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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Maulana, Fairuz Iqbal Prasetyo Adi, Puput Dani Pramono, Andi Rahayu, Anita Persada, Satria Fadil Nadlifatin, Reny School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Research Center for Telecommunication National Research and Innovation Agency Bandung Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Information System Surabaya Indonesia

ISBN: (纸本)9798350389654

The Internet of Things (IoT) has revolutionized the concept of Smart Cities by enabling the seamless integration of various technologies and devices to enhance urban living. This abstract presents a comprehensive overview of the research trends and advancements in IoT applications within Smart Cities from 2019 to 2023. By conducting a scientometric review and bibliometric analysis using R studio and VOSviewer software, this study aims to identify key focus areas, challenges, and opportunities in the implementation of IoT technologies in urban environments. Data selection from the Scopus database yielded a total of 3849 documents from 1515 sources. The most cited article from 2021 is 166 citations. Average citations per doc is 18.56. China, India, and Korea appear to dominate in terms of the number of published documents. Future research directions include exploring innovative solutions leveraging technologies like blockchain, edge computing, and artificial intelligence to improve the efficiency, sustainability, and resilience of Smart City initiatives. By synthesizing insights from existing literature and exploring emerging trends, this study contributes to the advancement of Smart Cities and the development of a more connected and intelligent urban future. © 2024 IEEE.

关键词： Sustainable city

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Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem

arXiv

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arXiv 2024年

作者： Campbell, Declan Rane, Sunayana Giallanza, Tyler De Sabbata, Nicolò Ghods, Kia Joshi, Amogh Ku, Alexander Frankland, Steven M. Griffiths, Thomas L. Cohen, Jonathan D. Webb, Taylor W. Princeton Neuroscience Institute United States Department of Psychology Princeton University United States Department of Computer Science EPFL Switzerland Department of Cognitive Science Dartmouth College United States Department of Computer Science Princeton University United States Microsoft Research United States

Recent work has documented striking heterogeneity in the performance of state-of-the-art vision language models (VLMs), including both multimodal language models and text-to-image models. These models are able to describe and generate a diverse array of complex, naturalistic images, yet they exhibit surprising failures on basic multi-object reasoning tasks – such as counting, localization, and simple forms of visual analogy – that humans perform with near perfect accuracy. To better understand this puzzling pattern of successes and failures, we turn to theoretical accounts of the binding problem in cognitive science and neuroscience, a fundamental problem that arises when a shared set of representational resources must be used to represent distinct entities (e.g., to represent multiple objects in an image), necessitating the use of serial processing to avoid interference. We find that many of the puzzling failures of state-of-the-art VLMs can be explained as arising due to the binding problem, and that these failure modes are strikingly similar to the limitations exhibited by rapid, feedforward processing in the human brain. © 2024, CC BY.

关键词： Visual languages

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MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench

arXiv

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arXiv 2024年

作者： Meser, Moritz Bhatt, Aditya Belousov, Boris Peters, Jan Intelligent Autonomous Systems Lab Department of Computer Science TU Darmstadt Germany Germany Centre for Cognitive Science Technical University of Darmstadt Germany Darmstadt Germany

We tackle the recently introduced benchmark for whole-body humanoid control HumanoidBench [9] using MuJoCo MPC [6]. We find that sparse reward functions of HumanoidBench yield undesirable and unrealistic behaviors when optimized;therefore, we propose a set of regularization terms that stabilize the robot behavior across tasks. Current evaluations on a subset of tasks demonstrate that our proposed reward function allows achieving the highest HumanoidBench scores while maintaining realistic posture and smooth control signals. Our code is publicly available and will become a part of MuJoCo MPC5, enabling rapid prototyping of robot behaviors. Copyright © 2024, The Authors. All rights reserved.

关键词： Anthropomorphic robots

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Evaluation of EIRLYS's E-Commerce Website from a User Experience Perspective using a User Experience Questionnaire (UEQ)

Evaluation of EIRLYS's E-Commerce Website from a User Experi...

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2022 International Conference on Electrical Engineering and Informatics, ICELTICs 2022

作者： Gabrila, Amara Nova Ramadhani, Mirza Fadila, Fujishiro Larasati Izdihar, N.S. Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia Bina Nusantara University Computer Science School of Computer Science Jakarta11480 Indonesia

ISBN: (数字)9781665487665

ISBN: (纸本)9781665487665

Fashion is one of the industrial sectors that never die. However, the majority of brands in this industrial sector are slowly forgetting the existence of Indonesian culture. EIRLYS is a company engaged in the fashion industry that produces clothing with the theme of Indonesian culture. Customers will be able to get clothes that have elements of Indonesian culture but still have a relaxed and informal impression. Clothing from EIRLYS emphasizes the principles of simplicity, minimalism, and elegance. These three principles want to be carried out in the design and user experience of the EIRLYS website to provide convenience for customers in transacting. Almost all industries, whether large, medium, or small, have used technology to promote their products in various ways, including using e-commerce websites. However, to ensure that EIRLYS has provided the best service through its website, it is important to know whether EIRLYS has met the overall User experience (UX) dimension. User experience Questionnaire (UEQ) is a technique that will be used to assess and test whether EIRLYS has met the expectations of users based on the User experience dimension before it can be used by customers. Based on the results of the user experience questionnaire filled out by EIRLYS users, it can be seen that EIRLYS has been able to meet user needs and expectations from all dimensions, ranging from attractiveness, perspicuity, efficiency, accuracy, stimulation, and novelty. © 2022 IEEE.

