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FDAM: Filter-Dedicated Approximate Multiplier Design for Real-Time CNN Acceleration

IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Nguyen, Kihwan Kim Xuan Truong Jeon, Dongsuk Lee, Hyuk-Jae Korea Republic of program Department of Electrical Engineering Seoul08826 Korea Republic of Inter-University Semiconductor Research Center Seoul National University Graduate School of Convergence Science and Technology Research Institute for Convergence Science Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Seoul08826 Korea Republic of

Video super-resolution (VSR) is widely used in various high-definition applications, such as HDTVs and smartphones, requiring a dedicated upscaling technique for realtime full-HD generation. To reduce on-chip buffers for largesize output feature maps, a streaming VSR accelerator may employ an output stationary dataflow, leading to a large energy consumption caused by frequent filter switching. To mitigate this, we introduce a new filter-dedicated multiplier design for realtime VSR acceleration. We replace costly multipliers with adders, shifters, and multiplexers (MUXes), referred to as unified multiple constant multiplications (UMCM). The conventional UMCM, however, may incur considerable area/power overhead due to the unified topology constraint among different filter sets. To address this problem, we propose a new approximated MCM (AMCM) problem to relax the constraint and an approximate compatible graph synthesis (A-CGS) framework to efficiently solve AMCM by jointly searching for approximated filters and constructing a unified graph. Additionally, we suggest a lightweight finetuning method by freezing approximated filters and only finetuning biases, which can recover the original model’s accuracy within a few epochs. Experimental results with synthetic data demonstrate that AMCM reduces the area by up to 49.8%, 44.8%, and 40.3% when considering constant sets of 2, 4, and 8, respectively. Our designs with SR application achieve up to a 73.3% reduction in energy consumption. Experiments with the Set5 and Set14 datasets show that our model with bias correction achieves similar restoration performance compared to the eightbit models. © 1982-2012 IEEE.

关键词： Acceleration

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Implementation and Evaluation of 0.6 µm CMOS Complex RCPF for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 25-37页

作者： Sato, Lina Fukagawa, Kanta Shouno, Kazuhiro Tanimoto, Hiroshi Muto, Cosy Moriyama, Seijiro Takahashi, Chikau Yoshino, Michitaka Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan Anagix Corporation 3-22-27 Numama Kanagawa Zushi249-0004 Japan Takamori Corporation Japan Research Center for Micro-Nano Technology Hosei University 3-11-15 Midori-cho Koganei Tokyo184-0003 Japan

This paper describes the implementation and evaluation of an RC polyphase filter (RCPF) and circuitry for measuring its frequency characteristics. The integrated circuit is fabricated on a 0.6 µm CMOS process and its supply voltage is 5 V. The integrated circuit includes a filter under test (FUT), a four-phase square wave generator, several analog switches and differential amplifiers to amplify the high-impedance signals of the RCPF. This FUT is a third-order complex RCPF whose passband is 8 − 40 MHz. This paper describes the design of these circuits in detail. This integrated circuit can select two measurement methods by means of external control signals. The first method uses a four-phase square wave. The frequency characteristics are measured by using an on-chip four-phase square wave generator driven by an external clock generator and by a spectrum analyzer tuned to the fundamental frequency. The second method uses an external network analyzer. Furthermore, this integrated circuit is equipped with a calibration circuit to measure the frequency characteristics of the circuitry except FUT by passing through the input / output signals of the FUT. As a result, the frequency characteristics of the FUT itself can be accurately measured. The effectiveness is confirmed through evaluation of the fabricated integrated circuit. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Differential amplifiers

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Towards Emotionally Intelligent Software Engineers: Understanding Students’ Self-Perceptions After a Cooperative Learning Experience

arXiv

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arXiv 2025年

作者： Araújo, Allysson Allex Kalinowski, Marcos Paixao, Matheus Graziotin, Daniel Center for Science and Technology Federal University of Cariri Juazeiro do Norte Brazil Department of Informatics Pontifical Catholic University of Rio de Janeiro Rio de Janeiro Brazil Graduate Program in Computer Science State University of Ceará Fortaleza Brazil University of Hohenheim Stuttgart Germany

