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3rd International Conference on Computational science and information Management, ICoCSIM 2019

作者： Marbun, Murni Zarlis, Muhammad Nasution, Zulkifli Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Teknik Informatika STMIK Pelita Nusantara Medan Indonesia

This research is an analysis of the application of the SAW, WP and TOPSIS methods to the support system for decision making at university. The types of scholarships provided are PPA education scholarships given by the Kementerian Riset, Teknologi dan Pendidikan Tinggi. The research variables are the attributes or criteria specified by the Directorate General of Learning and Student Affairs as contained in the 2018 Academic Achievement Improvement (PPA) guidebook. Decision Support Systems apply the classic FMADM method SAW, WP and TOPSIS. The results of this study are the application of the both methods of SAW and WP produce the same ranking and TOPSIS giving different rankings. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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program memory optimization for automatically generated tests for AUTOSAR RTE

Program memory optimization for automatically generated test...

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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Vlasicek, Kristijan Vidovic, Ivan Teslic, Nikola Pekez, Nenad Institute RT-RK Osijek Llc for Information Technology Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Osijek Croatia Faculty of Technical Science University of Novi Sad Serbia RT-RK Institute for Computer Based Systems Serbia

ISBN: (纸本)9781665404174

With the technological advancements in the automotive industry, the need for more electronic components has increased as well as for the appropriate software, that is, appropriate drivers. The development of such software is usually based on the AUTOSAR standard, while the required electronics use embedded computer systems. Considering that the embedded computer systems have limited resources, the software needs to be optimized. In this paper, the program memory of the considered software was optimized. The optimization was done using the following methods: introduction of generic functions, extraction of repetitive functions in the header files and dead code elimination. The optimization methods were applied by changing a code fragment written in C programming language. In that way, the program memory optimization method could be applied to all software components (SWCs) using Test Environment Generator (TEG). Afterward, the program code testing was done on a testing board. The results of the testing on board prove the functionality of the optimized program code. The applied methods optimized the memory usage (6.16% reduction) and preserved the functionality of the program code to an appropriate extent. © 2021 IEEE.

关键词： Embedded systems

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Designing of Learning Environment of an Intelligent Tutoring System for Academic Learning Needs of Learning-Disabled Learners Based on Survey Report of Region-Specific Target Group 2nd

Designing of Learning Environment of an Intelligent Tutoring...

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2nd International Conference on Emerging Technologies for Computing, Communications, and Smart Cities, ETCCS 2021

作者： Ahuja, Neelu Jyothi Thapliyal, Monika Nayyar, Anand Kumar, Adarsh Department of Systemics School of Computer Science University of Petroleum and Energy Studies Dehradun India Graduate School Duy Tan University Da Nang550000 Viet Nam Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

ISBN: (纸本)9789811902833

The twenty-first century is known for exponential growth in the technological as well as the education domain. However, conventional educational tools are still reliable to understand the actual scenario of performance and efficiency of the brain of young minds. If combined with technology this could play a vital role in getting a clear perception about what they feel and how they improve the educational methodology. Studies on dyslexia, dysgraphia and dyscalculia have shown that it is very tough and sometimes impossible to identify these learners without the help of professionals. Unlike physical challenges, the challenges from these disabilities are not measurable in quantified terms. For this, perception-based studies play a vital role. There are various studies, which suggest questionnaire-based survey, or direct interviews with the target group are a more reliable source of information. Also, regional-level data sometimes plays an important role to understand geographical and environmental impacts on the target group. Various reports were studied to understand the similarities. Authors collected information as a pilot project through a survey on 292 learners (learning-disabled and non-learning-disabled) in different institutes. 142 of them were dealing with single or multiple learning disabilities. Study helped in identifying the most affected learning domains and related multiple-criteria affecting the learners. This eventually is implemented in the domain model of an intelligent tutoring system to develop the four learner-centric learning environments. Results show that practice-based learning environment was the most relatable learning environment followed by visual-based learning environment. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Surveys

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Hypnopaedia-Aware Machine Unlearning via Psychometrics of Artificial Mental Imagery

