Reviewerly/exHarmony huggingface dataset:
Design of online retail commodity recommendation system based on Item-CF algorithm

With the rapid development of e-commerce, more and more consumers conduct consumption behavior through various online shopping platforms. The traditional e-commerce platform recommendation system is difficult to achieve more accurate matching according to the user input data. In view of this situation, this time through the personalized and diversified optimization and improvement of the traditional item algorithm, and on this basis, a commodity recommendation system is designed. In order to verify the comprehensive performance of the recommended algorithm, by comparing the performance indexes of the improved Item-CF algorithm with the other three algorithms, it can be seen that Item-CF has better accuracy, calling rate, coverage and diversity.
Data security

Equifax was hacked and many other organizations as well, and hacking is likely to be a continuing problem of the information age. The FTC and state attorneys general forged a publicized settlement with Equifax in which they provide a limited amount of money or tools to consumers as compensation. The tools allow consumers to monitor the companies which monitor them—assuming the consumers want to spend large parts of their free time and thought on the problem. There are four options for consumers to protect themselves from identity theft: alerts, freezes, locks, and monitoring, each of which requires a lot of energy for consumers to pursue. It is possible for consumers to spend about a thousand a year achieving this modestly useful and exhausting business, whipped up by articles on the topics news and encouraged by the CRAs themselves, to whom this is a new source of profit from data collection.
Craigslist’s People Problems

This chapter examines the problems that are created and solved as people connect with, sell to, exploit, and protect one another on craigslist. It draws on interviews with craigslist users and a scrape of craigslist's help forum to analyze the ways that people negotiate violations of platform policies. For the most part craigslist transactions go smoothly, but moments of success and failure are important to understanding the politics of everyday online life. When things go right, it is because formal and tacit policies are in place, and because a steady stream of users are working anonymously and without pay to enforce rules and norms. When things go wrong, however, the chapter reveals the limits of policies around community moderation. Interviews and the craigslist help forum has provided a better understanding of how users connect through and negotiate craigslist's policies around community moderation and flagging. In particular, the chapter focuses on craigslist's commitment to user anonymity, which can alternately be seen as a tool for privacy or a threatening way of being online.
Improved face recognition with accelerated robust features improved by means of mean shift k-means clustering

To improve the precision of heterogeneous face recognition model, a heterogeneous face recognition model method based on binary multilayer Gabor Extreme Learning Machine (GELM) is proposed in this paper. Firstly, a random weighted Gabor feature extraction scheme is proposed based on pixel weight. It propagates the locally geometric input image sub-block to the hidden node, and embeds the extracted Gabor feature to the hidden layer. Moreover, it conducts random weighting and sum using a group of Gabor kernels so as to realise convolution operation of non-linear activation function of the propagated pixel; then, it estimates the output layer by means of linear weighting that is similar to Extreme Learning Machine (ELM). At last, the performance of heterogeneous face recognition method of the proposed algorithm is verified through BERC VIS-TIR database and CASIA NIR-VIS 2.0 database.
Association Measures in Network Outlier Detection Methods

Detecting outliers before they cause any damage to the data in the network is a important constraint. Outlier detection methods need to be applied on various applications like fraud detection, network robustness analysis. This paper mainly focuses on detailed measures of both proposed intrusion and outlier detection methods with traditional methods. In the proposed work, KDD CUP data set is used. In this work, we initially divide the entire network into individual nodes for efficient monitoring. Later, the proposed methodology is applied on networks which can easily handle high / multidimensional data. While detection of outliers, the proposed method divides the entire network into sub-networks and each network is formed with density based strategy and then outlier detection is applied on them using a Efficient Crossover Design method which identifies the outliers more accurately. Finally ,the proposed method is evaluated and compared with traditional method will all possible parameters in network intrusion detection and the results prove that the performance levels of the proposed method is far better than the traditional methods.
Analysis of Crime Detection using Data Mining Techniques

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Type Ii Fuzzy Logic Controllers for VM Management and Task Assignment in Cloud System

Task distribution and VM (virtual machine) management are the foremost requirements for efficient resource utilization and ensuring SLO (service level objective) of a cloud computing system. To achieve this, it is important to configure VMs depending upon the requirements of the tasks, find proper VM-Task pairs to distribute the tasks over VMs and control the status of VMs. In this paper, a type-II fuzzy logic controller (FLC) based cloud resource management approach is presented. The presented approach contains four type-II FLCs based decision-making systems. The proposed algorithm firstly try to find the most suitable VM-task pair for task assignment, secondly, if it fails in the first step, then it creates a new VM with an appropriate configuration for the given task, at last, it controls the status (Active, Sleep, Shutdown, and Terminate) of running VMs based on their activities and resources utilization to free up resources and reduce power consumption. The simulation result shows that the proposed cloud VM management and task algorithm provides better QoS (quality of service), reduces the resources and power requirement.
Shadow Detection and Removal Techniques in Aerial Images

