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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Prasetyaningtyas, Sekar Wulan Rohman, Abdul Loeis, Minaldi Mahatmaputra, Samuel Siek, Michael Binus Business School Master Program Binus University Jakarta Indonesia Business Information System Program School of Computer Science Binus University Jakarta Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

This study expects to systemically review the current investigations on the relationship of people analytics adoption to support higher education's competitive advantage. Through a systematic literature review, with the help of Publish or Perish v8 Software, the assessment chose 19 papers, then played out a descriptive analysis of the writing to address the accompanying exploration questions: 1) what people analytics implies and its significance, and 2) what can People Analytics give to higher education competitive advantage? Researchers did a far-reaching writing audit investigation to accomplish the referenced targets of the paper. Given the examination, the adoption of people analytics to support higher education competitive advantage centers around instructing and learning investigation. The level of analytics is used primarily in the descriptive and diagnostics area. The predictive and prescriptive analytics were not much discussed. The empirical papers of this people analytics range from subject matters to data storage in the library business unit. The competitive advantages were mainly discussed regarding students' specific academic prescription to career paths in higher education. © 2022 IEEE.

关键词： Digital storage

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space

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Procedia computer science 2023年 227卷 1046-1053页

作者： Fergianto E. Gunawan Arief S. Budiman Bens Pardamean Endang Juana Sugiarto Romeli Tjeng W. Cenggoro Kartika Purwandari Alam A. Hidayat Anak. A.N.P. Redi Muhammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta 11440 Indonesia PT Impack Pratama Industri Jakarta 14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99.

关键词： closed space deep learning humity prediction indoor temperature prediction

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An Environmentally Friendly Fishing Android-Based Mobile Device App for Penghu Islands (Pescadores), Taiwan

An Environmentally Friendly Fishing Android-Based Mobile Dev...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Hung-Tu Lin Ke-Qing Yan Ying-Zun Fang Xiang-Rui Huang Liang-Bi Chen Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Electrical Engineering Master Program in Electrical Engineering and Computer Science National Penghu University of Science and Technology Penghu Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Penghu Islands (Pescadores), Taiwan's outlying islands surrounded by the sea, boast rich fishing resources that attract many anglers. However, successful fishing requires more than just gear: it involves understanding the varying fish species available in different locations, times, and climates, as well as adhering to relevant laws and regulations. To address these needs, this paper proposes an environmentally friendly fishing Android-based mobile device App specifically for the Penghu Islands. The proposed Android-based mobile device App aims to gather essential information, including local fishing regulations, aquatic safety tips, and important precautions. Its goal is to equip fishermen with the resources necessary to fish successfully and with peace of mind.

关键词： Sea measurements Length measurement Fish Regulation Mobile applications Tides Protection Smart phones Meteorology Lenses

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The Adoption Model of People Analytics in Higher Education: A Soft System Approach

The Adoption Model of People Analytics in Higher Education: ...

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2022 International Seminar on Application for Technology of Information and Communication, iSemantic 2022

作者： Prasetyaningtyas, Sekar Wulan Rohman, Abdul Loeis, Minaldi Mahatmaputra, Samuel Siek, Michael Binus University Binus Business School Master Program Jakarta Indonesia Binus University Business Information System Program School of Computer Science Jakarta Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

The Adoption of the People Analytics process, especially in higher education, is highly complex and should be understood by scholars. We use seven stages of soft systems methodology to contribute to a deeper understanding of The Adoption of the People Analytics process, especially in higher education as a policy issue. The research was done in one of Indonesia's most prominent private universities. The method used was an exploratory study. In-depth interviews were done to gather data. The main interviewees were all stakeholders (H.R. Director, Business Incubator Director, Research Manager, and more) related to the process. The outcomes showed the actors involved and the obstacles experienced by the actors in transforming the existing condition into the analytics one. The paper proposed a people analytics adoption model in higher education using the soft system approach. The research limitation was due to the limited research object used, so broader research using this approach is urgent to understand the model. © 2022 IEEE.

