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9th International Symposium on Computing and Networking Workshops, CANDARW 2021

作者： Saito, Daiki Hirofuchi, Takahiro Arai, Hiroko Sato, Yukinori Toyohashi University of Technology Department of Computer Science And Engineering Aichi Japan Digital Architecture Research Center Tokyo Japan Research Center For Emerging Computing Technologies Tsukuba Japan

ISBN: (纸本)9781665428354

In order to reduce power consumption of the main memory of computers, the use of MRAM (magnetoresistive random access memory) instead of DRAM is attractive, since MRAM does not require periodic refresh energy while achieving sufficiently small read/write latencies. Among various types of MRAM devices, VC-MRAM (voltage-controlled MRAM) has a great potential to realize massively energy-efficient memory subsystems. Its write energy is 2 times orders of magnitudes smaller than that of STT-MRAM. The problem with VC-MRAM, however, is that its write error rate (i.e., 10-4 with today's typical technologies) is much higher than the acceptable error rate that has been supposed to be required for the main memory (i.e., 10-9). In this paper, we investigate whether such errors derived from an erroneous memory device cause a problem in actual program execution in the memory subsystem with hierarchical cache memory. We develop a memory subsystem simulator that mimics the structure of the multi-level caches and the main memory based on a VC-MRAM model, and observe cell-level operations in the main memory throughout the execution of benchmark programs. From results, we find the number of bit corruptions depends greatly on the cache size and the error model of the device. This is because the number of memory accesses itself can be significantly reduced by passing through the cache. Furthermore, we observe that the occurrences of bit corruptions more than 3 bits that cannot be handled properly by the hamming ECC codes seldom happen. This observation leads us to the insight that VC-MRAM with Hamming ECC can be used as main memory in some applications if these are executed on CPUs with a large cache memory. © 2021 IEEE.

关键词： MRAM devices

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A Train with Automatic Functioning based on IoT with Solar Energy Source

A Train with Automatic Functioning based on IoT with Solar E...

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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Padmakala, S. Alkawak, Omar A. Reddy, G. Vidya Sagar Narendranathan, S.K. Muthuraman, M.S. Sendilvelan, S. Saveetha School of Engineering Simats Department of Computer Science and Engineering Tamil Nadu Chennai India Al-Mustaqbal University College Department of Air Conditioning and Refrigeration Technical Engineering Babil Hilla Iraq School of Architecture Koneru Lakshmaiah Educational Foundation Andhra Pradesh Guntur India Agni College of Technology Department of Mechanical Engineering Tamil Nadu Chennai India Psna College of Engineering and Technology Department of Mathematics Tamil Nadu Dindigul India Dr. M.G.R Educational and Research Institute Department of Mechanical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665474511

The railway industry is one of the most sustainable modes of transport. To reduce the carbon footprints, renewable energy sources are initiated. The proposal of attaching solar panels to railway sleepers, smart garbage bin, lighting, automatic closing and opening of doors that are accompanied with real time monitoring system with multiple technologies. Among the multiple technology the Internet of Things (IoT) plays a significant role by sending information and monitoring the overall functions. The solar energy obtained is used to generate electricity and further they are stored in battery for future usage. © 2023 IEEE.

关键词： Carbon footprint

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PROV-IO+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems

arXiv

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arXiv 2023年

作者： Han, Runzhou Zheng, Mai Byna, Suren Tang, Houjun Dong, Bin Dai, Dong Chen, Yong Kim, Dongkyun Hassoun, Joseph Thorsley, David Wolf, Matthew Department of Electrical and Computer Engineering Iowa State University United States Department of Computer Science and Engineering The Ohio State University United States Scientific Data Management Group Lawrence Berkeley National Laboratory United States Computer Science Department University of North Carolina Charlotte United States Systems Architecture Lab Samsung United States Samsung Advanced Institute of Technology Samsung Korea Republic of

