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IEEE Networking Letters 2024年第1期6卷 55-59页

作者： David, Fabio Rezende, Jose F. De Barbosa, Valmir C. Federal University of Rio de Janeiro Informatics and Computer Science Department Rio de Janeiro21941-914 Brazil Federal University of Rio de Janeiro Systems Engineering and Computer Science Program Centro de Tecnologia Rio de Janeiro21941-914 Brazil

Exact solutions of the Routing, Modulation, and Spectrum Allocation (RMSA) problem in Elastic Optical Networks (EONs), so that the number of admitted demands is maximized while those of regenerators and frequency slots used are minimized, require a complex ILP formulation taking into account frequency-slot continuity and contiguity. We introduce the first such formulation, ending a hiatus of some years since the last ILP formulation for a much simpler RMSA variation was introduced. By exploiting a number of problem and solver specificities, we use the NSFNET topology to illustrate the practicality and importance of obtaining exact solutions. © 2019 IEEE.

关键词： Topology

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Investigating the Impact on Data Recovery in computer Forensics 1

Investigating the Impact on Data Recovery in Computer Forens...

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1st IEEE International Conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Soewito, Benfano Bina Nusantara University Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

Defragmentation can potentially be employed as a tactic by perpetrators to conceal, misrepresent, or eliminate digital evidence. This study explores the effects of minor defragmentation, a potential method to conceal digital evidence, on recovering file system data in digital forensics. Our investigation sought to determine the influence of minor defragmentation on the effectiveness of data recovery and to identify methods that can augment the success rate post-defragmentation. We limited the scope of this study to defragmentation in Hard Disk Drives (HDDs), solid-state drives (SSDs), and USB drives. A mixed-method approach employs a literature review, case studies, and controlled experiments. Comparative analysis was used as the main data analysis technique to investigate its impact. Preliminary findings suggest that minor defragmentation hampers data recovery;however, certain strategies can augment success rates. These results can significantly influence the development of data recovery policies, particularly those of digital forensic analysts and law enforcement. The primary objective of this study is to bolster the efficiency and dependability of file system data recovery post-defragmentation while upholding ethical and legal standards. © 2023 IEEE.

关键词： Recovery

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Developer-Centric Task Allocation: An Intelligent Approach for Enhanced Software Productivity 15

Developer-Centric Task Allocation: An Intelligent Approach f...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Fensterseifer Filho, Evandro L. R. Assuncao, Joaquim V. C. Fontoura, Lisandra M. Federal University of Santa Maria - Ufsm Graduate Program in Computer Science RS Santa Maria Brazil Federal University of Santa Maria - Ufsm Applied Computing Department RS Santa Maria Brazil

ISBN: (纸本)9798350368833

Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essential to consider the skills and profile of each developer, thus maximizing their productivity. In projects with large teams, task allocation can be challenging, and the help of tools can facilitate its execution. In this work, we propose an intelligent approach for allocating software development tasks suitable to the profile of developers. From the literature, we define the appropriate skills and technical profiles for a development team, and the assessment is based on the developer completing a questionnaire. We developed a recommendation system to suggest tasks to be allocated to developers, employing text processing techniques. For validation, 495 tasks were used from an actual project developing simulator software for military training. The recommended allocations were evaluated by the project developers and used to improve the system. Validations showed that the developed approach makes consistent and coherent task recommendations to developers according to the developer profile, as participants agree with the recommendation for 76% of tasks. © 2024 IEEE.

关键词： Project management

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Evaluation of REAL-ESRGAN Using Different Types of Image Degradation 11

Evaluation of REAL-ESRGAN Using Different Types of Image Deg...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Andriadi, Kus Zarlis, Muhammad Heryadi, Yaya Chowanda, Andry Binus Graduate Program Bina Nusantara University Computer Science Department Jakarta Indonesia Binus Graduate Program Bina Nusantara University Information System Management Department Jakarta11480 Indonesia School of Computer Science Binus University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350389654

This study evaluates the performance of the REAL-ESRGAN [1] model on images with varying levels of degradation using the DIV2K dataset [2], such as the Wild, the Mild, the Difficult, and the x8 subsets. REAL-ESRGAN was created to solve super-resolution problems and aims to produce high-resolution images from low-resolution images. Experiments were conducted at scales of x2 and x4, and performance was measured using Full-Reference metrics (LPIPS, PSNR, SSIM) and No-Reference metrics (NIQE, MANIQA, CLIPIQA, and PI). The Results were good, especially with the x2 scale;it has higher PSNR and SSIM scores, lower LPIPS and NIQE values, and enhanced visual and perceptual quality. The model faced more significant challenges with the wild and the difficult datasets because they have more complex degradations and compression artifacts;it can be seen with unstable results of Full-Reference and No-Reference metrics. On the contrary, the Mild and x8 datasets yielded better results in both metrics;not only that, even the computational cost for Mild and x8 outperforms the rest of the dataset. This study shows the strengths and limitations of REAL-ESRGAN in handling different levels of image degradation. For future research, the model needs enhancement to tackle the degradation format of the wild and the difficult dataset. It would be good if the REAL-ESRGAN improvement could also maintain the computational cost. © 2024 IEEE.