[Background] Emotional Intelligence (EI) can impact Software Engineering (SE) outcomes through improved team communication, conflict resolution, and stress management. SE workers face increasing pressure to develop both technical and interpersonal skills, as modern software development emphasizes collaborative work and complex team interactions. Despite EI’s documented importance in professional practice, SE education continues to prioritize technical knowledge over emotional and social competencies. [Objective] This paper analyzes SE students’ self-perceptions of their EI after a two-month cooperative learning project, using Mayer and Salovey’s four-ability model to examine how students handle emotions in collaborative development. [Method] We conducted a case study with 29 SE students organized into four squads within a project-based learning course, collecting data through questionnaires and focus groups that included brainwriting and sharing circles, then analyzing the data using descriptive statistics and open coding. [Results] Students demonstrated stronger abilities in managing their own emotions compared to interpreting others’ emotional states. Despite limited formal EI training, they developed informal strategies for emotional management, including structured planning and peer support networks, which they connected to improved productivity and conflict resolution. [Conclusion] This study shows how SE students perceive EI in a collaborative learning context and provides evidence-based insights into the important role of emotional competencies in SE education. Copyright © 2025, The Authors. All rights reserved.

关键词： Students

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Observation of Photonic Chiral Flatbands

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Physical Review Letters 2025年第10期134卷 103801-103801页

作者： Minho Choi Andrea Alù Arka Majumdar Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA and Physics Program Graduate Center City University of New York New York New York 10031 USA Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA and Department of Physics University of Washington Seattle Washington 98195 USA

Distinct selectivity to the spin angular momenta of photons has garnered significant attention in recent years, for its relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces with strong chiral responses to the incident light have been reported, these responses are typically limited to a narrow range of incident angles. In this study, we demonstrate a nonlocal metasurface that showcases strong chirality, characterized by circular dichroism (∼0.6), over a wide range of incident angles ±5°. Its quality factor, circular dichroism and resonant frequency can be optimized by design. These findings pave the way to further advance the development of valley-selective optical cavities and augmented reality applications.

关键词： Natural frequencies

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Comparative Analysis of Normal and ASD EEG Data Using Hjorth Parameters

Comparative Analysis of Normal and ASD EEG Data Using Hjorth...

引用

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

作者： Muliyadi Muliyadi Melinda Melinda Yuwaldi Away Syahrul Gazali Doctoral Program School of Engineering Post Graduate Program Universitas Syiah Kuala Banda Aceh Indonesia Electrical Engineering Department Politeknik Negeri Lhokseumawe Aceh Indonesia Dept. Electrical Engineering and Computer Engineering Faculty Universitas Syiah Kuala Banda Aceh Indonesia Dept. Neurology Universitas Syiah Kuala Banda Aceh Indonesia Mahar Mardjono National Brain Center Hospital Jakarta Indonesia

ISBN: (数字)9798331510886

ISBN: (纸本)9798331510893

The increasing prevalence of autism spectrum disorder (ASD) in recent decades has underscored the need for more accurate and objective diagnostic methods. Electroencephalography (EEG) holds promise as a tool in ASD neurobiological research due to its ability to capture neural oscillatory activity with high temporal resolution. This study aims to analyze the neurophysiological differences between individuals with ASD and neurotypical populations by examining EEG data using Hjorth parameters. The preprocessing stage involved using a Butterworth filter to enhance EEG signal quality by eliminating noise in the frequency range of 4-40 Hz. The Hjorth parameters, including Activity, Mobility, and Complexity, were used to assess the statistical characteristics of the EEG signals. The analysis was conducted on EEG data collected from 5 typical individuals and 5 ASD ASD subjects. Our findings reveal that the Hjorth Activity parameter is notably lower in the ASD group across all regions, with the most significant differences observed in the left and right frontal areas, where average activity measures 0.236 μV 2 and 0.060 μV 2 in ASD individuals, compared to 0.512 μV 2 and 0.138 μV 2 in the neurotypical group. However, the Hjorth Complexity and Mobility values remained consistent between the two groups, implying that the fundamental structure of the EEG signals is relatively preserved. These findings offer insights into the neurobiological mechanisms of ASD and suggest the potential use of Hjorth parameters in developing more targeted interventions for individuals with ASD.

