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28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Du, Qianjin Kuang, Xiaohui Li, Xiang Zhao, Gang The Department of Computer Science and Technology Tsinghua University Beijing100084 China National Key Laboratory of Science and Technology on Information System Security Beijing100084 China

ISBN: (纸本)9783031306778

Vulnerability detection methods based on the deep learning have achieved remarkable performance improvements compared to traditional methods. Current deep learning-based detectors mostly use a single RNN or its variants (i.e., LSTM or GRU) to detect vulnerabilities. However, vulnerability detection is a multi-domain problem. Different types of vulnerabilities have different characteristics. Using a single neural network cannot perform well in all types of vulnerability detection tasks. Manually designing a matching neural network for each type of vulnerability detection task not only requires a lot of trials and computational resources but also highly relies on the knowledge and design experience of experts. To address this issue, in this paper, we propose a novel fine-grained vulnerability detection framework named A-DARTS, which is capable of searching for well-performed neural network architectures for different vulnerability detection tasks by introducing neural network architecture search (NAS) techniques. Specifically, we design a more efficient search space to ensure superior neural network architectures can be found by the search algorithm. Besides, we propose an adaptive differentiable search algorithm to search for superior neural network architectures. Experimental results show that searched models consistently outperform all baseline models and achieve significant performance improvements. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Sentiment Analysis of Public Opinion on Twitter about the Implementation of the Merdeka Curriculum Using the Support Vector Machine Algorithm

Sentiment Analysis of Public Opinion on Twitter about the Im...

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2023 International Conference on Modeling and E-information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Ramadhanti, Intan Widodo Nugraheni, Murien Universitas Negeri Jakarta Informatics and Computer Engineering Education Jakarta Indonesia Universitas Negeri Jakarta Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350369359

In 2022 the Head of Standards, Curriculum, Education Assessment (BSKAP) No. 0441HIKR/2022 issued a Decree (SK) regarding Education Units for the Implementation of the Merdeka Curriculum in 140 thousand educational units in Indonesia. The implementation of this new curriculum raises various public opinions on social media Twitter. Therefore, research on the analysis of public sentiment on the implementation of the Merdeka Curriculum was carried out. The tweets taken are tweets with positive and negative sentiments. This study aims to see whether the SVM algorithm is good at carrying out text classification for sentiment analysis of the Merdeka Curriculum by looking at the accuracy value and describing how the public's sentiment on Twitter is about the Merdeka Curriculum. The data used is a dataset of 1,186 tweets, that is 363 positive tweets and 823 negative tweets. The results showed that the accuracy of the Support Vector Machine algorithm with linear, polynomial, and sigmoid kernels was 91.82% and the RBF kernel was 89.88%. As well as seen from the results of the sentiment analysis of implementing the Merdeka Curriculum there were more negative responses, one of which was regarding too many assignments and projects that made students feel tired and stressed. © 2023 IEEE.

关键词： Support vector machines

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Optimizing Structural Modification Operation for B+-Tree on Byte-Addressable Devices 42

Optimizing Structural Modification Operation for B+-Tree on ...

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42nd IEEE International Conference on computer Design, ICCD 2024

作者： Hong, Dingze Hu, Jinlei Chen, Jianxi Feng, Dan Liu, Jian School of Computer Science and Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System of MoE China The Fifth Electronics Research Institute of Miit China

ISBN: (纸本)9798350380408

Persistent Memory (PM) offers both byte-address ability and non-volatility, making it well-suited for accelerating B+-Tree indexes. However, existing persistent B+-Tree indexes face significant performance challenges due to high structural modification operation (SMO) overhead. SMOs often result in costly item migrations and increased tail latency, which severely degrade the overall performance. In this paper, we present SSTree, a high-performance B+- Tree index specifically optimized to address SMO overhead. SSTree introduces three key innovations: (i) efficient leaf node expansion using a list of subnodes to postpone expensive node splits, (ii) delegated fingerprints to speed up search operations across subnodes, and (iii) proactive subnode compaction that employs out-of-place updates to optimize item organization. Our evaluation demonstrates that SSTree delivers up to 4.38× higher write throughput and up to 62× lower tail latency compared to state-of-the-art persistent B+-Tree indexes. © 2024 IEEE.

关键词： Trees (mathematics)

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Moodle-based Learning Management system Design as a Learning Media at SMKN 40 Jakarta 7

Moodle-based Learning Management System Design as a Learning...