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IEEE Access 2025年 13卷 103880-103897页

作者： Ching-Chun Chang Kai Gao Shuying Xu Anastasia Kordoni Christopher Leckie Isao Echizen Information and Society Research Division National Institute of Informatics Tokyo Japan Department of Information Engineering and Computer Science Feng Chia University Taichung Taiwan Department of Psychology Lancaster University Lancaster U.K. Department of Computing and Information Systems University of Melbourne Melbourne VIC Australia Graduate School of Information Science and Technology University of Tokyo Tokyo Japan School of Multidisciplinary Sciences Graduate University for Advanced Studies (SOKENDAI) Kanagawa Japan

Neural backdoors represent insidious cybersecurity loopholes that render learning machinery vulnerable to unauthorised manipulations, potentially enabling the weaponisation of artificial intelligence with catastrophic consequences. A backdoor attack involves the clandestine infiltration of a trigger during the learning process, metaphorically analogous to hypnopaedia, where ideas are implanted into a subject’s subconscious mind under the state of hypnosis or unconsciousness. When activated by a sensory stimulus, the trigger evokes a conditioned reflex that directs a machine to mount a predetermined response. In this study, we propose a cybernetic framework for constant surveillance of backdoor threats, driven by the dynamic nature of untrustworthy data sources. We develop a self-aware unlearning mechanism to autonomously detach a machine’s behaviour from the backdoor trigger. Through reverse engineering and statistical inference, we detect deceptive patterns and estimate the likelihood of backdoor infection. We employ model inversion to elicit artificial mental imagery, using stochastic processes to disrupt optimisation pathways and avoid convergent but potentially flawed patterns. This is followed by hypothesis analysis, which estimates the likelihood of each potentially malicious pattern as the true trigger and infers the probability of infection. The primary objective of this study is to maintain a stable state of equilibrium between knowledge fidelity and backdoor vulnerability.

关键词： Data models Soft sensors Vehicle dynamics Reverse engineering Predictive models Optimization Cyberspace Cybernetics Weapons Trojan horses

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The Impact of ICN/CCN Cache Decision Policies on Video and Audio Transmission QoE

The Impact of ICN/CCN Cache Decision Policies on Video and A...

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Australasian Telecommunication Networks and Applications Conference, ATNAC

作者： Keisuke Kobayashi Toshiro Nunome Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9781665471039

ISBN: (纸本)9781665471046

This paper considers video and audio transmission in ICN (information-Centric Networking) CCN (Content- Centric Networking), in which each intermediate node can cache content. LCE (Leave Copy Everywhere) has been known as a generic cache decision policy. However, because LCE caches at all the intermediate nodes, the cache of intermediate nodes can be duplicated. Therefore, various cache decision policies that eliminate redundancy have been proposed. In this paper, we evaluate the effect of the cache decision policies on QoE of video and audio transmission in ICN/CCN. We assess application-level QoS using a computer simulation with a tree network and QoE by means of subjective experiment.

关键词： computer simulation Redundancy information-centric networking Quality of service Liquid crystal displays Communications technology Quality of experience

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Optimal Reordering Trace Files for Improving Software Testing Suitcase

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computers, Materials & Continua 2021年第4期67卷 1225-1239页

作者： Yingfu Cai Sultan Noman Qasem Harish Garg Hamïd Parvïn Kim-Hung Pho Zulkefli Mansor School of Measurement and Communication Harbin University of Science&TechnologyHarbinChina Computer Science Department College of Computer and Information SciencesAl Imam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia Department of Computer Science Faculty of Applied ScienceTaiz UniversityTaizYemen School of Mathematics Thapar Institute of Engineering and TechnologyDeemed UniversityPatiala147004India Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Department of Computer Science Nourabad Mamasani BranchIslamic Azad UniversityMamasaniIran Fractional Calculus Optimization and Algebra Research GroupFaculty of Mathematics and StatisticsTon Duc Thang UniversityHo Chi Minh CityVietnam Fakulti Teknologi dan Sains Maklumat Universiti Kebangsan MalaysiaUKM BangiSelangor43600Malaysia