One of the complicated tasks is to detect &amp; remove Shadow from single images of aerial images. Significant research is being carried out on various techniques of shadow detection. Over past decades, many shadow identification &amp; removal approaches have been applied. Shadows are optical effects that arise when a region in the scene occurs when the primary light. Shadows are all over around us, so there is no confusion by their appearance. In this paper we provide an overview of the different methods used in the aerial images to identify &amp; eliminate shadows &amp; also provide their comparative study.
A Culling System for a Recipe using Sentiment Analysis Techniques

This System helps the user for providing the recipes in which they are particularly interested in a mentioned criteria of ingredients on which the user wants to prepare a recipe. The input given by the user like the ingredient on which he/she wants to prepare a recipe can be of text, speech or visual. The process of providing a list of gathered recipes from different trusted and verified sources is performed with the help of Sentiment Analysis(SA), Watson Text-to-Speech and Watson Visual Recognition(WVR). The recipe extraction from different sources which are required for the user is retrieved with the help of a standard Web Crawler. The tools and technologies used for the proposed system are from Artificial Intelligence(AI), Natural Language Processing(NLP). The system proposed assists the user in providing a list of recipes in a prioritized order based on the optimization process performed by the Naïve Bayes Algorithm(NBA) of Sentiment Analysis. In addition, the displayed results of recipes have been reviewed and rated by different users from different sources.
Privacy Preserving Using AES-Mapping in Mix Column Encryption Algorithm Cloud Approach

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
RESEARCH ON THE STATUS QUO AND IMPROVEMENT STRATEGIES OF COLLEGE STUDENTS’ INFORMATION LITERACY IN AUTONOMOUS ORAL ENGLISH LEARNING UNDER THE BACKGROUND OF "INTERNET+"

In today's global economic development, the exchanges between countries are becoming more frequent, and the requirements for foreign languages, especially English, the world language, are getting higher and higher.In business negotiations, international trade, and foreign cultural exchanges, English is an essential communication tool.In order to promote our country's foreign exchanges and cooperation, college students' English ability, especially the ability of spoken English, continues to improve.The society is now in an era of rapid development of scientific and technological information.The emergence and iterative update of the Internet has pushed people from the PC to the mobile.The mode of learning English has also developed from the most traditional physical teaching mode to online teaching.The mobile potential teaching model in the current situation.It promotes the diversification of teaching modes.
Development of Algorithm for Audio Watermarking Embedding and Decoding using Patchwork Method under Attacks

To protect digital multimedia content from unauthorized reproduction, digital audio watermarking played crucial role. Audio watermarking for the patchwork method has a relatively good level of perception quality.The challengesbetween security, robustness, and imperceptibility is contemporary area of researchand remains relevant issues. This paper introduces discrete cosine transforms (DCT)-based audio watermarking process using the patchwork method for conventional and advanced signal processing attacks. In the first stage of the watermarking audio signal is divided into an equal number of segments and its sub-segments, and then its coefficients are computed. After eliminating high-frequency related coefficients, remaining coefficients are used to form frame pairs of equal length. Watermarks are embedded in a frame using specific criteria and secured data key.The adjustments are made in such a way that the identification ofWatermarked pairs of DCT frames is done in the decoding process by applying the selection criteria used during the embedding process. From watermarked frames, watermark data is extracted by using a secure data key. The proposed audio watermarking algorithm is implemented and tested under conventional and advance signal processing attacks for robustness, imperceptibility, security, and data payload.
Prototype Creation

Now that we have used a Design Thinking approach to identify problems to be solved and then identified some appropriate potential solutions, we can begin creating technology-based prototypes to aid in the evaluation of these solutions. These technology prototypes can be viewed as early development attempts that might later evolve into full-fledged production-level solutions. At this stage, we need to control the scope of our development efforts and go just far enough to evaluate whether we are on the right track.
Employee Engagement leads to Job Satisfaction

Employees are the real asset of an organisation. As in today’s era competition is growing and in this competitive environment the organisation is looking up to strengthen themselves so as to be the best among the others. Employees can act as the reason for success and simultaneously they can be the reason behind the failure of an organisation if not taken care in proper direction. The concept “employee engagement” is being widely used in every organisation with an intention to improve the productivity level more. Employee engagement is nothing but the level of willingness, ability and attitude of employees towards their work or task. As per the researchers, many evidences has been found out which shows that more the employee is engaged more he/ she contributes towards the job and more they are likely to be satisfied. This research article portrays an interlink between employee engagement and job satisfaction. It shows that employee engagement is directly related to the job satisfaction. This research paper is descriptive in nature. The paper was developed taking the feedback from 30 respondents through the help of questionnaire. The questionnaire was developed taking into account the necessary determinants.
BUSINESS BACKGROUND AND COMPLIANCE BEHAVIOR: EVIDENCE FROM LIBRARIES