Data provenance, or data lineage, describes the life cycle of data. In scientific workflows on HPC systems, scientists often seek diverse provenance (e.g., origins of data products, usage patterns of datasets). Unfortunately, existing provenance solutions cannot address the challenges due to their incompatible provenance models and/or system implementations. In this paper, we analyze four representative scientific workflows in collaboration with the domain scientists to identify concrete provenance needs. Based on the first-hand analysis, we propose a provenance framework called PROV-IO+, which includes an I/O-centric provenance model for describing scientific data and the associated I/O operations and environments precisely. Moreover, we build a prototype of PROV-IO+ to enable end-to-end provenance support on real HPC systems with little manual effort. The PROV-IO+ framework can support both containerized and non-containerized workflows on different HPC platforms with flexibility in selecting various classes of provenance. Our experiments with realistic workflows show that PROV-IO+ can address the provenance needs of the domain scientists effectively with reasonable performance (e.g., less than 3.5% tracking overhead for most experiments). Moreover, PROV-IO+ outperforms a state-of-the-art system (i.e., ProvLake) in our experiments. © 2023, CC BY-NC-SA.

关键词： Life cycle

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Tighter Bounds of Speedup Factor of Partitioned EDF for Constrained-Deadline Sporadic Tasks 42

Tighter Bounds of Speedup Factor of Partitioned EDF for Cons...

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42nd IEEE Real-Time Systems Symposium, RTSS 2021

作者： Liu, Xingwu Chen, Zizhao Han, Xin Sun, Zhenyu Guo, Zhishan School of Mathematical Sciences Dalian University of Technology China SK-Lab of Media Convergence Production Technology and Systems Chinaso Inc School of Software Technology Dalian University of Technology China SK-Lab of Computer Architecture ICT CAS University of CAS Beijing China Department of Electrical and Computer Engineering University of Central Florida United States

ISBN: (纸本)9781665428026

Even though earliest-deadline-first (EDF) is optimal in terms of uniprocessor schedulability, it is co-NP-hard to precisely verify uniprocessor schedulability for constrained-deadline task sets. The most efficient way to solve this problem in polynomial time is via a partially linear approximation of the demand bound function. Such approximation leads to a simple uniprocessor schedulability testing with speedup factor ρ. Such a result further leads to Deadline-Monotonic Partitioned-EDF on multi-processors with speedup factor of 1 + ρ − 1/m (where m is the number of processors). The current state of the art results indicate that ρ is within the range [1.5, 14/9]. Especially, it has been a conjecture that ρ = 1.5. This paper improves the range of ρ to (1.5026, 1.5380). The improved lower bound disproves the conjecture of lower bound 1.5. A novel technique is to construct an auxiliary function that is larger than the approximate demand bound function but keeps the supremum ρ unchanged. It solves the dilemma that beating the lower bound 1.5 requires extremely large task sets, while the large size makes it difficult to check the schedulability. This technique not only enables us to disprove 1.5 by a task set of only eight tasks, but also sheds light on future work in transferring/downsizing task sets and deriving utilization bound based tests for various workload abstraction models, such as DAG tasks. ©2021 IEEE

关键词： Polynomial approximation

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ANALYSIS OF CONCRETE CRACKS AND FATIGUE IN SMART CITIES USING YOLOV3

ANALYSIS OF CONCRETE CRACKS AND FATIGUE IN SMART CITIES USIN...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023

作者： Archana, U. Sharma, Sarvdaman Singh, Sitesh Kumar Sureshkumar, R. Senthilkumar, P. Harish Babu, T. Department of Computer Science and Design R.M.K. Engineering College Chennai India Department of Civil Engineering University Institute of Engineering and Technology University of Jammu Jammu & Kashmir India Department of Civil Engineering Wollega University Oromia Nekemte Ethiopia Department of Electronics and Communication Engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai India KL School of Architecture Koneru Lakshmaiah Education Foundation Greenfield Vaddeswaram Andhra Pradesh Guntur India Department of Electrical and Electronics Engineering Sethu Institute of Technology Tamilnadu India