An invariant can be described as an essential relationship between program *** invariants are very useful in software checking and *** tools that are used to detect invariants are invariant *** are two types of invariant detectors:dynamic invariant detectors and static invariant *** software is an available computer program that implements a special case of a dynamic invariant detection *** proposes a dynamic invariant detection algorithm based on several runs of the tested program;then,it gathers the values of its variables,and finally,it detects relationships between the variables based on a simple statistical *** method has some *** of its biggest drawbacks is its overwhelming time *** is observed that the runtime for the Daikon invariant detection tool is dependent on the ordering of traces in the trace file.A mechanism is proposed in order to reduce differences in adjacent trace *** is done by applying some special techniques of mutation/crossover in genetic algorithm(GA).An experiment is run to assess the benefits of this *** findings reveal that the runtime of the proposed dynamic invariant detection algorithm is superior to the main approach with respect to these improvements.

关键词： Dynamic invariant detection software testing genetic algorithm

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Mapping Shallot in Lowland Areas Through Sentinel-2 Imagery and Machine Learning Approach 1

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10th International Seminar of Aerospace science and technology, ISAST 2024

作者： Arifandri, Robby Karolinoerita, Vicca Ramadhani, Fadhlullah Dirgahayu, Dede Devy, Lukita Habibie, Muhammad Iqbal Fanggidae, Yudi Riadi Dharmayanti Harahap, Robby Kurniawan Pratiwi, Swelandiah Endah Widiastuti Research Center for Artificial Intelligence and Cyber Security BRIN Bandung Indonesia Research Center for Geoinformatics BRIN Bandung Indonesia Research Center for Horticulture BRIN Cibinong Indonesia Research Center for Environmental and Clean Technology BRIN Tangerang Selatan Indonesia Research Center for Climate and Atmosphere BRIN Bandung Indonesia Faculty of Industrial Technology Gunadarma University Depok Indonesia Faculty of Computer Science and Information System Gunadarma University Depok Indonesia

ISBN: (数字)9789819613441

ISBN: (纸本)9789819613434

As one of the staple horticultural crops, Shallot requires accurate monitoring to understand its cultivation better and to face environmental challenges in lowland regions. Nevertheless, there are still limited studies on mapping shallot agriculture using remote sensing data. In this study, we aimed to enhance the accuracy and efficiency of mapping shallot cultivation in lowland areas by leveraging high-resolution Sentinel-2 imagery combined with machine-learning techniques, specifically Random Forest, to classify the cultivation areas accurately. Preprocessed Sentinel-2 data using Google Earth Engine and validation data from field surveys and high-resolution satellite imagery inspection are utilized to create training and testing datasets for the machine learning model. Our findings reveal that the Random Forest model resulted in an Overall Accuracy of 88% and a total area of 12,121 hectares in July 2023. The proposed method can be used to estimate the planting and harvested area regularly to support smart-climate agriculture. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Monitoring Applications for Vehicle based on Internet of Things (IoT) using the MQTT Protocol

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Procedia computer science 2023年 227卷 73-82页

作者： Nurudin Arief Agus Sukmandhani Muhammad Zarlis Computer Science Department BinusOnline Learning Bina Nusantara University Jakarta Indonesia 11480 Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480

Monitoring of vehicle conditions is needed as one of the securities in driving because one of the accident rates is negligence in checking the condition of the vehicle. This study aims to help reduce the level of accidents and increase human awareness for vehicle conditions, especially minibus type vehicles. The system works to provide information on the condition of vehicles sourced from the Engine Control Unit (ECU). ECU data cars are obtained by SNIP traffic broadcast message and ask for data directly at the ECU. The car can provide vehicle information using a Canbus communication protocol through the OBD-II socket. Vehicle information can be seen by users through the website in real time. Based on the evaluation from the user side, this system provides ease of monitoring vehicle conditions because it can be accessed via the internet using various kinds of devices.