关键词： E-learning

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Implementation of Dynamic Image for Facial Expression Recognition on Indonesian Facial Expression Dataset

Implementation of Dynamic Image for Facial Expression Recogn...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Irene Anindaputri Iswanto Andry Chowanda Haryono Soeparno Widodo Budiharto Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389692

ISBN: (纸本)9798350389708

In recent times, there has been considerable attention directed towards Facial Expression Recognition (FER) due to its extensive utility across diverse domains. However, the universality of facial expressions has been challenged by studies suggesting that cultural backgrounds significantly influence the perception and recognition of emotions. This paper addresses the need for culturally specific datasets in FER tasks, particularly in underrepresented regions like Indonesia. The study introduces dynamic images as an alternative input representation for facial expression recognition tasks, aiming to assess their efficacy using the Indonesian Mixed Emotions Dataset (IMED). Through experimentation using EfficientNet model, the performance of dynamic images is compared with static image and video inputs. Results indicate that dynamic images exhibit promising performance, with an accuracy of 94.28%. These results outperform static image datasets and nearly match the performance of video-based models, which achieved an accuracy of 97.93 %, despite using fewer data. Nonetheless, challenges such as data imbalance and the quality of generated dynamic images persist, suggesting avenues for further research and model refinement. This study provides valuable insights into methodological advancements in FER, particularly in limited dataset conditions, laying the groundwork for future developments in dynamic image-based facial expression recognition algorithms.

关键词： Emotion recognition Image recognition Accuracy Face recognition Heuristic algorithms Data models Cultural differences Artificial intelligence

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Explainable Tree-Based Boosting Algorithms for Smoker Detection Using Bio-Signals 7

Explainable Tree-Based Boosting Algorithms for Smoker Detect...

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7th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2024

作者： Sulistyawan, Jason Sebastian Setyo Nugroho, Kuncahyo Pardamean, Bens Bina Nusantara University BINUS Graduate Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia

ISBN: (纸本)9798331519643

Many smoking-related diseases are difficult to treat and often fatal. Rather than treating diseased smokers, preventing the diseased is more achievable, though, many of them deny to being smokers, leading to another problem. Thus, this study aims to detect important aspects that can detect that the person is a smoker or not through their bio-signals through using SHAP, along with a comprehensive analysis of the used methods, gradient-boosting algorithms XGBoost, LightGBM, and CatBoost, known for their efficiency in handling complex datasets and non-linear relationships. The study then found that triglyceride, Gtp, hemoglobins significantly affect the body's responses to smoking, based on the CatBoosts' results, having an AUC score of up to 0.8612 and an accuracy score of up to 0.7776 with the selected features. © 2024 IEEE.

关键词： Adaptive boosting

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Identification of Clustering Brisk Keypoint Feature in Grocery Product Using the Elbow Method

Identification of Clustering Brisk Keypoint Feature in Groce...

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IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

作者： Rissa Rahmania Maria Susan Anggreainy Iman Herwidiana Kartowisastro Widodo Budiharto Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350353464

ISBN: (纸本)9798350353471

In smart retail, the problem in grocery product image classification is fine-grained image representation. Product variants are characterized by differences in color, text, and size. However, while the process of image classification involves quite complex stages, there is still a misclassification of grocery products. This is because there are many areas of the image being calculated, which makes the models not optimally calculate the most important area. This paper aims to identify a number of patch image formations as an important area of the product by involving Binary Robust Invariant Scalable Keypoints (BRISK) as a feature descriptor, K-Means Clustering, and the elbow method. First, we experiment with the BRISK keypoint feature for grocery products with different categories of brands. Second, the keypoint features are clustered using K-Means clustering. Lastly, the number of clusters is analyzed using the elbow method to find the optimal number. The result shows that the number of clusters from 8 products has variations of 5, 5, and 6 clusters. Finally, each cluster represents an important area in forming patches to support fine-grained grocery product image classification.

关键词： Image color analysis Image representation Communications technology Pattern recognition Fourth Industrial Revolution Elbow Artificial intelligence

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Input Representation on Text Data for E-Commerce Product Review Summarization Using Graph Convolutional Network

Input Representation on Text Data for E-Commerce Product Rev...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Azani Cempaka Sari Yaya Heryadi Iman Herwidiana Kartowisastro Widodo Budiharto Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

This paper investigates recent advancements and methodologies in Automatic Text Summarization, a field that has garnered significant attention for its ability to condense lengthy documents into concise summaries while preserving key information and themes. The study examines the development of Automatic Text Summarization models, including both extractive and abstractive approaches. Additionally, the research delves into the use of graph convolutional networks for text representation in e-commerce product review summarization. The study employs an e-commerce dataset in conjunction with a graph convolutional network model, covering stages from preprocessing and tokenization to constructing graph-based data representation. The expected outcome is a graph-structured representation of input text data derived from Indonesian-language e-commerce product reviews.

