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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： Lv, Yiqi Meng, Xiang Luo, Yong Pei, Yan The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University China and Jt. International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai China Doctoral Program Grad. Sch. of Comp. Science and Engineering Graduate Department of Computer and Information Systems University of Aizu Aizuwakamatsu Japan Computer Science Division University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9798400700705

This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter of glucose with the concentration range of 0-300mg/dL in the 60-80 GHz frequency band by High Frequency Structure Simulator (HFSS) simulations. Then we combine the sensing model with a neural network to detect and predict the glucose concentration relying on the learning ability of the neural network. In the prediction of the concentration of unknown samples, the absolute error between the predicted value and the true value is within 5mg/dL, which confirms the ability of the proposed CVNN model. © 2023 ACM.

关键词： Millimeter waves

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AI Recommendations: Friend or Foe? Unraveling the Impact on Consumer Benefits and Privacy 11

AI Recommendations: Friend or Foe? Unraveling the Impact on ...

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

作者： Dewanthi, Desyra Sukma Kristopo, Hari Qomariyah, Nunung Nurul Axel, Muhammad Business Management & Marketing Program Binus Business School International Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Food Technology Department Jakarta11480 Indonesia School of Computing and Creative Arts Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350389654

Artificial Intelligence (AI) and marketing have transformed consumer behavior and shopping experiences, especially through Recommender Systems (RSs) in e-commerce. RSs use algorithms to provide personalized recommendations, enhancing shopping convenience. However, this raises data privacy and ethical concerns, as RSs rely on user data. This research explores the quality determinants of RSs and their impact on consumer behavior, focusing on privacy awareness and its effect on repurchase intentions. Using a qualitative approach with semi-structured interviews, the study targets Indonesian respondents aged 18-40 with e-commerce experience. Findings reveal that recommendation quality, especially self-reference and vividness, significantly influences purchasing decisions. Respondents prefer recommendations that match their preferences and are visually appealing. Positive shopping experiences are linked to efficient and accurate RSs, but there's a need for improvements in transparency, novelty, diversity, and advanced technologies like AR. Respondents are aware of digital data storage but have limited understanding of privacy concerns. They trust e-commerce platforms with basic personal details but are hesitant to share sensitive information. Despite privacy issues, e-commerce remains vital, with respondents emphasizing the need for transparency, robust security, and clear explanations for data use to maintain trust. Addressing these issues not only enhances customer experience but also demonstrates that consumer trust directly impacts the sustainability and success of the business. © 2024 IEEE.

关键词： Differential privacy

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NFT-Based Hydroponic Automated Control Using Adaptive Network-Based Fuzzy Inference System 2

NFT-Based Hydroponic Automated Control Using Adaptive Networ...

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2nd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2022

作者： Surantha, Nico Vincentdo, Vito Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia Tokyo City University Faculty of Scienc and Engineering Department of Electrical Electronics and Communication Engineering Japan

ISBN: (纸本)9781665459440

The rapid population growth and industrial development in developing countries harm the agricultural sector because many agricultural lands are converted into residential or industrial areas. Applying modern agriculture technologies such as hydroponic could help to overcome the problem. However, hydroponics requires special attention in adjusting the pH and nutrient levels to maximize plant growth, so an automated system is needed to manage the process. In this research, a smart hydroponic system is proposed by applying Adaptive Networkbased Fuzzy Inference System (ANFIS) and Internet-of-Things. The IoT system consists of sensor, actuator, and data processing layer is designed to monitor and control the condition of pH and nutrition of the observed plants. Then, the ANFIS algorithm is designed to control the level of pH and nutrition. The experiment results show that the system can automatically adjust the pH and nutrient levels to the expected range for growing plants, and the fuzzy controller made using ANFIS are more accurate and stable than the fuzzy controller made using Sugeno. This study shows that ANFIS has excellent performance when controlling multiple actuators, as long as the data set has great granularity and well defined. © 2022 IEEE.

关键词： Hydroponics

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Identifying The Types and Platforms of the Metaverse – a Systematic Literature Review

Identifying The Types and Platforms of the Metaverse – a Sy...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Satrio Pradono Suryodiningrat Harjanto Prabowo Arief Ramadhan Harry Budi Santoso Computer Science BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Graduate Program Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia

Metaverse is gaining a lot of traction lately, especially after Mark Zuckerberg’s Facebook changed its name to Meta as a preparation to enter another universe called metaverse. The eXtended Reality (XR) technology is also rapidly growing since the birth of Virtual Reality (VR), followed by Augmented Reality (AR), and Mixed Reality is the latest development of XR technology. As the XR technology is the perfect companion to support the metaverse and the understanding of the metaverse is already clear but unfortunately, there is a lot of misconception about the types of the metaverse as well as the platform for each type. This paper aims to point out the types and platforms of the metaverse. 49 articles have been collected and reviewed carefully as a quality assessment process, and 45 articles have been selected for further review. This review informs everybody that there are many types and platforms of the metaverse nowadays.

