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5th International Conference on Advancement in Data science, E-Learning and information Systems, ICADEIS 2023

作者： Syamsuar, Dedy Oktaharisetia, Muhammad Angga Witarsyah, Deden Luthfi, Ahmad Dell, Peter Permana, Yudistira Sira Antoni, Darius Bina Nusantara University School of Information Systems Information Systems Department Indonesia Universitas Bina Darma Program Pasca Sarjana Palembang Indonesia Telkom University School of Industrial Engineering Bandung Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Indonesia Curtin University School of Management and Marketing Faculty of Business and Law Australia Politeknik Sekayu Teknik Informatika Sekayu Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia

ISBN: (纸本)9798350303414

ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts. © 2023 IEEE.

关键词： Enterprise resource planning

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Ubi-Care: An Elderly Life Support Healthcare Framework Based on Ubiquitous Personal Online Data Stores

Ubi-Care: An Elderly Life Support Healthcare Framework Based...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Hong Chen Tao Zhou Bo Wu Graduate School of Human Sciences Waseda University Saitama Japan Department of Information and Electronics System Engineering Daiichi Institute of Technology Taito Tokyo Japan School of Computer Science Tokyo University of Technology Hachioji Tokyo Japan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In recent years, the global aging population has intensified, leading to a sharp increase in social security benefits and caregiving costs. The elderly face greater health risks, and their behaviors often indicate signs of crises and illnesses. The rapid development of IoT technology offers new solutions for detecting abnormal signs, thereby promoting healthy aging, independent living, and social participation for the elderly. However, the diversity of IoT devices has led to the phenomenon of personal data silos. When the elderly leave their usual IoT environment, the issue of continuity in healthcare services becomes more pronounced. To address this issue, this study proposes a decentralized Ubi-Care framework. The framework aims to achieve complete separation of data and applications. It is based on the ActivityPub protocol and integrates various data from wearable devices, smart home sensors, and social networks, storing this data in a ubiquitous personal online data store (UPOD) and assigning different roles based on data type. UPOD applications support bidirectional following, allowing users to access data associated with relevant roles, addressing issues related to data categorization, sharing, privacy, and security. Additionally, this study proposes a method for utilizing complete UPOD data to perform anomaly detection based on the hidden Markov model (HMM). By effectively integrating IoT data into UPOD and enhancing data interoperability. The data-sharing model proposed in this study also facilitates elderly individuals and their family members in sharing relevant data as needed, while ensuring privacy protection. The methods proposed in this study will help prevent accidental injuries and enable early diagnosis of diseases, providing strong technical support for elderly healthcare.

关键词： Data privacy Cloud computing Hidden Markov models Prototypes Aging Data models Internet of Things Security Older adults Medical diagnostic imaging

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DCGAN-based Medical Image Augmentation to Improve ELM Classification Performance 11

DCGAN-based Medical Image Augmentation to Improve ELM Classi...

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Rando Setiawan, Noor Akhmad Permanasari, Adhistya Erna Rulaningtyas, Riries Suksmono, Andriyan Bayu Sitanggang, Imas Sukaesih Universitas Gadjah Mada Dept. of Electrical and Information Engineering Yogyakarta Indonesia Biomedical Engineering Program Dept. of Physics Universitas Airlangga Surabaya Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Ipb University Department of Computer Science Bogor Indonesia

ISBN: (纸本)9781665460309

Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%. © 2022 IEEE.

关键词： Generative adversarial networks

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A Blockchain-Based Intelligent Framework for Secure and Sustainable Knowledge Management in Organizational Systems

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Procedia computer science 2025年 258卷 2899-2908页

作者： Kajal Singh Anand Singh Rajawat S.B. Goyal Hayyan Nassar Waked Business Analyst Barclays Bank 400 Jefferson Park Whippany NJ 07981 USA School of Computer Science & Engineering Sandip University Nashik Maharashtra India Faculty of Information Technology City University Petaling Jaya 46100 Malaysia City Graduate School City University Petaling Jaya 46100 Malaysia

