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Technology acceptance model (TAM) for mobile durian plantation apps(Pro Durian);the analysis for Malaysian farmers

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Technology acceptance model (TAM) for mobile durian plantati...

Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Noraziahtulhidayu Kamarudin Aiman Yusoff Abd Samad Hasan Basari Noor Zuraidin bin Mohd Safar Mohd Hatta Hussin Department of Multimedia Multimedia and Signal Processing Focus Group Faculty of Computer Science and Information Universiti Tun Hussein Onn Malaysia Department of Multimedia Faculty of Computer Science and Information Universiti Tun Hussein Onn Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Department of Information Security and Web Technology Faculty of Computer Science and Information Universiti Tun Hussein Onn Malaysia Johor Darul Takzim Pertubuhan Peladang Senggarang

During the application development process, it is important for a developer to analyze user requirements. This is crucial to the success of interactive systems and is an essential component of the design of information systems. User requirement analysis aids developers in understanding and analyzing users' needs and technology requirements. Throughout this case study, it is able to forecast the understanding, and technology acceptance, and at the same time improve the quality of work, reducing training and support costing and perennially improve customer or user satisfaction. The method of research selected is questionnaires that focused on collecting the data directly from Malaysian farmers through Google Forms as an online medium. The method was chosen because it is easy to implement and inexpensive due to the current situation of Covid-19. The questionnaire is designed with two sections where; a) includes the participant's demography to analyze information of the intended audience while b)focused on the knowledge of participants about recognition images. Results demonstrate the farmer's opinion and knowledge of the technology of image recognition in the agriculture sector. The quantitative research was undertaken using an online platform due to the Covid-19 pandemic. From the analysis, it is justified that the Technology Acceptance Model (TAM) together with the mobile farming image recognition app is useful in collecting farmers' feedback and positive results have an outcome on the challenges faced by the durian farmers.

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Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compression

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arXiv 2023年

作者： Burakhan Koyuncu, A. Jia, Panqi Boev, Atanas Alshina, Elena Steinbach, Eckehard The Technical University of Munich School of Computation Information and Technology Department of Computer Engineering Media Technology Munich80333 Germany The Friedrich-Alexander University Department of Electrical-Electronic-Communication Engineering Multimedia Communications and Signal Processing Erlangen91058 Germany The Huawei Munich Research Center Munich80992 Germany

Entropy estimation is essential for the performance of learned image compression. It has been demonstrated that a transformer-based entropy model is of critical importance for achieving a high compression ratio, however, at the expense of a significant computational effort. In this work, we introduce the Efficient Contextformer (eContextformer) - a computationally efficient transformer-based autoregressive context model for learned image compression. The eContextformer efficiently fuses the patch-wise, checkered, and channel-wise grouping techniques for parallel context modeling, and introduces a shifted window spatio-channel attention mechanism. We explore better training strategies and architectural designs and introduce additional complexity optimizations. During decoding, the proposed optimization techniques dynamically scale the attention span and cache the previous attention computations, drastically reducing the model and runtime complexity. Compared to the non-parallel approach, our proposal has ∼145x lower model complexity and ∼210x faster decoding speed, and achieves higher average bit savings on Kodak, CLIC2020, and Tecnick datasets. Additionally, the low complexity of our context model enables online rate-distortion algorithms, which further improve the compression performance. We achieve up to 17% bitrate savings over the intra coding of Versatile Video Coding (VVC) Test Model (VTM) 16.2 and surpass various learning-based compression models. © 2023, CC BY-NC-ND.

关键词： Image compression

40 Gb/s High-speed mode-division multiplexing transmission employing NRZ modulation format

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Journal of Optical Communications 2023年第s1期44卷 S1157-S1165页

作者： Sabitu, Rabiu Imam Khan, Nafizah Goriman Malekmohammadi, Amin Affiliated to the George Green Institute for Electromagnetics Research Nottingham United Kingdom Photonics Communication Systems and Signal Processing Research Group Kano University of Science and Technology Wudil KanoPMB 3244 Nigeria Semenyih Malaysia Department of Electrical and Computer Engineering California State University BakersfieldCA93311 United States Photonics Communication Systems and Signal Processing Research Group Kano University of Science and Technology Wudil KanoPMB 3244 Nigeria

This report examines the performance of a high-speed MDM transmission system supporting four nondegenerate spatial modes at 10 Gb/s. The analysis adopts the NRZ modulation format to evaluate the system performance in terms of a minimum power required (PN) and the nonlinear threshold power (PTH) at a BER of 10−9. The receiver sensitivity, optical signal-to-noise ratio, and the maximum transmission distance were investigated using the direct detection by employing a multimode erbium-doped amplifier (MM-EDFA). It was found that by properly optimizing the MM-EDFA, the system performance can significantly be improved. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Erbium doped fiber amplifiers

An Insight Into Neurodegeneration: Harnessing Functional MRI Connectivity in the Diagnosis of Mild Cognitive Impairment

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An Insight Into Neurodegeneration: Harnessing Functional MRI...

