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Profile and Rating Similarity Analysis for Recommendation Systems Using Deep Learning

computer Systems science & engineering 2022年第6期41卷 903-917页

作者： Lakshmi Palaniappan K.Selvaraj Department of Computer Science and Engineering Veerammal Engineering CollegeK.SingarakottaiDindigul624708India Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622India

Recommendation systems are going to be an integral part of any E-Business in near *** in any other E-business,recommendation systems also play a key role in the travel business where the user has to be recommended with a restaurant that best suits *** general,the recommendations to a user are made based on similarity that exists between the intended user and the other *** similarity can be calculated either based on the similarity between the user profiles or the similarity between the ratings made by the *** phase of this work concentrates on experimentally analyzing both these models and get a deep insight of these *** the lessons learned from the insights,second phase of the work concentrates on developing a deep learning *** model does not depend on the other user's profile or rating made by *** model is tested with a small restaurant dataset and the model can predict whether a user likes the restaurant or *** model is trained with different users and their *** system learns from it and in order to predict whether a new user likes or not a restaurant that he/she has not visited earlier,all the data the trained model needed is the rating made by the same user for different *** model is deployed in a cloud environment in order to extend it to be more realistic product in *** evaluated with dataset,it achieves 74.6%is accurate prediction of results,where as existing techniques achieves only 64%.

关键词： Deep learning restricted boltzman machine profile based similarity rating based similarity item based similarity

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Big Data and Machine Learning: Barriers and Methods 4

Big Data and Machine Learning: Barriers and Methods

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4th International Conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Agrawal, Monika Goel, Swati William, P. Agwan, Ritesh Bhangale, Sonal C. Ghige, Onkar Kopargaon Sppu Sanjivani College of Engineering Department of Computer Engineering MH Pune India Inderprastha Engineering College Department of Computer Science and Engineering UP Ghaziabad India Kopargaon Sppu Sanjivani College of Engineering Department of Information Technology MH Pune India Kopargaon Sppu Sanjivani College of Engineering Department of Mechatronics MH Pune India Kopargaon Sppu Sanjivani College of Engineering Department of Electrical Engineering MH Pune India

ISBN: (纸本)9798350307757

In this study, the researchers investigate the mutually beneficial relationship that exists between machine learning (ML) and big data, highlighting both the benefits and the challenges that are brought about by the combination of these two domains. Large datasets provide a difficult environment for machine learning (ML) algorithms to extract meaningful insights from, but ML also provides sophisticated tools to assist in navigating through the complexity of these datasets. Even while there is the potential for synergy, their full-fledged adoption is delayed by significant constraints such as the quality of the data, the need for computing, concerns around privacy, and the skills gap. In addition to highlighting recent advancements in algorithmic efficiency, data preparation, and ethical frameworks, this paper investigates the strategic strategies and techniques that are used to address these issues. An in-depth investigation of machine learning models on a variety of datasets is presented, which offers insights into the efficacy of these models and their applicability for instances that occur in the real world, particularly those that involve the pharmaceutical industry. The research sheds light on the ways in which the environment is undergoing transformations and the ways in which practitioners are actively searching for and putting these challenges into practice in order to fully grasp the revolutionary potential of big data and machine learning. © 2024 IEEE.

关键词： Large datasets

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Energy Efficiency Maximization for Cooperative NOMA with Hardware Impairments

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China Communications 2024年第12期21卷 80-91页

作者： Wang Zhengqiang Chang Ruifei Wan Xiaoyu Fan Zifu Duo Bin School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer Science and Cyber Security Chengdu University of TechnologyChengdu 610059China

The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)***,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the *** original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution ***,we use fractional programming to convert the EE maximization problem as a series of subtraction form ***,variable substitution and block coordinate descent(BCD)method are used to handle the ***,a resource allocation algorithm is proposed to maximize the EE of the ***,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.

关键词： block coordinate descent cooperative non-orthogonal multiple access energy efficiency hardware impairments resource allocation

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State-of-the-Art Approach: Boosting IoT Sensor Network Security with Visual Secret Sharing 10

State-of-the-Art Approach: Boosting IoT Sensor Network Secur...

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10th IEEE Smart World Congress, SWC 2024

作者： Ali, Sijjad Wang, Jia Leung, Victor Chung Ming Bhatti, Uzair Aslam Bhatti, Mughair Aslam Shenzhen University College of Computer Science and Software Engineering Guangdong China Hainan University School of Information and Communication Engineering China

ISBN: (纸本)9798331520861

This research paper is based on the issue of protecting the sensor networks in the era of IoT because the data is very sensitive and huge, and is collected in resource-constrained environments. We put forward a new approach to the enhancement of the security of IoT sensor networks by applying VSS on visual data. Our approach is based on the implementation of the VSS approach which implies that no single node will contain full information about the visual input which will be divided among the nodes. Furthermore, this approach also increases the security of the data, and at the same time is appropriate for the IoT environments since it does not require a large amount of computational power and network bandwidth. In addition, we explain how this method can be used, discuss its features, and based on the data from the experiments, prove the effectiveness of the suggested approach. The results of the research show that data security and the ability to counteract attacks can be resist if VSS is used in systems of IoT sensor networks. © 2024 IEEE.

