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Intercommunication Method Between Local Edge Computing Devices Using QUIC-Based CYPHONIC

Intercommunication Method Between Local Edge Computing Devic...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Shota Horisaki Kazushige Matama Ren Goto Katsuhiro Naito Hidekazu Suzuki Graduate School of Science and Technology Meijo University Nagoya Japan Graduate School of Business Administration and Computer Science Aichi Institute of Technology Toyota Japan Faculty of Information Science Aichi Institute of Technology Toyota Japan Faculty of Information Engineering Meijo University Nagoya Japan

Internet of Things (IoT) devices are installed in various locations to realize smart cities, smart factories, smart homes, etc., and are connected to the Internet for data communication. Most current IoT systems are built on a client-server model using servers built on the cloud. On the other hand, edge computing services are increasing and there are still demands to manage sensitive data in a local environment, and a local edge computing is emerging as a new concept to address these demands. Next-generation IoT services are expected to increase the importance of interoperability between different IoT systems, and connectivity to the local edge computing environment will be required. The authors have proposed QUIC-based CYPHONIC (CYber PHysical Overlay Network over Internet Communication) as a communication architecture that simultaneously achieves communication connectivity and mobility transparency in a mixed IPv4/IPv6 environment. This paper shows that QUIC-based CYPHONIC can be used to realize end-to-end encrypted communication between local edge devices located in different local networks over the actual Internet environment with practically acceptable performance.

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Mixed Reality System for Teaching and Learning: A Systematic Literature Review 5

Mixed Reality System for Teaching and Learning: A Systematic...

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5th IEEE International Conference on information technology, information Systems and Electrical Engineering, ICITISEE 2021

作者： Suryodiningrat, Satrio Pradono Prabowo, Harjanto Meyliana Hidayanto, Achmad Nizar Bina Nusantara University Faculty Of Computing And Media Computer Science Department BINUS Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Computer Science Graduate Program Jakarta Indonesia Bina Nusantara University School Of Information Systems Information Systems Department Jakarta Indonesia Universitas Indonesia Faculty Of Computer Science Depok Indonesia

ISBN: (纸本)9781665401968

Mixed reality is becoming more popular, and a lot of technology companies trying to develop and enhance mixed reality technology and using it not just in manufactures or industries but lately the technology is used for teaching and learning, either in school or for training purposes. While traditional teaching and learning processes are not effective anymore and most of the time, the learning objectives are not reached. This paper has an objective to point out the benefits of using mixed reality for teaching and learning. 99 articles have been collected and reviewed carefully as a quality assessment process, there are 41 articles has been selected for further review and top 5 benefits will be discussed. This review informs educators and scholars that there are common benefits, and the most popular benefit is better learning engagement. © 2021 IEEE.

关键词： Mixed reality

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The Effectiveness of Online Project-Based Learning (PJBL) to Improve Sustainability Education at Private University 7

The Effectiveness of Online Project-Based Learning (PJBL) to...

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7th International Conference on information Management and technology, ICIMTech 2022

作者： Oktavia, Tanty Prayoga, Agung Vincent Kenth Devani, Vannesa Milewis, Ivena Gaol, Ford Lumban Hosoda, Takaaki BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

Currently, online project-based learning is one of the methodologies used in university student assessment. Furthermore, this study is supported by several factors and current conditions applied to learning, such as the pandemic situation where all learning activities and assignments are carried out online and also the many applications of online project-based learning as a learning method to increase students' knowledges and abilities. The purpose of this study is to see how flow experience perception, self-efficacy, product evaluation, and learning motivation affect online PjBL effectiveness at a private university in Jakarta to improve sustain ability education. We surveyed 62 active undergraduate students with online PjBL experience and interviewed one of these five responders from various majors for more information. Flow experience perception, self-efficacy, product evaluation, and learning motivation all have a positive influence on online PjBL, according to multiple linier regression. © 2022 IEEE.

关键词： Students

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Weather Prediction in Agriculture Yields with Transformer Model 9th

Weather Prediction in Agriculture Yields with Transformer Mo...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Arifin, Yulyani Sonata, Ilvico Maryani Gunawan, Elizabeth Paskahlia Computer Science Department Binus Graduate Program Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta11480 Indonesia

Agriculture has a lot of relations with SDG from United Nations especially in end hungers and sustainable agriculture. One of factor important in agriculture is weather. Weather prediction is very important in agriculture. Weather greatly influences agricultural yields and the types of crops to be planted. Weather predictions, especially temperature and humidity, can be done using time series data analysis. Current developments in deep learning enable more accurate predictions of temperature and humidity based on time series dataset. Some deep learning models can be used to predict data based on training using time series data. The deep programming models used include Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). The Transformer deep learning model, which was first introduced in 2017, is a sequence-to-sequence model which is very suitable for predicting time series data. This paper will explain temperature and humidity prediction using the Transformer deep learning model. Experimental results show that the Transformer model can predict temperature and humidity based on training results using a time series dataset. The accuracy obtained by the Transformer deep learning model is better compared to the LSTM deep learning model as indicated by lower MAE, MSE and RMSE values compared to the LSTM model. © 2024 The Authors.

