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2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Ju, Xin He, Jun Wen, Mei Feng, Jing Cao, Yasong Shen, Junzhong Chen, Zhaoyun Shi, Yang School of Computer National University of Defense Technology Key Laboratory of Advanced Microprocessor Chips and Systems Changsha410073 China

ISBN: (纸本)9783982674100

Deep Neural Networks (DNNs) impose significant computational demands, necessitating optimizations for computational and energy efficiencies. Per-vector scaling, which applies a scaling factor to blocks of elements using narrow integer types, effectively reduces storage and computational overhead. However, the frequent occurrence of floating-point accumulations between vectors limits further improvements in energy efficiency. State-of-the-art accelerators address this challenge by grouping and summing vector products based on their exponent differences, thereby reducing the overhead associated with intra-group shifting and accumulation. Nevertheless, this approach increases the complexity of register usage and grouping logic, leading to limited energy benefits and hardware efficiency. In this context, we introduce WinAcc, a novel algorithm and architecture co-designed solution that utilizes a low-cost accumu-lator to handle the majority of data in DNNs, offering low area overhead and high energy efficiency gains. Our key insight is that the data of DNNs follows a Laplace-like distribution, which enables the use of a customized data format with a narrow dynamic range to encode most of the data. This allows for the design of a low-cost accumulator with narrow shifters and adders, significantly reducing reliance on floating-point accumulator and consequently improving energy efficiency. Compared with state-of-the-art architecture Bucket, WinAcc achieves 33.95% energy reduction across seven representative DNNs and reduces area by 9.5% while maintaining superior model performance. © 2025 EDAA.

关键词： Deep neural networks

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Design and Simulation of a PV System with Battery Storage Using Bifacial Halfcut Module 8

Design and Simulation of a PV System with Battery Storage Us...

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8th International Conference on Electronics, Materials Engineering and Nano-technology, IEMENTech 2025

作者： Bala, Sourav Sarkar, Sudipta Maity, Santanu Mukhopadhyay, Sumita School of Advanced Materials Indian Institute of Engineering Science and Technology Green Energy and Sensor Systems Howrah Shibpur India

ISBN: (纸本)9798331520762

In the absence of conventional energy sources renewable energy is the only suitable option left. Multiple renewable energy sources like Hydroelectric Energy, Tidal Energy, Geothermal Energy, and Solar Electrical Energy are becoming popular every day. There are multiple reasons such as its availability in small to large sizes, predictability, easy installation, smooth maintenance process, drop in system installation cost, and mostly fast return on investment. With the increase in demand for solar photovoltaic panels, the demand for producing higher power output from less area is increasing rapidly. Hence with every breakthrough, the efficiency of the Photovoltaic Panel is increasing rapidly. With continuous development, the PV modules are developed in such a way that light can be absorbed from the front and rear on both sides. In the Bi-facial module, the direct sunlight gets absorbed from the front, and the albedo is also absorbed from the back to increase the power generation further. With the implementation of half-cut technology, the shading losses are minimized further. Rapid development is also being done on MPPT and Inverter to improve efficiency. Presently a generalized mathematical model for bifacial half-cut module is not published in any literature. In this paper, the research gap is covered by designing a Bifacial Half-cut PV Module along with an MPPT and also a bidirectional DC-DC Converter for charging and discharging of Battery Bank. Finally, we have integrated the system and also have simulated the designed system to check its stability. Such a model helps in analyzing and validating performance characteristics of commercially available bifacial modules and half-cut modules. © 2025 IEEE.

关键词： Tidal power

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A Hybrid Deep Learning Approach for Epileptic Seizure Detection in EEG signals

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IEEE Journal of Biomedical and Health Informatics 2023年 PP卷 1-12页

作者： Ahmad, Ijaz Wang, Xin Javeed, Danish Kumar, Prabhat Samuel, Oluwarotimi Williams Chen, Shixiong CAS Key Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong China

Early detection and proper treatment of epilepsy is essential and meaningful to those who suffer from this disease. The adoption of deep learning (DL) techniques for automated epileptic seizure detection using electroencephalography (EEG) signals has shown great potential in making the most appropriate and fast medical decisions. However, DL algorithms have high computational complexity and suffer low accuracy with imbalanced medical data in multi seizure-classification task. Motivated from the aforementioned challenges, we present a simple and effective hybrid DL approach for epileptic seizure detection in EEG signals. Specifically, first we use a K-means Synthetic minority oversampling technique (SMOTE) to balance the sampling data. Second, we integrate a 1D Convolutional Neural Network (CNN) with a Bidirectional Long Short-Term Memory (BiLSTM) network based on Truncated Backpropagation Through Time (TBPTT) to efficiently extract spatial and temporal sequence information while reducing computational complexity. Finally, the proposed DL architecture uses softmax and sigmoid classifiers at the classification layer to perform multi and binary seizure-classification tasks. In addition, the 10-fold cross-validation technique is performed to show the significance of the proposed DL approach. Experimental results using the publicly available UCI epileptic seizure recognition data set shows better performance in terms of precision, sensitivity, specificity, and F1-score over some baseline DL algorithms and recent state-of-the-art techniques. IEEE

