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Data Security Enhancement in Cloud Computing by Proposing a DKE Encryption Protocol

Data Security Enhancement in Cloud Computing by Proposing a ...

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2023 International Conference on Advances in Artificial Intelligence and Applications, AAIA 2023

作者： Ebadinezhad, Sahar Abdulmajed, Halmat Ayub Department of Computer Information Systems Near East University Nicosia Cyprus Near East University Nicosia Cyprus Dept. Engineering and Computer Systems Lebanese French University Erbil Iraq

ISBN: (纸本)9798400708268

This study uses cryptography to tackle the important problem of data security in cloud computing. Two keys are used in the Dual Key Encryption (DKE) method for both encryption and decryption. DKE employs a public key for the first encryption round before cloud upload and a user-only private key for the second round of encryption. Decryption operates oppositely. When tested and simulated with different file sizes on a CloudAnalyst simulator, DKE operates faster and more efficiently than cryptographic methods such as Triple DES (3DES), AES, RSA, and DES. Thanks to developments in information technology, cloud computing has made several services available online. Data security assurance is still very difficult to achieve, nevertheless. In this context, cryptography is essential and has led to the creation of the novel DKE technology. This technology is not only far more efficient than well-known cryptographic techniques such as 3DES, but it also improves data security. © 2023 Copyright held by the owner/author(s).

关键词： Cryptography

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POCS-based Image Compression: An Empirical Examination 7

POCS-based Image Compression: An Empirical Examination

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7th International Conference on Green Technology and Sustainable Development, GTSD 2024

作者： Do, Truong-Dong Tran, Le-Anh Nguyen, Thanh-Dat Truong, Nghe-Nhan Park, Dong-Chul Le, My-Ha Sejong University Dept. of Aerospace Systems Engineering Seoul Korea Republic of Myongji University Dept. of Electronics Engineering Yongin Korea Republic of Dept. of Research and Development Ocst Co. Ltd. Seoul Korea Republic of Sejong University Dept. of Computer Science & Engineering Seoul Korea Republic of Hcmc University of Technology & Education Dept. of Electrical & Electronics Engineering Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350386073

This paper investigates the applicability of the Pro-jection onto Convex Set (POCS)-based clustering algorithm to image compression tasks. The POCS-based clustering approach treats all data points in a given dataset as non-intersecting convex sets and performs POCS-based parallel projections from each cluster prototype onto corresponding member data points to minimize an objective function and update cluster prototypes. The POCS-based clustering algorithm has been proven to be able to yield promising results against other prevailing clustering approaches in terms of convergence time and clustering error on general clustering tasks. In this study, a comparison of various clustering schemes for image compression applications has been conducted. The evaluations and analyses on various standard test images verify that the POCS-based clustering algorithm can perform competitively against other conventional clustering methods in image compression problems. © 2024 IEEE.

关键词： Unsupervised learning

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Scalability in Autoencoder-based OFDM Communication System 2

Scalability in Autoencoder-based OFDM Communication System

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2nd IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2023

作者： Tsugawa, Seizan Toma, Takao Oshiro, Shiho Wada, Tomohisa University of the Ryukyus Computer Science and Intelligent Systems Program Okinawa Japan Magna Design Net Inc Okinawa Japan University of the Ryukyus Information Technology Center Okinawa Japan University of the Ryukyus Area of Computer Science and Intelligent Systems Dept. of Engineering Okinawa Japan