The modern-day organizational system requires secure and constant knowledge management to work efficiently in the in a competitive age—blockchain-based Intelligent Framework for Securing and Managing Knowledge Management Process Lifecycle within Organizations. Utilizing blockchain capabilities and integrated with artificial intelligence (AI), the system combines a comprehensive solution to manage knowledge, including security. Blockchain secures data integrity and transparency via decentralized ledgers, smart contracts, and consensus algorithms — tokenizing their B2B economic relationships, while AI allows the system to analyze knowledge flows better, predict, and optimize. The proposed framework uses blockchain to allow storage and verification of knowledge transactions, resulting in an immutable versioning system that logs all touches. AI algorithms, especially machine learning models, are used in knowledge mining techniques to scrutinize the patterns of using acquaintance, from which it may predict what we need and can be disseminated at the right time. The integration provides the ability for real-time monitoring and management of knowledge assets to help you keep your information accessible in a way that is both quick and can be done without risk from attackers. Experimental results show that the proposed framework performed well in terms of secure data management, high prediction accuracy, and recommendation. AI-powered Kasistos set the stage to drive knowledge from siloes, and blockchain ensures every piece of newly-permission wisdom into its walls is securely lodged: all verified by it. In such a process, we will ensure that organizational knowledge is retained, which helps in the long run to ensure resources are being used effectively and redundancy is minimized. Blockchain-Based Intelligent and Innovative Framework provides a complete platform for the current complexity of knowledge management obstacles with advanced technologies blending to secure organiz

关键词： Blockchain Artificial Intelligence Knowledge Management Data Security Predictive Analytics Organizational Systems

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Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction 39

Rethinking Pseudo-Label Guided Learning for Weakly Supervise...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Quan Qi, Yuxin Tang, Xi Yuan, Rui Lin, Xi Zhang, Ke Yuan, Chun Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai China School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)157735897X

Pseudo-label learning methods have been widely applied in weakly-supervised temporal action localization. Existing works directly utilize weakly-supervised base model to generate instance-level pseudo-labels for training the fully-supervised detection head. We argue that the noise in pseudo-labels would interfere with the learning of fully-supervised detection head, leading to significant performance leakage. Issues with noisy labels include:(1) inaccurate boundary localization;(2) undetected short action clips;(3) multiple adjacent segments incorrectly detected as one segment. To target these issues, we introduce a two-stage noisy label learning strategy to harness every potential useful signal in noisy labels. First, we propose a frame-level pseudo-label generation model with a context-aware denoising algorithm to refine the boundaries. Second, we introduce an online-revised teacher-student framework with a missing instance compensation module and an ambiguous instance correction module to solve the short-action-missing and many-to-one problems. Besides, we apply a high-quality pseudo-label mining loss in our online-revised teacher-student framework to add different weights to the noisy labels to train more effectively. Our model outperforms the previous state-of-the-art method in detection accuracy and inference speed greatly upon the THUMOS14 and ActivityNet v1.2 benchmarks. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Semi-supervised learning

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The Integration of 6G and Blockchain into an Efficient AIoT-Based Smart Education Model

The Integration of 6G and Blockchain into an Efficient AIoT-...

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IEEE World Symposium on Communication engineering (WSCE)

作者： Anna Lioupa Vasileios A. Memos Christos L. Stergiou Yutaka Ishibashi Konstantinos E. Psannis Dept. of Applied Informatics School of Information Sciences University of Macedonia Thessaloniki Greece Dept. of Computer Science Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

The technological advances impact the future classrooms and the whole education system. The evolution of 6G promises faster speeds based on terahertz, wireless communication, the leverage of artificial intelligence (AL), virtually reality (VR) and generally a fully connected world. The use of applications of IoT and AIoT improves the education environment, but the intelligent network services undoubtedly gather, store and analyze big data which are vulnerable to attackers. As a solution we may consider the technology of blockchain. The trust and security of next generation intelligent networks are essential part of their design. In this article we suggest a data security system based on blockchain for AL applications in 6G networks. First, we present two Al-enabled applications, indoor positioning and mobile payment within the framework of 6G in the university area. We present the efficiency of blockchain in data security for Al-enabled systems using two case studies of indoor positioning system and mobile payment. The 6G system which is fully supported by Al and the integration of this in technology of blockchain, is ensured the security in future wireless communication.

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Constructions of Binary MDS Array Codes with Optimal Cooperative Repair Bandwidth

Constructions of Binary MDS Array Codes with Optimal Coopera...