关键词： Information hiding

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A fixed clustering protocol based on random relay strategy for EHWSN

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Digital Communications and Networks 2023年第1期9卷 90-100页

作者： Xianquan Luoa Chunjiong Zhang Longju Bai College of Artificial Intelligence Yango UniversityFujian350015China Department of Computer Science Tongji UniversityShanghai201804China College of Engineering Beijing Forestry UniversityBeijing100191China

In Energy Harvesting Wireless Sensor Networks(EHWSN),the communication protocol will directly affect the final performance of the network,so it is necessary to study the communication protocol based on *** this paper,for the low-cost fixed clustering problem,a fixed clustering protocol RRCEH is based on random *** proposed RRCEH abandons the inefficient inter-cluster communication method of the traditional fixed clustering *** coordinate the data upload of the cluster head,RRCEH allocates different random relay vectors to each ring area of the network,and combines all the random relay vectors into a random relay matrix of *** each communication round,the cluster head node randomly selects its relay target node to send data according to the probability distribution in the random relay vector in the *** two different cluster head configuration scenarios,by optimizing the random relay matrix,RRCEH can effectively reduce the network's configuration requirements for cluster head energy harvesting capability,thus reducing the deployment cost of EHWSN.

关键词： Energy harvesting Wireless sensor networks Clustering protocol Random relay strategy

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Design of Fuzzy Logic Control Framework for QoS Routing in MANET

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Intelligent Automation & Soft Computing 2023年第3期35卷 3479-3499页

作者： M.Vargheese S.Vanithamani D.Stalin David Ganga Rama Koteswara Rao Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia Department of Master of Computer Applications M.Kumarasamy College of EngineeringKarur639113Tamil NaduIndia Department of Information Technology Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062Tamil NaduIndia Department of Computer Science and Information Technology Koneru Lakshmaiah Education FoundationVaddeswaram522502Andhra PradeshIndia

Wireless networks with no infrastructure arise as a result of multiple wireless devices working *** Mobile Ad hoc Network(MANET)is a system for connecting independently located Mobile Nodes(MNs)via wireless links.A MANET is self-conﬁguring in telecommunications,while MN produces non-infrastructure networks that are entirely *** the MAC and routing layers of MANETs take into account issues related to Quality of Service(QoS).When culling a line of optical discernment communication,MANET can be an effective and cost-saving route cull *** maintain QoS,however,more or fewer challenges must be *** paper proposes a Fuzzy Logic Control(FLC)methodology for specifying a probabilistic QoS guaranteed for *** framework uses network node mobility to establish the probabil-istic quality of *** Logic(FL)implementations were added to Network Simulator-3(NS-3)and used with the proposed FLC framework for *** have found that for a given node’s mobility,the path’s bandwidth decreases with time,hop count,and *** is resolutely based on this fuzzy rule that the priority index for a packet is ***,by avoiding sending pack-ets(PKT)out of source networks when there are no beneﬁcial routes,bandwidth is not *** FLC outperforms the scheduling methods with a wide range of *** improve QoS within MANETs,it is therefore recommended that FLC is used to synchronize ***,using these performance metrics,the QoS-responsible routing can opt for more stable *** on network simulation,it is evident that incorporating QoS into routing protocols is meant to improve traf-ﬁc performance,in particular authentic-time trafﬁc.

关键词： MANET quality of service fuzzy logic mobile node network trafﬁc

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Exploit Reversible Gates to Implement Fast Quantum Sorting Algorithm 1

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5th International Conference on computer and Communication Technologies, IC3T 2023

作者： Bhattacharjee, Subhasree Das, Kunal Sadhu, Arindam Sarkar, Soumyadip Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology West Bengal Kolkata India Department of Computer Science Acharya Prafulla Chandra College West Bengal Kolkata India Department of Electronics and Communication Engineering Greater Kolkata College of Engineering and Management West Bengal Kolkata India Department of Computer Science and Engineering JIS College of Engineering West Bengal Kalyani India

ISBN: (数字)9789819997046

ISBN: (纸本)9789819997039

This paper proposes an algorithm of divide-compare-swap-based (DCS) sorting that reduces time complexity by utilizing quantum parallelism. A new cost optimized comparator circuit has been designed and simulated using qiskit for comparing two quantum numbers. The sorting process consists of divide, compare-swap and merge. The set of n quantum numbers are divided equally into two sub arrays followed by comparing-swapping of two middle elements. This process continues in two sub arrays till array with single element is found. The sorting circuit performs well in qiskit with time complexity n, which has a significant improvement over existing quantum sorting technique. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： computer circuits

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THE INFLUENCE OF COVID-19 ON EMPLOYEES’ USE OF ORGANIZATIONAL INFORMATION SYSTEMS

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Interdisciplinary Journal of Information, Knowledge, and Management 2023年 18卷 353-368页

作者： Nakash, Maayan Bouhnik, Dan Department of Information Science Bar-Ilan University Ramat Gan Israel Department of Computer Science and Engineering Jerusalem College of Technology Jerusalem Israel

