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Review of image encryption and compression techniques

AIP Conference Proceedings 2022年第1期2555卷

作者： Mandeep Kaur Sandhu Surender Singh 1Computer Science and Engineering Chandigarh University Gharuan Mohali Punjab India

This paper presents a survey on image encryption and compression techniques. The main aim of using encryption and compression together is to reduce the size; to ensure a quality during reconstruction; to reduce bandwidth requirement, to increase the speed of data communication over a network; to reduce the computational time, and to ensure its safety. To carry out the Image compression and encryption together three different ways are there. The three existing combinations are as encryption technique followed by compression, in this method compression ratio is more, but there are some security issues as compared with next. The next combination is a compression technique followed by encryption technique, in this method, researchers focus more on security of the image rather than to compress the size of the image. The last combination is joint encryption and compression strategies in this strategy encryption and compression happens at the same time either to some extent or as compressive detecting. With low computational time it gives a decent security. The compression procedure utilized in every one of the blends can be lossless, lossy, or mix of both.

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Cloud based system for reservation of medical appointments

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AIP Conference Proceedings 2022年第1期2570卷

作者： Veneta Aleksieva Hristo Valchanov Monika Vangelova 1Computer Science and Engineering Department Technical University of Varna Varna Bulgaria

Easy, fast and effective access to healthcare is one of the main goals of the World Health Organization, especially in a pandemic environment. This paper presents a cloud-based system for booking appointments for clinic examinations and remote consultations. A comparison is made among three different solutions. The experimental results show that the proposed cloud-based solution is the best option in terms of response speed, scalability, easiest administration and cost-effectiveness.

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A review on cloud computing security issues

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AIP Conference Proceedings 2023年第1期2523卷

作者： Rajeswari C. Mahalakshmi S. K. Latha Madhavan K. 1Computer Science and Engineering Chennai Institute of Technology Kundrathur Tamil Nadu India 2Sri Sairam Engineering College Chennai Tamil Nadu India

Cloud computing be a great facility with the purpose of allows the cloud users to develop the possessions situated within the cloud servers with pay-per-use or lay the blame on per-use type all the way through the internet. The cloud users are enjoying the on-demand services provided by the cloud computing background exclusive of maintaining the numbers in a narrow structure. The cloud computing systems are IT services with the intention of being provided to a client above a system on the foundation of data storage. The turn of expression cloud computing originates beginning the diagrams worn to stand for the internet. Cloud computing is a system with so many features and can provide great service. Cloud computing provides different types of service models with some cloud deployed models too. Cloud computing has some issues too which are not friendly for the customers. In this article we will see about definition, function and classification of cloud computing, the general issues and the security issues.

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A review analysis on load balancing as a crust of cloud computing

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AIP Conference Proceedings 2022年第1期2555卷

作者： Surinder Kaur Vishal Bharti Gurpreet Singh 1Computer Science and Engineering Chandigarh University Mohali Punjab India 2Computer Science and Engineering Chitkara University Rajpura Punjab India

Cloud Computing (CC) has gained a tremendous popularity in past few years. The concept of distributed systems in computing network has been reached to a large scale. To implement the cloud environment efficiently, several challenges are to be faced. This paper elaborates the concept of Cloud Computing and throws light on the various challenges in the way of successful implementation of Load Balancing (LB) in cloud computing environment. LB is the major concern in CC environment which imbalances the robustness of the cloud computing system. This paper illustrates the need of load balancing and explores the available techniques of load balancing. The paper also concentrates on the requirement of fault tolerance (FT) in CC and discusses various FT methods. In the last, comparative analysis between present load balancing techniques is represented.

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Comparative analysis of stock market price behaviors using machine learning techniques

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AIP Conference Proceedings 2022年第1期2385卷

作者： Surya Rajeswar Pon Ramalingam T. SudalaiMuthu 1Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India 2School of Management Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India

The stock market price prediction is an increasing concern in dividend yield sectors. The study associates the enactment of learning algorithms includes Levenberg-Marquardt, Linear regression, and K nearest neighbour to predict the performance of timeseries range of 15 minutes dataset. The stock market price behaviours of stock exchange, volatility, collection of investment, and trading volume values were yielded good performance in the various dimension of evaluation. It yielded an accuracy result of 82.58%. The yielded results can help to predict the stock exchange price in Initial Public Offering.

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Stock market prediction analysis by incorporating financial industry using machine learning

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AIP Conference Proceedings 2022年第1期2385卷

Market Limit Trading value analysis is the increasing concern of the stock exchange. This paper presents the ensemble algorithm of Random Forest, Support Vector Machine and Linear Regression has used to analyze the stock price position between the sectors of Finance, and Utilities. The results were compared with Actual data. SVM yielded better performance with mean square error rate of 0.73 using technical indicators of relative strength index, exponential moving average, money flow index, and Stochastic Oscillator.

