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CRISP - DM Process in Smart Building Management 11

CRISP - DM Process in Smart Building Management

引用

11th International Conference on Electrical and Electronics Engineering, ICEEE 2024

作者： Dursun, Mahir Sabyrzhan, Moldir Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey Graduate School of Informatics Gazi University Department of Computer Science Ankara Turkey

ISBN: (纸本)9798350362541

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM). © 2024 IEEE.

关键词： Information management

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Utilizing Semi-supervised Method in Predicting BRCA1 Pathogenicity Variants 8

Utilizing Semi-supervised Method in Predicting BRCA1 Pathoge...

引用

8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Hidayat, Alam Ahmad Trinugroho, Joko Pebrianto Nirwantono, Rudi Sudigyo, Digdo Pardamean, Bens Department of Mathematics School of Computer Science Bina Nusantara University 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

Quantifying the effect of mutations in the BRCA1 gene is useful for understanding their clinical consequences on breast cancer. Machine learning models can be applied to predict the landscape of protein variant effects that might not be always accessible by experiments. In this work, we propose a simple semi-supervised learning method using a Gaussian mixture model to predict ~90% of the unlabeled missense variants of the BRCA1 gene collected from the ClinVar database. High-quality embeddings are used as a feature of the protein sequences, extracted using the latest pre-trained transformer-based language protein model. A statistical test show that the protein embeddings are effective and robust for predicting pathogenicity. Further, the lower representations of the features are then fed into the semi-supervised model. The prediction performance of the model only for the labeled testing data achieves an AUC score and an accuracy of 79.27% and 71.58%, respectively. Using our defined pathogenic probability score, we find that ~94% of variants in our unlabeled dataset are well-separated into either benign or pathogenic classes according to that scoring. Our scores obtain a moderate Spearman rank correlation with the results of established unsupervised variant effect models. Finally, our approach can potentially be developed for more accurate and biologically reliable predictions of the variant effects. © 2023 The Authors. Published by Elsevier B.V.

关键词： embeddings language model mutation effect protein sequence semi-supervised learning

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review 10

Critical Factors of Immersive Learning in Higher Education: ...

引用

10th International Conference on ICT for Smart Society, ICISS 2023

作者： Sunardi Meyliana Ramadhan, Arief Rosmansyah, Yusep Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information System Bina Nusantara University Information System Departement Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350339543

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education. © 2023 IEEE.

关键词： E-learning

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3D Structure Estimation of Room Environment Using Semantic Segmentation and Model Fitting

3D Structure Estimation of Room Environment Using Semantic S...

引用

Metrology for Living Environment (MetroLivEn), IEEE International Workshop on

作者： Junya Morioka Ryusuke Miyamoto Department of Computer Science Graduate School of Science and Technology Meiji University Kawasaki Japan Department of Computer Science School of Science and Technology Meiji University Kawasaki Japan

ISBN: (数字)9798350385014

ISBN: (纸本)9798350385021

Recent advances in VR devices and technology have increased the demand for technologies that reflect real space in virtual space. In particular, technologies that reflect the indoor environment in a virtual space are used in various fields such as architecture, interior design, and robotics. To reflect a real space in a virtual space, estimating the 3D structure of the real space is significant. Yet, this requires expensive equipment and poses challenges in computational complexity and ease of measurement. In this study, we propose a method of estimating 3D structure of indoor environments using a single image. Existing methods generally use depth estimation, but in this study, we introduce a new approach using semantic segmentation and rectangular fitting. Experimental results with 3D CG show that the proposed method outperforms existing methods in accuracy and competitive results.

关键词： Solid modeling Three-dimensional displays Accuracy Semantic segmentation Fitting Estimation Cameras

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The Effect of Semantic Consistence on P300-Based Brain-computer Interface 17

The Effect of Semantic Consistence on P300-Based Brain-Compu...