关键词： OBD-II Blackbox Sstem Logging ECU

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P4toNFV: Offloading from P4 switches to NFV in programmable data planes

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International Journal of Communication Systems 2024年第5期37卷 e5687-e5687页

作者： Pekar, Adrian Makara, Laszlo A. Lai, Yuan-Cheng Lin, Ying-Dar Seah, Winston Department of Networked Systems and Services Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary HUN-REN-BME Information Systems Research Group Budapest University of Technology and Economics Budapest Hungary Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand

P4 combines the benefits of hardware-based networking with the adaptability of software-based network operations. However, when faced with intricate network functions, P4 switches reveal constraints in memory and processing primitives. To address these, we advocate offloading traffic demanding intricate processing from the programmable data plane to network function virtualization (NFV). By leveraging this approach, P4 switches handle the core data plane, ensuring maximum performance, whereas virtualized network functions (VNF) cater to the intricate processing. Central to our research is the optimization of this offloading process, specifically considering delay constraints. We developed an analytical model that examines a P4 switch overseen by an SDN controller, integrating an offloading capability to NFV. The principal objective was to determine an offloading rate that minimizes packet processing delay. To this end, we employed a Bounded method, an advancement from Brent's method, to determine this optimal rate. The findings indicate that offloading approximately 66% of packets to the VNF achieves the lowest total delay, registering at 0.1505 (Formula presented.) s. This strategy of optimal offloading can notably reduce the system's average delay as the demand for network functions increases. The optimization technique we adopted exhibited rapid convergence in our experiments, reflecting the method's efficacy. Furthermore, a rigorous parametric sensitivity analysis spanning no offloading, full offloading, and optimal offloading strategies underscores that optimal offloading to NFV consistently augments system performance, particularly in terms of delay reduction. Conclusively, our study furnishes valuable insights into offloading strategies, augmenting the narrative on resource allocation in both PNFs and VNFs. © 2023 The Authors. International Journal of Communication Systems published by John Wiley & Sons Ltd.

关键词： Network function virtualization

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BioBERT Based Efficient Clustering Framework for Biomedical Document Analysis 14th

BioBERT Based Efficient Clustering Framework for Biomedical ...

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14th International Conference on Genetic and Evolutionary Computing, ICGEC 2021

作者： Davagdorj, Khishigsuren Park, Kwang Ho Amarbayasgalan, Tsatsral Munkhdalai, Lkhagvadorj Wang, Ling Li, Meijing Ryu, Keun Ho College of Electrical and Computer Engineering Chungbuk National University Cheongju28644 Korea Republic of Department of Computer Science and Technology School of Computer Science Northeast Electric Power University Jilin City China College of Information Engineering Shanghai Maritime University 1550 Haigang Avenue Pudong New Area Shanghai213 China Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City700000 Viet Nam Biomedical Engineering Institute Chiang Mai University Chiang Mai50200 Thailand Department of Computer Science College of Electrical and Computer Engineering Chungbuk National University Cheongju28644 Korea Republic of

ISBN: (纸本)9789811684296

The large volumes of biomedical documents have been generating exponentially in modern applications. Document clustering methods play an important role in gathering textual content documents into a few meaningful coherent groups. However, clustering unstructured and unlabeled text is challenging to extract informative representations and find the relevant articles from the rapid growth biomedical literature. Therefore, traditional text document clustering methods often represent unsatisfactory results due to general non-contextualized vector space representations, which neglect the semantic relation between bio medical texts. Pre-trained language models have been gaining attention recently in variety of natural language processing tasks. In this paper, we propose a heavily pre-trained language representation BioBERT based clustering framework for biomedical document analysis in order to improve the clustering accuracy. In experimental architecture, we provide benchmarks of the pre-trained transformer model, statistical technique and word-embedding methods while incorporating with clustering algorithms. In order to distinguish the efficiency of the models, Fowlkes mallows score (FM), silhouette coefficient (SC), adjusted rand index (ARI), Davies-Bouldin score (DB) metrics are used. The comprehensive experimental results show that the BioBERT based K-means model achieves better clustering accuracies than other models. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Semantics

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