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Computer System, Information Technology, and Electrical engineering (COSITE), International Conference on

作者： Emigawaty Kusworo Adi Adian Fatchur Rochim Doctoral Program of Information System Universitas Diponegoro Yogyakarta Indonesia Department of Computer Engineering Universitas Diponegoro Yogyakarta Indonesia

Open Government Data (OGD) initiatives have the potential to provide various benefits to the business sectors, such as market insights analysis, new product innovation, cost savings, improved decision-making, enriched collaboration, and increased transparency. However, OGD also carries potential negative consequences, including data inaccuracy, low data quality, privacy and security, data bias and discrimination, and legal compliance. Thus, this paper aims to comprehensively understand the potential risks and benefits associated with OGD portals and their causality levels. To investigate the causal relationships involved, a Bayesian Belief Networks (BBNs) model was employed, which is constructed using an explanatory strategy based on six main phases. In this research, interview sessions were conducted with five business practitioners who have experience in accessing and using datasets on the OGD portals. The study’s results indicate that the use of datasets on the OGD portal has a moderate level of potential risk, especially in terms of low data quality. Additionally, the potential benefits of using the OGD portal are also significant, particularly in helping businesses make informed decisions to improve their product innovation and services. This paper’s contribution lies in comprehensively understanding the potential risks and benefits of Open Government Data (OGD) portals for business sectors.

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A Unified Approach to the Computation and Analysis of Strings of Gene Expression States

A Unified Approach to the Computation and Analysis of String...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Jaime Seguel Marie Lluberes Department of Electrical and Computer Engineering University of Puerto Rico at Mayaguez Doctoral Program in Computing and Information Sciences and Engineering University of Puerto Rico at Mayaguez

ISBN: (纸本)9781467368001

The problem of deciding whether or not a concentration of messenger RNA corresponds to a gene in expressed state is crucial in the Boolean representation of gene regulatory networks. Since there is no independent mathematical description of gene expressions, the computational answers of this problem are affected by uncertainties in the model used for the design of the computer algorithms, and by the number of concentration measurements available. In this article, we handle these uncertainties by computing their probability distributions and unifying heterogeneous algorithmic models with aggregation rules. This approach renders an algorithmic framework that computes a set of probabilistic strings of states and, within it, the elected string, which results from the collective decision of the algorithms on the state of the gene in each of the concentration measurements. The set of probabilistic strings is endowed with a metric and a pseudo metric function that makes it possible to analyze the elected string against the expected and the highest probability strings in the set, among other considerations. The method is applied on biological data sets and the results are compared with those of four previously published algorithms.

关键词： Area measurement Biology Arrays

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Haze effect removal from image via haze density estimation in optical model

Haze effect removal from image via haze density estimation i...

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作者： Yeh, Chia-Hung Kang, Li-Wei Lee, Ming-Sui Lin, Cheng-Yang Department of Electrical Engineering National Sun Yat-sen University 804 Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 640 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 106 Taiwan

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior. ©2013 Optical Society of America.

关键词： Pixels

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ORGANIZING THE RECOGNIZED CONCEPTS OF THE WORK MIND BY SELF-ORGANIZING MAP − Comprehensive indicators that contribute to design and operate a better workplace −

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AIJ Journal of Technology and Design 2022年第70期28卷 1390-1395页

作者： Ishiyama, Nozomi Matsumoto, Yuji Doctoral Program of Engineering Design Graduate School of Science and Technology Kyoto Institute of Technology Japan Faculty of Design and Architecture Kyoto Institute of Technology Japan

The purpose of this study is to focus on the indicators related to motivation in the Work Mind, and to organize the concepts by Pile Sort experiments using the sentences of the question items that compose each indicator. By polymerizing the personal conceptual system by Self-Organizing Map, the map of the Work Mind with some degree of completeness and generality is drawn. It is expected that this map will be a material for getting the general picture of the Work Mind and will be treated as a ruler when designing and operating a better workplace. © 2022 Architectural Institute of Japan. All rights reserved.

关键词： Piles

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Transforming the academic workplace: An evaluation of the ADVANCE program in colleges of engineering (2001-2008)

Transforming the academic workplace: An evaluation of the AD...