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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Setya, Oktaviano Nanda Prima Widodo Nugraheni, Murien State Jakarta University Informatics and Computer Engineering Education Jakarta Indonesia State Jakarta University Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350307504

Indonesia is currently in the final stages of the COVID-19 pandemic, which has changed the world of the online learning. Online learning has many benefits, one of which students can learn anywhere and anytime. SMK Negeri 40 Jakarta is one of the vocational high schools located in DKI Jakarta. Based on observation at SMKN 40 Jakarta, teachers use a learning management system for daily learning. Therefore, a Moodle-based learning management system is needed. Learning Management system is a web application to manage various learning activities automatically, which is built using Moodle platform with RAD (Rapid Application Development) methodology. The result is a Moodle-based learning management system application that can be useful in supporting the teaching and learning process at school. Based on the results of black box testing and user acceptance testing, the learning management system created is very good, therefore it can be concluded this application can be accepted and implemented at SMK Negeri 40 Jakarta. © 2023 IEEE.

关键词： Black-box testing

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Chiang Rai Phra That Nine Choms Attraction Promoting Mobile Application for Cultural Tourism 20

Chiang Rai Phra That Nine Choms Attraction Promoting Mobile ...

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20th International Conference on Electrical Engineering/Electronics, computer, Telecommunications and information technology, ECTI-CON 2023

作者： Chaidee, Kamonlak Boontasri, Kanchana Chaidee, Ekkachai Wongchai, Wiwat Phamon, Suphakorn Preedee, Suruswadee Rajamangala University of Technology Lanna Chiangrai Faculty of Business Administration and Liberal Arts Department of Computer Information System Chiang Rai Thailand

ISBN: (纸本)9798350310467

This study aimed to create a mobile application to promote and guide the cultural tourism attraction Phra That Nine Choms in Chiang Rai Province, Thailand. The critical information about Phra That Nine Choms is gathered and analyzed to identify the problem and user requirements. The operation of the mobile application is designed using a use case diagram, class diagram, and sequence diagram. The Java programming language creates the mobile application through the Eclipse program, Android SDK, and JAVA JDK development tools. 95 Thai and foreign tourists tested the resulting application. Their satisfaction was evaluated through a questionnaire and analyzed. The interpreting results showed that the mobile application is suitable for providing travel recommendations and can serve as a guide for future development to support tourism activities, particularly for cultural and local attractions. © 2023 IEEE.

关键词： Global positioning system

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MAML MOT: Multiple Object Tracking Based on Meta-Learning

MAML MOT: Multiple Object Tracking Based on Meta-Learning

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Chen, Jiayi Deng, Chunhua School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China

ISBN: (纸本)9781665410205

With the advancement of video analysis technology, the multi-object tracking (MOT) problem in complex scenes involving pedestrians is gaining increasing importance. This challenge primarily involves two key tasks: pedestrian detection and re-identification. While significant progress has been achieved in pedestrian detection tasks in recent years, enhancing the effectiveness of re-identification tasks remains a persistent challenge. This difficulty arises from the large total number of pedestrian samples in multi-object tracking datasets and the scarcity of individual instance samples. Motivated by recent rapid advancements in meta-learning techniques, we introduce MAML MOT, a meta-learning-based training approach for multi-object tracking. This approach leverages the rapid learning capability of meta-learning to tackle the issue of sample scarcity in pedestrian re-identification tasks, aiming to improve the model's generalization performance and robustness. Experimental results demonstrate that the proposed method achieves high accuracy on mainstream datasets in the MOT Challenge. This offers new perspectives and solutions for research in the field of pedestrian multi-object tracking. © 2024 IEEE.

关键词： Contrastive Learning

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A Mathematical Model for COVID-19 Image Enhancement based on Mittag-Leffler-Chebyshev Shift

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computers, Materials & Continua 2022年第10期73卷 1307-1316页

作者： Ibtisam Aldawish Hamid A.Jalab Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic UniversityRiyadh11432Saudi Arabia Department of Computer System&Technology Faculty of Computer Scienceand Information TechnologyUniversiti Malaya50603Kuala LumpurMalaysia

The lungs CT scan is used to visualize the spread of the disease across the lungs to obtain better knowledge of the state of the COVID-19 *** diagnosing of COVID-19 disease is a complex challenge that medical system face during the pandemic *** address this problem,this paper proposes a COVID-19 image enhancement based on Mittag-Leffler-Chebyshev polynomial as pre-processing step for COVID-19 detection and *** proposed approach comprises the MittagLeffler sum convoluted with Chebyshev *** idea for using the proposed image enhancement model is that it improves images with low graylevel changes by estimating the probability of each *** proposed image enhancement technique is tested on a variety of lungs computed tomography(CT)scan dataset of varying quality to demonstrate that it is robust and can resist significant quality *** blind/referenceless image spatial quality evaluator(BRISQUE),and the natural image quality evaluator(NIQE)measures for CT scans were 38.78,and 7.43 *** to the findings,the proposed image enhancement model produces the best image quality ***,this model considerably enhances the details of the given datasets,and it may be able to assist medical professionals in the diagnosing process.