关键词： Websites

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E-Learning Satisfaction: Analysis of the Support Factors 10

E-Learning Satisfaction: Analysis of the Support Factors

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10th International Conference on Information Technology, computer, and Electrical Engineering, ICITACEE 2023

作者： Siswanto, Boby Alamsyah, Doni Purnama Morika, Doni Othman, Norfaridatul Akmaliah Wijaya, Billiam Christofer Adinda, Putri Giyan Bina Nusantara University Computer Science Study Program School of Computer Science Jakarta11480 Indonesia Bina Nusantara University BINUS Business School Entrepreneurship Department Jakarta11480 Indonesia Bina Nusantara University Interior Design Study Program School of Design Jakarta11480 Indonesia Universiti Teknikal Malaysia Melaka Department of Management Technology Melaka76100 Malaysia

ISBN: (纸本)9798350322729

E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and the factors that can increase student e-learning satisfaction. This study uses a quantitative survey method with a questionnaire as a data collection tool. The research respondents were randomly selected e-learning students from several educational institutions that use Big Data technology in their e-learning platforms. There are 663 data collected through online questionnaires, then the data is processed through SmartPLS to test the research hypothesis. The results of the study show that the use of Big Data technology in an e-learning environment has a positive impact on student satisfaction. Several factors determine e-learning satisfaction including usability requirements, quality level, learning competence, and material relatedness. Relatedness to e-learning is more important in increasing student motivation in learning, as can be seen from the correlation value which is more dominant in forming student satisfaction. The e-learning platform must have navigation that is easy for users to understand and use. Learning content must be well-designed and follow established learning standards. The use of Big Data technology in e-learning can have a significant impact on student satisfaction and the quality of learning. Future research can develop a more personal and adaptive e-learning platform, using Big Data technology as the basis for its development. © 2023 IEEE.

关键词： E-learning

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The Pivotal Role of Red Teaming in Cybersecurity Drill Tests in Enhancing Indonesia's Cyber Defenses

SSRN

引用

SSRN 2024年

作者： Yulianto, Semi Soewito, Benfano Gaol, Ford Lumban Kurniawan, Aditiya Computer Science Department Binus Graduate Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Bina Nusantara University Jakarta11480 Indonesia

This study examines the pivotal role of red teaming within the context of cybersecurity drill tests, focusing on its contribution to enhancing Indonesia's cyber defenses. Through a detailed analysis, this research examines Red Teaming's capacity to elevate organizational readiness against cyber threats, identify latent vulnerabilities, and ensure compliance with Indonesia's rigorous cybersecurity regulations. Key findings revealed the profound effect of red teaming on fortifying cybersecurity protocols, showing its capability to discover and effectively counteract security vulnerabilities. This study positions Red Teaming as an essential strategy in the array of cybersecurity practices, offering valuable insights into its application and impact on meeting regulatory standards. Ultimately, this investigation underscores the indispensable role of red teaming in advancing Indonesia's cybersecurity posture amid the constantly evolving digital threat landscape. © 2024, The Authors. All rights reserved.

关键词： Regulatory compliance

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Efficient Automatic External Defibrillator Using the Slope of Hilbert Transformed ECG Signals 11

Efficient Automatic External Defibrillator Using the Slope o...

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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Elsagheer, Samir A. Sayed, Mohammed S. Hassan, Mohsen A. Egypt-Japan University of Science and Technology Computer Science and Information Technology Alexandria21934 Egypt Aswan Universty Facurlty of Engineering Aswan Egypt Egypt-Japan University of Science and Technology Department of Electronics and Communications Engineering Alexandria21934 Egypt Zagazig University Department of Electronics and Communications Engineering Zagazig Egypt Egypt-Japan University of Science and Technology Materials science and engineering program IDE Alexandria21934 Egypt