ISBN: (纸本)9798350305708

This study focuses on the application of the YOLOv3 (You Only Look Once version 3) object detection algorithm for the analysis of concrete cracks and fatigue within Smart Cities. Concrete infrastructure plays a crucial role in urban environments, and its structural integrity is paramount for ensuring public safety and sustainable development. The proposed approach utilizes YOLOv3 to identify and localize instances of concrete cracks and signs of fatigue in images and videos captured from various urban settings. By leveraging deep learning techniques, this research aims to enhance the efficiency and accuracy of monitoring and maintaining concrete structures, contributing to the overall resilience and longevity of Smart Cities. The findings of this study present valuable insights into the potential of utilizing advanced computer vision methods for proactive infrastructure management in the urban landscape. © 2023 IEEE.

关键词： Concrete cracks Fatigue analysis Infrastructure monitoring Smart Cities YOLOv3

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Event Graphs: Syntax, Semantics, and Implementation 23

Event Graphs: Syntax, Semantics, and Implementation

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Proceedings of the Winter Simulation Conference

作者： Murat M. Gunal Yahya Ismail Osais Gerd Wagner Faculty of Engineering and Architecture Fenerbahce University Ataşehir Istanbul TURKEY Computer Engineering Department Center for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Dhahran SAUDI ARABIA Brandenburg University of Technology Cottbus GERMANY

ISBN: (纸本)9798350369663

This tutorial aims to introduce Event Graphs (EGs), invented 40 years ago by Lee Schruben to allow event-based modeling of discrete dynamic systems. Their simplicity and naturalness in causality modelling and simulation modelling made EGs popular in research and practice. In a simulation, an event causes state changes in a system as well as other events to happen in the future. EGs provide a parsimonious diagram representation for the Event Scheduling paradigm of Discrete Event Simulation. We first introduce their visual syntax and informal semantics, and then present a recent extension by adding objects to EGs. Our tutorial also includes an introduction to the formal semantics of EGs and a Python implementation for executing EGs.

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Brain Surface Can Predict Fiber Connections

Brain Surface Can Predict Fiber Connections

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IEEE International Symposium on Biomedical Imaging

作者： Zili Kang Yifan Lv Mengshen He Yiheng Liu Tianming Liu Bao Ge School of Physics & Information Technology Shaanxi Normal University Xi’an China Department of Computer Science and Bioimaging Research Center Cortical Architecture Imaging and Discovery Lab The University of Georgia GA USA

It has been of great interest to study relationship between white matter and gray matter in brain science. Previous studies have found that that the formation of gray matter is closely related to white matter. This paper attempts explore the relationship between cerebral cortex and white matter from the perspective of brain image, which tries to predict fiber connection information by using brain cortical information alone. The extensive experiments on HCP dataset demonstrate that brain cortical surface can be used to predict the presence or absence of fibers between any two cortical regions with about 80% accuracy, furtherly, it can be used to predict the fractional anisotropy (FA) value for each fiber, the experiments show that the FA value can be also predicted with a percentage error of about 20%. These results demonstrate that the brain surface can be used to predict fiber connection information, and there is a close relationship between the gray matter and white matter fiber. This work provides a new perspective for further study of the relationship between cerebral cortex and axonal fiber.

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EskayApp: An Eskaya-Latin Script OCR Transliteration e-Learning Android Application using Supervised Machine Learning 21

EskayApp: An Eskaya-Latin Script OCR Transliteration e-Learn...

