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检索条件"机构=dept. of Computer Computer Systems Engineering"

共 66490 条记录，以下是131-140 订阅

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Implementation of Blockchain and IPFS to safeguard evidentiary data

Implementation of Blockchain and IPFS to safeguard evidentia...

引用

2024 International Conference on Knowledge engineering and Communication systems, ICKECS 2024

作者： Srivastava, Supriya Kaur, GeetKiran Himank Singla, Sanjay Chandigarh University Dept. of Computer Science & Engineering Mohali140413 India Chandigarh University Dept. of Computer Science & Engineering Gharuan India

ISBN: (纸本)9798350359688

Nowadays due to increasing cases of evidence alteration the need of a robust evidence protection system is increasing rapidly. This paper presents an innovative solution that combines the InterPlanetary File System (IPFS) with blockchain technology to enhance the security, immutability, and transparency of evidential data obtained from crime *** proposed system initiates by utilizing IPFS, a decentralized and distributed file storage protocol, to securely store multimedia evidence, such as photographs. The content-addressed nature of IPFS guarantees tamper-resistant storage, making it an ideal choice for preserving the integrity of sensitive evidentiary materials. The IPFS addresses obtained from IPFS are then embedded within the blockchain, establishing a decentralized and verifiable link between the evidence and its storage location. We use multi-signature wallet to upload the data on blockchain so that we can make it more secure and monitored about who is uploading evidence state data. To verify links and integrity of evidence usage we set up a system of periodical updates of state of evidence whenever accessed. These updates serve as a mechanism to record the state of the evidence at different points in time, adding an additional layer of reliability and accountability. © 2024 IEEE.

关键词： Blockchain

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A Searchable Encryption Technique for Secure Color Image Retrieval 15

A Searchable Encryption Technique for Secure Color Image Ret...

引用

15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Ahmad, Ijaz Kim, Joongheon Shin, Seokjoo Korea University Dept. of Electrical and Computer Engineering Seoul Korea Republic of Chosun University Dept. of Computer Engineering Gwangju Korea Republic of

ISBN: (纸本)9798350364637

Image retrieval is one of the fundamental tasks in computer vision that involves searching and retrieving relevant images to a query from a large collection of images. It has applications in various domains, including online education, image search engines and disease diagnosis. For image owners, it is often cost-effective to avail third-party owned computation and storage resources such as a cloud paradigm, to facilitate their image retrieval application. However, in addition to the associated privacy risks during transmission, storage and computation;image owners lose control over their data, which is not desirable, especially for privacy sensitive data. Therefore, this work proposes a searchable encryption scheme that protects images in a way that their features can be extracted in the encryption domain to ensure privacy. Also, it allows image owners to encrypt images with their own keys before uploading them to the cloud-server, thus leaving them in control of their data. In addition, we propose a feature fusion technique that combines fuzzy logic and color micro-structures to define an image in a high-dimensional feature space for retrieval application. The simulation analysis shows that for non-secure image retrieval, proposed fusion technique delivered up to 3% better precision score. On the other hand, our proposed searchable encryption method degraded precision up to 2% at best for secure image retrieval applications compared to its non-secure counterpart. © 2024 IEEE.

关键词： Image retrieval

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TOPMG: Trust-Based Crowdsourcing through Multilateral Bargaining Game Theory

TOPMG: Trust-Based Crowdsourcing through Multilateral Bargai...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Charatsaris, Panagiotis Adesokan, Adedamola Rahman, Aisha B Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

Crowdsourcing plays a critical role in modern information gathering and task execution, yet it faces challenges regarding the task selection and equitable monetary incentives distribution. In this paper, we introduce the TOPMG framework, which addresses these challenges by enabling the workers to select tasks based on their historically experienced monetary incentives and the platforms' trustworthiness. Specifically, the TOPMG framework utilizes a reinforcement learning approach based on the principles of Optimistic Q-learning with Upper Confidence Bound (OQ-UCB) algorithm, guiding the platform selection process by considering the workers' monetary incentives, profit, and the platforms' trustworthiness. Also, the proposed framework introduces a multilateral bargaining game to allocate the platforms' monetary incentives to the workers by prioritizing their information contribution, fairness, and the platforms' reputation. Simulation results demonstrate TOPMG's operational dynamics, scalability, and efficacy, as well as its superiority over existing methodologies. © 2024 IEEE.