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17th International Conference on Complex Medical Engineering, CME 2023

作者： Yang, Jingjing Dong, Xiao Wu, Qi Gao, Xiang Wu, Jinglong Changchun University of Science and Technology The School of Artificial Intelligence 7089 Weixing Road Jilin Changchun China Changchun University of Science and Technology The School of Computer Science and Technology 7089 Weixing Road Jilin Changchun China Okayama University The Graduate School of Natural Science and Technology Tsushima-Naka 3-1-1 Kita-Ku Okayama700-8530 Japan

ISBN: (纸本)9798350316117

Brain-computer interface (BCI) technology enables direct communication between the brain and the outside world. In recent years, there have been more and more researches on character output systems based on brain-computer interfaces, but most of the studies so far have been based on monomodal stimulation. This study adopted a novel bimodal stimulation mechanism that combined both visual and auditory models. Visual stimuli were for English letters, the auditory stimuli were the pronunciation of letters. This study designed two models of semantically consistent stimulus and semantically inconsistent stimulus. Study the impact of semantic consistency on the character recognition of brain-computer interfaces. Sixteen participants participated in this experiment. Participants only need to pay attention to the visual images and count the number of occurrences with a small probability. It was found that the P300 component induced by semantic inconsistency was significantly greater than that under semantic consistency conditions. The semantic consistency of the stimulus significantly affects the event-related potential. © 2023 IEEE.

关键词： Character recognition

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Personal Identification Based on Joint Motions with Error Correction Using Particle Filter

Personal Identification Based on Joint Motions with Error Co...

引用

IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Kosuke Aoyagi Yuki Yuda Masakazu Ohkoba Miho Adachi Ryusuke Miyamoto Department of Computer Science School of Science and Technology Meiji University Kawasaki Japan Department of Computer Science Graduate School of Science and Technology Meiji University Kawasaki Japan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

Gait analysis is useful for personal identification in public spaces. Since the emergence of deep learning that can accurately estimate the joint locations of a human in an image, gait analysis has become feasible in practical applications that have only a visible light camera. This paper proposes a novel method for personal identification based on joint motions that can improve utility of gait analysis. Specifically, the proposed method adopts a particle filter to correct the misclassification of left and right legs using the time-series input of their locations. Experimental results using datasets comprising real-world images showed that the proposed error correction improved the accuracy of personal classification from $84.19 \%$ to $85.94 \%$ when joint locations were estimated using ViTPose.

关键词： Legged locomotion Deep learning Accuracy Surveillance Estimation Cameras Particle filters Vectors Error correction Gait recognition

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Optimizing Big Data Implementation to Create Business Value and Architecture Proposed in the Banking Industry: A Systematic Review

Optimizing Big Data Implementation to Create Business Value ...

引用

2023 International Conference on computer science, Information technology and Engineering, ICCoSITE 2023

作者： Kristiana, Idha Meyliana, Meyliana Hidayanto, Achmad Nizar Prabowo, Harjanto Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Management Departement Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

The exponential growth of data is compelling organizations to employ data in decision-making. As one of the businesses with an ecosystem that contributes to data growth, banks have challenges in generating insight. A high level of data security is frequently linked to a high level of data access difficulties. This poses a challenge to the implementation of data-driven business, where taking control of our data is one of the best ways to ensure that we not only own data but also have the ability to process and use data to extract business value. Through literature review, a number of challenges to optimizing the implementation of big data analytics in the banking industry were discovered. Data governance refers to the methods and procedures that assist banks in managing and securing data. A big data architecture is presented to address the highlighted issues, particularly with a multi-tiered approach to big data structures. With the adoption of this architecture, it will be simpler to generate business-value-generating insights for the banking industry using big data with accessibility and protection of data. © 2023 IEEE.

关键词： Big data

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Semantic Literature Review on Non-Fungible Token: Expansion Area of Usage & Trends 8

Semantic Literature Review on Non-Fungible Token: Expansion ...

