Reviewerly/exHarmony huggingface dataset:
Emotion Analysis for Opinion Mining From Text

In the past few years, web documents, blogs, and reviews have played an important role in many fields as organizations always aim to find consumer or public opinions about their products and services. On the other hand, individual consumers also seek the opinions or emotions of existing users of a certain product before purchasing it. This method is currently one of the most vital methods for adapting the organizations' plans. In this article, the authors provide a survey for different techniques and approaches for emotion analysis from the text. They also demonstrate the techniques and the methods that have been proposed by different researchers with criticizing many of these methods according to the applied approach and the accuracy level.
Exploring New Handwriting Parameters for Writer Identification

The automatic processing of handwriting samples is part of the computational biometric. It applies qualitative and quantitative techniques by means of capturing, visualizing, and analyzing handwriting. The main applications are writer identification and text understanding. Two significantly different situations appear: online and offline data capturing. In the former, the samples are obtained in a dedicated framework, where the writing instrument and the surface have several sensors. In the latter, the unique information available comes from the residues left on paper. This chapter deals with the second situation. Width, grey value, direction, and other parameters of the residual manuscript text are influenced by the psychomotor characteristics of the writer. Some of these personal parameters may be estimated from the observable properties of the written text.
Byzantine Fault-Tolerant Architecture in Cloud Data Management

One of the main challenges in cloud computing is to build a healthy and efficient storage for securely managing and preserving data. This means a cloud service provider needs to make sure that its clients' outsourced data are stored securely and, data queries and retrievals are executed correctly and privately. On the other hand, it may also mean businesses are willing to outsource their data to a third party only if they trust their data are not accessible and visible to the service provider and other non-authorized parties. However, one of the major obstacles faced here for ensuring data reliability and security is Byzantine faults. While Byzantine fault tolerance (BFT) has received growing attention from the academic research community, the research done is generally from the distributed computing point of view, and hence finds little practical use in cloud computing. To that end, the focus of this paper is to discuss how these faults can be tolerated with the authors' proposed conceptualization of Byzantine data faults and fault-tolerant architecture in cloud data management.
Deterrence in Cyberspace: An Interdisciplinary Review of the Empirical Literature

The popularity of the deterrence perspective across multiple scientific disciplines has sparked a lively debate regarding its relevance in influencing both offenders and targets in cyberspace. Unfortunately, due to the invisible borders between academic disciplines, most of the published literature on deterrence in cyberspace is confined within unique scientific disciplines. This chapter therefore provides an interdisciplinary review of the issue of deterrence in cyberspace. It begins with a short overview of the deterrence perspective, presenting the ongoing debates concerning the relevance of deterrence pillars in influencing cybercriminals’ and cyberattackers’ operations in cyberspace. It then reviews the existing scientific evidence assessing various aspects of deterrence in the context of several disciplines: criminology, law, information systems, and political science. This chapter ends with a few policy implications and proposed directions for future interdisciplinary academic research.
On the Effectiveness of Hybrid Canopy With Hoeffding Adaptive Naive Bayes Trees

The Big Data, due to its complicated and diverse nature, poses a lot of challenges for extracting meaningful observations. This sought smart and efficient algorithms that can deal with computational complexity along with memory constraints out of their iterative behavior. This issue may be solved by using parallel computing techniques, where a single machine or a multiple machine can perform the work simultaneously, dividing the problem into sub problems and assigning some private memory to each sub problems. Clustering analysis are found to be useful in handling such a huge data in the recent past. Even though, there are many investigations in Big data analysis are on, still, to solve this issue, Canopy and K-Means++ clustering are used for processing the large-scale data in shorter amount of time with no memory constraints. In order to find the suitability of the approach, several data sets are considered ranging from small to very large ones having diverse filed of applications. The experimental results opine that the proposed approach is fast and accurate.
Cooperative Observation Oriented UAVs Tracking Model in Uncertain Environment

Target tracking is one of the crucial technologies in UAV applications, which has been extensively interested and researched in recent years. To solve the issue that the UAV is susceptible to be disturbed by complex environment when tracking a moving target, resulting in low tracking accuracy. This paper proposes a novel approach of cooperative tracking model based on UAVs in the uncertain environment. Specifically, considering that multiple UAVs are affected by various interferences such as obstacles and motion angles during the tracking process, the tracking rate of individual UAV is introduced to design corresponding cooperative rules. Furthermore, we establish a multi-UAV cooperative model with moving displacement as the objective function, and dynamically adjust the observation position of each UAV relative to the target according to different rules to improve the tracking accuracy. Simulation results show that our model has superior tracking accuracy and cooperative efficiency.
Secure Mobile Multi Cloud Architecture for Authentication and Data Storage

