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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Mantoro, Teddy Ginanjar, Agung Ayu, Media Anugerah Aditiawarman, Umar Sampoerna University Faculty of Engineering and Technology Department of Computer Science Jakarta Indonesia Nusa Putra University Postgraduate Program - School of Computer Science Sukabumi Indonesia

ISBN: (纸本)9798350370126

Malware had been a problem for quite some times since it spreads easily and can cause various problems. Currently, malware is also one of the big threats for internet users. With a huge number of internet users today, techniques that can automatically detect malware before it infects the system is required. This study aims to develop malware detection using machine learning approach with Principal Component Analysis (PCA) as feature reduction. PCA (Principal Component Analysis) is expected to be able to reduce the number of features which then could also reduce the learning time but do not reduce its accuracy significantly. There were four machine learning classifiers used in this study, i.e. K-Nearest Neighbor, Decision Tree, Naïve bayes, and Random Forest. The n-components used in this study were 20 and 34 and the ratio of test and train in the dataset was 35% for test and 65% for training. The results have shown that the best performance come from the detection using random forest with 34 n-component and 100 n-estimator with the average accuracy was 0.991688. © 2023 IEEE.

关键词： Principal component analysis

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Climate change and artificial intelligence: assessing the global research landscape

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Discover Artificial Intelligence 2024年第1期4卷 64页

作者： Lewis, Joanna I. Toney, Autumn Shi, Xinglan Science Technology and International Affairs Program Edmund A. Walsh School of Foreign Service Georgetown University WashingtonDC United States Center for Security and Emerging Technology Edmund A. Walsh School of Foreign Service Georgetown University WashingtonDC United States Department of Computer Science Georgetown University WashingtonDC United States Communications Culture and Technology Program Georgetown University WashingtonDC United States

Artificial Intelligence (AI) could revolutionize our ability to understand and address climate change. Studies to date have focused on specific AI applications to climate science, technologies, and policy. Yet despite the vast demonstrated potential for AI to change the way in which climate research is conducted, no study has presented a systematic and comprehensive understanding of the way in which AI is intersecting with climate research around the world. Using a novel merged corpus of scholarly literature which contains millions of unique scholarly documents in multiple languages, we review the community of knowledge at the intersection of climate change and AI to understand how AI methods are being applied to climate-related research and which countries are leading in this area. We find that Chinese research institutions lead the world in publishing and funding research at the intersection of climate and AI, followed by the United States. In mapping the specific AI tasks or methods being applied to specific climate research fields, we highlight gaps and identify opportunities to expand the use of AI in climate research. This paper can therefore greatly improve our understanding of both the current use and the potential use of AI for climate research. © The Author(s) 2024.

关键词： AI AI tasks and methods China Climate change Publication analysis

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HYPERTENSION SELF-MANAGEMENT SUCCESS IN 2 WEEKS;3 PILOT STUDIES 36

HYPERTENSION SELF-MANAGEMENT SUCCESS IN 2 WEEKS;3 PILOT STUD...

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36th Bled eConference, BLED 2023

作者： Simons, Luuk P.A. Wielaard, Bas Neerincx, Mark Delft University of Technology Faculty of Computer Science Delft Netherlands Health Coach Program Hague Netherlands

ISBN: (纸本)9789612867515

Platform business models like Uber Ride or Airbnb Lodging enable innovative business models by operating digital platforms to connect providers and consumers of products and services in two-sided markets. A particular challenge with platform business models is designing an appropriate revenue model to capture value. This paper presents a taxonomy that classifies the different dimensions and characteristics of revenue models for platform business models. A proven taxonomy development method is used that includes a review of current literature related to platform business models. The taxonomy provides a comprehensive classification of platform revenue models and is applied to a real-life case. The results of this paper include a UML class model and a final taxonomy with 14 dimensions and 64 characteristics. The paper contributes to the design process of novel platform business models and expands the understanding of how digital platforms can generate revenues. © University of Maribor, University Press.