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Proceedings of the 5th International Conference on Digital technology in Education

作者： Max Angelo Dapitilla Perin Larmie Santos Feliscuzo Cherry Lyn Cando Sta. Romana Department of Computer Science Cebu Institute of Technology - University Philippines and College of Engineering Architecture and Industrial Design Bohol Island State University - Main Campus Philippines College of Computer Studies Cebu Institute of Technology - University Philippines

ISBN: (纸本)9781450384995

A language dies when the population that speaks it fails to pass it to their future generations. This study aims to address such problems for the Eskayas and Boholanos. The proposed EskayApp is an OCR Transliteration e-Learning Android Application that will serve as a tool to learn Eskaya. The app uses the k-Nearest Neighbors Algorithm (k-NN) for its business logic layer or backend and Supervised Machine Learning to create the application programming interface (API) for the said application. The Android application accesses the camera to capture an image of an Eskaya character and returns the Latin transliteration and the equivalent Latin character. The application got a 4.524-star rating through Google Play Store. After conducting testing, the machine learning model accuracy was 89.93% based on a 2x2 confusion matrix. A usability test was also conducted with members of the tribe as respondents. The usability review has 3 measurement items in which users can respond from 1 (Very Poor) to 5 (Excellent). The average for all the measurement items gathered from the users is 4.3-star and all the respondents want to use the e-Learning application again.

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TAPEMAN: Towards an Optimal Data Gathering Mechanism in Wireless Sensor Networks

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Chinese Journal of Electronics 2023年第4期19卷 594-598页

作者： Yu Gu Yusheng Ji Hongyang Chen Baohua Zhao Department of Computer Science University of Science and Technology of China Hefei China State Key Laboratory of Networking and Switching Technology Beijing China Information Systems Architecture Science Research Division NII Tokyo Japan Institute of Industrial Science University of Tokyo Tokyo Japan

In this paper, we study the lifetime optimization problem using a mobile sink node in a storage-constrained wireless sensor network, and propose an optimal data gathering mechanism named (TAPEMAN) which runs in three steps: first a tight upper bound of the network lifetime is derived through analysis of energy consumption, then we generate a Traveling salesman problem (TSP) solution based on a 2-approximation $O(n^{2})$ algorithm. A judgment will be made about whether this solution is optimal. If the answer is yes, TAPEMAN terminates. If not, a novel data diffusion scheme is used to distribute data to neighboring nodes, in order to avoid data leaking. We prove that under some reasonable assumptions, our algorithm can achieve this upperbound. Simulation results demonstrate the efficiency of our proposed solution and substantiate the importance of using sink mobility for energy-constrained sensor networks.

关键词： Wireless communication Wireless sensor networks Energy consumption Upper bound Simulation Traveling salesman problems Delays

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Sentiment Analysis on Students’ Evaluation of Higher Educational Institutions

Sentiment Analysis on Students’ Evaluation of Higher Educat...

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International Conference on Intelligent and Fuzzy Systems, INFUS 2020

作者： Toçoğlu, Mansur Alp Onan, Aytuğ Department of Software Engineering Faculty of Technology Manisa Celal Bayar University Manisa45400 Turkey Department of Computer Engineering Faculty of Engineering and Architecture İzmir Katip Çelebi University İzmir35620 Turkey

ISBN: (纸本)9783030511555

Sentiment analysis is the method of identifying and classifying the views of users from text documents into different sentiments, such as positive, negative or neutral. Sentiment analysis can be employed to extract structured and informative knowledge from unstructured text pieces. This knowledge can serve as an important source of information for decision support systems and individual decision makers. Sentiment analysis plays an important role in many fields like education, where student input is crucial for assessing the effectiveness of educational institutions. In this paper, we present a machine learning based approach to sentiment analysis on students’ evaluation of higher educational institutions. We analyze a corpus containing approximately 700 student reviews written in Turkish, with the use of conventional text representation schemes and machine learning classifiers. In the experimental analysis, three conventional text representation schemes (i.e., term-presence, term-frequency, TF-IDF scheme) and three N-gram models (1-gram, 2-gram and 3-gram) have been considered in conjunction with four classifiers (i.e., support vector machines, Naïve Bayes, logistic regression, and random forest algorithm). The predictive performance of four ensemble learners (i.e., AdaBoost, Bagging and Random Subspace and voting algorithm) have been also evaluated. The empirical results indicate that machine learning based approach yields promising results on students’ evaluation of higher educational institutions. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sentiment analysis

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