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2nd International Conference on computer System, Information Technology, and Electrical Engineering, COSITE 2023

作者： Elwirehardja, Gregorius Natanael Isnan, Mahmud Perbangsa, Anzaludin Samsinga Muchtar, Kahlil Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mahmud Isnan Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350343069

Depressive Disorders (DD) is one of the most prevalent mental disorders in the world that may lead to suicide cases. To prevent the latter, ubiquitous early detection systems may be effective. Recent studies have since researched the development of such systems by exploiting several forms of data, including video, audio, Ecological Momentary Assessments (EMA), and passive sensing data using sensors embedded in mobile devices. To summarize the trends, opportunities, and existing challenges in this field, this study reviewed 15 papers to answer four research questions. EMA was the most popular data to be used in this task, but other approaches, such as using video, audio, and typing behaviors, may be considered due to the subjectivity of EMA. These data were typically recorded using smartphones and analyzed using Machine Learning (ML). However, most of the developed systems had yet to be implemented. Overall, it was concluded that further studies may need to explore usages of more objective data in multimodal approaches as well as consider using Mobile Cloud Computing (MCC) to deploy these systems to provide more effective and efficient diagnoses. Future studies must also take into account the existing challenges of the data and infrastructures, such as the weaknesses of several data types, limitations of mobile devices, as well as the challenges of diagnosis approaches. © 2023 IEEE.

关键词： Machine learning

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Multi-Lingual ESG Impact Duration Inference 7

Multi-Lingual ESG Impact Duration Inference

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Joint Workshop of the 7th Financial Technology and Natural Language Processing, 5th Knowledge Discovery from Unstructured Data in Financial Services and 4th Economics and Natural Language Processing, FinNLP-KDF-ECONLP 2024

作者： Chen, Chung-Chi Tseng, Yu-Min Kang, Juyeon Lhuissier, Anaïs Seki, Yohei Lee, Hanwool Day, Min-Yuh Tu, Teng-Tsai Chen, Hsin-Hsi AIST Japan Data Science Degree Program National Taiwan University Academia Sinica Taiwan 3DS Outscale France University of Tsukuba Japan NCSOFT Korea Republic of Graduate Institute of Information Management National Taipei University Taiwan Graduate Institute of International Business National Taipei University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan

ISBN: (纸本)9782493814197

To accurately assess the dynamic impact of a company’s activities on its Environmental, Social, and Governance (ESG) scores, we have initiated a series of shared tasks, named ML-ESG. These tasks adhere to the MSCI guidelines for annotating news articles across various languages. This paper details the third iteration of our series, ML-ESG-3, with a focus on impact duration inference—a task that poses significant challenges in estimating the enduring influence of events, even for human analysts. In ML-ESG-3, we provide datasets in five languages (Chinese, English, French, Korean, and Japanese) and share insights from our experience in compiling such subjective datasets. Additionally, this paper reviews the methodologies proposed by ML-ESG-3 participants and offers a comparative analysis of the models’ performances. Concluding the paper, we introduce the concept for the forthcoming series of shared tasks, namely multi-lingual ESG promise verification, and discuss its potential contributions to the field. © 2024 ELRA Language Resource Association.

关键词： Iterative methods

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Comparing the performance of machine learning models for predicting the compressive strength of concrete

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Discover Civil Engineering 2024年第1期1卷 1-14页

作者： Loureiro, Arthur Afonso Bitencourt Stefani, Ricardo Graduate Program in Materials Science Federal University of Mato Grosso Barra do Garças Brazil Department of Chemistry Institute of Exact and Biological Sciences Federal University of Ouro Preto Ouro Preto Brazil

This work aimed to investigate and compare the performance of different machine learning models in predicting the compressive strength of concrete using a data set of 1234 compressive strength values. The predictive variables were selected based on their relevance using the SelectKBest method, resulting in an analysis of eight and six predictive variables. The evaluation was conducted through linear correlation studies via simple linear regression and non-linear correlation studies using support vector regression (SVR), random forest (RF), gradient boosting (GB), and artificial neural networks (ANN). The results showed a coefficient of determination (R2) = 0.897 and a root mean square error (RMSE) = 6.535 MPa for SVR, R2 = 0.885 and RMSE = 5.437 MPa for GB, R2 = 0.868 and RMSE = 5.859 MPa for GB and R2 = 0.894 and RMSE = 5.192 MPa for ANN, all for test set and eight predictor variables. The comparison between the machine learning methods revealed significant differences. For instance, ANN stood out with a higher R2 value, demonstrating its remarkable ability to explain the variability in the data. ANN also showed the lowest RMSE value, indicating notable accuracy in the predictions. Although ANN has demonstrated higher performance, GB shows a closer performance, which no differences from a practical application. The choice between these approaches depends on considerations regarding the balance between explainability and accuracy. While GB provides a more in-depth understanding of the relationship between variables, ANN stands out for the accuracy of its predictions.