关键词： Human computer interaction Autism Frontal lobe Noise Neural activity Electroencephalography Complexity theory Signal resolution Robots Optimization

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Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

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International Symposium on Applied science 2024, ISAS 2024

作者： Raza, Aquib Ching, Congo Tak Shing Liu, Peng-Ta Phan, Thien-Luan Tran, Ngoc-Luan Nguyen, Ha Anh T. Rameez, Mohammad Li, Hung-Chung Linh, Dao Nguyen Phuong Van Hieu, Nguyen Tran, Trung Nghia National Taiwan University Taipei City10673 Taiwan Research Center for Information Technology Academia Sinica Taipei City11529 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan Advanced Plant and Food Crop Biotechnology Center National Chung Hsing University Taichung402 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan Fall Prevention Center Department of Physical Medicine & Rehabilitation Changhua Christian Hospital Changhua500 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University - Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Department of Computer Science University of York York HeslingtonYO10 5DD United Kingdom Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan Ho Chi Minh City72409 Viet Nam HCMUT Vietnam National University Ho Chi Minh City Thu Duc Ho Chi Minh City71308 Viet Nam

This research introduces a deep learning framework that combines convolutional neural networks with autoencoders to improve the diagnostic accuracy of knee osteoarthritis. The study utilized a publicly available dataset from the Mendeley Data repository, where knee joint images were preprocessed using Contrast Limited Adaptive Histogram Equalization to enhance contrast and ensure consistent image sizing. Initially, an autoencoder was employed in an unsupervised manner to learn compressed representations of the data. These representations were then used to train a CNN to classify knee images into 'healthy' and 'osteoarthritic' categories. The model was trained using an 80:20 split for training and testing data, incorporating early stopping and data augmentation techniques to prevent overfitting and enhance generalization. Performance metrics such as accuracy, precision, recall, and the area under the Receiver Operating Characteristic curve (ROCAUC) were used to evaluate the model, resulting in a high test accuracy of 98.95%. The high precision and recall rates further confirmed the model's robustness in diagnosing KOA. To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to identify critical regions in the images that influenced the model's decisions. Additionally, t-Distributed Stochastic Neighbor Embedding (t-SNE) was used to visualize the high-dimensional encoded features in a two-dimensional space, providing deeper insights into how the model differentiates between classes. The promising results of this deep learning approach suggest its potential for broader applications in medical imaging diagnostics. By providing healthcare professionals with a tool that enhances diagnostic accuracy and operational efficiency, this framework lays the foundation for developing scalable, AI-driven diagnostic systems for various complex medical conditions. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Joints (anatomy)

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Reproducing ATT&CK Techniques and Lifecycles to Train Machine Learning Classifier

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IEEE Network 2025年

作者： Yudha, Fietyata Lin, Ying-Dar Lai, Yuan-Cheng Sudyana, Didik Hwang, Ren-Hung EECS International Graduate Program National Yang Ming Chiao Tung University Hsinchu City300 Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu City300 Taiwan The Department of Information Management National Taiwan University of Science and Technology Tapei106 Taiwan The Computer and Network Center National Cheng Kung University Tainan701 Taiwan The College of Artificial Intelligence National Yang Ming Chiao Tung University Tainan711 Taiwan

he MITRE ATT&CK framework categorizes threat actor behaviors into a sequence of techniques called the attack lifecycle. Based on this, Our work introduces a dual-labeled dataset that is accurately labeled with distinct techniques and lifecycles defined by ATT&CK. The dataset offered a more thorough perspective than previous datasets that employed binary or attack classification. It encompassed 17 distinct techniques throughout five lifecycles and was generated through an automated method that guarantees reproducibility and learnability. Reproducibility guarantees the dataset’s consistency, whereas learnability signifies its use in training machine learning models. Our analysis produced a positive result. The dataset achieved a Pearson correlation coefficient of 0.7 for reproducibility. Regarding distinguishing classes, it exhibits an average AUC-ROC score of 0.92 for techniques and 0.82 for lifecycles. The model training yielded an average F1 score of 0.95 for technique classification and 0.9 for lifecycle classification, but only for the traffic dataset. © 1986-2012 IEEE.