关键词： Solid modeling Systematics Metaverse Extended reality Bibliographies Mixed reality Second Life

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LoGra: an LSTM-DDPG Integrated MPQUIC Scheduler for Mobile Video Streaming

LoGra: an LSTM-DDPG Integrated MPQUIC Scheduler for Mobile V...

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IEEE Conference on Vehicular technology (VTC)

作者： Minh Hai Vu Thanh Trung Nguyen Thi Ha Ly Dinh Phi Le Nguyen Kien Nguyen School of Information and Communication Technology Hanoi University of Science and Technology Hanoi Vietnam Faculty of Computer Science Phenikaa University Hanoi Vietnam Institute for Advanced Academic Research Chiba University Japan Graduate School of Informatics Chiba University Japan

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

With the increasing demand for video streaming services, efficient video streaming with MPQUIC in mobile wireless networks is gaining interest. Although MPQUIC can leverage multiple network connections (e.g., Wi-Fi, 5G) for simultaneous transfer, improving bandwidth and resilience, its performance is heavily dependent on the MPQUIC scheduler. In mobile scenarios, network fluctuations challenge the scheduler to adapt to dynamic conditions while maintaining good video streaming quality. Addressing this issue, this paper proposes a novel MPQUIC scheduler named LoGra (i.e., LSTM-DDPG integrated MPQUIC Scheduler) with two advanced features. First, LoGra utilizes Long Short-Term Memory (LSTM) to model the temporal correlation of network conditions over time and handle the challenges posed by mobility patterns. Second, it leverages the Deep Deterministic Policy Gradient (DDPG), with its self-learning capabilities and the strength of deep neural networks, to analyze the informative temporal feature vector to influence scheduling decisions. We have implemented the proposed scheduler and compared it to existing ones. The results show that the LoGra scheduler effectively manages multipath communication in heterogeneous wireless networks under mobility scenarios. Moreover, compared to existing schedulers, LoGra achieves significant improvements in data transmission, both in general metrics (loss, goodput) and streaming-related metrics (bitrate, freezing time).

关键词： Measurement Vehicular and wireless technologies Fluctuations Wireless networks Propagation losses Vectors Mobile video Long short term memory Wireless fidelity Resilience

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Soft Computing Based Metaheuristic Algorithms for Resource Management in Edge Computing Environment

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computers, Materials & Continua 2022年第9期72卷 5233-5250页

作者： Nawaf Alhebaishi Abdulrhman M.Alshareef Tawfiq Hasanin Raed Alsini Gyanendra Prasad Joshi Seongsoo Cho Doo Ill Chul Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Sejong UniversitySeoulKorea School of Software Soongsil UniversitySeoul06978Korea Artificial Intelligence Education Hankuk University of Foreign StudiesDongdaemun-guSeoul02450Korea

In recent times,internet of things(IoT)applications on the cloud might not be the effective solution for every IoT scenario,particularly for time sensitive applications.A significant alternative to use is edge computing that resolves the problem of requiring high bandwidth by end *** computing is considered a method of forwarding the processing and communication resources in the cloud towards the *** of the considerations of the edge computing environment is resource management that involves resource scheduling,load balancing,task scheduling,and quality of service(QoS)to accomplish improved *** this motivation,this paper presents new soft computing based metaheuristic algorithms for resource scheduling(RS)in the edge computing *** SCBMARS model involves the hybridization of the Group Teaching Optimization Algorithm(GTOA)with rat swarm optimizer(RSO)algorithm for optimal resource *** goal of the SCBMA-RS model is to identify and allocate resources to every incoming user request in such a way,that the client’s necessities are satisfied with the minimum number of possible resources and optimal energy *** problem is formulated based on the availability of VMs,task characteristics,and queue *** integration of GTOA and RSO algorithms assist to improve the allocation of resources among VMs in the data *** experimental validation,a comprehensive set of simulations were performed using the CloudSim *** experimental results showcased the superior performance of the SCBMA-RS model interms of different measures.

关键词： Resource scheduling edge computing soft computing fitness function virtual machines

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The Social Media Implications on the Sales of Business Products

The Social Media Implications on the Sales of Business Produ...