17th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2024

作者： Han, Shuning Sun, Zhe Zhao, Kanhao Duan, Feng Caiafa, Cesar F. Zhang, Yu Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Catalonia Vic08500 Spain Image Processing Research Group RIKEN Center for Advanced Photonics Riken Saitama Wako-Shi Japan Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Bioengineering Lehigh University BethlehemPA18015 United States Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Instituto Argentino de Radioastronomía-CCT La Plata CONICET/ CIC-PBA/ UNLP V. Elisa 1894 Argentina Department of Electrical and Computer Engineering Lehigh University BethlehemPA18015 United States Department of Psychiatry University of Cambridge CambridgeCB20SZ United Kingdom

Alzheimer’s disease is a progressive form of memory loss that worsens over time. Detecting it early, when memory issues are mild, is crucial for effective interventions. Recent advancements in computer technology, specifically Graph Convolutional Networks (GCNs), have proven to be powerful tools for analyzing Magnetic Resonance Imaging (MRI) data comprehensively. In this study, we developed a GCN framework for diagnosing mild cognitive impairment (MCI) by examining the functional connectivity (FC) derived from resting-state functional MRI (rfMRI) data. Our research systematically explored various types and processing methods of FC, evaluating their performance on the OASIS-3 dataset. The experimental results revealed several key findings. On the one hand, the proposed GCN exhibited significantly superior performance over both the baseline GCN and the Support Vector Machine (SVM) models, with statistically significant differences. It attained the highest average accuracy of 80.3% and a peak accuracy of 88.2%. On the other hand, the GCN frame work obtained using individual FCs showed overall slightly better performance than the one using global FCs. However, it is important to note that GCNs using global networks with appropriate connectivity can achieve comparable or even better performance than individual networks in certain cases. Finally, our results also indicate that the connectivity within specific brain regions, such as VIS, DMN, SMN, VAN, and FPC, may play a more significant role in GCN-based MRI classification for MCI diagnosis. These findings significantly contribute to the understanding of neurodegenerative disorders and offer valuable insights into the diverse ap plications of GCNs in brain analysis and disease detection. © 2024 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Neurodegenerative diseases

Minimax Robust Detection: Classic Results and Recent Advances

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arXiv 2021年

作者： Zoubir, Abdelhak M. Fauß, Michael Vincent Poor, H. Department of Electrical and Computer Engineering Princeton University PrincetonNJ United States Signal Processing Group Technische

—This paper provides an overview of results and concepts in minimax robust hypothesis testing for two and multiple hypotheses. It starts with an introduction to the subject, highlighting its connection to other areas of robust statistics and giving a brief recount of the most prominent developments. Subsequently, the minimax principle is introduced and its strengths and limitations are discussed. The first part of the paper focuses on the two-hypothesis case. After briefly reviewing the basics of statistical hypothesis testing, uncertainty sets are introduced as a generic way of modeling distributional uncertainty. The design of minimax detectors is then shown to reduce to the problem of determining a pair of least favorable distributions, and different criteria for their characterization are discussed. Explicit expressions are given for least favorable distributions under three types of uncertainty: Ε-contamination, probability density bands, and f-divergence balls. Using examples, it is shown how the properties of these least favorable distributions translate to properties of the corresponding minimax detectors. The second part of the paper deals with the problem of robustly testing multiple hypotheses, starting with a discussion of why this is fundamentally different from the binary problem. Sequential detection is then introduced as a technique that enables the design of strictly minimax optimal tests in the multi-hypothesis case. Finally, the usefulness of robust detectors in practice is showcased using the example of ground penetrating radar. The paper concludes with an outlook on robust detection beyond the minimax principle and a brief summary of the presented *** Codes 62G10, 62G35 Copyright © 2021, The Authors. All rights reserved.

关键词： Ground penetrating radar systems

Variational Autoencoder with Embedded Student-t Mixture Model for Authorship Attribution 28

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Variational Autoencoder with Embedded Student-t Mixture Mode...

28th International Conference on Computational Linguistics, COLING 2020

作者： Boenninghoff, Benedikt Zeiler, Steffen Nickel, Robert M. Kolossa, Dorothea Cognitive Signal Processing Group Ruhr University Bochum Germany Department of Electrical and Computer Engineering Bucknell University LewisburgPA United States

ISBN: (纸本)9781952148279

Traditional computational authorship attribution describes a classification task in a closed-set scenario. Given a finite set of candidate authors and corresponding labeled texts, the objective is to determine which of the authors has written another set of anonymous or disputed texts. In this work, we propose a probabilistic autoencoding framework to deal with this supervised classification task. Variational autoencoders (VAEs) have had tremendous success in learning latent representations. However, existing VAEs are currently still bound by limitations imposed by the assumed Gaussianity of the underlying probability distributions in the latent space. In this work, we are extending a VAE with an embedded Gaussian mixture model to a Student-t mixture model, which allows for an independent control of the "heaviness" of the respective tails of the implied probability densities. Experiments over an Amazon review dataset indicate superior performance of the proposed method. © 2020 COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference. All rights reserved.

