kinsner Dept. of Electr. & Comput. Eng. Manitoba Univ. Winnipeg Man. Canada Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper examines the chaotic and multifractal characteristics of the electrocardiogram (ECG) through its time series. Although multifractalities exist in the reconstructed strange attractor we find some limitations of strange attractor reconstruction from low-rate sampled (333 Hz) ECG signals by investigating the convergence of the false nearest neighbours and the Renyi dimension. The reconstruction parameters, lag of 4 and embedding dimension of 7, are obtained from experiments.

关键词： Sampling methods Electrocardiography Biomedical measurements Nonlinear dynamical systems Fractals Chaos Convergence Rhythm Time measurement Frequency

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A radio transmitter fingerprinting system ODO-1

A radio transmitter fingerprinting system ODO-1

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Canadian Conference on electrical and computer engineering (CCECE)

作者： J. Toonstra W. Kinsner Dept. of Electr. & Comput. Eng. Manitoba Univ. Winnipeg Man. Canada Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper presents a new method for the capture, analysis, and classification of radio transmitter transients. This method involves the use of a capturing subsystem consisting of an Icom IC-R7000 communications receiver and a Sound Blaster 16 sound card running on a PC. The radio transients are sampled at 44,100 samples per second and have 16 bits accuracy. Once the transmitter transient has been captured, a genetic algorithm selects the critical features from the wavelet coefficients for classification. The selected wavelet coefficients are considered to be fingerprints, and are presented to a back propagation neural network for transmitter classification. The capturing and analysis system, ODO-1, is able to classify both transients of the same model type as well as individual transmitters with 100% accuracy on a small data base of transmitter fingerprints.

关键词： Radio transmitters Fingerprint recognition Transient analysis Genetic algorithms Wavelet analysis Loudspeakers Wavelet coefficients Neural networks Frequency synthesizers Algorithm design and analysis

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Personalized Multimedia Recommendation Systems Using Higher-Order Tensor Singular-Value-Decomposition

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IEEE Transactions on Broadcasting 2024年第1期70卷 148-160页

作者： Chang, Shih Yu Wu, Hsiao-Chun Yan, Kun Chen, Xinjia Huang, Scott Chih-Hao Wu, Yiyan San Jose State University Department of Applied Data Science San JoseCA95192 United States Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for AI Applications Chungli32003 Taiwan Guilin University of Electronic Technology Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Department of Information and Telecommunication Guilin541004 China Northwestern State University Department of Engineering Technology NatchitochesLA71497 United States National Tsing Hua University Department of Electrical Engineering Hsinchu300 Taiwan Communications Research Centre Canada OttawaK2H 8S2 Canada

Because of rapid growth of multimedia data over the Internet, the infobesity has been emerging in recent years. Many recommender systems (RSs) have been proposed using a variety of techniques, including artificial intelligence, machine learning, statistical analysis, and data mining. Nowadays, E-commerce companies such as Amazon, eBay, Netflix, etc. have applied RSs conveniently to provide better customer services than before by enabling customized multimedia-content recommendations. It is well known that classical RSs are almost all based on the user-item attribute matrices. However, this two-fold user-item relationship should be extended to the emerging many-fold relationship among an arbitrary number of attribute groups so that the corresponding new RSs may lead to better performances. Therefore, in this paper, we introduce a novel personalized multimedia recommender system (PMRS) according to our proposed new parallel higher-order tensor singular-value-decomposition (PHOTSVD) algorithm. This PHOTSVD algorithm is capable of accommodating an arbitrary number of entities such as social-media channels, users, queries, webpages, etc. in a robust RS. Furthermore, we also investigate the cold start and data bias problems critical to RSs. Finally, we compare the performances of our proposed new PMRS and three other existing tensor-based RSs over realworld data with respect to the well-adopted metric, namely normalized root-mean-square error (NRMSE). Our proposed new PMRS greatly outperforms the other three existing tensor-based RSs in terms of NRMSE. © 1963-12012 IEEE.

关键词： Singular value decomposition

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Enhancing waveform interpolative coding with weighted REW parametric quantization

Enhancing waveform interpolative coding with weighted REW pa...