关键词： Reinforcement learning

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Synergia: Device-Edge Server Association for ISAC-assisted Mobile Edge Computing systems

Synergia: Device-Edge Server Association for ISAC-assisted M...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Charatsaris, Panagiotis Penafiel, Arianna Santamaria Diamanti, Maria Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

The efficient operation of the unified Integrated Sensing and Communication (ISAC) - Mobile Edge Computing (MEC) systems is important for enhancing data sensing, communication, and computation processes in next-generation wireless systems. Despite prior research focusing on these systems, little attention has been given to optimizing the device-edge server associations. This paper addresses this gap by introducing the novel two-stage device-edge server association Synergia framework. Firstly, representative utility functions capture the characteristics of the devices and MEC servers by jointly considering their sensing, communication, and computation characteristics. Secondly, the Estimated Synergia framework leverages the Matching Theory to rapidly determine an initial device-server matching by disregarding the devices' externalities, i.e., the matching decisions of other devices. Thirdly, the Accurate Synergia model refines and improves this matching by using the coalition formation games, while considering the devices' externalities in optimizing the utilities of both the devices and the MEC servers. Extensive numerical evaluations demonstrate the Synergia's operational efficiency and scalability, outperforming reinforcement learningbased approaches. Also, a real-world application involving car accident detection validates its applicability. © 2024 IEEE.

关键词： Mobile edge computing

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Pseudo-Holographic Display of Plant Models based on Pepper's Ghost Illusion 13

Pseudo-Holographic Display of Plant Models based on Pepper's...

引用

Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Umezu, Nobuyuki Iijima, Satoshi Ibaraki University Dept. of Computer and Information Sciences Hitachi Japan Ibaraki University Dept. of Mechanical Systems Engineering Hitachi Japan

ISBN: (纸本)9798350373332

We propose a new display method for visualizing flower models using a pseudo-holographic technique known as the Pepper's ghost illusion. This classic optical illusion technique creates the appearance of floating objects by reflecting them off a transparent panel, thereby producing a convincing visual effect that simulates three-dimensionality. In our approach, we utilized this illusion to display six distinct flower models obtained from a comprehensive photogrammetry archive of various plant species. These models were rendered to overlay onto a transparent glass vase, enhancing the realism of quality. To facilitate user interaction with the displayed models, we incorporated a dept. sensor (Intel D415) to track the user's hand position. A user study revealed that participants were notably attracted to the display, indicating successful capture of their attention. Feedback, however, suggested that the system requires enhancements in usability and dept. perception to improve the overall user experience. Our future work includes addressing these limitations by developing a larger display setup that could accommodate more complex interactions and by integrating motion-parallax techniques to enhance the three-dimensional view. This could be implemented using head-tracking technology, further advancing the effectiveness of the pseudo-holographic display. © 2024 IEEE.

关键词： Holographic displays

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Hybrid Image Encryption for IoT Applications: Integrating Cellular Automata and Henon Map to Improve Security and Performance 4

Hybrid Image Encryption for IoT Applications: Integrating Ce...

引用

4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024

作者： Yogi, Biswarup Khan, Ajoy Kumar Roy, Satyabrata Mizoram University Dept. of Computer Engineering Mizoram Aizawl India Manipal University Dept. of Computer Science and Engineering Rajasthan Jaipur India

ISBN: (纸本)9798350387490

Securing the vast volumes of data exchanged over networks is crucial in IoT (Internet of Things) applications. This study introduces an innovative image encryption algorithm that combines the interactive properties of Cellular Automata (CA) and the Henon map to improve both security and performance. CA, renowned for its simplicity and parallelism, are utilized to produce intricate pseudorandom sequences. These sequences are then used as the keystream for encryption purposes. Whereas, the Henon map is employed to incorporate further levels of unpredictability and intricacy into the encryption procedure. The proposed method is thoroughly assessed through considerable experimentation and is compared with existing methodologies. The findings demonstrate substantial enhancements with respect to various standard metrics such as 'Mean Squared Error (MSE)'., 'Peak Signal-to-Noise Ratio (PSNR)'., 'Unified Average Changing Intensity (UACI)'., and 'Number of Pixels Change Rate (NPCR)' measurements., underscoring the resilience and efficacy of the proposed methodology. The results emphasize the capability of this hybrid method to offer a secure and robust performance for image encryption in IoT applications. This method guarantees the integrity and confidentiality of data while outperforming current encryption techniques in performance. © 2024 IEEE.

关键词： Mean square error

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Passing Practice Support for Soccer Players Using First-Person Videos 13

Passing Practice Support for Soccer Players Using First-Pers...

引用

Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Umezu, Nobuyuki Imada, Yuya Ibaraki University Dept. of Computer and Information Sciences Hitachi Japan Ibaraki University Dept. of Mechanical Systems Engineering Hitachi Japan

ISBN: (纸本)9798350373332

We propose a novel visualization system to enhance soccer passing practice by providing potential pass courses and their scores. The proposed system is based on a first-person video footage captured during soccer play and extracts frames for pass-course suggestions using the rate of ground-surface pixels in the frame and dept. estimation. Possible pass courses were scored according to their direction and distance to the closest player. To validate the proposed method's effectiveness, we conducted a series of experiments involving 17 participants, comprising 12 museum visitors and five university students. The estimated score of visualized pass courses using the proposed method was generally successful, whereas some pass courses received lower scores from participants owing to limitations in the system's ability to accurately detect the color of players' uniforms, which affected the overall evaluation of certain passing options. © 2024 IEEE.