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Group-wise inhibition based feature regularization for robust classification

arXiv

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arXiv 2021年

作者： Liu, Haozhe Wu, Haoqian Xie, Weicheng Liu, Feng Shen, Linlin 1Computer Vision Institute College of Computer Science and Software Engineering 2SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society 3National Engineering Laboratory for Big Data System Computing Technology 4Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen 518060 China

The convolutional neural network (CNN) is vulnerable to degraded images with even very small variations (e.g. corrupted and adversarial samples). One of the possible reasons is that CNN pays more attention to the most discriminative regions, but ignores the auxiliary features when learning, leading to the lack of feature diversity for final judgment. In our method, we propose to dynamically suppress significant activation values of CNN by group-wise inhibition, but not fixedly or randomly handle them when training. The feature maps with different activation distribution are then processed separately to take the feature independence into account. CNN is finally guided to learn richer discriminative features hierarchically for robust classification according to the proposed regularization. Our method is comprehensively evaluated under multiple settings, including classification against corruptions, adversarial attacks and low data regime. Extensive experimental results show that the proposed method can achieve significant improvements in terms of both robustness and generalization performances, when compared with the state-of-the-art methods. Code is available at https://***/LinusWu/TENET_Training. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Dilated convolutional neural network for WSD

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AIP Conference Proceedings 2022年第1期2670卷

作者： S. Rajini A. Vasuki 1Computer Science and Engineering Kumaraguru College of Technology Coimbatore-641049 India 2Mechatronics Engineering Kumaraguru College of Technology Coimbatore 641049 India

In language processing, the identification of correct sense of word is a difficult one until to date. The reason behind this problem is the contribution of different meanings for a single word. A single word can give multiple meanings based on their expression and the neighboring words. This necessitates research in the field of understanding the correct sense of context. The research process has been started from the golden era to modern days using different approaches like supervised learning, unsupervised and semi-supervised learning. This paper is about the supervised learning approach for the discrimination of sense of words. The approach is based on the training of a type of Convolutional neural network called Dilated Convolutional Neural Network. The practical simulation of the proposed method is implemented using WORDNET. The proposed method produced the good results with an accuracy of 98.1% on SEMEVAL TASK 11.

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Uncovering the differences between the violin and erhu musical instruments by statistical analysis of multiple musical pieces

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Proceedings of Meetings on Acoustics 2022年第1期50卷

作者： Wenyi Song Andrew Brian Horner 1Computer Science and Engineering The Hong Kong University of Science and Technology School of Engineering Hong Kong HONG KONG wsongak@cse.ust.hk horner@cse.ust.hk

The violin and erhu are two of Western and Chinese music’s main bowed string instruments. Recent work has compared the different emotional characteristics between the violin and erhu on the Butterfly Lovers Concerto. In our study, we examine several hypotheses to investigate whether the previous studies’ results hold generally. Four musical excerpts were extracted from four famous Chinese and Western classical pieces, and the excerpts were divided into four emotional categories: Happy, Sad, Agitated, and Calm. Based on the Butterfly Lovers results, we expected that: (1) the violin has a more Happy emotional characteristic than the erhu, while the erhu is comparatively more Sad, and (2) the violin is better at conveying high-Arousal excerpts. We used the Bradley-Terry-Luce (BTL) paired-comparison model to obtain the ranking scores and identify statistically significant differences between the two instruments. The erhu was consistently perceived as sadder than the violin for all Sad excerpts, while the violin was generally calmer and more agitated for those categories. Further study with more listeners and excerpts is needed to verify whether these results generally hold and at a statistically significant level.

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Review analysis of content based image retrieval for plant disease identification using deep learning algorithms

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AIP Conference Proceedings 2022年第1期2555卷

作者： Gaganjot Kaur Meenu Gupta Rakesh Kumar Shakeel Ahmed 1Computer Science and Engineering Department Chandigarh University Mohali Punjab India 2College of Computer Sciences and Information Technology King Faisal University Al-Hassa Saudi Arabia

A large segment of revenue in many developing countries comes from agriculture. But the perennial incline of diseases in crops is much severe issues and seeks attention of researchers during the past few years. Agriculturists are unable to make timely prediction of diseases due to lack of knowledge and large cultivation areas. Presently, Machine learning (ML) and its sub branch Deep learning (DL) brings a sea level change in conventional disease prediction methods and incline accuracy also. Using visualization techniques many DL architectures are implemented for identification and classification of plant diseases. This paper provides a systematic review of various existing DL and ML models for content-based image retrieval for data sets related to agriculture and investigate the future scope which helps to learn the potential of DL along with multiple visualization methods for recognizing plant diseases which is fruitful for farmers. Prediction and analysis of diseases instead of leaves at other parts of plants is not done yet, DL can help to work from this perspective also. The main motive of this study is to prediction of diseases at various parts of plant to overcome the issues in agriculture field to incline the profit of Farmers.

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