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2023 International Conference on Networking, Electrical Engineering, computer science, and Technology, IConNECT 2023

作者： Sirait, Tamsir Hasudungan Lumban Gaol, Ford Supangkat, Suhono Harso Ranti, Benny Bina Nusantara University Binus Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Universitas Indonesia Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350331172

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology. © 2023 IEEE.

关键词： Information management

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Supporting Transparent Distributed Transactions among Containerized RESTful Microservices 10

Supporting Transparent Distributed Transactions among Contai...

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10th International Conference on Platform Technology and Service, PlatCon 2024

作者： Huang, Wei-Lun Liao, Chun-Feng Department of Computer Science National Chengchi University Taipei Taiwan Program in Digital Content and Technologies National Chengchi University Taipei Taiwan

ISBN: (纸本)9798350367874

In modern software systems, supporting transactions across multiple services presents a significant challenge. Among the various interaction approaches, the RESTful architectural style stands out as a popular choice. With the rise of microservice architecture and the growing popularity of hosting microservices in containers, the need for efficient and scalable transaction management mechanisms for containerized RESTful services has become increasingly important. This paper introduces a novel approach that transparently enhances existing non-transactional containerized RESTful services with transaction capabilities. The main idea is to implement transaction handling logic in a sidecar container, which can be attached to service containers as needed. Unlike other distributed transaction mechanisms for RESTful services, this approach eliminates the need to modify both the service logic and the communication protocol (HTTP). This research demonstrates the feasibility of the proposed method through case studies and experiments. Overall, this approach offers a seamless and efficient solution for integrating transaction management into containerized microservices. © 2024 IEEE.

关键词： HTTP

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Stemming Algorithm for the Indonesian Language: A Scientometric View

Stemming Algorithm for the Indonesian Language: A Scientomet...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Maesya, Aries Ramadhan, Arief Abdurachman, Edi Trisetyarso, Agung Zarlis, Muhammad Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665468763

Stemming is the process of cutting affixes, both prefixes and suffixes from a term to get the root of the word that has affixes. Stemming can be done in any language, especially in Indonesia Language. Indonesian which is rooted in Malay and Sanskrit has a bigger influence on Language. The algorithm of stemming that has developed is the one that is based on the dictionary of a root word. This kind of algorithm was started by Nazief- Adriani and it grew up to be Confix Stripping (CS), and then was perfected to be Enhanced Confix Stripping (ECS). A scientometric analysis is a mathematical method used to identify academic publications related to citations and scientific matters and is intended for use in libraries or other fields. In this research, the publication of which using stemming algorithm selected and collected using keywords related to Nazief Adriani and ECS. The publications are collected from *** (an online database for advance scientific research). From those publication we did the analysis bibliometric help by the VOS Viewer application using the analysis technique of co-authorship and citation technique, and all done. The result are, from 310 publications that have keywords Nazief Adriani and 119 publications containing the keyword ECS, it was found that the owning documents will be the reference sources of the next research in which the most citation and co-authorship are found in Indonesia. © 2022 IEEE.

关键词： Publishing

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Help Wanted - Challenges in Data Collection, Analysis and Communication of Cyber Threats in Security Operation Centers 17

Help Wanted - Challenges in Data Collection, Analysis and Co...

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Basyurt, Ali Sercan Fromm, Jennifer Kuehn, Philipp Kaufhold, Marc-André Mirbabaie, Milad University of Duisburg-Essen Department of Computer Science and Applied Cognitive Science Duisburg Germany Technical University of Darmstadt Department of Computer Science Darmstadt Germany Paderborn University Department of Information Systems Paderborn Germany

Security Operation Centers are tasked with collecting and analyzing cyber threat data from multiple sources to communicate warning messages and solutions. These tasks are extensive and resource consuming, which makes supporting approaches valuable to experts. However, to implement such approaches, information about the challenges these experts face while performing these tasks is necessary. We therefore conducted semi-structured expert interviews to identify these challenges. By doing so, valuable insights into these challenges based on expert knowledge is acquired, which in return could be leveraged to develop automated approaches to support experts and address these challenges. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Cybersecurity

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Prototype UX Design: Mobile Augmented Reality Application based on Gamification for Cultural Heritage Tourism 8

Prototype UX Design: Mobile Augmented Reality Application ba...

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8th International HCI and UX Conference in Indonesia, CHIuXiD 2022

作者： Hiererra, Siti Elda Meyliana Ramadhan, Arief Purnomo, Fredy Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665476645

This study aims to identify the processes of UX designing a mobile application, Augmented Reality based on Gamification for Cultural Heritage Tourism, and to provide the prototype design and the testing result;this research employs the Design Thinking Method to design the prototype and uses the System Usability Scale (SUS) to identify and validate the testing result;the author establishes two research questions for this study, then explains the answers through a clear description of the stages of making a prototype which consists of the empathize, define, ideate, prototype, and testing stages, then to find out the testing results, the author uses the SUS method, scoring 88.5 in the excellent and acceptable categories;the originality of the research, this study provides the Design Thinking method to investigate the process of UX designing and the SUS Score method to calculate the resting result, helps build a complete understanding of developing the prototype and validation through testing comprehensively. © 2022 IEEE.

关键词： Augmented reality

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Tactics for Enhancing Write Ahead Log for Long-Term System Maintenance 10

Tactics for Enhancing Write Ahead Log for Long-Term System M...