关键词： Adversarial machine learning

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AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Taiwan International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei11529 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu30013 Taiwan National Chengchi University Department of Computer Science Taipei11605 Taiwan National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu300044 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan

The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utilize visual modality or audio modality. While some methods exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multimodal datasets of deepfake videos involving acoustic and visual manipulations, and are mostly based on convolutional neural networks with low detection accuracy. Considering that human cognition instinctively integrates multisensory information including audio and visual cues to perceive and interpret content and the success of transformer in various fields, this study introduces the audio-visual transformer-based ensemble network (AVTENet). This innovative framework tackles the complexities of deepfake technology by integrating both acoustic and visual manipulations to enhance the accuracy of video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multimodal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that the proposed model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. We also compare AVTENet against humans in detecting video forgery. The results show that AVTENet significantly outperforms humans. © 2016 IEEE.

关键词： audio-visual AVTENet Deepfake detection

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Self-referentiality in the Brouwer-Heyting-Kolmogorov semantics of intuitionistic logic

Self-referentiality in the Brouwer-Heyting-Kolmogorov semant...

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International Symposium on Logical Foundations of computer science, LFCS 2013

作者： Yu, Junhua Doctoral Program in Computer Science Graduate Center City University of New York United States

ISBN: (纸本)9783642357213

The intended provability semantics of Intuitionistic Propositional Logic IPC (also called Brouwer-Heyting-Kolmogorov semantics) has been formalized within Gödel-Artemov's framework. According to this approach, IPC is embedded in modal logic S4 by Gödel embedding and S4 is realized in Artemov's Logic of Proofs LP which has a provability interpretation in Peano Arithmetic. Artemov's realization of S4 in LP uses self-referential LP-formulas of the form t : ö(t), namely, 't is a proof of a formula φ containing t itself.' Kuznets showed that this is not avoidable by offering S4-theorems that cannot be realized without using self-referential LP-formulas. This paper extends Kuznets' method to find IPC-theorems that call for direct self-referentiality in LP. Roughly speaking, examples include double-negations of tautologies that are not IPC-theorems, e.g., ≠≠(≠≠p → p), and there are also examples in the purely implicational fragment IPC →. This suggests that the Brouwer-Heyting-Kolmogorov semantics of intuitionistic logic is intrinsically self-referential. © Springer-Verlag 2013.

关键词： Semantics

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Nonsaturated large magnetoresistance and transport dynamics in a n-doped cryogenic WSe2 field-effect device

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Physical Review B 2025年第12期111卷 125307-125307页

作者： Wei-Chen Lin Ching-Chen Yeh Jia-Zhu Zou Nhat Anh Nguyen Phan Inayat Uddin Hai Yen Le Thi Kenji Watanabe Takashi Taniguchi Gil-Ho Kim Department of Engineering and System Science National Tsing Hua University Hsinchu 300 Taiwan Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan Department of Physics National Taiwan University Taipei 106 Taiwan Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon 164 Republic of Korea Sungkyunkwan Advanced Institute of Nano Technology (SAINT) Sungkyunkwan University (SKKU) Suwon 16419 Republic of Korea Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan

Interest in the two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) continues to intensify, driven by their suitable band gaps to supplant silicon as next-generation semiconductor materials. Among various TMDs, tungsten diselenide (WSe2) is renowned for its superior electrical properties in carrier density and mobility under ambient conditions. Despite its notable attributes, the behavior of monolayer WSe2 in the electron-doped regime under cryogenic conditions remains largely uncharted, particularly concerning its magnetotransport properties. In this study, we reveal the transport mechanisms of monolayer WSe2 from high temperatures down to the cryogenic regime. As evident by Efros–Shklovskii variable-range hopping (E-S VRH) in the cryogenic regime, strong Coulomb interactions arise between electrons. Above 8 K, an uncommon nonsaturated quadratic large magnetoresistance (MR) can be explained by the wave-function shrinkage model, which is consistent with the E-S VRH transport mechanism. Notably, the nonsaturated quadratic large MR shows a magnitude up to 1740% at 13 T. These findings underscore the potential applications for monolayer WSe2 in cryogenic field-effect devices, magnetic sensors, and memory devices and mark a significant advance in magnetotransport research.

关键词： Monolayers

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