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Execution of Reconfiguration System on Chip Design for Internet of Things

Execution of Reconfiguration System on Chip Design for Inter...

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Advances in computing, Communication Control and networking (ICAC3N), International conference on

作者： Ipseeta Nanda J. Midhunchakkaravarthy Faculty of Computer Science and Multimedia Lincoln University College Kota Bharu Malaysia

ISBN: (数字)9798350330861

ISBN: (纸本)9798350330878

To address the demand for additional resources on the DPR stands for dynamic partial reconfiguration and field programmable gate array. was introduced. PDR can alter the system’s efficiency and functioning to make room for additional hardware modules, reduce power consumption, and conserve fabric area. PDR entails designing modules that are self-contained and able to be sequentially loaded in the same fabric region. The authors of this work modify a small portion of the FPGA at runtime to add new functionality, leaving the other portions of the device unchanged. A tool developed by XILINX called PLANAHEAD, which can construct systems that are changeable for every VIRTEX field programmable gate array during runtime, can help simplify the complications of this process. The first graphical environment for partial reconfiguration, PLANAHEAD offers the freedom to adapt a design in the field, save power consumption, and save board area.

关键词： Runtime Power demand Logic gates Dynamic scheduling Fabrics Hardware System-on-chip

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A Non-normal Warning System for Dam Operation Using Machine Learning 24

A Non-normal Warning System for Dam Operation Using Machine ...

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24th IEEE/ACIS International Winter conference on Software Engineering, Artificial Intelligence, networking and Parallel/Distributed computing, SNPD 2022

作者： Chang, Meng-Wei Liu, I-Hsien Liu, Chuan-Kang Lin, Wei-Min Su, Zhi-Yuan Li, Jung-Shian Inst. Computer and Communication Engineering National Cheng Kung University Dept. of Electrical Engineering Tainan Taiwan National Chin-Yi University of Technology Dept. of Artificial Intelligence and Computer Engineering Taichung Taiwan Chia Nan University of Pharmacy and Science Dept. of Multimedia and Game Development Tainan71710 Taiwan

ISBN: (纸本)9798350310412

A country's critical infrastructures are heavily related to the quality of life and safety of the people. As a result, the security protection aspect of critical infrastructure has gained more and more attention nowadays, especially the security of its industrial control system (ICS). To avoid the abnormal condition happening in the critical infrastructure which could put people in great danger, a system that is capable of detecting any abnormal state of the ICS promptly is needed. Fortunately, due to the dramatic growth of the applications of machine learning in recent years, some researchers have already proposed anomaly detection methods with machine learning to provide instant warning and protection for ICS. However, most of the existing anomaly detection research tends to only target one cause that harms the system, such as attacks on the network or physical equipment failures. The ICS will be more comprehensively secured if the anomaly detection system can cover multiple aspects of the ICS. Therefore, we have established a non-normal warning system with the Generative Adversarial Network (GAN) for dam operations in this study, which can detect various types of non-normal operations and notify relevant personnel right away. Note that we use real historical data to make predictions and verify our warning system, and we improve it even more by implementing the visual analysis method, which makes up the indecipherable results often found in unsupervised learning. © 2022 IEEE.

关键词： Critical infrastructures

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Comprehensive Examination of Depression Detection Through multimedia Content on Social Media Platforms

Comprehensive Examination of Depression Detection Through Mu...

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Cognitive computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International conference on

作者： Chayan Preet Walia Priti Maheshwary Rabindranath Tagore University Bhopal India Department of Computer Science and Engineering Rabindranath Tagore University Bhopal India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Depression is a mental health disorder that causes persistent feelings of sadness, hopelessness, and a loss of interest or pleasure in activities that one used to enjoy. It can be caused by a combination of genetic, biological, environmental, and psychological factors. Identifying depression causes in social media involves the use of data mining and natural language processing techniques to analyze user-generated content and behavior. Depression analysis is a popular research topic in the natural language processing field, and researchers are increasingly publishing papers on this subject. This review paper aims to explore the use of machine learning techniques for depression analysis using social media text, audio, and video data. The paper provides an overview of the different machine learning techniques used for depression analysis and their effectiveness. The review paper can help researchers understand the current state of knowledge on depression analysis using social media text, images, and videos along with machine learning techniques and identify potential areas for future research.

关键词： Analytical models Social networking (online) Reviews Computational modeling Biological system modeling User-generated content Mental health Depression Natural language processing Data models

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The Impact of Social Media Exposure on Consumer Banking Decisions in Sri Lanka

The Impact of Social Media Exposure on Consumer Banking Deci...