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IEEE International Symposium on information Theory

作者： Lei Li Xinchun Yu Chenhao Ying Liang Chen Yuanyuan Dong Yuan Luo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Institute of Data and Information Tsinghua University Shenzhen International Graduate School Shenzhen China Alibaba Group Hangzhou China

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

Erasure codes are widely implemented in distributed storage systems to provide high fault tolerance with small storage overhead. Maximum distance separable codes are an common choice as they achieve the optimal tradeoff between fault tolerance and storage overhead. In this paper, we focus on the repair of multiple erasures of binary MDS array codes. Specifically, we present constructions of binary MDS array codes with optimal cooperative repair bandwidth by stacking multiple Blaum-Roth code instances whose “evaluation points” are judiciously designed. The constructed array codes with length $n$ and dimension $k$ can achieve the optimal cooperative repair bandwidth for $2\leq h\leq n-k$ and $k+1\leq d\leq n-h$ where $h$ and $d$ are the numbers of failed nodes and helper nodes, respectively. As the codes are constructed on a special polynomial ring over binary field, computation operations involved in nodes repair and file reconstruction for these codes are only XORs and cyclic shifts. Moreover, due to the inherent parallel structure of the codes, both the encoding and decoding procedures can be finished in parallel, speeding up the computing process.

关键词： Fault tolerance Codes Stacking Fault tolerant systems Bandwidth Maintenance engineering Polynomials

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Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction

arXiv

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arXiv 2025年

关键词： Self-supervised learning

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PRV-based Stress Analysis on Display Color Temperatur in VR Environments

PRV-based Stress Analysis on Display Color Temperatur in VR ...

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International Conference on Fuzzy Theory and it's Applications (iFUZZY)

作者： Sungmin Lee Minjeong Lee Younghoon Shin Byung-Jae Choi Miran Lee Graduate School of IT Convergence Engineering Daegu University South Korea Department of Electronic Engineering Daegu University South Korea Department of Computer and Information Science Daegu University South Korea

With the interest in VR increases, the number of users and the usage time increases as various contents are developed in virtual environments. In addition to VR, different mobile devices, tablets, PCs, etc., include functions based on display brightness and color temperature control, and there is also an opinion that using VR for a long time can cause eye diseases such as dry eyes and visual disturbance. This paper investigated the effect of VR device display color temperature on human stress in a VR environment. As a result, pulse rate variability parameters in the time- and frequency-domains all showed significant differences between cool white and warm white (dark mode) conditions, and it was confirmed that the LF/HF ratio, known as the parameter most closely related to stress, was observed to be lower in warm white conditions.

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A Blockchain-Integrated AI Framework for Enhancing Energy Efficiency and Sustainability in Smart Grids

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Procedia computer science 2025年 258卷 2302-2311页

作者： Kajal Singh S.B. Goyal Anand Singh Rajawat Hayyan Nassar Waked Business Analyst Barclays Bank 400 Jefferson Park Whippany NJ 07981 USA Faculty of Information Technology City University Petaling Jaya 46100 Malaysia School of Computer Science & Engineering Sandip University Nashik Maharashtra India City Graduate School City University Petaling Jaya 46100 Malaysia

In the pursuit of energy efficiency and sustainability in smart grids, leveraging blockchain integration with artificial intelligence could provide a disruptive paradigm that offers numerous benefits. In this paper, a new framework is presented using blockchain with AI in order to provide optimal energy management and sustainable smart grid. The new model combines blockchain, which provides a secure an unchangeable log of transactions; with algorithms based on AI in order to analyse and predict patterns of electricity consumption as well as provide demand response control (the ability needed by users who want to be active prosumers) accompanied by optimization of the energy delivery chain. Blockchain enforces transparency and trust among multiple stakeholders, it helps verify data integrity across entities involved in a transaction to prevent any kind of tampering or fraud. At the same time, AI-driven insights allow real-time data to inform energy systems and lead with scheduling dynamic changes in order to prevent grid losses that would result in wasted energy. The inclusion of these technologies is what helps to solve the major problems such as energy theft, data security and also reduce inefficient use of power. Indeed, this integration helps reduce operational costs and enables a shift towards cleaner and sustainable sources of energy. Simulations and real-world use cases are performed to evaluate the effectiveness of the proposed framework in improving energy efficiency for smart grid towards more sustainability.

关键词： Blockchain Technology Artificial Intelligence (AI) Smart Grids Energy Efficiency Sustainability Decentralized Systems

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