ISBN: (纸本)9798350305142

This paper proposed Scalability in Autoencoder-based Orthogonal Frequency Division Multiplexing(OFDM) communication system. In the previous research, only the comparison between IEEE802.11a and Autoencoder by the conventional OFDM communication system was performed, and it was proved that the communication system created by Autoencoder exceeded the performance of the conventional system. Therefore, in this paper, it uses IEEE802.11n and compare whether it can be improved by expanding the bandwidth and using ***802.11n standard has an FFT length of 128, a subcarrier number of 114 (108 for data), and modulation schemes of Quadrature Phase Shift Keying(QPSK), 16 Quadrature Amplitude Modulation (16QAM). The GI length is 800ns and the symbol length is 4000ns. In the simulation, a computer simulation was performed using a conventional OFDM communication system and a communication system generated by Autoencoder. Assuming that the simulation environment had an Signal-to-Noise Ratio (SNR) of 0 to 30 and an amplitude r of 0.0 to 1.0, the Symbol Error Rate (SER) status for each SNR was output. As a result of computer simulation, QPSK converged at SNR 27 at IEEE 802.11a, but was able to reduce SER overwhelmingly to SNR 12 at IEEE 802.11n. Also, in 16QAM the convergence at r=0.0 is the same as for SNR22 , but in IEEE 802.11a it does not converge after r=0.6, but in IEEE 802.11n it does not converge only at r=0.9 and r=1.0. As a future task, it will use IEEE802.11ac, which enables communication speeds several times faster than IEEE802.11n, examine whether it is possible to further improve accuracy. And it will continue our research to correspond MIMO communication. © 2023 IEEE.

关键词： Orthogonal frequency division multiplexing

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Intelligent Constellation Generation based on Autoencoder Communication System 2

Intelligent Constellation Generation based on Autoencoder Co...

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2nd IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2023

作者： Matsumoto, Kaisei Toma, Takao Oshiro, Shiho Wada, Tomohisa Computer Science and Intelligent Systems Program University of the Ryukyus Okinawa Japan Magna Design Net Inc Okinawa Japan Information Technology Center University of the Ryukyus Okinawa Japan Area of Computer Science and Intelligent Systems University of the Ryukyus Dept. of Engineering Okinawa Japan

ISBN: (纸本)9798350305142

This paper discusses intelligent constellation generation based on autoencoder communication system. In previous studies, the amplitude was set to fluctuate between r=0.0 and 1.0. However, when checking the generated constellation, distortion was confirmed instead of the conventional symbol arrangement. Therefore, in this paper, it compares the case where the amplitude is constant, the case where the average amplitude within a Minibatch is 1, and the case where the average amplitude is 1 for Interval time. The communication standard used in this research is IEEE 802.11a, assuming wireless Local Area Network (LAN) specifications. The IEEE 802.11a standard has an Fast Fourier Transform (FFT) length of 64, a subcarrier number of 52, and Quadrature Phase Shift Keying (QPSK) and 16 Quadrature Amplitude Modulation (QAM), modulation methods. A guard interval of 800 ns is added and the symbol length is 4000 ns. First, a simulation was performed under the condition that the amplitude was kept constant. QPSK with 4 symbols, constant amplitude model is rounded more than previous research result. 16QAM with 16 symbols is arranged regularly like lined up on a line. Second, the simulation was performed under the condition that the average amplitude within the minibatch was set to 1. QPSK with 4 symbols, appears to rotate clockwise. 16QAM with 16 symbols has a more uniform symbol placement than previous research result. Third, a simulation was performed under the condition that the average amplitude within Interval time was set to 1. QPSK with 4 symbols, is the closest to square among QPSK output results so far. The direction is slightly tilted, but if it can be rotated a little more, it may be possible to reproduce the same symbol arrangement as before. 16QAM with 16 symbols, the symbol arrangement is biased as a whole. However, it can be seen that are arranged in line on the line, perhaps due to regularity. As future work, in addition to the conditions set this time, it will exa

关键词： Quadrature phase shift keying

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Stratification of metastatic melanoma patients based on mutational signatures

Stratification of metastatic melanoma patients based on muta...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Alfano, Caterina Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome Program in Network Oncology and Precision Medicine Dept. of Computer Control and Management Engineering Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Genetic instability is one of the hallmarks of cancer, however mutations can occur for different causes and induce different effects. Mutational signatures are characteristic patterns of somatic mutations in cancer genomes, reflecting the underlying mutational processes. A mutational signature can be determined by studying the kind of mutations a patient has acquired during their life: patient stratification based on mutational signatures has become more and more useful in genomic studies, given its possible clinical implications. In this work we focused on Single Base Substitution (SBS) signatures to study a cohort of 115 metastatic melanoma patients. We inferred and identified two mutational signatures characterizing the patients. Based on these signatures we divided patients into two group: the bigger group was characterized by a signature associated with exposure to ultraviolet light, while the smaller group resulted to be mostly composed of patients which did not respond to immunotherapy (anti-PD1) and that presented a low mutational count. More importantly this second group showed a significantly worse survival outcome. The use of mutational signatures is clearly a powerful tool to identify disease sub-types that have a clinical relevance, however we believe that this topic needs further investigation focused on the characterization of patient subtypes with a multi-omics based approach. © 2023 IEEE.