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2010 ASEE Annual Conference and Exposition

作者： Zajicek, Anna M. Rencis, Joseph Morimoto, Shauna A. Hunt, Valerie H. Department of Sociology University of Arkansas United States Department of Mechanical Engineering University of Arkansas Fayetteville United States Department of Sociology and Criminal Justice University of Arkansas United States Doctoral Study in the Interdisciplinary Public Policy Program University of Arkansas Fayetteville United States

For over two decades, the US government has supported gender equity programs in Science, Technology, engineering, and Mathematics (STEM) disciplines. In 2001, the National Science Foundation (NSF) initiated the ADVANCE Institutional Transformation (IT) program with the primary goal to increase the representation of women in STEM. Since 2001, 37 institutions of higher education have received the NSF ADVANCE IT awards, and 19 have completed their five-year projects. Using the American Society of engineering Education (ASEE) data, we assess the changes in the representation of full-time tenure-track women faculty in engineering colleges. While earlier cross-institutional studies of the ADVANCE IT program focus only on ADVANCE institutions, we also compare engineering colleges at ADVANCE institutions to their university peers. Our analysis suggests that while the average gains in the percentage of full-time tenure-track engineering women faculty for Cohort 2 were almost twice the national average, the gains were uneven not only between the two cohorts, but also among the engineering colleges in each cohort. Similarly, the ADVANCE institutions showed an uneven performance when compared with their peers. We therefore raise important questions regarding how success is defined and conclude by highlighting the most interesting instances of successful and not so successful efforts along with the importance of conducting multi-level comparative analyses of ADVANCE and non-ADVANCE institutions. © American Society for engineering Education, 2010.

关键词： Professional aspects

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Correction: Optimized framework for evaluating F3 transgressive segregants in cayenne pepper

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BMC plant biology 2025年第1期25卷 300页

作者： Ifayanti Ridwan Muh Farid Feranita Haring Nuniek Widiayani Ahmad Yani Nirwansyah Amier Muhammad Alfan Ikhlasul Amal Jekvy Hendra Nawab Ali Mekhled M Alenazi Mahmoud F Seleiman Willy Bayuardi Suwarno Muhammad Fuad Anshori Department of Agronomy Faculty of Agriculture Hasanuddin University Makassar 90245 Indonesia. Agrotechnology Bachelor Study Program Faculty of Agriculture Hasanuddin University Makassar 90245 Indonesia. Agrotechnology Master Study Program Faculty of Agriculture Hasanuddin University Makassar 90245 Indonesia. Agricultural Science Doctoral Program Graduate School Hasanuddin University Makassar 90245 Indonesia. Directorate of Horticultural Protection Agricultural Ministry Jakarta 12520 Indonesia. Department of Biosystems and Agricultural Engineering (BAE) College of Agriculture and Natural Resources Michigan State University East Lansing USA. Department of Plant Production College of Food and Agriculture Sciences King Saud University Riyadh Saudi Arabia. Department of Agronomy and Horticulture Faculty of Agriculture IPB University Bogor 11680 Indonesia. Department of Agronomy Faculty of Agriculture Hasanuddin University Makassar 90245 Indonesia. fuad.anshori@unhas.ac.id.

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Visual Localization of Intersections on Autonomous Vehicles Based on HD Map 23

Visual Localization of Intersections on Autonomous Vehicles ...

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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Utsula, Bizza S. Ashedananta, Muhammad D. Azis, Nadana A. Nazaruddin, Yul Y. Nadhira, Vebi Institut Teknologi Bandung Faculty of Industrial Technology Department of Engineering Physics Bandung40132 Indonesia Institut Teknologi Bandung Engineering Physics Doctoral Program Faculty of Industrial Technology Bandung40132 Indonesia Instrumentation and Control Research Group Institut Teknologi Bandung Faculty of Industrial Technology Bandung40132 Indonesia

ISBN: (纸本)9788993215274

The increasing number of autonomous vehicles will result in a safety factor that must be maintained. One of the crucial prerequisites for this is proper localization, especially at intersections where most road accidents occur each year. This research is proposed to improve the localization process, which has drawbacks such as the inaccurate Global Positioning System (GPS) when satellite signals are blocked, and Light Detection and Ranging (LiDAR), which is expensive and needs heavy computing time. This is done by implementing the High Definition Map (HD Map) method, which maps the condition of an area that is stored as memory on an autonomous vehicle computer. The proposed system uses a monocular camera to be processed into a semantic segmentation feature map at the pixel level, then uses point cloud to reconstruct a 3D intersection model, which is then segmented semantically as well so that position data is obtained after merging using the occupancy grid and scoring function. The results of this CNN-based approach localization produce less accuracy and Mean Intersection over Union (MIoU) values with 60% average accuracy and 62.3 MioU when compared to GPS data and other 3D semantic segmentation systems, but the proposed approach can save costs and computational burden. © 2023 ICROS.

关键词： Autonomous vehicles

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Multi Task Classification Using Deep Learning Approaches for Big Five Personality Traits Prediction: A Review 11

Multi Task Classification Using Deep Learning Approaches for...

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11th International Conference on Information Technology, Computer and Electrical engineering, ICITACEE 2024

作者： Nudin, Salamun Rohman Gernowo, Rahmat Somantri, Maman Wibowo, Adi Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Diponegoro University Faculty of Engineering Department of Electrical Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350389289

This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the Science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98%), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67%), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36%) and lowest (59%). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG. © 2024 IEEE.