ISBN: (纸本)9798350369328

Sudden cardiac arrest (SCA) is a life-threatening condition that demands immediate intervention. The key to survival often lies in the timely and precise analysis of electrocardiogram (ECG) signals to determine the necessity of a shock from an Automatic External Defibrillator (AED). In this paper, we address the critical need for improved accuracy in AED decision-making by presenting a novel approach that leverages the Hilbert Transform to calculate the slope of ECG signals by harnessing the analytical power of Hilbert Transformed ECG signals. By scrutinizing the heart's electrical activity through this method, we aim to enhance the AED's ability to differentiate between cases of ventricular fibrillation and other non-shockable rhythms, ultimately leading to more efficient and effective treatment. Our research explores two distinct approaches for signal analysis and correlates their findings to achieve higher precision in defibrillation decisions. To validate the effectiveness of our approach, we employ a diverse and publicly available dataset containing various heart conditions, allowing us to demonstrate the robustness of our method across a wide spectrum of cases. This study represents a significant advancement in the field of automatic external defibrillation, with the potential to save countless lives through more accurate and timely interventions. © 2023 IEEE.

关键词： Defibrillators

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Improving AlphaZero Using Monte-Carlo Graph Search 31

Improving AlphaZero Using Monte-Carlo Graph Search

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31st International Conference on Automated Planning and Scheduling, ICAPS 2021

作者： Czech, Johannes Korus, Patrick Kersting, Kristian Department of Computer Science TU Darmstadt Germany Centre for Cognitive Science TU Darmstadt Germany Darmstadt Germany

ISBN: (纸本)9781713832317

The AlphaZero algorithm has been successfully applied in a range of discrete domains, most notably board games. It utilizes a neural network that learns a value and policy function to guide the exploration in a Monte-Carlo Tree Search. Although many search improvements such as graph search have been proposed for Monte-Carlo Tree Search in the past, most of them refer to an older variant of the Upper Confidence bounds for Trees algorithm that does not use a policy for planning. We improve the search algorithm for AlphaZero by generalizing the search tree to a directed acyclic graph. This enables information flow across different subtrees and greatly reduces memory consumption. Along with Monte-Carlo Graph Search, we propose a number of further extensions, such as the inclusion of Ε-greedy exploration, a revised terminal solver and the integration of domain knowledge as constraints. In our empirical evaluations, we use the CrazyAra engine on chess and crazyhouse as examples to show that these changes bring significant improvements to AlphaZero. Copyright © 2021, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Trees (mathematics)

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Cancer Classification in Imbalance Data Using Double Filtering Approach

Cancer Classification in Imbalance Data Using Double Filteri...

引用

International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Almuzhidul Mujhid Jeffrey Junior Tedjasulaksana Nikita Ananda Putri Masaling Abba Suganda Girsang Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Cancer, also known as malignant neoplasm, is a complex and potentially fatal disease characterized by uncontrolled and abnormal cell growth in the body. The main problems with microarray cancer studies are the high curse of dimensionality and small sample size caused by redundant and irrelevant genes. To deal with the number of features that exceed the amount of data, this research purposed double filtering method Lasso-GA, Lasso is used to select the features based on feature correlation while Genetic Algorithm is used to optimize the most important features with accuracy traditional machine learning as its fitness function. The results show how effective the suggested method is; in breast cancer, the linear SVC model achieves excellent accuracy (0.93), precision (0.94), recall (0.94), and F1 score (0.94), while in lung cancer, the linear SVC, random forest, and logistic regression models perform well (accuracy: 0.95, precision: 0.92, recall: 1, F1 score: 0.95). Logistic regression is the most effective method for bladder cancer, with an accuracy of 0.82, precision of 0.77, recall of 1, and F1 score of 0.87.

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Fostering AI Synergy in the Workplace: The Mediating Role of Indonesian Employees Well-Being in Authentic Leadership and AI Experience

Fostering AI Synergy in the Workplace: The Mediating Role of...

引用

Innovative Research in Applied science, Engineering and Technology (IRASET),Conference on

作者： Daniella Tjung Justin Axela Darmanto Jason William Kelanajaya Maria Grace Herlina Karto Iskandar Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

The present study explores into the relationships between authentic leadership, employee well-being, and AI experience among white-collar workers in Greater Jakarta, Indonesia. The study employs a cross-sectional survey and partial least squares structural equation modeling (PLS-SEM) to reveal that authentic leadership significantly enhances employee well-being, subsequently leading to positive interactions between employees and AI systems. The relationship between authentic leadership and AI experience is partially mediated by employee well-being, demonstrating the significance of leadership qualities like transparency, integrity, and self-awareness in creating a supportive organizational culture. The findings highlight the importance of initiatives focused on employees, such as mental health support and work-life balance, in facilitating AI adoption. However, the study also highlights certain limitations, including geographic and methodological constraints. Future investigations should broaden their scope to encompass various contexts, utilize longitudinal methodologies, and integrate supplementary elements such as technological infrastructure and user perspectives to enhance comprehension. These insights contribute to the growing discourse on leadership, well-being, and technology integration in modern workplaces.

关键词： Training Surveys Industries Leadership Technological innovation Employment Organizations Mental health Mathematical models Artificial intelligence

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