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10th International Conference on Platform Technology and Service, PlatCon 2024

作者： Ho, Evan Chiu, Yi-Hsiu Liao, Chun-Feng Department of Computer Science National Chengchi University Taipei Taiwan Program in Digital Content and Technologies National Chengchi University Taipei Taiwan

ISBN: (纸本)9798350367874

With the rapid advancement of IT technology, data resilience has become crucial for driving the digital transformation of modern enterprises. In this technological trend, Write Ahead Log (WAL) has emerged as a fundamental technique for ensuring data resilience, highlighting its growing importance. However, most WAL literature does not address design issues in long-term maintenance. This study explores three design issues related to long-term WAL maintenance: acquiring the latest index, log segmentation and reassembly, and index reset after consolidation. The proposed designs are implemented as a proof-of-concept prototype. Subsequently, a series of experiments are conducted to examine the impact of these designs on performance, CPU/memory resource consumption, and index optimization. We hope that the proposed techniques will contribute to practical WAL design. © 2024 IEEE.

关键词： Database DevOps Write Ahead Log

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NOISE-CONDITIONED ENERGY-BASED ANNEALED REWARDS (NEAR): A GENERATIVE FRAMEWORK FOR IMITATION LEARNING FROM OBSERVATION

arXiv

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arXiv 2025年

作者： Diwan, Anish Abhijit Urain, Julen Kober, Jens Peters, Jan Department of Cognitive Robotics TU Delft Netherlands Department of Computer Science TU Darmstadt Germany Germany Center for Cognitive Science TU Darmstadt Germany Germany

This paper introduces a new imitation learning framework based on energy-based generative models capable of learning complex, physics-dependent, robot motion policies through state-only expert motion trajectories. Our algorithm, called Noise-conditioned Energy-based Annealed Rewards (NEAR), constructs several perturbed versions of the expert’s motion data distribution and learns smooth, and well-defined representations of the data distribution’s energy function using denoising score matching. We propose to use these learnt energy functions as reward functions to learn imitation policies via reinforcement learning. We also present a strategy to gradually switch between the learnt energy functions, ensuring that the learnt rewards are always well-defined in the manifold of policy-generated samples. We evaluate our algorithm on complex humanoid tasks such as locomotion and martial arts and compare it with state-only adversarial imitation learning algorithms like Adversarial Motion Priors (AMP). Our framework sidesteps the optimisation challenges of adversarial imitation learning techniques and produces results comparable to AMP in several quantitative metrics across multiple imitation settings. Code and videos available at ***/noise-conditionedenergy-based-annealed-rewards/ © 2025, CC BY.

关键词： Adversarial machine learning

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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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ROOTS: Object-centric representation and rendering of 3D scenes

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Journal of Machine Learning Research 2021年第1期22卷 1-36页

作者： Chen, Chang Deng, Fei Ahn, Sungjin Department of Computer Science Rutgers University PiscatawayNJ08854 United States Department of Computer Science Center for Cognitive Science Rutgers University PiscatawayNJ08854 United States

A crucial ability of human intelligence is to build up models of individual 3D objects from partial scene observations. Recent works either achieve object-centric generation but without the ability to infer the representation, or achieve 3D scene representation learning but without object-centric compositionality. Therefore, learning to both represent and render 3D scenes with object-centric compositionality remains elusive. In this paper, we propose a probabilistic generative model for learning to build modular and compositional 3D object models from partial observations of a multi-object scene. The proposed model can (i) infer the 3D object representations by learning to search and group object areas, and also (ii) render from an arbitrary viewpoint not only individual objects but also the full scene by compositing the objects. The entire learning process is unsupervised and end-to-end. In experiments, in addition to generation quality, we also demonstrate that the learned representation permits object-wise manipulation and novel scene generation, and generalizes to various settings. Results can be found on our project website: https://***/view/roots3d. ©2021 Chang Chen, Fei Deng, and Sungjin Ahn.

关键词： Three dimensional computer graphics

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Diffusion Decision Modeling of Retrieval Following the Temporal Selection of Behaviorally Relevant Moments

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Computational Brain and Behavior 2022年第3期5卷 302-325页

作者： Turker, Hamid B. Swallow, Khena M. Department of Psychology & Cognitive Science Program Cornell University 211 Uris Hall Ithaca 14853 NY United States

When targets appear in a detection task, unrelated but concurrent stimuli benefit from an encoding enhancement (the attentional boost effect). For instance, visual scenes paired with target cues (e.g., female, but not male, faces) are subsequently better recognized than those paired with distractors. Recent work suggests that this also benefits incidental relational memory for all features of the visual display, such as which cue appeared with a given scene, and not just the scene itself. However, it remains unclear whether this can be accounted for by response bias or uninstructed memorization of those concurrent items. This study used diffusion decision modeling to investigate the contributions of evidence accumulation rates (indicative of richer or more easily accessed representations) and response bias to recognition memory. Furthermore, two new experiments investigated the effects of intentionality during encoding. Across all five experiments, target-paired information was subsequently recognized with a higher drift rate than distractor-paired information. While there was evidence of response bias in some cases, keeping bias fixed produced better model fits. Moreover, the new experiments replicated earlier findings, extended them to spatial features, and demonstrated that instructing participants to divide attention across three aspects of a trial (scene, face gender, and face identity) rather than two (scene and face gender) increased, rather than reduced, the magnitude of the attentional boost effect for both the background scenes and relational memory. This study strengthens the claim that temporal selection boosts intentional and incidental encoding of the relationships between co-occurring stimuli. © 2022, Society for Mathematical Psychology.

关键词： Attentional boost effect Diffusion decision modeling Incidental memory Relational memory Temporal selection

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