The use of Cloud Computing in the mobile networks offer more advantages and possibilities to the mobile users such as storing, downloading and making calculation on data on demand and its offer more resources to these users such as the storage resources and calculation power. So, Mobile Cloud Computing allows users to fully utilize mobile technologies to store, to download, share and retrieve their personal data anywhere and anytime. As many recent researches show, the main problem of fully expansion and use of mobile cloud computing is security, and it's because the increasing flows and data circulation through internet that many security problems emerged and sparked the interest of the attackers. To face all this security problems, we propose in this paper an authentication and confidentiality scheme based on homomorphic encryption, and also a recovery mechanism to secure access for mobile users to the remote multi cloud servers. We also provide an implementation of our framework to demonstrate its robustness and efficiently, and a security analysis.
The Online Reviews' Effects on Internet Consumer Behavior

Consumer behaviors have always been the hot spot of the study. With the arrival of the network age and the popularity of e-commerce, the consumption pattern of shopping online is beginning. Until December of 2014, there were 649 million Internet users in China, and it's increasing. In the year of 2014, the number of most mainstream online shoppers has increased by 23.7% and shopping online has become an irresistible trend. New consumption mode can produce a new research subject, the study of Internet consumer behaviors becomes very important. This article used LocoySpider, a data mining software, to mine Taobao online reviews. Through the analysis of online reviews, we can study the effect of online reviews on consumer behaviors. During the study, we set the risk perception as intermediary variable. By the study, we can help the electronic commercial enterprises to attract customers, retain customers and reduce the information search cost.
Neural Networks Development Using the Java Encog Framework

To learn how to do network program development using Java, we will develop our first simple program using the function initially shown in the “Example: Manual Approximation of a Function at a Single Point” section of Chapter 3 .
DP-gSpan: A Pattern Growth-based Differentially Private Frequent Subgraph Mining Algorithm

Frequent subgraph mining has been one of the researches focuses in the field of data mining, which plays an important role in understanding social interaction mechanisms, urban planning, and studying the spread of diseases in social networks. Frequent subgraph mining provides a lot of valuable information. However, mining and publishing frequent subgraphs brings more and more risks of privacy leakage. In order to solve the problem of privacy leakage, the combination of frequent subgraph mining based on Apriori and differential privacy has become the mainstream method. Nevertheless, most of the existing research studies suffer from too large candidate subgraph sets, low accuracy, and low efficiency. Therefore, we propose a more secure and effective depth-first search algorithm for frequent subgraph mining under differential privacy, which is referred to as DP-gSpan. We design a heuristic truncation strategy and a new privacy budget allocation strategy to realize the reduction of the candidate set size and the rational allocation of the privacy budget. Through privacy analysis, we prove that DP-gSpan satisfies <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\varepsilon$</tex> -differential privacy. Experimental results over a large number of real-world datasets prove that the performance of the proposed mechanism is better.
New Tools for Cyber Security Using Blockchain Technology and Avatar-Based Management Technique

The chapter introduces the perspectives on the use of avatar-based management techniques for designing new tools to improve blockchain as technology for cyber security issues. The purpose of this chapter was to develop an avatar-based closed model with strong empirical grounding that provides a uniform platform to address issues in different areas of digital economy and creating new tools to improve blockchain technology using the intelligent visualization techniques. The authors show the essence, dignity, current state, and development prospects of avatar-based management using blockchain technology for improving implementation of economic solutions in the digital economy of Russia.
Flexible Clustering

Flexibility of cluster analysis is sometimes understood as the robustness of final partition of objects to the changes in the list of diagnostic variables—deleting some from the list or adding some. In this paper, we propose a procedure which makes possible to calculate a distance matrix on the basis of different subsets of variables, but the selection of variables is somehow unified. The procedure starts with the classical standardization of each variable. Before the calculation of a distance between two objects, we eliminate the variables with the largest absolute value in the first object and in the second object. If by chance the same variable is pointed for elimination for both objects, the next variable with the largest absolute value (for both objects) should be eliminated. With this procedure, each element of the distance matrix is based on the same number of variables, but the variables can be different. As an example, a data set of 17 variables describing human smart society characteristics for 28 European Union countries is used.
An Improved Task Scheduling Mechanism Using Multi-Criteria Decision Making in Cloud Computing