关键词： Contrastive Learning

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Designing sustainable cement free compositions with rice husk ash to improve mechanical performance in next generation ecoblocks

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Scientific Reports 2025年第1期15卷 1-18页

作者： Valenzuela, Marian Tuninetti, Víctor Ciudad, Gustavo Miranda, Alejandra Oñate, Angelo Doctoral Program in Sciences of Natural Resources Universidad de La Frontera Casilla 54-D Temuco 4780000 Chile Sustainable Building Design Lab Department UEE Faculty of Applied Sciences University of Liège Liege 4000 Belgium Department of Mechanical Engineering Universidad de La Frontera Temuco 4780000 Chile Department ArGEnCo-MSM University of Liège Liège 4000 Belgium Departamento de Ingeniería Química Facultad de Ingeniería y Ciencias Universidad de La Frontera Temuco 4780000 Chile Centro de Excelencia en Investigación Biotecnología Aplicada al Medio Ambiente (CIBAMA) Universidad de La Frontera Temuco 4780000 Chile Doctorado en Ingeniería Facultad de Ingeniería Universidad de Concepción Edmundo Larenas 219 Concepción 4070409 Chile Departamento de Ingeniería Civil Facultad de Ingeniería Universidad de Concepción Edmundo Larenas 219 Concepción 4070409 Chile Department of Materials Engineering (DIMAT) Faculty of Engineering Universidad de Concepción Edmundo Larenas 315 Concepción Chile

This study examines the use of low-value rice husk ash as a stabilizer to optimize the mechanical performance and strength of compressed earth blocks made with local soil from the Cauquenes Province, Chile. The use of locally sourced earth construction materials in Chile is limited by their lower compressive strength compared to conventional fired bricks, along with the demanding seismic conditions of the region. To address these limitations, this study details the methodology for collecting, preparing, and mixing raw materials to manufacture compressed earth blocks, compacted under 10 MPa using a novel cylindrical polylactic acid mold designed for miniaturized samples. Fourteen different samples representing nine mixtures of rice husk ash and soil were evaluated using an optimized experimental design. The resulting mechanical properties, including fracture analysis correlated with performance, were assessed through statistical analysis to determine the significance of the optimum mix and the observed trends in strength, modulus of elasticity, yield strength, and associated plastic work. The maximum compressive strength achieved was 3.3 MPa. Notably, the optimum mix of rice husk ash-stabilized compressed earth blocks exhibited a 60% increase in strength compared to pure soil compressed earth blocks, demonstrating the potential of rice husk ash as a cement substitute. © The Author(s) 2025.

关键词： Compressive strength Experimental design Mechanical properties Rice husk ash Stabilization Waste materials

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Motivation increase of mathematics students in engineering-A proposal from Game Based Learning

Motivation increase of mathematics students in Engineering-A...

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2019 International Symposium on engineering Accreditation and Education, ICACIT 2019

作者： Zabala-Vargas, Sergio A. Garcia-Mora, Lewis H. Ardila-Segovia, Dayan A. De Benito-Crosetti, Barbara L. Universidad Santo Tomás Faculty of Telecommunications Engineering Bucaramanga Colombia Universidad Santo Tomás Curriculum Development Unit and Teacher Training Bucaramanga Colombia Universidad de Las Islas Baleares Doctoral Program in Educational Technology Palma de Mallorca Spain

ISBN: (纸本)9781728135670

Training and capacity building for students in engineering programs, including developing competencies and skills in mathematics, have been well-established in literature. There is less known about lowering rates of desertion (understood as the non-completion of an academic program). While it is generally agreed that there are multiple causes (individual, institutional, and state), several authors suggest that low academic results and low motivation in an educational process are important causes. In the case of Santo Tomás University, the site of study for this research project, the desertion index in engineering programs is close to 45%. The course with the highest failure rates is introductory mathematics (offered in the first year). Given this context, this research project proposed innovative pedagogical strategies and mediations, targeting the motivation indexes of university-aged students enrolled in mathematics courses. Game-based learning and mixed methods were employed to design a set of two didactic strategies: (A) Kahoot Online Testing Tool, and (B) Online Crossword. The target population was represented by 20 students enrolled in a differential calculus course, as part of the first-year engineering program. For benchmarking purposes, the participants were given a diagnostic calculus test. Next, an adaptation of Instructional Material Motivation Survey was applied, which allowed me to measure the dimensions of attention, confidence, satisfaction, and relevance. The results demonstrated that the pedagogical innovation positively impacted student motivation. The most significant results include the importance of planning rigorous learning activities, incorporating problems from the real student environment, and the importance of offering immediate feedback. © 2019 IEEE.

关键词： Students

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