关键词： Feature extraction

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Arti cial neural network-based predictive model for output characteristics in drilling of quartz cyanate ester polymeric composite

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Scientia Iranica 2023年第2B期30卷 391-408页

作者： Ramalingam, T. Nath, N. Kishore Selvaraj, N. Advanced Systems Laboratory DRDO Telangana Hyderabad500058 India Department of Mechanical Engineering National Institute of Technology Telangana Warangal506004 India

Apart from the widely used polymeric bers, Quartz ber is the one that possesses various characteristics. Quartz polymeric ber in combination with Cyanate Ester resin produces a high-performance composite that has excellent properties and is used primarily in military applications. The present investigation aims at developing a model to predict the output characteristics of hole in the drilling of Quartz composite laminate. Output parameters considered are thrust force, torque, exit delamination factor, hole diameter, cylindricity, and surface roughness. Vacuum Assisted Resin Transfer Molding (VARTM) process was adopted for laminate manufacturing. Full factorial design of experiments was considered for the selected input parameters and experiments were carried out. Further modeling was developed to predict the output parameters employing Back Propagation Neural Network (BPNN) method and it was found that the optimal network architecture was 3-45-15-10-6 with Mean Squared Error (MSE) of 0.0105. Experimental results were analyzed and the in uence of input parameters in this drilling process was studied. The testing data were consistent with the output parameters predicted from the model and the obtained maximum error was 7.58%. Further, the model developed was validated with a new batch of experiments and the values obtained were satisfactory with maximum error of 7.17%. © 2023 Sharif University of technology. All rights reserved.

关键词： Design of experiments

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Reconfiguration of vertex-disjoint shortest paths on graphs

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Journal of Graph Algorithms and Applications 2024年第3期28卷 87-101页

作者： Saito, Rin Eto, Hiroshi Ito, Takehiro Uehara, Ryuhei Graduate School of Information Sciences Tohoku University Sendai Japan School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan School of Information Science Japan Advanced Institute of Science and Technology Nomi Japan

We introduce and study reconfiguration problems for (internally) vertex-disjoint shortest paths: Given two tuples of internally vertex-disjoint shortest paths for fixed terminal pairs in an unweighted graph, we are asked to determine whether one tuple can be transformed into the other by exchanging a single vertex of one shortest path in the tuple at a time, so that all intermediate results remain tuples of internally vertex-disjoint shortest paths. We also study the shortest variant of the problem, that is, we wish to minimize the number of vertex-exchange steps required for such a transformation, if exists. These problems generalize the well-studied Shortest Path Reconfiguration problem. In this paper, we analyze the complexity of these problems from the viewpoint of graph classes, and give some interesting contrast. © 2024, Brown University. All rights reserved.

关键词： Graph theory

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A STUDY ON CHIP DELAY MEASUREMENT SENSOR BASED ON SCAN CHAIN 10

A STUDY ON CHIP DELAY MEASUREMENT SENSOR BASED ON SCAN CHAIN

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Liu, Peixin Hu, Xiao Yi, Xinjie National University of Defense Technology Changsha China Key Laboratory of Advanced Microprocessor Chips and Systems Changsha China

ISBN: (纸本)9781837242672

The reliability and performance of integrated circuits degrade over time, with one critical factor being the aging of numerous internal combinational logic circuits. Delay variations in these circuits not only reflect the chip's external environmental conditions but also indicate the degree of aging during its operational life. Traditional aging delay measurement sensors typically employ dedicated sampling circuits, which pose challenges for comprehensive detection of delays across all combinational logic paths within the chip. This study introduces a novel chip aging sensor, termed the FATE-Sensor, which leverages the internal scan chains of the chip. By performing a full-chip frequency scan of the combinational logic circuits, the FATE-Sensor can detect delay variations at various combinational logic locations using the extensive coverage provided by the scan chains. This paper presents a detailed investigation of the FATE-Sensor's characteristics, including its consistency, repeatability, temperature and voltage dependencies, and resolution enhancement. Experimental calibration of the FATE-Sensor demonstrates its effectiveness in monitoring and reflecting delay variations within the chip's internal circuits. This capability allows for accurate assessment of the chip path delay status, thus enhancing the reliability of chips used in high-precision and advanced applications. This technology not only aids in identifying potential faulty chips and supports chip timing verification testing but also provides new insights for understanding and extending chip lifespan. © The Institution of Engineering & technology 2024.