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Advanced Research in computing (ICARC), International conference on

作者： Muditha L. Samarasinghe Amila S. Withanaarachchi Department of Industrial Management University of Kelaniya Kelaniya Sri Lanka

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

Social media (SM) has been a crucial medium for influencing Sri Lankan individuals, where financial institutions have increasingly felt the need to adopt SM marketing practices coupled with customer engagement. This study investigates the relationship between SM factors and customer banking decisions mediated by customer trust and satisfaction with their bank(s). The moderating roles of consumers' digital literacy and demographic factors are also examined. The findings confirm SM platforms such as Facebook, Instagram, and LinkedIn make up for the improvement in terms of consumer engagement. Content quality is important when shaping customers' satisfaction and trust levels. Based on the survey, building trust and pleasure with SM banking services rests much on customer digital literacy. A higher level of digital literacy considerably raises the chance of both trusting and using banking services via SM, while demographic characteristics—age, gender, income, and education—also influence consumers' reactions. Younger consumers indicate a higher preference for dynamic and interactive content, while older ones show a preference for security and reliability. These results highlight the need for digital literacy programs and focused communication plans to better satisfy and engage customers using SM banking.

关键词： Surveys Social networking (online) Reviews Banking Digital intelligence Web sites Security Reliability multimedia communication Stress

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QoE Assessment of Cloud-Based Social Extended Reality Applications Over Heterogeneous Access Networks

QoE Assessment of Cloud-Based Social Extended Reality Applic...

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Consumer Communications and networking conference, CCNC IEEE

作者： Karan Mitra Henrique Souza Rossi Justin Gavrell Christer Åhlund Department of Computer Science Electrical and Space Engineering Pervasive and Mobile Computing Luleå University of Technology Skellefteå Sweden

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

The next generation of immersive applications, such as eXtended reality (XR), will likely be cloud-based and streamed over mobile networks using myriad technologies such as WiFi and 6th-generation mobile networks. Mobile networks promise ubiquitous connectivity but are prone to stochastic network conditions that may be detrimental to end users' quality of experience (QoE). The impact of network conditions on QoE has been studied extensively by industry and academia regarding various multimedia services such as audio, video, and gaming. However, the impact of network conditions on users' QoE for XR-based social applications has yet to be thoroughly investigated. This paper presents novel results assessing the impact of network conditions $(\boldsymbol{N}=\mathbf{20})$ involving factors such as round trip time (RTT), jitter (RJ), and packet losses (PL) on users' QoE via realistic subjective tests $(\boldsymbol{N}=\mathbf{28})$ regarding social XR application. Our results show that social XR applications require stringent QoS conditions. In particular, our results show that increasing RTT values do not significantly affect users' QoE up to 77ms. Combined PL and RTT cases cause significant QoE degradation from 77ms onward with greater than 2% PL. Most importantly, results show that a very small jitter value with one standard deviation beyond 52 milliseconds can lead to significant QoE degradation. Further, jitter values beyond three standard deviations for 27ms RTT and beyond should be avoided.

关键词： Degradation Cloud computing Extended reality Packet loss Quality of service Jitter Streaming media Quality of experience Standards Wireless fidelity

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A BP -based Key Management Protocol for Data Sharing on Cloud Storage with Access Control 45

A BP -based Key Management Protocol for Data Sharing on Clou...

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45th International conference on Telecommunications and Signal Processing (TSP)

作者： Abi-Char, Pierre E. Amer Univ Middle East Coll Engn & Technol Egaila Kuwait

ISBN: (数字)9781665469487

ISBN: (纸本)9781665469487

Cloud computing is an emerging technology, which provides a variety of services including computational platform, computational power, storage and applications. Many enterprises are gaining great benefits from cloud storage services by sharing their corporate data with other users. However, the massive use of cloud computing and the lack of effective security mechanisms lead to many challenges in cloud computing. There are significant security and privacy concerns regarding data sharing as data might be stolen, eavesdropped or destroyed. In addition, data needs to be kept confidential not only from users sharing the cloud, but also from the cloud provider itself. In this paper, we propose a key management scheme for data sharing on cloud computing. Our proposed scheme allows data owners to store their files on remote servers using the cloud storage, and to share those files with other users in a secure manner. The proposed mechanism is based on bilinear pairing and provides access control by providing data owners the power to set permissions and rules over the data. Therefore, it guarantees that only authorized users can access the right data. Moreover, the proposed scheme ensures the security and privacy of data stored on cloud. Finally, informal security analysis of the proposed scheme is presented and analyzed, which demonstrates that the scheme is secure and can resist a variety of attacks.

关键词： Cloud computing Elliptic Curve Cryptosystem Key Management Hierarchical Access Control Cloud Security

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Exploring Permission Control Flaws in Mini-apps

Exploring Permission Control Flaws in Mini-apps

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IEEE International conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Jun Li Yuting Zhang Wu Zhou Shengzhi Zhang Department of Computer Science Metropolitan College Boston University Boston MA USA Meta Platforms Menlo Park CA USA

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

Mini-apps, running within super apps like WeChat, Snapchat, Telegram, etc., have become quite popular these years, expanding the capability of super apps to offer almost any functionality users might desire in their daily lives. However, developers of both super apps and mini-apps typically focus on functionality, thus overlooking security measures essential for protecting users’ sensitive information and safeguarding critical operations. In this paper, we utilize a static analysis approach, revealing two major security flaws of mini-apps and super apps: users’ sensitive information leakage and caller impersonation attacks. We analyzed 10,000 popular mini-apps on WeChat and found that 2,554 are vulnerable to the users’ sensitive information leakage. For the caller impersonation attack, we found one example that is vulnerable to such an attack.

