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3rd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Byeon, Haewon Nair, Rajit Mahalakshmi, V. Khalaf, Mohammed I. Kaushik, Bharat Shabaz, Mohammad Inje University Department Of Ai And Software Gimhae50834 Korea Republic of School Of Computing Science & Engineering Vit Bhopal University Bhopal India College Of Engineering And Computer Science Jazan University Department Of Computer Science Jazan45142 Saudi Arabia Al Maarif University College Department Of Computer Science Al Anbar 31001 Iraq Masters University Of Northern Iowa IA United States Model Institute Of Engineering And Technology J&K Jammu India

ISBN: (纸本)9798350318609

Perioperative nutrition evaluation is crucial for patient care and resource efficiency in healthcare. This work proposes a deep learning-based perioperative nutrition evaluation tool that leverages sophisticated machine learning to improve predictions and assist clinicians in making better choices. As surgical techniques become more complex and medical technology progresses, a thorough postoperative nutrition study becomes more important than ever. An extensive review demonstrates that the recommended strategy performs better than other machine learning techniques. Our model's accuracy, precision, memory, and F1-score let it predict surgical outcomes more accurately. The higher AVC-ROC and AVC-PR values of the suggested approach show that it performs particularly well. Its sensitivity-specificity balance is demonstrated by this. Our approach generates fewer errors, according to the confusion matrix analysis, which makes it reliable for healthcare decisions. Our work enhances critical healthcare by assessing nutrition with state-of-the-art techniques. © 2024 IEEE.

关键词： Diagnosis

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Magnetic Domain Observation of Milled Nanocrystalline Alloy Powder

Magnetic Domain Observation of Milled Nanocrystalline Alloy ...

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2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Takezawa, Masaaki Nagaki, Tomoya Motozuka, Satoshi Sasaki, Iwao Ando, Yoshito Narahara, Hiroyuki Mori, Naoki Shikayama, Toru Mukai, Shinichiro Maeda, Shuhei Sakima, Shuhei Ishii, Takaaki Kyushu Institute of Technology Faculty of Engineering Kitakyushu804-8550 Japan Kyushu Institute of Technology Graduate School of Life Science and Systems Engineering Kitakyushu808-0196 Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering Iizuka820-8502 Japan Yaskawa Electric Corporation Kitakyushu806-0004 Japan

ISBN: (纸本)9798350338362

Fe-based nanocrystalline alloys have high magnetic flux density and low loss. So, in this study, the magnetic domain structure of ball-milled magnetic powders of these nanocrystalline alloys was observed using a Kerr effect microscope. The effect of strain removal heat treatment on the magnetic properties of the powder was also investigated by observing and comparing the magnetic domain structure of the milled powder before and after heat treatment during the preparation process of the nanocrystalline milled powder. Our findings showed that the strain removal heat treatment changed the size and shape of the magnetic domains to a simple structure. In addition, the magnetic wall motion was found to occur quickly, resulting in soft magnetic properties. © 2023 IEEE.

关键词： Nanocrystals

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Active Learning of One-Clock Timed Automata Using Constraint Solving 20th

Active Learning of One-Clock Timed Automata Using Constrain...

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20th International Symposium on Automated Technology for Verification and Analysis, ATVA 2022

作者： Xu, Runqing An, Jie Zhan, Bohua State Key Laboratory of Computer Science Institute of Software CAS Beijing China University of Chinese Academy of Sciences Beijing China Max Planck Institute for Software Systems Kaiserslautern Germany

ISBN: (纸本)9783031199912

Active automata learning in the framework of Angluin’s L∗ algorithm has been applied to learning many kinds of automata models. In applications to timed models such as timed automata, the main challenge is to determine guards on the clock value in transitions as well as which transitions reset the clock. In this paper, we introduce a new algorithm for active learning of deterministic one-clock timed automata and timed Mealy machines. The algorithm uses observation tables that do not commit to specific choices of reset, but instead rely on constraint solving to determine reset choices that satisfy readiness conditions. We evaluate our algorithm on randomly-generated examples as well as practical case studies, showing that it is applicable to larger models, and competitive with existing work for learning other forms of timed models. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Codes (symbols)

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Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

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computer systems science & engineering 2023年第5期45卷 1199-1210页

作者： Himanshu Sharma karthikeyan Rajagopal G.Gugapriya Rajneesh Pareek Arun Kumar HayaMesfer Alshahrani Mohamed K.Nour Hany Mahgoub Mohamed Mousa Anwer Mustafa Hilal Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia School of Electronics Engineering Vellore Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Electrical Engineering Department Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Multicarrier Waveform(MCW)has several advantages and plays a very important role in cellular *** generation(5G)MCW such as Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC)are thought to be important in 5G *** Peak to Average Power Ratio(PAPR)is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user *** paper presents a novel Divergence Selective Mapping(DSLM)and Divergence Partial Transmission Sequence(D-PTS)for 5G *** is seen that the proposed D-SLM and PTS lower PAPR with low computational *** work highlighted a combination of multi-data block partial transmit schemes along with tone *** this,an overlapping factor is used to determine the number of data blocks for every ***,considering only those data blocks that have minimum signal power,the use of DSLM and DPTS are required to eliminate the segment’s *** results reveal that the suggested hybrid technique proves to be better than the conventional PTS ***,the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing(OFDM)waveform.