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A Systematic Literature Review of Recent Trends and Challenges in Digital Twin Implementation 10

A Systematic Literature Review of Recent Trends and Challeng...

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

作者： Arin, Ikrar Adinata Meyliana Warnars, Harco Leslie Hendric Spits Murad, Dina Fitria Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta Indonesia Bina Nusantara University BINUS Online Learning Information Systems Department Jakarta Indonesia

ISBN: (纸本)9798350339543

This paper reviews the latest trends and challenges in implementing digital twin technology. A digital twin is a tool used in various industries to improve efficiency, optimize processes, and enable advanced analysis. The review involved searching major research databases and search engines for articles published between 2018 and 2023. The findings reveal several important trends, including the development of different types of digital twin dimensions, each with its own advantages and limitations. The benefits of digital twin implementation include improved decision-making, increased productivity, and operational efficiency. However, there are challenges, such as data integration, security and privacy concerns, a lack of standardization, and the need for experts to effectively design and operate digital twins. The implications of these trends and challenges are discussed regarding their impact on the successful adoption and implementation of digital twin technology. The review also highlights the need to address these challenges and explore new approaches for maximizing the benefits of digital twin technology. Overall, this comprehensive review is a valuable resource for researchers, practitioners, and organizations seeking to understand the current landscape, identify areas for improvement, and make informed decisions when implementing digital twin technology. © 2023 IEEE.

关键词： Decision making

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Decision Theory and Risk Simulation Analysis for Optimizing Profit in PayLater Services

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Procedia computer science 2023年 219卷 60-67页

作者： Nicholas Dominic Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The projected increase in PayLater utilization reaches up to five million people by 2025. To optimize the yearly profit from their PayLater service, fintech companies must examine all possible risks before a unanimous decision is taken. Therefore, we proposed a unified decision framework derived from decision theory and the Monte Carlo simulation technique. Two schemes were coined: (1) a decision-making scheme, and (2) a risk simulation scheme. Throughout experiments, the framework was able to estimate several alternative decisions and their impacts, analyze the causes of failure and delays in the development of the PayLater service, and execute Monte Carlo simulations in up to 10,000 trials. Outputs of this study will benefit decision-makers in the fintech initiative before launching their PayLater products.

关键词： PayLater decision-making Bayesian analysis fault tree analysis critical path method Monte Carlo simulation

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Hybrid approach sentiment analysis using Transformer-LSTM in the Indonesian language

Hybrid approach sentiment analysis using Transformer-LSTM in...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Angel Karentia Ferdinand Winaya Derwin Suhartono Computer Science Department BINUS Graduate Program – Master of Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

Sentiment analysis is widely used as a tool to find valuable insight from texts without explicitly expressed. Lots of techniques have already been used to get it but there still have shortcomings in data source or the model strategy itself. Indonesian language approximately has 199 million speakers across the world where 44 million speakers natively. Even with that great number, the resources for the Indonesian language's natural language processing are still limited, and hard to find the perfect way to define sentiment analysis in the Indonesian language. The state-of-the-art sentiment analysis method uses LSTM on a small corpus while the best in town is Transformer where it's easy to transfer learning from the Transformer pre-trained model into specific tasks. From this potential, combining the Transformer pre-trained model with LSTM can be an innovative strategy. This research compared the hybrid model of Transformer-LSTM build using three Indonesian languages’ Transformer-based pre-trained model on sentiment analysis task which can surpass the Transformer model with the highest increased 2.40% accuracy and 3.02% on F1 score.

关键词： Seminars Sentiment analysis Analytical models Accuracy Law Soft sensors Transfer learning Medical services Transformers Long short term memory

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Development of Buffer Zone into Living Lab-Garuda Smart City Framework: Systematic Review 10

Development of Buffer Zone into Living Lab-Garuda Smart City...

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

作者： Emmanuel, Gunadi Supangkat, Suhono Harso Gaol, Ford Lumban Ranti, Benny Bina Nusantara University Doctor of Computer Science Jakarta Indonesia Univ. Katolik Musi Charitas Fakultas Sains Dan Teknologi Palembang Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350339543

The phenomenon of urbanization in Indonesia is inevitable. The new residential and economic centers in suburban areas is also a problem in city development. The gradual planning and development of smart cities in a living lab require consideration of the right location for a living lab. This study wants to show that suburban areas as city buffer zones can become living laboratories for smart city development. The diversity of situations in cities and regencies across Indonesia, the potential for resources, and the problems faced are the challenges of developing a living lab-Garuda Smart City Framework. This research uses the method of reviewing the literature of research publications for the last five years (2019-2023) to obtain information on Smart City development in Indonesia. We collected selected articles from databases in Google Scholar, IEEE, and Scopus using the Publish and Perish 8. The search keywords used were garuda AND Smart city AND Framework. The findings show the potential and dynamics of buffer zones to become appropriate living laboratories. Smart city regional planning can more holistically involve neighborhoods and address urban issues. © 2023 IEEE.