关键词： Gaussian distribution

Independent Vector Extraction Constrained on Manifold of Half-Length Filters

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Independent Vector Extraction Constrained on Manifold of Hal...

European signal processing Conference (EUSIPCO)

作者： Zbyněk Koldovský Jaroslav Čmejla Tülay Adali Stephen O'Regan Acoustic Signal Analysis and Processing Group Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Czech Republic Department of Electrical and Computer Engineering University of Maryland Baltimore County Baltimore MD USA Naval Surface Warfare Center Carderock Division West Bethesda Maryland USA

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Efficient and Self-Recursive Delay Vandermonde Algorithm for Multi-Beam Antenna Arrays

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arXiv 2022年

作者： Perera, S.M. Madanayake, A. Cintra, R.J. The Department of Mathematics Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States The Signal Processing Group UFPE Brazil

This paper presents a self-contained factorization for the delay Vandermonde matrix (DVM), which is the super class of the discrete Fourier transform, using sparse and companion matrices. An efficient DVM algorithm is proposed to reduce the complexity of radio-frequency (RF) N-beam analog beamforming systems. There exist applications for wideband multi-beam beamformers in wireless communication networks such as 5G/6G systems, system capacity can be improved by exploiting the improvement of the signal to noise ratio (SNR) using coherent summation of propagating waves based on their directions of propagation. The presence of a multitude of RF beams allows multiple independent wireless links to be established at high SNR, or used in conjunction with multiple-input multiple-output (MIMO) wireless systems, with the overall goal of improving system SNR and therefore capacity. To realize such multi-beam beamformers at acceptable analog circuit complexities, we use sparse factorization of the DVM in order to derive a low arithmetic complexity DVM algorithm. The paper also establishes an error bound and stability analysis of the proposed DVM algorithm. The proposed efficient DVM algorithm is aimed at implementation using analog realizations. For purposes of evaluation, the algorithm can be realized using both digital hardware as well as software defined radio platforms. Copyright © 2022, The Authors. All rights reserved.

关键词： Beamforming

Towards a Low-SWaP 1024-beam Digital Array: A 32-beam Sub-System at 5.8 GHz

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arXiv 2022年

作者： Madanayake, Arjuna Ariyarathna, Viduneth Madishetty, Suresh Pulipati, Sravan Cintra, R.J. Coelho, Diego Oliveira, Raíza Bayer, Fábio M. Belostotski, Leonid Mandal, Soumyajit Rappaport, Theodore S. Department of Electrical and Computer Engineering Florida International University MiamiFL United States Department of Electrical and Computer Engineering University of Akron AkronOH United States Signal Processing Group UFPE Brazil Calgary AB Canada Departamento de Estatística LACESM UFSM Brazil Department of Electrical and Computer Engineering University of Calgary CalgaryAB Canada Department of Electrical Engineering and Computer Science Case Western Reserve University ClevelandOH United States NYU Wireless Department of Electrical and Computer Engineering New York University Tandon School of Engineering New YorkNY United States

Millimeter wave communications require multibeam beamforming in order to utilize wireless channels that suffer from obstructions, path loss, and multi-path effects. Digital multibeam beamforming has maximum degrees of freedom compared to analog phased arrays. However, circuit complexity and power consumption are important constraints for digital multibeam systems. A low-complexity digital computing architecture is proposed for a multiplication-free 32-point linear transform that approximates multiple simultaneous RF beams similar to a discrete Fourier transform (DFT). Arithmetic complexity due to multiplication is reduced from the FFT complexity of O(N log N) for DFT realizations, down to zero, thus yielding a 46% and 55% reduction in chip area and dynamic power consumption, respectively, for the N = 32 case considered. The paper describes the proposed 32-point DFT approximation targeting a 1024-beams using a 2D array, and shows the multiplierless approximation and its mapping to a 32-beam sub-system consisting of 5.8 GHz antennas that can be used for generating 1024 digital beams without multiplications. Real-time beam computation is achieved using a Xilinx FPGA at 120 MHz bandwidth per beam. Theoretical beam performance is compared with measured RF patterns from both a fixed-point FFT as well as the proposed multiplier-free algorithm and are in good agreement. Copyright © 2022, The Authors. All rights reserved.

关键词： Beamforming