关键词： 5G PAPR D-SLM D-PTS

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Don't Forget the Exception! : Considering Robustness Changes to Identify Design Problems 20

Don't Forget the Exception! : Considering Robustness Changes...

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20th IEEE/ACM International Conference on Mining software Repositories, MSR 2023

作者： Oliveira, Anderson Correia, Joao Sousa, Leonardo Assuncao, Wesley K. G. Coutinho, Daniel Garcia, Alessandro Oizumi, Willian Barbosa, Caio Uchoa, Anderson Pereira, Juliana Alves Informatics Department - Pontifical Catholic Rio de Janeiro Brazil Carnegie Mellon University Department of Electrical and Computer Engineering Pittsburgh United States Institute of Software Systems Engineering Linz Austria Itapajé Brazil

ISBN: (纸本)9798350311846

Modern programming languages, such as Java, use exception-handling mechanisms to guarantee the robustness of software systems. Although important, the quality of exception code is usually poor and neglected by developers. Indiscriminate robustness changes (e.g., the addition of empty catch blocks) can indicate design decisions that negatively impact the internal quality of software systems. As it is known in the literature, multiple occurrences of poor code structures, namely code smells, are strong indicators of design problems. Still, existing studies focus mainly on the correlation of maintainability smells with design problems. However, using only these smells may not be enough since developers need more context (e.g., system domain) to identify the problems in certain scenarios. Moreover, these studies do not explore how changes in the exceptional code of the methods combined with maintainability smells can give complementary evidence of design problems. By covering both regular and exception codes, the developer can have more context about the system and find complementary code smells that reinforce the presence of design problems. This work aims to leverage the identification of design problems by tracking poor robustness changes combined with maintainability smells. We investigated the correlation between robustness changes and maintainability smells on the commit history of more than 160k methods from different releases of 10 open-source software systems. We observed that maintainability smells can be worsened or even introduced when robustness changes are performed. This scenario mainly happened for the smells Feature Envy, Long Method, and Dispersed Coupling. We also analyzed the co-occurrence between robustness and maintainability smells. We identified that the empty catch block and catch throwable robustness smells were the ones that co-occurred the most with maintainability smells related to the Concern Overload and Misplaced Concern design problems. T

关键词： Maintainability

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Runtime Enforcement of CPS against Signal Temporal Logic 28

Runtime Enforcement of CPS against Signal Temporal Logic

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28th International Conference on Hybrid systems: Computation and Control, HSCC 2025, held as part of the 18th Cyber-Physical systems and Internet-of-Things Week, CPS-IoT Week 2025

作者： Su, Han Shankar, Saumya Pinisetty, Srinivas Roop, Partha S. Zhan, Naijun Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Department of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand School of Electrical and Computer Sciences Indian Institute of Technology Bhubaneswar Bhubaneswar India Peking University School of Computer Science Key Lab. of High Confidence Software Technology Beijing China

ISBN: (纸本)9798400715044

Cyber-Physical systems (CPSs), especially those involving autonomy, need guarantees of their safety. Runtime Enforcement (RE) is a lightweight method to formally ensure that some specified properties are satisfied over the executions of the system. Hence, there is recent interest in the RE of CPS. However, existing methods are not designed to tackle specifications suitable for the hybrid dynamics of CPS. With this in mind, we develop runtime enforcement of CPS using properties defined in Signal Temporal Logic (STL). In this work, we aim to construct a runtime enforcer for a given STL formula to minimally modify a signal to satisfy the formula. To achieve this, the STL formula to be enforced is first translated into a timed transducer, while the signal to be corrected is encoded as timed words. We provide timed transducers for the temporal operators until and release noting that other temporal operators can be expressed using these two. Our approach enables effective enforcement of STL properties for CPS. A case study is provided to illustrate the approach and generate empirical evidence of its suitability for CPS. © 2025 Copyright held by the owner/author(s).

关键词： Reactive System Runtime Enforcement Signal Temporal Logic Timed Automata Timed Transducer

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AgileShard: Turning the Sharded Blockchain into a Real-Time Transaction Processing System 44

AgileShard: Turning the Sharded Blockchain into a Real-Time ...