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IEEE Workshop on Speech Coding Proceedings

作者： O. Gottesman A. Gersho Dept. of Electr. & Comput. Eng. California Univ. Santa Barbara CA USA Signal Compression Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

This paper presents an efficient quantization technique for the rapidly-evolving waveforms in waveform interpolative (WI) coders. The scheme, based on a parametrization of the rapidly-evolving waveform (REW) magnitude, and analysis-by-synthesis (AbS) vector quantization (VQ) of the REW parameters, allows both higher temporal and spectral resolution of the REW. A perceptually weighted distortion measure takes advantage of spectral and temporal masking and leads to improved reconstructed speech quality, most notably in mixed voiced and unvoiced speech segments. The technique is an important component of the enhanced waveform interpolative (EWI) speech coder at 2.8 kbps that achieves a subjective quality slightly better than that of G.723.1 at 6.3 kbps.

关键词： Quantization Distortion measurement Laboratories Frequency Weight measurement Speech coding Interpolation Bit rate Piecewise linear techniques Speech enhancement

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Novel Personalized Multimedia Recommendation Systems Using Tensor Singular-Value-Decomposition

Novel Personalized Multimedia Recommendation Systems Using T...

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2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2023

作者： Chang, Shih Yu Wu, Hsiao-Chun Yan, Kun Chen, Xinjia Wu, Yiyan San Jose State University Department of Applied Data Science San JoseCA95192 United States Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Guilin University of Electronic Technology Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin541004 China Guilin University of Electronic Technology Department of Information and Telecommunication Guilin541004 China Northwestern State University of Louisiana Department of Engineering Technology NatchitochesLA71497 United States Communications Research Centre Canada OttawaONK2H 8S2 Canada

ISBN: (纸本)9798350321524

Nowadays, multimedia data are often produced by various sources, e.g., Internet of Things (IoT), social media, customer databases, etc. As tremendous multimedia data are produced every day, users or E-commerce customers cannot infer information from such data by themselves and therefore recommender systems have been developed to help users to select the products or services which better fit users' preferences or requirements. Nonetheless, there exists few works on the incorporation of side information or multiple attributes about items into the design of a more robust recommender system. In this work, we propose a novel approach based on the third-order tensor singular-value-decomposition (T3-SVD) to design new personalized multimedia recommender systems (PMRSs) for internet users. A PMRS can dynamically adjust its recommendation strategy subject to a particular user's on-line transaction behavior. To evaluate the effectiveness of our proposed PMRS based on T3-SVD, we compare the performances of our proposed new PMRS and two other existing tensor-based recommendation systems over realworld data in terms of normalized root-mean-square error (NRMSE). As a result, our proposed new PMRS greatly outperforms the other two existing systems. © 2023 IEEE.

关键词： Recommender systems

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Network coding for wireless applications

Network coding for wireless applications

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Unmanned/Unattended Sensors and Sensor Networks II

作者： Lun, Desmond S. Ahmed, Ebad Brothers, L. Reggie DeBardelaben, James A. Effros, Michelle Ho, Tracey Karger, David Koetter, Ralf Lee, Anna MacMullan, Samuel J. Médard, Muriel Zhao, Fang Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA 02139 United States DARPA ATO 3701 N. Fairfax Dr. Arlington VA 22203 United States Johns Hopkins University Applied Physics Laboratory 11100 Johns Hopkins Rd. Laurel MD 20769 United States Data Compression Laboratory California Institute of Technology Pasadena CA 91125 United States Department of Electrical Engineering California Institute of Technology Pasadena CA 91125 United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA 02139 United States Coordinated Science Laboratory University of Illinois at Urbana-Champaign Urbana IL 61801 United States Lorenz Research Associates Inc. 4443 Brookfield Corporate Dr. Chantilly VA 20151 United States

The advent of network coding promises to change many aspects of networking. Network coding moves away from the classical approach of networking, which treats networks as akin to physical transportation systems. We overview some of the main features of network coding that are most relevant to wireless networks. In particular, we discuss the fact that random distributed network coding is asymptotically optimal for wireless networks with and without packet erasures. These results are extremely general and allow packet loss correlation, such as may occur in fading wireless channels. The coded network lends itself, for multicast connections, to a cost optimization which not only outperforms traditional routing tree-based approaches, but also lends itself to a distributed implementation and to a dynamic implementation when changing conditions, such as mobility, arise. We illustrate the performance of such optimization methods for energy efficiency in wireless networks and propose some new directions for research in the area.

关键词： signal encoding

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