引用

8th International Conference on Information Management and technology, ICIMTech 2023

作者： Martha, Gede Indra Raditya Warnars, Harco Leslie Hendric Spits Prabowo, Harjanto Meyliana Hidayanto, Achmad Nizar Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta11480 Indonesia University of Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350326093

Blockchain, Metaverse & NFT are technologies that were booming during the Pandemic. As a derivative product of blockchain, the Non-Fungible Token (NFT) is one of the technologies that has attracted the most interest from investors and the public because of its potential benefits and has always been closely associated with the Metaverse as a main purposes research of the NFTs. This paper is to explore the possibilities and provide an overview of the current use of NFT technology so that it can provide insight for further research & gap with the big picture that it is trying to present in this paper. However, after exploring further related to NFT in this research, it was found that the problem that most people are trying to solve through NFT is related to the topic of Decentralization & Web3 not as a Metaverse main backbone. © 2023 IEEE.

关键词： Blockchain

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Optimization of Pose Recognition Algorithms in Smart Wearable Devices 4

Optimization of Pose Recognition Algorithms in Smart Wearabl...

引用

4th International Conference on Intelligent Computing and Human-computer Interaction, ICHCI 2023

作者： Luo, Mingze Huang, Jueqiao Zheng, Bowen Lin, Guofei Zhao, Tianze Cao, Kangjie School of Electronic Science and Engineering Southeast University Jiangsu Nanjing China Minzu University of China Department of Computer Science and Technology China Fok Ying Tung Graduate School Hong Kong University of Science and Technology Hong Kong School of Accounting and Finance Jiageng College Xiamen University Fujian Zhangzhou China Minzu University of China Department of Computer Science and Technology Beijing China

ISBN: (纸本)9798350343113

With the surge in popularity of smart wearable devices, the necessity for pose recognition has become paramount, especially in fields like motion analysis, health monitoring, and virtual reality. Yet, achieving efficient and precise pose recognition on devices with limited resources poses significant hurdles. Addressing this, we introduce an innovative optimization method for pose recognition algorithms, harnessing the power of the C++ compiler. Our approach uniquely integrates traditional machine learning paradigms with model simplification techniques. Furthermore, by exploiting C++ functionalities such as inline assembly, template metaprogramming, and compile-time optimization, we craft an optimization tailored explicitly for wearable hardware. Evaluations conducted on various devices testify to our method's superiority, marking a 10% surge in accuracy, 30% boost in efficiency, and a 15% dip in energy consumption relative to contemporary methods. Apart from achieving stellar accuracy and real-time performance, our method distinguishes itself in resource efficiency and scalability. This article offers an in-depth exploration of our design philosophies, optimization tactics, experimentation methodologies, and seminal discoveries, signposting the future trajectory of pose recognition in smart wearables and highlighting its commercial potential. © 2023 IEEE.

关键词： Machine learning

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Design of Violence Event Detection System Based on CCTVs by Human Body Pose Recognition

Design of Violence Event Detection System Based on CCTVs by ...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Chang, Kuei-Chung Liao, Yi-Ching National Yunlin University of Science and Technology International Graduate School of Artificial Intelligence Taiwan National Changhua University of Education Dept. of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Violent incidents have happened regularly and usually cause tragedies due to without rescued immediately. Therefore, we expect to study a violence detection and alarm system based on human body pose recognition of images captured from public CCTVs. The system uses OpenPose for real-time skeleton recognition to detect poses based on the abnormal angles or speeds of movement between the various joints of the limbs to determine whether it is violent behavior or not. If possible violent events are detected, the system will trigger an alarm and notify the police or security guard to deter the attacker. Victims will be able to get assistance as soon as possible through this recognition system even if they have obstacles for calling help by themselves. Experimental results show that the target violence behaviors can be detected successfully. © 2023 IEEE.

关键词： Gesture recognition

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