关键词： Gallium nitride

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Artificial Intelligence-Powered Intent Classification for Indonesian E-Wallet Customer Service Chatbots 4

Artificial Intelligence-Powered Intent Classification for In...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Owen, Christopher Suhartono, Derwin Binus Graduate Program Bina Nusantara University Computer Science Department Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331506490

The rapid expansion of e-wallet services in Indonesia has significantly heightened the need for efficient customer service solutions, making chatbots an essential tool for user support. However, many providers continue to rely on rule-based chatbots, resulting in rigid interactions that struggle to meet diverse user needs or handle the linguistic complexities of the Indonesian language. This study addresses these limitations by developing an AI-powered intent classification model specifically tailored for Indonesian e-wallet customer service, aimed at delivering a more accurate, adaptive, and user-centered experience. A custom dataset was created from user comments on social media associated with Indonesia's top e-wallet providers, followed by data pre-processing and clustering using the BERTopic model. To improve interpretability, OpenAI's GPT-4 was employed for label refinement, resulting in enhanced clarity. Various models were tested, including IndoBERT, RoBERTa, and Convolutional Neural Network (CNN) architectures in both 2D and 3D configurations. The highest-performing model combined IndoBERT embeddings with a 3D CNN classifier, achieving an accuracy of 84.30%, precision of 84.33%, recall of 84.30%, and an F1-score of 84.24%. This study contributes a unique Indonesian-specific dataset and demonstrates the potential of AI to transform customer service interactions in Indonesia's e-wallet sector, offering a clear advancement over traditional rule-based approaches. © 2024 IEEE.

关键词： Sales

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Development of an Automated Scoring Model Using SentenceTransformers for Discussion Forums in Online Learning Environments

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Journal of Computing and Information Technology 2022年第2期30卷 85-99页

作者： Dhini, Bachriah Fatwa Girsang, Abba Suganda Department of Computer Science BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

Due to the limitations of public datasets, research on automatic essay scoring in Indonesian has been restrained and resulted in suboptimal accuracy. In general, the main goal of the essay scoring system is to improve execution time, which is usually done manually with human judgment. This study uses a discussion forum in online learning to generate an assessment between the responses and the lecturer's rubric in the automated essay scoring. A SentenceTransformers pre-trained model that can construct the highest vector embedding was proposed to identify the semantic meaning between the responses and the lecturer's rubric. The effectiveness of monolingual and multilingual models was compared. This research aims to determine the model's effectiveness and the appropriate model for the Automated Essay Scoring (AES) used in paired sentence Natural Language Processing tasks. The distiluse-base-multilingual-cased-v1 model, which employed the Pearson correlation method, obtained the highest performance. Specifically, it obtained a correlation value of 0.63 and a mean absolute error (MAE) score of 0.70. It indicates that the overall prediction result is enhanced when compared to the earlier regression task research. ACM CCS (2012) Classification: Computing methodologies → Modeling and simulation → Model development and analysis → Model verification and validation Applied computing → Education → Distance learning. © 2022, university of Zagreb Faculty of Electrical Engineering and Computing. All rights reserved.

关键词： Semantics

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Ransomware Resilience: Investigating Organizational Security Culture and Its Impact on Cybersecurity Practices against Ransomware Threats

Ransomware Resilience: Investigating Organizational Security...

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2023 International Conference on Informatics Engineering, science and Technology, INCITEST 2023

作者： Yulianto, Semi Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350317862

The increasing threat of ransomware attacks in an interconnected and digital world presents important hurdles for cybersecurity, prompting further examination into how organizational security culture affects their ability to withstand these malicious threats. This study examines the impact and importance of organizational security culture in ransomware threat mitigation. We have surveyed five organizations, giving points from 1 to 5 for each question on cultural factors, leadership support, employee awareness and involvement (compliance), communication, behavior change or BBS practice incorporation, learning/training delivery methodology, and Size and industry impact on their security culture. The results indicate that a robust security culture, with leadership and effective communication, builds stronger resilience to ransomware. Organizations with jointly accountable cybersecurity and training practices are highly efficient. Suggestions range from establishing a secure environment to increasing management buy-in and integrating compliance. This work helps advance our understanding of ransomware resilience and highlights the key role of organizational security culture. The resulting learnings can help to inform organizations' security posture, ultimately helping them better protect their defenses against ransomware threats. © 2023 IEEE.