关键词： Privacy Social networking (online) Static analysis Impersonation attacks Computer architecture Message services Information leakage Web sites multimedia communication Payloads

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A Study of Fake News Detection Using Machine Learning Techniques

A Study of Fake News Detection Using Machine Learning Techni...

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computing, Sciences and Communications (ICCSC), International conference on

作者： Shailja Bhardwaj Akash Sanghi Y.D.S. Arya Gaurav Agarwal Anshika Agarwal Department of CSE Invertis University Bareilly India Department of Information Technology ABES Engineering College Ghaziabad India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353655

The number of people using the Internet has significantly expanded due to the advancement of information and communication technology. It converts people's conventional news and information consumption habits into online ones, benefiting news broadcasters and readers by enabling comfort, speed. These days, massive false reports (news) are constantly uploaded by hostile clients with deceitful objectives, prompting calamitous social consequences for people and society and making ceaseless dangers a majority rule government, equity, and public trust. It is especially significant in online entertainment stages (e.g., Snapchat, Twitter, Facebook) because to their inherent, unrestrained publishing methods and platforms. Same issues have determined the work of the academic world as well as enterprises for growing more precise fake news recognition. In this paper, different machine learning methods are introduced, which are implemented in other datasets to observe which method is most efficient in this field.

关键词： Machine learning algorithms Social networking (online) Publishing Machine learning Internet Information and communication technology Web sites multimedia communication Fake news Regression tree analysis

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Image Cryptography using AES-256 Algorithm

Image Cryptography using AES-256 Algorithm

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Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International conference on

作者： Taniska Chandel Ninad Gangodkar Abhiraj Gautam Yogesh Lohumi Mohd Rehan Ghazi Ashtha Goyal Department of Computer Science and Engineering Graphic Era (Deemed to be) University Dehradun India School of Computing Graphic Era Hill University Dehradun India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Due to the advancement of technology, information security and user privacy have become a critical issue resulting in the use of various encryption techniques. Especially with the increasing use of social networking, it has become necessary to secure multimedia messages and prevent data threats and data manipulation. Image Cryptography focuses on the encryption of images and securing them from unauthorized access and protect their confidentiality and integrity. In order to encrypt and decode pictures, this paper focuses on the Advanced Encryption Standard Algorithm (AES) which is a symmetric encryption algorithm. Furthermore, it reflects on the efficiency of the algorithm by determining the security of the algorithm using various parameters like entropy, NPCR, MSE and Histogram analysis. For better comparison all five of AES modes are presented in this paper; Electronic Codebook (ECB), Cipher Block Chaining (CBC), Cipher Feedback (CFB), Output Feedback (OFB), and Counter (CTR). Overall, it can be concluded that AES is a secure algorithm that can be used for safe data transfer. Furthermore, through the result of the parameters used to determine the security of each mode of the AES algorithm, it can further be concluded that CTR mode of the algorithm is the most secure.

关键词： Ciphers Steganography Privacy Social networking (online) Entropy Encryption Security Cryptography Standards Output feedback

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Beyond Search: A Network-Based Exploration of Buyer Behavior in the OLX Car Market

Beyond Search: A Network-Based Exploration of Buyer Behavior...

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multimedia Processing, Communication & Information Technology (MPCIT), International conference on

作者： Y. Moin Ashvath Ramya G R Department of Computer Science and Engineering Amrita School of Computing Coimbatore India

ISBN: (数字)9798350375466

ISBN: (纸本)9798350375473

The information on used cars offers a thorough analysis of the second-hand car industry. This dataset may be utilized to construct predictive models that can estimate the price of a used car based on its characteristics, including the make, model, year, mileage, fuel type, and condition. This dataset enables comprehensive data analysis to extract insights into market trends, pricing dynamics, and buyer-seller behavior. The main goals are to examine price patterns depending on different characteristics, assess the influence of fuel type and geographical factors on pricing and demand, investigate the correlation between mileage and resale value, and determine the most popular automobile models. Furthermore, the dataset enables the development of predictive models that can estimate both selling prices and the amount of time it takes to sell a product. Methodologies encompass the processes of data cleaning and exploratory data analysis (EDA). The results will assist in identifying communities or clusters within the dataset, uncovering groups of cars with similar attributes or market characteristics. The results aim to offer comprehensive market insights, improve comprehension of buyer behavior, and create predictive tools to assist sellers, buyers, and platform operators in decision-making. Ultimately, this will optimize strategies and operations in the used car market.

关键词： Data analysis Social networking (online) Shape Pricing Predictive models Market research Automobiles Fuels Stakeholders Vehicle dynamics

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