关键词： Sentiment analysis Graph convolutional networks Reviews Text summarization Tokenization Multilingual Electronic commerce Meteors Recommender systems Postal services

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Deceptive Topographic Path Planning 23

Deceptive Topographic Path Planning

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Proceedings of the 22nd Brazilian Symposium on Games and Digital Entertainment

作者： Crhistopher Lenhard Henrique L. Krever Ricardo K. Schlsener Rafael H. Bordini Luis A. L. Silva Graduate Program in Computer Science UFSM Brazil Undergraduate Course in Computer Science UFSM Brazil School of Technology PUCRS Brazil

ISBN: (纸本)9798400716270

Deception is essential to model real-world agent behaviors in entertainment and serious games. This paper approaches the challenge of planning deceptive routes on topographic terrains where topographic path costs and other deceptive path factors are analyzed. The work explores alternative deceptive strategies tuned to explore the terrain costs to determine how deceptive the path search nodes are and to return paths with low topographic costs. In addition to the A* algorithm, the Theta* algorithm is explored in the search for smoother deceptive routes, which better represent routes used by terrestrial agents in real-world adversarial situations. It also analyzes deceptive topographic paths computed according to the Last Deceptive Point (LDP) and Last Topographic Deceptive Point (LDPT) notions, where examples of returned paths are presented with the help of terrain relief scenarios. Experimental results with the proposed methods are statistically analyzed according to various path search metrics, showing that all deceptive strategies with A* compute topographic paths with higher numbers of deceptive nodes on reduced execution times. Moreover, the strategies with Theta* and LDPT return paths that show a useful combination of topographic path quality and number of deceptive nodes.

关键词： Deception Deceptive path planning strategies. Path planning Topographic path planning

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Fabrication of versatile poly(xylitol sebacate)-co-poly(ethylene glycol) hydrogels through multifunctional crosslinkers and dynamic bonds for wound healing

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Acta Biomaterialia 2023年 170卷 344-359页

作者： Yeh, Ying-Yu Lin, Yi-Yun Wang, Ting-Teng Yeh, Yu-Jia Chiu, Ting-Hsiang Wang, Reuben Bai, Meng-Yi Yeh, Yi-Cheun Institute of Polymer Science and Engineering National Taiwan University Taipei Taiwan Institute of Biomedical Engineering National Taiwan University Taipei Taiwan Biomedical Engineering Program Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei Taiwan Institute of Food Safety and Health National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan Adjunct Appointment to the Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Program National Taiwan University Taipei Taiwan GIP-TRIAD Master's Degree in Agro-Biomedical Science National Taiwan University Taipei Taiwan

Poly(polyol sebacate) (PPS) polymer family has been recognized as promising biomaterials for biomedical applications with their characteristics of easy production, elasticity, biodegradation, and cytocompatibility. Poly(xylitol sebacate)-co-poly(ethylene glycol) (PXS-co-PEG) has been developed to fabricate PPS-based hydrogels;however, current PXS-co-PEG hydrogels presented limited properties and functions due to the limitations of the crosslinkers and crosslinking chemistry used in the hydrogel formation. Here, we fabricate a new type of PXS-co-PEG hydrogels through the use of multifunctional crosslinkers as well as dynamic bonds. In our design, polyethyleneimine-polydopamine (PEI-PDA) macromers are utilized to crosslink aldehyde-functionalized PXS-co-PEG (APP) through imine bonds and hydrogen bonds. PEI-PDA/APP hydrogels present multiple functional properties (e.g., fluorescent, elastomeric, biodegradable, self-healing, bioadhesive, antioxidant, and antibacterial behaviors). These properties of PEI-PDA/APP hydrogels can be fine-tuned by changing the PDA grafting degrees in the PEI-PDA crosslinkers. Most importantly, PEI-PDA/APP hydrogels are considered promising wound dressings to promote tissue remodeling and prevent bacterial infection in vivo. Taken together, PEI-PDA/APP hydrogels have been demonstrated as versatile biomaterials to provide multiple tailorable properties and desirable functions to expand the utility of PPS-based hydrogels for advanced biomedical applications. Statement of significance: Various strategies have been developed to fabricate poly(polyol sebacate) (PPS)-based hydrogels. However, current PPS-based hydrogels present limited properties and functions due to the limitations of the crosslinkers and crosslinking chemistry used in the hydrogel formation. This work describes that co-engineering crosslinkers and interfacial crosslinking is a promising approach to synthesizing a new type of poly(xylitol sebacate)-co-poly(ethylene glycol) (PXS-co-

关键词： Polyols

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