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Smart Data Intelligence (ICSMDI), International Conference on

作者： Elvina Jacia Gabriel Dyan Amelia Ifan Ford Lumban Gaol Tokuro Matsuo Department of Information System Bina Nusantara University Alam Sutera Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

The use of technology nowadays does not feel strange. Everyday people who use technology for their daily needs, starting with each other, seeking knowledge, can even earn income by doing business using technology. Social media is a tool that can be used by people to become with each other by creating, sharing, and exchanging information virtually through a network. However, in the current era, the notion of social media is not only about exchanging information, but also to support business products. The problem is how to compete tightly in this modern era in increasing the selling value of business products. The positive impact of social media for sales in business products are huge such as, increase sales, increase product promotion, greater market distribution. On the other side, the negative impact also takes part such as, the more competitors, the products compete fiercely in the market. This research aims to identify more the impact of social media on sales of business products that focused on business, benefit, and factor. The research method that we used is quantitative which focuses on the number of samples of respondents to support the research results and the results are in the form of a graphic that shows the answers of the respondents to the questionnaire.

关键词： Graphics Freeware Video on demand Social networking (online) Multimedia Web sites Media Internet telephony

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Attention Convolutional Neural Network for Sentiment Analysis on ChatGPT

Attention Convolutional Neural Network for Sentiment Analysi...

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information technology Research and Innovation (ICITRI), International Conference on

作者： Dedi Irawan Hilman Ferdinandus Pardede Anton Sukmawati Anggraeni Putri Tati Mardiana Graduate School of Computer Science Nusa Mandiri University Jakarta Indonesia National Research and Innovation Agency Bandung Indonesia Faculty of Information Technology Nusa Mandiri University Jakarta Indonesia

ISBN: (数字)9798350376210

ISBN: (纸本)9798350376227

Sentiment analysis is a technique that is able to analyze reviews, sentiment, people’s behavior and emotions towards entities such as services, products, organizations, events and social media. Several sentiment analysis approaches have been carried out, one of which uses deep learning such as Convolutional Neural Network (CNN). This research implements the Attentive model using 3 models, namely Attention network, Multi-head Attention and Convolutional Block Attention Module (CBAM). Attentive mechanisms are used to capture important words so that the model can understand important information. Combining Attentive and CNN models to find optimal performance for each model can be done by hyperparameters tuning settings. From the results of selecting the best hyperparameters, it proves that the Attentive mechanism model is able to increase the performance of the baseline model, each accuracy value that increases is Attention network 0.37%, Multi-head Attention 0.43%, and CBAM 0.21%. The highest improvement value was obtained by Multi-head Attention.

关键词： Deep learning Training Sentiment analysis Analytical models Technological innovation Accuracy Chatbots Data models Convolutional neural networks Tuning

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A Unified Conceptual Model Based on Business Artifacts for information Systems

A Unified Conceptual Model Based on Business Artifacts for I...

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information technology (ACIT)

作者： Maroun Abi Assaf Charbel Fares Ali Rachini Youakim Badr Kablan Barbar Department of Computer Science and Information Technology Holy Spirit University of Kaslik Jounieh Lebanon School of Graduate Professional Studies The Pennsylvania State University USA Department of Computer Science Faculty of Sciences Lebanese University Jdeidet Lebanon

Conceptual modeling captures information Systems requirements and specifications in a graphical representation at a high-level without including low-level implementation details. Entity Relationship Model (ER Model) and Business Process Model and Notation (BPMN) are two major conceptual models for modeling respectively data and process aspects of an information System. On the other hand, Conceptual Artifact Model (CAM) is an alternative conceptual model for modeling both data and process aspects in a single model based on the notion of Artifacts. In this article, we formalize the CAM and define algorithms for generating both Database and Workflow specifications from this model. These specifications are then used to create the Relational Database and execute the Workflow of the information System. Benefits of such alternative modeling approach are not limited to reducing the time and effort of designing information Systems but also of implementing them.

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Database Design for Pre-Eclampsia Case Administration

Database Design for Pre-Eclampsia Case Administration

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information technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Faisal Asadi Gregorius Natanael Elwirehardja Joko Pebrianto Trinugroho Reza Rahutomo Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

The Ministry of Health of Indonesia has referred to pre-eclampsia as one of the most severe diseases affecting women. As an urgency, it is crucial to administrate pre-eclampsia cases for disease prevention as a long-term national healthcare strategy. Regarding health science, case data was significant in developing research and innovation. However, the main problem regarding pre-eclampsia case administration is data handling, recording, and management incompetence. Hence, this research proposed a conceptual design of a database for pre-eclampsia case administration. The proposed design covered conceptual, logical, and physical design. We elaborate the concept into three concepts of pre-eclampsia disease: pre-treatment, treatment, and post-treatment. This study proposed a solution to gain more data and study pre-eclampsia disease in Indonesia.

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