关键词： Prediction models

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Integration of Artificial Intelligence in Software Defined Networking technology through Developing Machine Learning Algorithms 3

Integration of Artificial Intelligence in Software Defined N...

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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Naibaho, Lamhot Saxena, Pulkit Raj Sharma, Kuldeep Alfurhood, Badria Sulaiman Pallavi, L. Pant, Bhasker Faculty of Letters and Languages Christian University of Indonesia English Language Education Study Program Indonesia Teer Thanker Mahaveer University College of Computing Science and Information Technology Uttar Pradesh Moradabad India Lovely Professional University Department of Computer Science and Engineering Punjab Jalandhar Phagwara India College of Computer Information Sciences Princess Nourah Bint Abdulrahman University Department of Computer Sciences Saudi Arabia B v Raju Institute of Technology Cse Telangana Narsapur India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350399264

A future networking design called "software-defined networking"combines network programmability with centralized administration (SDN). Network administration is currently handled by SDN, which, at the regulator, which acts as the cable network processor and divides the data plane into a control plane and a data aircraft. Recent breakthroughs in artificial intelligence (Al) have shown a stronger inclination for the science community to benefit from their ability to give learning capabilities and enhance Indicator. The author of this research provides a comprehensive analysis of initiatives underway to incorporate Al with SDN. The study concluded that the three primary Al thread where scientific research was centered were computer science, conceptual, and fuzzy reasoning systems. The authors of this paper explore the several fields in which these approaches may be used, their potential future applications, and the innovations made possible by the integration of AI-based methods into the SDN paradigm. By choosing the right SDN controller, any large organization may lower network complexity, implementation expenses, and maintenance costs. The focus of this article is software defined networking's benefits and downsides (SDN). Following is a basic explanation of artificial intelligence and a list of some of its most significant applications in SDN. © 2023 IEEE.

关键词： Software defined networking

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Exploring Tourist Feedback on Riau Attractions Through Indonesian Language YouTube Opinion Using Naïve Bayes Algorithm

Exploring Tourist Feedback on Riau Attractions Through Indon...

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2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2023

作者： Kurniawan, Rahmad Iskandar, Iwan Lestari, Fitra Harpizon, Habibi Al Rasyid Husti, Ilyas Faculty of Mathematics and Natural Sciences Universitas Riau Department of Computer Science Pekanbaru Indonesia Universitas Islam Negeri Sultan Syarif Kasim Riau Department of Informatics Engineering Pekanbaru Indonesia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi Malaysia Graduate Program Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia

ISBN: (纸本)9798350313635

YouTube is a widely-used platform in Indonesia, with 93.8% of its users. As such, it presents a valuable opportunity for marketing tourist destinations, particularly in Riau province, which aims to become Indonesia's top Halal travel destination. Tourism is a vital contributor to the economic growth of regions, and each province in Indonesia competes to promote its tourist attractions to attract more visitors every year. However, the large volume of data can challenge the manual analysis of feedback from YouTube's features, such as likes, dislikes, and comments. A literature review suggests that the Naive Bayes algorithm, which uses machine learning, is helpful for sentiment analysis. Therefore, this study aims to analyze public sentiment toward tourist destinations in Riau province by analyzing YouTube comments using the Naïve Bayes algorithm. The study used 1680 opinions collected from 10 YouTube videos showcasing tourist destinations in Riau. The Naive Bayes algorithm classified 60% of the comments as positive, 32% as neutral, and 8% as negative. The experimental results indicated an accuracy and precision of 73%, a recall of 94%, and an F-1 Score of 82%. The study used the word frequency technique to reveal that Riau could become a popular halal tourist destination based on several frequently occurring words in the comments. © 2023 IEEE.

关键词： Sentiment analysis

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Hotel information System Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

引用

Innovation in technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management information technology Interviews information systems

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Automated COVID-19 screening framework via Deep Convolutional Neural Network with Chest X-ray Medical Images 6

Automated COVID-19 screening framework via Deep Convolutiona...