关键词： computational medicine genomics metastatic melanoma mutational signatures patient stratification precision oncology

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Enhancing Public Engagement in Sustainable systems through Augmented Reality 41

Enhancing Public Engagement in Sustainable Systems through A...

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41st International Symposium on Automation and Robotics in Construction, ISARC 2024

作者： Lee, Yu-Chen Alsuhaibani, Abdullah Cheng, Chih-Shen Leite, Fernanda Sustainable Systems Program Maseeh Dept. of Civil Architectural and Environmental Engineering The University of Texas at Austin AustinTX United States Civil Engineering and Project Management Program Maseeh Dept. of Civil Architectural and Environmental Engineering The University of Texas at Austin AustinTX United States Civil Engineering and Project Management Program Maseeh Dept. of Civil Architectural and Environmental Engineering The University of Texas at Austin AustinTX United States Dean for Research Cockrell School of Engineering Joe J. King Professor in the Maseeh Dept. of Civil Architectural and Environmental Engineering The University of Texas at Austin AustinTX United States

ISBN: (纸本)9780645832211

The sustainability of building infrastructure has been a growing critical global concern. However, stakeholders often overlook the sustainability aspect of systems in their everyday lives. This paper presents an exploration of the potential of augmented reality (AR) technology as a tool for enhancing public engagement around sustainable systems in buildings. We introduce an innovative approach to address the challenge of gap between sustainable infrastructure and user awareness. Through data collection such as access counts, usage duration, and user feedback, we can evaluate the effectiveness of AR applications in improving awareness and engagement in sustainability. This study illustrates how AR technology can facilitate a deeper connection between the public and sustainable systems, thus paving the way for a more environmentally friendly society. © 2024 ISARC. All Rights Reserved.

关键词： Sustainable development

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Optimizing Mobility IoT Device Networks with Dynamic RIS in mMIMO-Cooperative NOMA 6G systems 1

Optimizing Mobility IoT Device Networks with Dynamic RIS in ...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Hassan, Khalil Hassan, Mohamed Hamid, Khalid Hassan, Elmuntaser Mokhtar, Rania A. Saeed, Mamoon M. Dept. of Comm. Systems Uni. of Science & Technology Omdurman Sudan Dept. of Electrical Eng. Omdurman Islamic Uni. Omdurman Sudan Dept. of Computer Science Al-Neelain University Khartoum Sudan Department of Computer Engineering Taif University Taif Saudi Arabia Yemen

ISBN: (纸本)9798331533557

Advanced technologies like reconfigurable intelligent surfaces (RISs), massive multiple-input multiple-output (mMIMO), and non-orthogonal multiple access (NOMA) are crucial for the upcoming 6G communications landscape, particularly for IoT applications. This study uniquely explores the effects of RIS dynamics on the performance of mMIMO downlink (DL) cooperative NOMA systems in dense IoT environments. It introduces a novel methodology for modeling dynamic traffic distribution and integrating RIS, focusing on key performance metrics such as network capacity, spectral efficiency (SE), latency, and energy efficiency (EE). Various scenarios are evaluated, considering different distributions of IoT devices and signal-to-noise ratios (SNRs). Using simulation software, the research analyzes performance under unstable channel conditions with varying device distances, speeds, and power locations, employing 256-QAM modulation and successive interference cancellation (SIC). The results demonstrate that dynamic RIS significantly enhances capacity, spectrum efficiency, latency, and EE, paving the way for optimized IoT network architecture in future wireless systems. © 2024 IEEE.