关键词： CT scans COVID-19 Mittag-Leffler Chebyshev polynomial fractional calculus

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Clustering Mechanism in Particle Swarm Optimization Algorithm for Data Aggregation 13

Clustering Mechanism in Particle Swarm Optimization Algorith...

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13th IEEE Symposium on computer Applications and Industrial Electronics, ISCAIE 2023

作者： Sharmin, Sharmin Ahmedy, Ismail Noor, Rafidah Md Ismail, Habibah Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Univesrsiti Teknologi MARA Computer Science Unit Centre of Foundation Studies Selangor Dengkil43800 Malaysia

ISBN: (纸本)9798350347319

Wireless Sensor Networks (WSNs) consist of numerous sensor nodes with distinct resources working together to achieve a common objective efficiently. A critical issue is extending the network lifetime of WSNs, especially for data transfer, as sensor nodes depend on their internal batteries to carry out essential functions and communicate with one another. Efficient energy use per sensor is essential for ensuring the overall energy efficiency of the network. Clustering has been the most energy-efficient approach but lacking a method for selecting the most effective cluster head results in decreased data aggregation efficiency, leading to the increased power consumption of sensor nodes. The project aims to enhance energy efficiency and extend network service life by using Particle Swarm optimization (PSO) for clustering in WSNs. PSO is used to select the cluster head based on member node distance from the base station and remaining energy. The proposed PSO technique was tested against Low Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP), Zonal Stable Election Protocol Z-SEP, and Extended Stable Election Protocol (EZ-SEP) and found to be more effective in reducing energy usage and prolonging the network's lifespan. The recommended technique can extend the service life of WSNs and reduce energy consumption, ultimately leading to more cost-effective and eco-friendly solutions for various applications such as environmental monitoring, surveillance, and healthcare. © 2023 IEEE.

关键词： Energy utilization

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Anomaly Detection in Microservice systems Using Autoencoders 4

Anomaly Detection in Microservice Systems Using Autoencoders

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4th International Conference on Advancements in Computing, ICAC 2022

作者： de Silva, Manul Daniel, Sam Kumarapeli, Manith Mahadura, Sashika Rupasinghe, Lakmal Liyanapathirana, Chethana Computer System Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

The adaptation of microservice architecture has increased massively during the last few years with the emergence of the cloud. Containers have become a common choice for microservices architecture instead of VMs (Virtual Machines) due to their portability and optimized resource usage characteristics. Along with the containers, container-orchestration platforms are also becoming an integral part of microservice-based systems, considering the flexibility and scalability offered by the container-orchestration media. With the virtualized implementation and the dynamic attribute of modern microservice architecture, it has been a cumbersome task to implement a proper observability mechanism to detect abnormal behaviour using conventional monitoring tools, which are most suitable for static infrastructures. We present a system that will collect required data with the understanding of the dynamic attribute of the system and identify anomalies with efficient data analysis methods. © 2022 IEEE.

关键词： Containers

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Relationship Quality Analysis Using technology in the Business Sector 11

Relationship Quality Analysis Using Technology in the Busine...

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11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Aini, Qurotul Sediyono, Eko Hartomo, Kristoko Dwi Manongga, Danny Rahardja, Untung Sembiring, Irwan Santoso, Nesti Anggraini Satya Wacana Christian University Computer Science and Technology Central Java Indonesia Satya Wacana Christian University Information System Central Java Indonesia University of Technology Malaysia Computer Science and Technology Malaysia University of Raharja Computer Science and Technology Tangerang Indonesia

ISBN: (纸本)9798350305968

In the current era of Industry 5.0, the use of technology in the business sector, namely Digital Marketing, is put to good use by business actors. With social media as a medium of communication, business actors must establish good relationships with customers so that QU (Relationship Quality) is seen with BE (Customer Behavior), EX (Customer Experience) SMA (Social Media Marketing Activity). The basis for the urgency of this research is that many business actors do not know how important QU is, even though this can be used as a benchmark for business progress. The purpose of this research is to measure QU for BE, EX, and SMA using quantitative research methods by distributing online questionnaires to all social media users in Indonesia. A total of 49 questionnaires filled out by social media users were then analyzed and model-tested using PLS (Partial Least Squares). The results obtained are the findings of the H1 - H3 Hypothesis test which is declared 'Accepted' where SMA, EX, and BE affect QU positively. The novelty of this research is the results of measurement data on BE, EX, and SMA which can be used to improve quality and marketing strategy. © 2023 IEEE.

关键词： Least squares approximations

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