关键词： Cybersecurity

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Visualization and Simulation of Any MPU Architecture Design with Meta-Instruction 23

Visualization and Simulation of Any MPU Architecture Design ...

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23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Morimoto, Tomoyuki Wang, Ziming Luo, Jiahui Ogawa, Sota Tsutsumi, Toshiyuki Meiji University Department of Computer Science School of Science and Technology Kanagawa Japan Graduate School of Science and Technology Meiji University Computer Science Program Kanagawa Japan

ISBN: (纸本)9798350353952

Our conventional architecture design tool converted instructions of microprocessor (MPU) into meta-instructions with both semantic and functional expressions, and it displayed a circuit diagram of the meta-instruction. The tool was able to perform dynamic simulation only on an educational processor called COMET. However, the meta-instruction must be able to express the arbitrary instruction of at least different significant existing MPUs in order to design arbitrary MPUs. Furthermore, it should be possible to visualize all instructions and then execute them. Therefore, we have improved the meta-instruction so that the architecture design tool applies to major MPUs: MIPS, ARM, and RISC-V in addition to COMET. The improved architecture design tool visualizes and simulates the circuit diagram of the improved meta-instruction. The result shows the possibility of the meta-instruction-based architecture design tool being able to design any MPU. © 2024 IEEE.

关键词： Microprocessor chips

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SIS-ASTROS: An Integrated Simulation Environment for the Artillery Saturation Rocket System (ASTROS) 1

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12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2022

作者： Pozzer, Cesar Tadeu Martins, Joao Baptista Fontoura, Lisandra Manzoni Silva, Luis Alvaro Lima Rutzig, Mateus Beck Nunes, Raul Ceretta de Freitas, Edison Pignaton Graduate Program in Computer Science Federal University of Santa Maria Av. Roraima n. 1000 Santa Maria97105-900 Brazil Graduate Program in Computer Science Federal University of Rio Grande do Sul CP 15064 Porto Alegre91501-970 Brazil

ISBN: (数字)9783031438240

ISBN: (纸本)9783031438233

Simulation is an important technique to support military training. There are different training goals depending on the different ranks of the military personnel being trained, which are addressed by different types of simulation (live, virtual, or constructive). However, a trend in current military training is the combination of different types of simulation in an integrated setup. Observing such kind of blended simulation, the Brazilian Army is making efforts to develop integrated simulation solutions. This work describes the conception of an integrated simulation environment for the Brazilian Army Artillery called SIS-ASTROS. Besides integrating different types of simulators, SIS-ASTROS presents a virtual tactical simulator to train ASTROS artillery batteries deployment activities of mid-rank officers. This simulator addresses aspects that can be classified as constructive, but also virtual ones. Due to this particularity in its design, the conception of this simulator represents an innovative contribution. Moreover, its development demanded solutions in the area of artificial intelligence, computer graphics, and distributed systems applied to simulation problems. This paper presents the key components of the integrated simulation system, highlighting the main contributions in the research and development of the virtual tactical simulator. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Personnel training

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Model of Text-to-Text Transfer Transformer for Hadith Question Answering System 11

Model of Text-to-Text Transfer Transformer for Hadith Questi...

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11th International Conference on Information Technology, computer and Electrical Engineering, ICITACEE 2024

作者： Sulistio, Bambang Suhartono, Derwin Soeparno, Haryono Budiharto, Widodo Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Program Jakarta11480 Indonesia

ISBN: (纸本)9798350389289

The advancement of Artificial Intelligence (AI), notably in Natural Language Processing (NLP), has been remarkable. Among its applications, Question-Answering (QA) systems stand out, assisting users in accessing pertinent information across various topics, including religious contexts. Religion plays a significant role in providing guidance on moral values to modern society, such as tolerance, compassion and social norms. Religious practices taught by religion serve as significant foundations for addressing the increasingly advancing influence of technology. The primary goal of this paper is to create a question-answering system proficient in analyzing user inquiries and precisely extracting data from translated Indonesian Hadith datasets. This research endeavors to enhance question-answering accuracy through Deep Learning techniques. Employing pre-processing methods, the system interprets user query intents. Furthermore, the Text-to-Text Transfer Transformer (T5), a text-based language Transformer model, is utilized to streamline the retrieval process for Hadith-related queries based on relevant subjects. The research findings demonstrate the precision of answers through BLEU and ROUGE scores. The novelty of this study lies in the creation of a dataset of hadith translations in Indonesian and the fine-tuning of the T5 model that has been trained using a dataset of questions and answers based on these translations. This research demonstrates the following evaluation scores: BLEU: 0.606, ROUGE-1: 0.702, ROUGE-2: 0.548, and ROUGE-L: 0.701, indicating that the answers generated by this particular research model are better compared to those produced using the standard mT5 model. © 2024 IEEE.

关键词： Deep learning

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