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44th IEEE Real-Time systems Symposium, RTSS 2023

作者： Shi, Jianfeng Wu, Heng Liu, Wang Gao, Heran Zhang, Wenbo University of Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Nanjing China Software Engineering Technology Research and Development Center Institute of Software Chinese Academy of Sciences Beijing China Nanjing Institute of Software Technology Nanjing China Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Beijing China

ISBN: (纸本)9798350328578

Blockchain, as an emerging transaction processing system, suffers from low throughput and high latency. Sharded blockchains can significantly increase throughput by dividing nodes into groups (i.e., shards) to process disjoint transactions in parallel. However, the diverse latency requirements of transactions in current sharded blockchains are not well met. Three challenges prevent the sharded blockchain from becoming a real-time transaction processing system, namely, the static block size, the first-come-first-served transaction packing strategy, and the load imbalance. Therefore, this paper proposes 3 methods to help turn the sharded blockchain into a real-time transaction processing system. First, we propose an inter-shard dynamic block size negotiation method that enables shards to adaptively determine the globally optimal block size based on the deadlines of pending transactions. Then, we propose a DAG-based transaction packing method for reducing the number of deadline violations and improving parallelism. Finally, we propose a minimum-cost-flow-based shard reconfiguration method to address load imbalance. Under real datasets on Ethereum, experimental results show that AgileShard using the above three methods can effectively improve the transaction deadline satisfaction rate. © 2023 IEEE.

关键词： Blockchain

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Retinal Image Analysis for Early Deduction of Diabetic Retinopathy 9

Retinal Image Analysis for Early Deduction of Diabetic Retin...

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9th International Conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Chinnasamy, A. Selvakumari, P. SRMIST School of Computing Department of Data Science and Business Systems Chennai India Anna University Chennai Institute of Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397376

The prevalence of DR is steadily rising, which necessitates the automatic disease severity extraction and classification. About 2% of those with this illness are entirely blind because of the diabetic mellitus problem and 10% get vision impairment after 15 years of diabetes as a result of the DR complication. It is also a significant contributor to blindness in both middle aged and older age groups. The patient may develop to severe stages of irreversible blindness if the condition is not detected early. The growing number of diabetic patients face a major issue due to a lack of ophthalmologists. It is suggested that an automated DR screening system be created to aid the ophthalmologist in making decisions. One of the primary symptoms of the DR is hard exudates. The detection of hard exudates is crucial for screening purposes and aids in disease monitoring and diagnosis. Thus, utilising Lloyd's clustering technique, this work offered a unique techniques to segment the exudates and irregularities in DR were found. © 2023 IEEE.

关键词： Mean square error

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mmMC: A Contactless Wood Moisture Content Measurement System based on COTS FMCW mmWave Radar 21

mmMC: A Contactless Wood Moisture Content Measurement System...

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21st Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2024

作者： Hu, Xueyang Liu, Tian Islam, Minarul Shu, Tao Department of Broadband Communication Peng Cheng Laboratory China Institute of Agricultural Equipment Zhejiang Academy of Agricultural Sciences Hangzhou China Department of Computer Science and Software Engineering Auburn University United States

ISBN: (纸本)9798331519186

Estimation of wood moisture content (MC) is a fundamental aspect of woodworking, construction, and various other industries that rely on the versatile properties of wood. In this paper, we present mmMC, a novel system that estimates the MC of wood by a single commercial off-the-shelf (COTS) mmWave radar, which provides accurate end-to-end real-time wood moisture measurement results while being non-invasive, portable, and flexible in deployment. The proposed system uses a novel target reflection feature (TRF) to determine the reflectivity of the wood, thereby correlating it with specific MC levels. To robustly and accurately estimate the TRF of the wood from the mmWave signal, a signal processing pipeline is proposed. Specifically, an object detection and signal extraction module is designed to resolve the range of the object and eliminate multipath effects of the original signal. Then, a multiple chirps/antennas signals processing module is proposed to obtain a stable TRF from the extracted signals by using signals from different antennas and chirps. The TRF is associated with the MC of wood by a regression to enable real-time MC estimation. Through extensive real-world experiments, we have demonstrated that the proposed system has high accuracy and reliability. © 2024 IEEE.

关键词： mmWave sensing noninvasive sensing wood moisture content

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Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem 30

Benchmarking Hallucination in Large Language Models based on...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Sun, Yuhong Yin, Zhangyue Guo, Qipeng Wu, Jiawen Qiu, Xipeng Zhao, Hui Software Engineering Institute East China Normal University China School of Computer Science Fudan University China Shanghai AI Laboratory China Shanghai Key Laboratory of Trustworthy Computing Shanghai China

ISBN: (纸本)9782493814104

Large language models (LLMs) are highly effective in various natural language processing (NLP) tasks. However, they are susceptible to producing unreliable conjectures in ambiguous contexts called hallucination. This paper presents a new method for evaluating LLM hallucination in Question Answering (QA) based on the unanswerable math word problem (MWP). To support this approach, we innovatively develop a dataset called Unanswerable Math Word Problem (UMWP) which comprises 5200 questions across five categories. We developed an evaluation methodology combining text similarity and mathematical expression detection to determine whether LLM considers the question unanswerable. The results of extensive experiments conducted on 31 LLMs, including GPT-3, InstructGPT, LLaMA, and Claude, demonstrate that in-context learning and reinforcement learning with human feedback (RLHF) training significantly enhance the model's ability to avoid hallucination. We show that utilizing MWP is a reliable and effective approach to assess hallucination. Our code and data are available at https://***/Yuki-Asuuna/UMWP. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Reinforcement learning

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