In this work, the authors propose Multi-criteria Decision-making to schedule deadline based tasks in cloud computing. The existing backfilling task scheduling algorithm could not handle similar tasks for scheduling. In backfilling algorithm, tasks are backfilled to provide ideal resources to schedule other deadline sensitive tasks. However, the task to be backfilled is selected on first come, first serve (FCFS) basis from scheduling queue. The scheduling performances require to be improved when, there are similar tasks. In this proposed work, the authors propose to implement MCDM technique, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to improve the performance of the backfilling algorithm through scheduling deadline sensitive tasks in cloud computing. It resolves the conflicts among the similar tasks that is used as a decision support system. The work is simulated with synthetic data sets based on slack values of the tasks. The performance results affirm the task completion and reduction in task rejection compared to the existing backfilling algorithm.
Optimization Design of Mining Device Based on Soybean Worm Harvester

research-article Optimization Design of Mining Device Based on Soybean Worm Harvester Share on Authors: Guangteng Zhang Shandong Agricultural and Engineering University, China Shandong Agricultural and Engineering University, ChinaSearch about this author , Xiangyang Mu Shandong Agricultural and Engineering University, China Shandong Agricultural and Engineering University, ChinaSearch about this author , Qing Chang Shandong Agricultural and Engineering University, China Shandong Agricultural and Engineering University, ChinaSearch about this author , Shengwei Zhu Shandong Agricultural and Engineering University, China Shandong Agricultural and Engineering University, ChinaSearch about this author , Haozheng Sun Shandong Agricultural and Engineering University, China Shandong Agricultural and Engineering University, ChinaSearch about this author , Xiaoyu Zhuo Shandong Agricultural and Engineering University, China Shandong Agricultural and Engineering University, ChinaSearch about this author Authors Info & Claims AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced ManufactureOctober 2021 Pages 2659–2663https://doi.org/10.1145/3495018.3501159Online:14 March 2022Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Experiments with the Cryptool Software

Researchers have developed many different types of software for implementing Cryptography algorithms. One such software is Cryptool. This software can be used to demonstrate many Classical Cryptosystems and symmetric-Key Cryptosystems like DES and AES. This software can be used to demonstrate Public Key Cryptosystems like RSA and ECC as well as many hash algorithms like MD5, SHA-1, SHA-256, and SHA-512. The usage of the algorithms and sample input and outputs obtained from the software are included for the beginners and learners to the area of Cryptography.
Challenges of Off-Site Library Storage Facilities: Cataloging, Access and Management of Off-Site Serials

SUMMARY. This session presented several case studies of libraries facing challenges following a decision to move materials to an off-site storage facility. The presenters described the entire process of moving materials to an off-site location: from planning and selecting materials to organizing the collection off-site, with an emphasis on the unique problems created by serials. All three presenters shared strategies and decisionmaking methods with the audience. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docddiveiy@haworthpress.com &gt; Website: &lt; https://www.HaworthPress.com &gt;]
Big Ideas

Blockchain is disrupting every domain of the business and part of human life and society. What is your big idea? In this chapter, readers will be exposed to conceive, design, and develop their big ideas for blockchain space to disrupt the market.
Future of Engineering within the Ecosystem