关键词： Taxonomies

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New Media as a Tools to Improve Creative Thinking: A Systematic Literature Review 7

New Media as a Tools to Improve Creative Thinking: A Systema...

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7th International Conference on Information technology, Information Systems and Electrical Engineering, ICITISEE 2023

作者： Hermawan, Hellik Mahardika, Fajar Darmayanti, Irma Sumantri, R. Bagus Bambang Saputra, Dhanar Intan Surya Aminuddin, Afrig Universitas Amikom Purwokerto Faculty of Computer Science Department of Informatics Jawa Tengah Banyumas Indonesia Institut Teknologi Dan Sains Nahdlatul Computer Technology Study Program Faculty of Science and Technology Ulama Pekalongan Indonesia Universitas Amikom Purwokerto Faculty of Computer Science Department of Information Technology Jawa Tengah Banyumas Indonesia Universitas Harapan Information Systems Study Program Faculty of Science and Technology Bangsa Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Sleman Indonesia

ISBN: (纸本)9798350382266

This systematic literature review (SLR) study aims to analyze the role of New Media as a Tool to Improve Creative Thinking, with relevant articles from 2018 to 2023 taken from reputable international journals. It uses three research questions (RQ) to explore New Media's relevance in stimulating creativity. The results indicate that interactive platforms such as social media and online collaboration tools positively influence creative thinking skills. Interaction through New Media allows individuals to share ideas, discuss, and be exposed to various points of view, all of which stimulate creative thinking. In addition, New Media also facilitates the creative process of solving problems and generating original ideas. The immersive experiences offered by this technology can enhance the exploration of ideas and increase the ability to think out-of-the-box. While New Media offers great potential to enhance creativity, there are also potential risks, such as false information, media addiction, and privacy concerns. Therefore, awareness of the wise use of New Media needs to be increased, especially in education and everyday life. Overall, this literature review provides in-depth insight into the role of New Media in enhancing creative thinking skills and driving innovation. With the right approach, New Media can be an effective tool in stimulating creative thinking and encouraging the creation of original ideas beneficial for future social and technological developments. © 2023 IEEE.

关键词： Creative Thinking New Media Original Ideas Systematic Literature Review The Effect of Using New Media

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"Nyctophy": Assessing the effectiveness of serious game for nyctophobia based on virtual reality by usability and heart rate monitoring

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Procedia computer science 2024年 245卷 185-192页

作者： Elshad Ryan Ardiyanto Patrick Alexander Edyth Novian Putra Dimas Ramdhan Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta

Nyctophobia is a phobia of the dark and is common among children but also found in adults. While the phobia itself is commonly known, the diversity of its treatment is still minimal. As technology has reached its highest point, numerous inventions and innovations have emerged in the medical sector. This study aimed to examine the usability of Virtual Reality and Keyboard and Mouse as an interface using the Extended Reality Game Usability Questionnaire (XR-GUQ) in Nyctophobia therapy and to analyze the heart rate response, impact, and implications using t-test Paired/Wilcoxon Signed Rank. Thirty-four Bina Nusantara University students from various backgrounds completed the test using interfaces and a smartwatch. They were divided into two groups, high- and low fear, using the modified Acrophobia Questionnaire (AQ), which resulted in a significant difference. The XR-GUQ result was insignificant in all variables, which indicates similar usability scores on both interfaces. The t-test Paired/Wilcoxon Signed Rank test revealed a significant difference between the high- and low-fear groups when using the Virtual Reality interface compared to the Keyboard and Mouse interface. This significant difference was found within each group regardless of the interface used. This research shows similar scores in terms of usability but a significant difference in heart rate response with the help of a serious game to give a new sensation of phobia therapy.

关键词： Nyctophobia Virtual Reality Keyboard and Mouse Usability Heart Rate Serious Game Effectiveness

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Advancements in Deep Learning Optimization for Post-Earthquake Building Damage Detection A Systematic Review

Advancements in Deep Learning Optimization for Post-Earthqua...