关键词： Quadrature amplitude modulation

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Analysis and optimization of clinical pathways using timed continuous Petri nets. 28

Analysis and optimization of clinical pathways using timed c...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Arzola, César Mahulea, Cristian Júlvez, Jorge Universidad de Zaragoza Dept. of Computer Science and Systems Engineering Spain Universidad de Zaragoza Aragón Institute for Engineering Research Spain

ISBN: (纸本)9798350339918

This paper presents a novel approach to analyze and optimize healthcare systems based on clinical pathways, using timed continuous Petri nets (TCPNs) under infinite server semantics. TCPNs allow for an efficient continuous-time analysis of the patient flow and resource utilization dynamics of these types of systems. We demonstrate the feasibility and effectiveness of our method through a case study of a hip fracture pathway at the "Lozano Blesa"University Clinical Hospital, in Zaragoza Spain. Additionally, we propose a method to optimize the behavior of the modeled system by taking a control theory approach, which enables the system to achieve maximum throughput more efficiently. Finally, we provide simulation results to demonstrate the effectiveness of the proposed controller in practical settings. © 2023 IEEE.

关键词： Nonlinear analysis

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Estimation of Soil Moisture with Meteorological Variables in Supervised Machine Learning Models 3

Estimation of Soil Moisture with Meteorological Variables in...

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3rd International Conference on Electrical, computer and Communication engineering, ECCE 2023

作者： Hussain, Mariam Sharmin, Nusrat Shafiul, Sumayea Binte Ewha Womans University Dept. of Climate and Energy Systems Engineering Seoul Korea Republic of University of Science and Technology Dept. of Computer Science and Engineering Chittagong Bangladesh Bangladesh University of Health Sciences Dept. of Epidemiology Dhaka Bangladesh

ISBN: (纸本)9798350345360

Water cycles, climate-related hazards, and agroirrigation are strongly controlled by soil moisture (SM) content. For water resource management, prediction is a key to mitigate and regulate expected economic losses and property damages. This paper compares two supervised machine learning (ML) techniques: support vector regression (SVR) and random forest (RF) to predict SM. In RStudio, various meteorological variables: temperature, relative humidity, wind speed, and rainfall are trained to estimate SM. For eight divisions, SM and weather variables are obtained from the National Aeronautics and Space Administration (NASA) Prediction of Worldwide Energy Resources (POWER). The experiments include daily observations for 39 (1982 to 2020) to develop SVR and RF models. To estimate SM from the predictive model, datasets from diverse regions: Rajshahi, Mymensingh, Chittagong, and Sylhet are utilized in training (60%) and Rangpur, Barisal, Khulna, and Dhaka are segregated for validation (40%) resulting in accuracy of 88 to 95.8%. This model further is applied to forecast daily SM for each city including two districts (Bogra and Jessore) and found slightly higher model performance for SVR (90.7%) than RF (90.1%) on average (Year: 2021). For agricultural, industrial and urban water supplies as well as drought, landslides, and river erosions can be mitigated by an accurate estimation of soil moisture. The investigations encourage for providing SM budget to public with supervised ML techniques mostly among data-sparse regions. © 2023 IEEE.

关键词： Soil moisture

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Power and Rate Allocation for Energy-Efficient Rate-Splitting Multiple Access via Deep Q-Learning

Power and Rate Allocation for Energy-Efficient Rate-Splittin...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

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

ISBN: (纸本)9798350370218

Rate-Splitting Multiple Access (RSMA) has recently emerged as an effective technique for increasing network capacity by smartly controlling the tradeoff between decoding and treating interference as noise. In this paper, aligned with the need for sustainable wireless networks, we study the energy-efficient power and rate allocation of the common and private messages in the downlink of a network where rate-splitting is adopted. The corresponding energy efficiency maximization problem is transformed into a multi-agent Deep Reinforcement Learning (DRL) problem, based on which each private stream transmitted in the downlink constitutes a different DRL agent. The formulated DRL problem is solved by using Deep Q-Learning (DQL) algorithm and training a single Deep Q-Network (DQN) from the cumulative experiences gained from the DRL agents and their exploration of the environment, i.e., the exploration of different private-message power allocations. Numerical results obtained via modeling and simulation verify the effectiveness of the proposed DQL algorithm, demonstrating that it concludes solutions that outperform existing approaches from the literature in the achieved energy efficiency. © 2023 IEEE.

关键词： Deep Reinforcement Learning (DRL) Energy Efficiency Maximization Rate-Splitting Multiple Access (RSMA)

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