The principles of future of engineering ought to be derived through the Environmental Possibilism evolution, in order that future generations benefit from it. It has been said that the scientific and the technological innovations provided by the scientists and engineers have been resulting in economic prosperity and that's verily so. However, due to the economic growth that has been enjoyed by the society, the environment has been setback as discussed in the author’s articles in CEAI’s ViewPoints, (”Environment and Climate Change,” March 2018; “Built Environment-Energy Conservation for Utilities,” September 2018; and the “Engineering Consultancy for Nation Building,” December 2018). The consequences have been climate changes across the globe.Moreover, the future of engineering is inter linked to the conceptual needs within the competitive landscape, and one of these examples is the innovative designed urban planning implemented in Dubai evolving high technology applied in most of the buildings skyscrapers that have been constructed within their building-built environment.Because of developing technology which as known today and the future generation with the increasing usage of the Internet of Things (IoT), through innovative machine learning and augmented reality, it could transform how organizations capture and use project data. Those are just some of the features in the competitive landscape being introduced today.However, within the built environment, the future of engineering would focus on the importance of energy conservation with the use of the Treated Sewage Treatment System, Renewable Energy, Chilled Water Plant District Cooling, District Heating, and using the Building Information Modelling within the Energy Conservation and Sustainability platform. Energy conservation would play a significant role in reducing the effect on global climate change. Replacement of non-renewable resources with renewable ones can impact the environmental possibilism in the competitive landscape, which are now being practiced as part of the future engineering scenario within the ecosystem.In the author’s articles in the CEAI ViewPoint, March 2019 on “Remote Sensing and Remote Monitoring” it is brought out that it would become an indispensible part of the future through the Building Management and Control Systems to enable all building operations to be monitored for precise building controls and services in time of emergency constraints and solving building maintenance issues even without the presence of any human.With all the above mentioned as part of the future, the essential thing to innovate and understand would be the implications of manufactured, bottled water, the electronics and the creation of seed vault for the preservation within the ecosystem as part of the competitive landscape. These are discussed in the following sections.
Question Selection in Template-Based Test Paper Models

The success of any educational program depends on its evaluation system. Examinations are a part of learning process which acts as an element in evaluation. For the smooth conduct of examinations of various universities and academic institutions, the test paper generation process would be helpful. However, examination test paper composition is a multi-constraint concurrent optimization problem. Question selection plays a key role in test paper generation systems. Also, it is the most significant and time-consuming activity. The question selection is handled in traditional test paper generation systems by using a specified test paper format containing a listing of weightages to be allotted to each unit/module of the syllabus.
ARTIFICIAL NEURAL NETWORKS IN FOREX CURRENCY MARKETS

The Artificial Intelligence is growing and covering various aspects of our daily life. The idea seems to be very complex. It seems that a program cannot be developed using our home PC. But believe me, it's not that difficult. Let us try to understand what the neural networks are and how they can be applied in trading. Artificial Neural Networks can be used in forex Currency Trading, for finding or predicting the next possible movements. We know that Artificial Neural Networks involves study of neurons in the human brain, sometimes called as biological network.ANN is based on connections of nodes, units called as artificial nodes or neurons. Neural network is an entity consisting of artificial neurons, among which there is an organized relationship. These relations are similar to a biological brain.
RESEARCH OF PECULIARITIES OF MOTIVATION OF STUDENTS TECHNICAL UNIVERSITY

Motivation plays a significant role in a person's life, since it is a process that controls a person's be-havior, makes him grow in various fields of activity, develop and move forward, allowing him to over-come difficulties and new boundaries, to achieve better results in self-development and personal growth.
Transcript Generation for American Sign Language Gestures using Convolutional Neural Network

The common man is not able to understand and interpret the sign language easily. This is the biggest hurdle for communicating with a person suffering from mutism. It is often observed that common words can be identified through hand gesture easily but when context is not known then it is difficult to interpret uncommon words or sentences. Hence there is a need for some automated system which can ease up the process of interpreting sign language. This need motivated us to design a system which will generate the transcript for hand gestures of American Sign Language. Primarily Convolutional Neural Networks is used for identifying the words from hand gestures and natural language processing is used to build the appropriate sentences. The system will take images as an input and process it to extract the part of image containing the hand gesture using OpenCV. Then features are extracted which can be further used for hand gesture classification. Convolutional Neural Network is used for classification based on which correct label associated with the hand gesture is extracted. This system is able to not only identify alphabets and words but can also generate the contextually correct transcript containing sequences of sentences. Word segmentation is used to create meaningful statements.
An Implementation of Fraudulent URL Detection with Advanced Feature and ML Technique

“Phishing is a deceptive attempt to steal the individual’s details, primarily via email.”Phishing is getting more aggressive by the day, and early detection is critical. The term ‘phishing’ is considered to be a one of the social engineering strategies that gather personal information from a business or an individual by posing as a trustworthy institution or organization instead of malicious websites and misleading e-mail to canvass personal information from any organization or an individual. Phishing also targets email by using it as a vehicle and even delivering messages via email to users who serve a firm or belongs to the particular organization that is responsible to execute the key business tasks, that mainly includes financial establishment or a bank etc. Our focus is mainly on the wide range of data mining algorithms as well as the techniques for evaluating functionality. These targeted algorithms will help us to clear the views about the detail structure of phishing URLs. The best machine learning algorithm for discriminating between phishing and the original site is selected using key functional parameters.