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2024 International Conference on Advanced Information Scientific Development, ICAISD 2024

作者： Sonang, Sahat Yuhandri, Y. Tajuddin, Muhammad Universitas Putra Indonesia Yptk Information Technology Study Program Padang Indonesia Universitas Bumigora Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350392036

This study conducts a systematic literature review (SLR) that focuses on optimizing deep-learning techniques for post-earthquake building damage detection. By employing the PRISMA protocol, this review aimed to collect, analyze, and summarize the findings of various studies published between 2014 and 2024. This research identifies and evaluates optimization methods such as hyperparameter tuning, transfer learning, and data augmentation, highlighting their effectiveness and implementation. Challenges such as data quality, computational costs, and model interpretability were also discussed. The findings indicate that while deep learning techniques significantly enhance the accuracy and efficiency of damage detection, further research is required to address existing challenges and improve model robustness in diverse earthquake scenarios. © 2024 IEEE.

关键词： Contrastive Learning

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A Multi-UAV Charging Station Enabling Free Landing by Grid Pattern Transmitter 14

A Multi-UAV Charging Station Enabling Free Landing by Grid P...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Kim, Jungho Jo, Hyunkyeong Seo, Seoktae Lee, Bonyoung Min, Hyungki Bien, Franklin Ulsan National Institute of Science and Technology School of Electrical and Computer Engineering Ulsan Korea Republic of Ulsan National Institute of Science and Technology Program in Information & Communication Technology Convergence Ulsan Korea Republic of

ISBN: (纸本)9798331516116

This paper proposed a novel landing platform with wireless power transfer (WPT) to charge multiple unmanned aerial vehicles (UAVs) without restrictions on landing locations or alignment. A transmitter is designed using wires to charge a wide area. To overcome the disadvantages of system made by wires, a grid pattern transmitter and double power line are proposed. These structures provide multiple charging with free positioning of receivers and excite the transmitter lines in wide area properly. The optimized system is composed of 0.15m square cells, providing a 0.9 m by 0.9 m charging area. By experiment, it can efficiently charge four 0.1 m square receivers located anywhere in transmitter. The overall efficiency of four receivers is 37.5%. Also, the experimental results verify that it is unnecessary to align the receiver within the cell, as it has a 2.62% error due to rotation and a 2.94 % error due to position within the cell. © 2025 IEEE.

关键词： Drones

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A Hybrid Approach with BRKGA and Data Mining for the Early/Tardy Scheduling Problem 13

A Hybrid Approach with BRKGA and Data Mining for the Early/T...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Mendonça, Israel Fatyanosa, Tirana Noor Aritsugi, Masayoshi Silva, Pedro Henrique González Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan Brawijaya University Faculty of Computer Science Malang Indonesia Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil

ISBN: (纸本)9798350308365

This paper introduces a novel hybrid genetic algorithm combined with data mining to solve a version of the early/tardy scheduling problem in which no unforced idle time may be inserted in a sequence. The chromosome representation of the problem is based on random keys and we use the Biased Random-Key Genetic Algorithm (BRKGA) to establish an order in which jobs are scheduled. A data mining component gathers data from the evolutionary steps of BRKGA and suggests chromosomes based on past observations. In this way, we address a key challenge in BRKGA - the exploration of solutions near an individual gene - by leveraging data-driven insights to refine and enhance the search space. Comparative analysis reveals that our hybrid algorithm significantly benefits from the pattern recognition capabilities of data mining, leading to improved scheduled efficiency. The results of a series of computational experiments underscore the potential of this hybrid approach that, although requiring slightly longer computational times, is better than the previous baseline BRKGA algorithm in terms of solution quality. © 2024 IEEE.

关键词： Scheduling algorithms

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Automatic Identification and Reconstruction 3D Image of the Rhinosinusitis Mucus 12

Automatic Identification and Reconstruction 3D Image of the ...