关键词： Smart city

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Amico: Message Exchange Service for Elderly People 11

Amico: Message Exchange Service for Elderly People

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Isozaki, Atsushi Fukae, Kazuki Arai, Kenichi Kobayashi, Toru Nakamura, Masahide Nagasaki University Computer and Information Science Program Graduate School of Engineering Nagasaki Japan Nagasaki University Division of Electrical Engineering and Computer Science Graduate School of Engineering Nagasaki Japan Kobe University Center of Mathematical and Data Sciences Hyogo Japan

ISBN: (纸本)9781665492324

This study is related to a system that enables elderly people to communicate interactively with young people who use existing message exchange services by simply speaking to an avatar on a tablet PC, without having to perform complicated operations of the tablet PC. On the other hand, the young people side can bring in elderly people who could not previously participate in existing message exchange services groups. The effectiveness of the system was verified through demonstration experiments with two households consisting of elderly people in their 80s. © 2022 IEEE.

关键词： Personal computers

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An Analysis of Interventions with Students with Autistic Spectrum Disorder (ASD) Using Gamified Geometric Thinking

An Analysis of Interventions with Students with Autistic Spe...

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Frontiers in Education (FIE) Conference

作者： Lidiane Maciel Pereira Regina Barwaldt Vinícius Menezes de Oliveira Mateus Oliveira Jung Graduate Program in Science Education Federal University of Rio Grande Rio Grande Brazil Graduate Program in Computing Federal University of Rio Grande Rio Grande Brazil Graduate Program in Computional Modeling Federal University of Rio Grande Rio Grande Brazil

Studies have been indicating the use of digital resources for interventions with children diagnosed with Autism Spectrum Disorder (ASD), especially when it comes to supporting communication and social interaction. However, there is research that suggests the use of digital environments not only in these aspects but also to assist them in their academic knowledge, such as in their mathematical skills, specifically related to geometric thinking. From this context, Active Methodologies point to various ways of rethinking traditional teaching, one of them being gamification, which can be understood as the use of game elements in non-game situations. Gamification has shown significant benefits for this audience, proving to be an effective tool to aid in the development and learning of these individuals. Therefore, this article in its complete form presents an excerpt from a doctoral thesis that seeks to understand the geometric thinking of nine autistic participants through gamified activities in their real mode. The research is divided into two stages: the first stage involves a preliminary survey with five teachers through structured interviews, aiming to investigate the demand for gamified activities for students with ASD, as well as indicating possibilities for such activities. From the Discursive Textual Analysis (DTA) of these interviews, three categories emerged: opportunities, skills, and limitations. As for the second stage, conducted with nine participants, who are students with ASD, interventions were carried out with these activities in their real mode, which will be implemented digitally later. Through the researcher's observation analysis, based on recorded videos of the interventions, three subcategories related to the initial categories can be identified: potential interactions (opportunities); strategies for geometric thinking (skills); and gamification in the real mode (limitations). The first subcategory emerged due to the need to describe how students

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Total Antioxidant Capacity of Meals Suggested in the Dietary Guidelines for the Brazilian Population

SSRN

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SSRN 2025年

作者： Ranzi, Maria Eduarda Noronha, Luana Alberti Arruda, Giovana Eduarda Koehnlein, Eloá Angélica Federal University of Fronteira Sul Realeza Brazil Post-Graduate Program in Food Science and Technology Federal University of Fronteira Sul Laranjeiras do Sul Brazil

Chronic non-communicable diseases have modifiable risk factors, with dietary habits being a key component. A diet abundant in antioxidant-rich foods is inversely correlated with the onset and progression of these diseases. This study aimed to estimate the total antioxidant capacity (TAC) of meals suggested in the Dietary Guidelines for the Brazilian population (DGBP) (2014), as well as identify the main contributing foods. The research was quantitative and descriptive, based on the analysis of secondary data from photographic records of the suggested meals (breakfast, lunch, and dinner) in the DGBP. The foods, their preparation methods, and portion sizes were identified. The TAC of the foods was primarily estimated according to Carlsen et al. (2010), through the Ferric-Reducing Ability of Plasma (FRAP) assay. Subsequently, the TAC of the meals, the percentage contribution of each food item, and the TAC adjusted to 250 kcal were estimated. The average TAC found was 3.01 ± 1.35 mmol in breakfast suggestions, 1.93 ± 0.84 mmol in lunch suggestions, and 2.49 ± 3.34 mmol in dinner suggestions, with no significant differences when comparing the TAC results among the three meals (p=0.608). However, coffee was identified as the main contributor in breakfast suggestions, while beans stood out as the main contributor in lunch and dinner suggestions. Therefore, the foods that most prominently contributed to the TAC of the meals suggested by DGBP were those that, in addition to being part of the national food culture, are classified as in natura or minimally processed, highlighting their importance in providing bioactive compounds with health benefits. © 2025, The Authors. All rights reserved.

关键词： Food ingredients

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