Aim/Purpose COVID-19 was an unprecedented disruptive event that accelerated the shift to remote work and encouraged widespread adoption of digital tools in organizations. This empirical study was conducted from an organizational-strategic perspective, with the aim of examining how the COVID-19 pandemic outbreak affected employees’ use of organizational information systems (IS) as reflected in frequency. Background To date, only a limited effort has been made, and a rather narrow perspective has been adopted, regarding the consequences of the adoption of new work environments following COVID-19. It seems that the literature is lacking in information regarding employee use of organizational IS since the outbreak of the pandemic. Specifically, this issue has not yet been examined in relation to employees’ perception about the organization’s digital efforts and technological maturity for remote work. The present study bridges this gap. Methodology The public sector in Israel, which employs about a third of the Israeli workforce, was chosen as a case study of information-intensive organizations. During the first year of COVID-19, 716 questionnaires were completed by employees and managers belonging to four government ministries operating in Israel. The responses were statistically analyzed using a Chi-Square and Spearman’s Rho tests. Contribution Given that the global pandemic is an ongoing phenomenon and not a passing episode, the findings provide important theoretical and practical contributions. The period prior to the COVID-19 pandemic and the period of the pandemic are compared with regard to organizational IS use. Specifically, the study sheds new light on the fact that employee perceptions motivated increased IS use during an emergency. The results contribute to the developing body of empirical knowledge in the IS field in the era of digital transformation (DT). Findings More than half of the respondents who reported that they did not use IS before COVID-19 stated

关键词： COVID-19

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Smart Agriculture: Explainable Deep Learning Approach with Gradient-Weighted Class Activation Mapping

Smart Agriculture: Explainable Deep Learning Approach with G...

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2024 International Conference on computer, Electronics, Electrical engineering and their Applications, IC2E3 2024

作者： Shaik, Mohammad Khaja Prasad, Mudarakola Lakshmi Sowmya Reddy, Y. Asif, S. Kalpana, D. Reddy, Pundru Chandra Shaker Electronics and Communication Engineering St. Ann's College of Engineering and Technology Andhra Pradesh Chirala India Computer Science and Engineering Institute of Aeronautical Engineering Telangana Dundigal India CVR College of Engineering Hyderabad India Computer Science and Engineering Koneru Lakshmaiah Education Foundation Bowrampet Telangana Hyderabad India Telangana Hyderabad India School of Computer Science and Artificial Intelligence SR University Telangana Warangal India

ISBN: (纸本)9798350388534

In light of the pressing need to guarantee food security in the face of threats posed by climate change, an increasing global population together with rising incomes, worsening soil erosion, and dwindling water resources, crop yield forecasting has assumed more significance in recent years. A relatively new area of study, 'Explainable AI' seeks to provide context for the findings produced by Deep learning models. Nevertheless, there is a pressing need for more comprehensive evaluations of deep learning models for object classification in images. Due to this, the research suggests two steps for implementing Explainable AI: (1) assessing the deep-learning(DL)-strategies accuracy utilizing evaluation methods, and (2) evaluating the feature recognition skill of an scan when recognized by DL utilizing Grad-CAM for model construal. Compared to EfficientNetV2S and Xception, the results reveal that MobieNet model has lower dependability but higher accuracy. When taking the ratio match rate into account, though, MobileNetV2 achieves the best accuracy. Building intelligent agriculture support systems (with the help of automated fruit-picking robots that discard bad fruits) is one application of the study's findings. Another is the utilization of the Explainable AI model's output to determine the best deep learning model for processing. © 2024 IEEE.

关键词： Deep reinforcement learning

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Efficient Authentication System Using Wavelet Embeddings of Otoacoustic Emission Signals

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computer Systems science & engineering 2023年第5期45卷 1851-1867页

作者： V.Harshini T.Dhanwin A.Shahina N.Safiyyah A.Nayeemulla Khan Department of Information Technology Sri Sivasubramaniya Nadar College of EngineeringChennai603110India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India

Biometrics,which has become integrated with our daily lives,could fall prey to falsification attacks,leading to security *** our paper,we use Transient Evoked Otoacoustic Emissions(TEOAE)that are generated by the human cochlea in response to an external sound stimulus,as a biometric *** are robust to falsification attacks,as the uniqueness of an individual’s inner ear cannot be *** this study,we use both the raw 1D TEOAE signals,as well as the 2D time-frequency representation of the signal using Continuous Wavelet Transform(CWT).We use 1D and 2D Convolutional Neural Networks(CNN)for the former and latter,respectively,to derive the feature *** corresponding lower-dimensional feature maps are obtained using principal component analysis,which is then used as features to build classifiers using machine learning techniques for the task of person identification.T-SNE plots of these feature maps show that they discriminate well among the *** the various architectures explored,we achieve a best-performing accuracy of 98.95%and 100%using the feature maps of the 1D-CNN and 2D-CNN,respectively,with the latter performance being an improvement over all the earlier *** performance makes the TEOAE based person identification systems deployable in real-world situations,along with the added advantage of robustness to falsification attacks.

关键词： Person identification system cochlea:transient evoked otoacoustic emission wavelet transform convolutional neural network

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