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12th International Conference on Information and Communication technology, ICoICT 2024

作者： Eka Putra, Ondra Sumijan Tajuddin, Muhammad Universitas Putra Indonesia YPTK Padang Faculty of Computer Science Department of Informatics Technology Padang Indonesia Doctoral Program in Information Technology Universitas Putra Indonesia YPTK Padang Padang Indonesia Bumigora University Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350363432

Rhinosinusitis Mucus is mucus produced by mucus glands found in the nose in the paranasal sinus area which indicates inflammation. Segmentation of rhinosinusitis mucus is very difficult to do because of the many characteristics of different objects in the image of the paranasal Sinus CT-Scan in separating the mucus object with its background before the extraction process. The purpose of this study was to accurately identify and measure the mucus area of rhinosinusitis from CT-scan images of rhinosinusitis patients. The test data used in this study is secondary data from CT-Scan of paranasal sinus sagittal view in radiology RSUP M. Djamil Padang, Padang City, West Sumatra, Indonesia, using the Philips Ingenuity CT CT-Scan model type MRC880 numbered Tube series 163889. The segmentation process is carried out to obtain the optimal multi threshold value from each slice of the test image using the Improved Adaptive Multi Threshold (IAMT) segmentation method which produces a binary image to separate the mucus object with its background before the extraction process. Furthermore, the results of IAMT are applied to the identification and extraction model automatically to obtain the area of the rhinosinusitis mucus object. The extraction results were used for 2D to 3D image reconstruction in calculating the volume of rhinosinusitis mucus objects. The test results showed that the smallest area of rhinosinusitis mucus was 0.516 cm2 and the largest was 1.807 cm2, and the average volume was 0.95 cm3 with Accuracy is 96,5%. The identified areas and volumes indicate inflammation in the area of the paranasal sinuses and require treatment. Thus, this study can help doctors in making the right decision to take further medical action. © 2024 IEEE.

关键词： computerized tomography

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Analyzing Human Observer Ability in Morphing Attack Detection - Where Do We Stand?

IEEE Transactions on Technology and Society

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IEEE Transactions on technology and Society 2023年第2期4卷 125-145页

作者： Godage, Sankini Rancha Lovasdal, Froy Venkatesh, Sushma Raja, Kiran Ramachandra, Raghavendra Busch, Christoph Norwegian University of Science and Technology Department of Computer Science Trondheim 22 Gjovik2815 Norway National Police Directorate National Technology Team Euis Program Oslo0369 Norway Norwegian University of Science and Technology Department of Information Security and Communication Technology Trondheim 22 Gjovik2815 Norway

Morphing attacks are based on the technique of digitally fusing two (or more) face images into one, with the final visage resembling the contributing faces. Morphed images not only pose a challenge to Face-Recognition Systems (FRS) but also challenge experienced human observers due to high quality, postprocessing eliminating any visible artifacts, and further the printing and scanning process. Few studies have concentrated on examining how human observers can recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS to morphing attacks and offered morphing attack detection (MAD) approaches. MAD approaches base their decisions either on a single image with no reference to compare against (Single-Image MAD (S-MAD)) or using a reference image (Differential MAD (D-MAD)). One prevalent misconception is that an examiner's or observer's capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue. No works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs. As human observers are involved in checking ID documents having facial images, a lapse in their competence can result in significant societal challenges. To assess the observers' proficiency, this research first builds a new benchmark database of realistic morphing attacks from 48 different subjects, resulting in 400 morphed images. Unlike the previous works, we also capture images from Automated Border Control (ABC) gates to mimic realistic border-crossing scenarios in the D-MAD setting with 400 probe images, to study the ability of human observers to detect morphed images. A new dataset of 180 morphing images is also produced to research human capacity in the S-MAD environment. In addition to creating a new evaluation platform to conduct S-MAD and D-MAD analysis, the study employs 469 observers for D-MAD and 410 observers for S-MAD who are primarily governmenta

关键词： Face recognition

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