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6th International Conference on information technology, InCIT 2022

作者： Damkham, Waris Thaipisutikul, Tipajin Supratak, Akara Kraisangka, Jidapa Mongkolwat, Pattanasak Wang, Jja-Ching Mahidol University Faculty of Information and Communication Technology Thailand National Central University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781665489126

COVID-19 screening using chest X-rays plays a significant role in the early diagnosis of COVID-19 illness during the ongoing pandemic. Manually identifying this infection from chest X-ray films is a challenging and time-consuming technique due to time restrictions and the competence of radiologists. Also, the manual Covid-19 identification technique is made much more difficult and opaquer by the feature similarity between positive and negative chest X-ray images. Therefore, we propose an automated COVID-19 screening framework that utilizes artificial intelligence techniques with a transfer learning approach for COVID-19 diagnosis using chest X-ray images. Specifically, we employ the transfer learning concept for feature extraction before further processing with modified deep neural networks. Also, Grad-CAM visualization is used for our case study to support the predicted diagnosis. The results of the experiments on the publicly accessible dataset show that the convolutional neural network model, which is simple yet effective, performs significantly better than other deep learning techniques across all metrics, including accuracy, precision, recall, and F-measure. © 2022 IEEE.

关键词： COVID-19

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Smart Campus and Education: The Study of Individual Performance in E-Learning Environments 11

Smart Campus and Education: The Study of Individual Performa...

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

作者： Purnama Alamsyah, Doni Morika, Doni Siswanto, Boby Othman, Norfaridatul Akmaliah Binus Business School Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia School of Design Bina Nusantara University Design Interior Study Program Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Study Program Jakarta11480 Indonesia Universiti Teknikal Malaysia Melaka Faculty of Technology Management and Technopreneurship Department of Technology Management Melaka76100 Malaysia

ISBN: (纸本)9798350389654

The Learning Management System (LMS) is a component of the Smart Campus and is implemented with e-learning. E-learning can be effective if it gives satisfaction to the user and improves academic performance. Therefore, it is important to evaluate online learning users to support learning outcomes. The purpose of this study is to examine the relationship model of individual performance with support for user satisfaction and flexibility in an e-learning environment. This study was carried out using a survey to 615 e-learning users. Users are among the universities students in the city of Bandung (Indonesia). Data were collected quantitatively through questionnaires distributed online. Data processing is done with SmartPLS, where there are two model tests, namely the PLS Algorithm and Bootstrapping. Results of this study model test found that user satisfaction can be increased by information quality from e-learning. Online learning has perceived flexibility that is assessed by users and can increase user satisfaction and individual performance. It was found that user satisfaction was able to support the individual performance achievements of students as e-learning users. The results from this study provide valuable insights into the role of user satisfaction as a mediator in controlling individual student performance, highlighting the significance of integrating Smart Campus solutions. © 2024 IEEE.

关键词： Individual Performance information Quality Perceived Flexibility User Satisfaction

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Advancing Network Security: A Big Data Analytics Approach to Trust and Integrity 5th

Advancing Network Security: A Big Data Analytics Approach to...

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5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Zou, Shui Long Goyal, S.B. Rajawat, Anand Singh Paramasivam, Godiswary City Graduate School City University Petaling Jaya46100 Malaysia Nanchang Institute of Science and Technology Nanchang China Faculty of Business & Technology University of Cyberjaya Persiaran Bestari Cyber 11 Cyberjaya63000 Malaysia School of Computer Science and Engineering Sandip University Nashik India

ISBN: (纸本)9789819767250

Network security is critical today in the growing world of technology with all its advents. Combining network security along with big data is a recipe for disaster with the amount of stuff available on the Internet. This research employed a mixed-methods strategy by combining quantitative surveys with qualitative interviews to explore more deeply the intricate interconnections among secure network communication, big data analytics, and personal privacy. Given the numbers, big data analytics are being mostly adopted, and mostly out of fear as indicated above. The potential power of data drives businesses more and more as we go. Data integrity problems continue to plague us even when we have encryption and access controls in place. Many organizations are implementing proactive threat detection featuring machine learning algorithms and behavioral analytics. All of the leading endpoint protection solutions now include the capability to spot low-level or zero-day malware. We must launch programs to get people to work together and to exchange information about security threats. Through a mixed-methods approach, we investigate the impact of algorithm complexity, data integrity mechanisms, and adaptability on network security effectiveness. One important finding from the qualitative analysis is the sheer scope of the security paperwork, policy, and regulatory compliance that the business must comply just as complicated are how firms comprise the opposing interests of rivals and customers. The implications for this are far reaching such as the need to boost security spending. This has to be done for the purpose of threat detection as we cannot prevent any cybersecurity attack but early detection of any malicious activity can help mitigating the impact of this kind of actions. Moreover, we might have to apply behavioral analytics in order to track any abnormal behavior of our own employees and, finally, part of our cyber resilience strategy it could be opening and maintain a

关键词： Data integrity

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