关键词： Visualization

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Interactive Museum Kiosk for Visualizng Visitor Activities 13

Interactive Museum Kiosk for Visualizng Visitor Activities

引用

13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Umezu, Nobuyuki Nishida, Saku Ibaraki University Dept. of Computer and Information Sciences Hitachi Japan Ibaraki University Dept. of Mechanical Systems Engineering Hitachi Japan

ISBN: (纸本)9798350355079

We propose an interactive information kiosk for tracking and visualizing visitor activities in museums. Each visitor is assigned a sheet of paper with one's own QR code and recocnized by presenting the code before interacting with our kiosks and other exhibits. The proposed kiosk has a 32 inch LCD built into a wooden stand and a inexpensive two-dimensional LiDAR sensor mounted at the top to detect visitor interactions of hand gestures towards the display surface. We implemented a four-choice quiz with 40 questions, an personal review of visitor activity, and a museum floor guide which can be scrolled using hand gestures. A server system has been also developed to collect information from kiosks and summarize it. A series of experiments was conducted in a local science museum for two days to evaluate the proposed system to track and visualize visitor activities. Our future work includes improving the system with various sensors and larger-scale experiments with more kiosks with multiple types of content. © 2024 IEEE.

关键词： Liquid crystal displays

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TRUSTCACHE: Trust-based Content Caching in Information-Centric Networks

TRUSTCACHE: Trust-based Content Caching in Information-Centr...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Tsikteris, Sean Rahman, Aisha B. Siraj, Md Sadman Charatsaris, Panagiotis Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

The Information-Centric Networking (ICN) paradigm has reshaped the modern network architectures and promises efficient content delivery to the end-users. This paper introduces TRUSTCACHE, a novel framework enabling the content caching within ICNs and focusing on the trust-based ICN selection and optimal cache memory allocation to the Content Providers (CPs). The TRUSTCACHE framework incorporates the Optimistic Q-learning with Upper Confidence Bound reinforcement learning algorithm that enables the CPs to autonomously select ICNs based on their cache memory availability and trust levels. Also, TRUSTCACHE enables the CPs to jointly consider the reliability of the ICNs and their cache memory availability by integrating a novel trust model. Furthermore, TRUSTCACHE leverages the multilateral bargaining principles in order to ensure the optimal cache memory allocation among the CPs, in terms of aligning with their profit margin characteristics. Simulation-based experiments validate TRUSTCACHE's operational efficiency across diverse CP profit margin profiles and highlight its superiority over alternative models lacking trust-based ICN selection or employing proportional fairness strategies for cache memory allocation. © 2024 IEEE.

关键词： Reinforcement learning

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Automated Identification of Pneumonia Employing Convolution Neural Networks and the VGG-16 Model 1

Automated Identification of Pneumonia Employing Convolution ...

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1st International Conference on Computing, Sciences and Communications, ICCSC 2024

作者： Srivastava, Anamika Gupta, Anuj Kaushik, Deepti Gupta, Neha Chadha, Shikha Chauhan, Rosey Noida Institute Of Engineering Technology Dept. of Computer Science & Engineering Gerater Noida India Sharda Unviersity Dept. of Computer Science & Engineering Gerater Noida India School of Engineering and Technology IIMT University Dept. of Computer Science and Engineering U.P Meerut India ABES Engineering College Dept. of Computer Science UP Ghaziabad India

ISBN: (纸本)9798350353648

Pneumonia, an inflammatory lung disease, impacts the small air sacs known as alveoli and is typically caused by the bacteria Streptococcus pneumonia. Symptoms commonly include a combination of productive or dry cough, chest pains, difficulty breathing, and fever. In India, where Covid-19 is prevalent, community-acquired pneumonia (CAP) poses a significant risk factor for mortality, accounting for one-third of fatalities, as reported by the World Health Organization (WHO).Diagnosing and predicting the outcome of pneumonia typically involves examining chest imaging radiographs of patients exhibiting clinically similar symptoms (e.g., fever, dyspnea, cough, and sputum production). Therefore, the development of an automated method for pneumonia detection could offer valuable advantages, particularly in remote regions, facilitating prompt treatment. Deep learning (DL) models enable the analysis of various chest radiographs, with Convolutional Neural Networks (CNNs) receiving considerable attention in disease classification. Leveraging features learned. © 2024 IEEE.

关键词： Convolutional neural networks

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