关键词： Delay circuits

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Single-Wavelength Laminar Optical Tomography for In Vivo Microvascular Three-Dimensional Imaging 46

Single-Wavelength Laminar Optical Tomography for In Vivo Mic...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Cui, Han Han, Dewei Liu, Wenquan Deng, Xinping Xin, Zhixuan Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China

ISBN: (纸本)9798350371499

Laminar Optical Tomography (LOT) is a promising non-invasive technique for three-dimensional imaging of complex biological structures, combining high resolution and deep penetration. In this study, a LOT system was assembled using a 520nm continuous-wave laser, exploiting the contrast mechanism provided by the unique optical absorption coefficient of hemoglobin at this wavelength for microvascular imaging. The system utilizes raster scanning to illuminate the target tissue's surface, capturing backscattered light intensity with a multi-channel Photomultiplier Tubes. The inverse problem of light propagation within the tissue is solved to reconstruct a three-dimensional image of microvasculature. Phantom and in-vivo rat ear results demonstrate the system's ability to image micro vessels with diameters of several hundred micrometers within the tissue. The implemented LOT system, known for its simplicity and cost-effectiveness, showcases its potential for applications in microvascular physiological and pathological research, as well as clinical diagnostics. © 2024 IEEE.

关键词： Clinical research

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Nuclei Segmentation in Histopathology Images Using Structure-Preserving Color Normalization Based Ensemble Deep Learning Frameworks

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Computers, Materials & Continua 2023年第12期77卷 3077-3094页

作者： Manas Ranjan Prusty Rishi Dinesh Hariket Sukesh Kumar Sheth Alapati Lakshmi Viswanath Sandeep Kumar Satapathy Centre for Cyber-Physical Systems Vellore Institute of TechnologyChennai600127India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Centre for Advanced Data Science Vellore Institute of TechnologyChennai600127India

This paper presents a novel computerized technique for the segmentation of nuclei in hematoxylin and eosin(H&E)stained histopathology *** purpose of this study is to overcome the challenges faced in automated nuclei segmentation due to the diversity of nuclei structures that arise from differences in tissue types and staining protocols,as well as the segmentation of variable-sized and overlapping *** this extent,the approach proposed in this study uses an ensemble of the UNet architecture with various Convolutional Neural Networks(CNN)architectures as encoder backbones,along with stain normalization and test time augmentation,to improve segmentation ***,this paper employs a Structure-Preserving Color Normalization(SPCN)technique as a preprocessing step for stain *** proposed model was trained and tested on both single-organ and multi-organ datasets,yielding an F1 score of 84.11%,mean Intersection over Union(IoU)of 81.67%,dice score of 84.11%,accuracy of 92.58%and precision of 83.78%on the multi-organ dataset,and an F1 score of 87.04%,mean IoU of 86.66%,dice score of 87.04%,accuracy of 96.69%and precision of 87.57%on the single-organ *** findings demonstrate that the proposed model ensemble coupled with the right pre-processing and post-processing techniques enhances nuclei segmentation capabilities.

关键词： Nuclei segmentation image segmentation ensemble U-Net deep learning histopathology image convolutional neural networks

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Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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Science China Chemistry 2025年第5期68卷 2027-2034页

作者： Jie Zhang Yi Chen Guijun Li Zelin Sun Zhengong Meng Wai-Yeung Wong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer EngineeringThe Hong Kong University of Science and Technology School of Flexible Electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

关键词： organometallic precursor magnetic nanoparticles block copolymer self-assembly nanoimprint lithography

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Chatbots in Academia: A Retrieval-Augmented Generation Approach for Improved Efficient Information Access 16

Chatbots in Academia: A Retrieval-Augmented Generation Appro...

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16th International Conference on Knowledge and Smart technology, KST 2024

作者： Maryamah, Maryamah Irfani, Muhammad Maula Tri Raharjo, Edric Boby Rahmi, Netri Alia Ghani, Mohammad Raharjana, Indra Kharisma Universitas Airlangga Data Science Technology Faculty of Advanced Technology and Multidiscipline Surabaya Indonesia Universitas Airlangga Informations Systems Faculty of Science and Technology Surabaya Indonesia

ISBN: (纸本)9798350370737

In today's digital age, higher education utilizes chatbots as virtual assistants to assist users, especially prospective students to access information easily. A chatbot is an application in natural language conversations to simulate intelligent interactions. Intelligent chatbots are needed to understand user needs and answer questions relevantly. We propose a chatbot with Retrieval Augmented Generation approach involving a retriever with cosine similarity search using OpenAI Ada embeddings to obtain relevant documents. The LLM OpenAI GPT-3.5- Turbo then generates the final answer. The chatbot mechanism begins with the retrieval module systematically identifying documents stored in the vector database that contain relevant information related to the user's query. The selected documents and query are provided to the LLM as part of the prompt to generate responses based on the knowledge provided in the relevant documents. The retrieval method is evaluated based on two criteria: the search method and the embedding model. The comparison method uses similarity search with Maximum Marginal Relevance (MMR) Search and the proposed embedding method against other models such as Google Embedding-001 and MPNet-Multilingual. The retrieval process is assessed using an evaluation dataset that incorporates Recall and Precision metrics, while answer generation is measured with BLEU and ROUGE Score. The observed disparity result between similarity search and MMR is not notably significant. Nonetheless, our chatbot holds an advantage in referencing past conversations due to its ability to store conversation history. Furthermore, potential enhancements are identified by augmenting the knowledge provided to the LLM in forthcoming iterations. © 2024 IEEE.

关键词： Embeddings

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