During the last decades, there has been a heated debate related to the effects of a business background on ethical behavior. According to some authors, students majoring in business courses – such as accounting, economics, and management – would be more likely to free ride or defect from coalitions in collective action situations, given the emphasis of such courses on individualistic values. Other authors have challenged that view, presenting empirical evidence that questions the link between business education and opportunistic behaviors. The present paper revisits this debate, by studying the impact of business education on compliance behavior in a specific type of information commons (libraries). Employing a novel dataset related to more than 700,000 library transactions during a 10-year period (2006-2015), I correlate business background with users’ compliance behavior, while controlling for their time-invariant characteristics. I find no evidence of a significant effect of business education on compliance behavior in this specific setting. The results reported in the paper have important implications for ethical theories in business, with an emphasis on standard explanations of organizational behavior, such as principal-agent theory, transaction-cost economics, and teamwork theory.
Hard Words

This paper suggests that the chief limiting factor in acquiring a vocabulary of natural languages consists not in overcoming conceptual difficulties with abstract word meanings, but rather in mapping these meanings onto their corresponding lexical forms. We describe an overlapping series of steps through which novices move in representing the lexical forms and phrase structures of the exposure language, a probabilistic multiple-cue learning process known as syntactic bootstrapping.
Conclusion

This book has presented both a methodology for analyzing form in rock songs and a theory of formal organization in the rock output of the 1960s, ’70s, and ’80s. The methodology grows out of the general concept of form as process described in the introduction, where rock songs are seen as cohesive entities unfolding through time. From this point of view, we approach a rock song by listening for broad trajectories, identifying points of stability and tension in small-scale phrases and sections as well as large-scale cycles and entire songs. More specifically, we focus first on a song’s harmonic trajectory, interpreting a prolongational progression through a functional circuit (or noting one’s absence), and then aligning that trajectory with the layout of formal functions. From this methodology comes the theory that the rock repertoire in question is based on a small set of conventional formal-harmonic patterns, what I have been calling rock’s ...
Cybersecurity

Cybersecurity threats are unlocked doors opened by vulnerability points left unchecked. As we add new technologies to our organizations, new vulnerabilities are created. As we change the way people work and live using technology, new vulnerability points are formed. As the infrastructure to daily life is more reliant on Internet connections, data clouds, and wireless nodes, the ability for hackers to target central services like transportation, financial services, and health care to wreak havoc or destabilize a region continues to increase.
Analysis on Anti-Corruption Initiatives in Senegal and Côte d´Ivoire towards Breaking with Systemic Corruption: Focusing on the Theory of Rothstein and Teorell

세계은행에 따르면 전 세계의 부패로 인한 연간 비용이 글로벌 GDP의 약 5%에 해당하며, 취약국에서 부패 문제가 가장 심각하다. 부패 근절의 중요성과 시급성에도 불구하고 취약국들 중 부패인식지수(CPI)가 개선되고 있는 나라를 찾아보기 힘들다. 이러한 실정에서 아프리카의 세네갈과 코트디부아르는 예외적으로 성과를 보이고 있다. 두 나라의 정치 지도자들은 반부패 이니셔티브의 기치를 올리고 비교적 단기간에 주목할 만한 발전을 거두었다. 본 연구는 제도적 부패에 관한 Rothstein과 Teorell의 이론을 중심으로 세네갈과 코트디부아르의 현 대통령들이 취임 이후 주창했던 반부패 이니셔티브들을 분석한다. 분석 결과 양국이 상당히 유사한 양상을 보이나 분석틀의 rkr 요소에서 성과의 차이가 있음을 알 수 있었다. 또한 두 나라의 노력에도 불구하고, 공정하고 독립적인 사법부를 보장하고 제도적 부패를 타파하기 위해서는 여전히 많은 과제가 남아있음을 확인할 수 있었다.The World Bank estimates that the annual cost of global corruption equals roughly 5% of global GDP, and the problem is most severe in fragile states. Despite the importance and urgency of fighting corruption, few of the fragile states are improving in terms of their Corruption Perception Indices (CPI). However, two countries are striving in the opposite direction; Senegal and C&#244;te d´Ivoire. Under their current leaders, the countries have launched several anti-corruption measures that seems to have borne fruit over the short term. By analysing how the initiatives taken by the current presidents since their entry into office are addressing the factors as brought forward by Rothstein and Teorell (2015) as crucial if a country is to break with systemic corruption, the analysis shows that both countries have taken momentous steps compared to under previous administration to break with systemic corruption. It is illustrated that both countries are launching similar initiatives, yet with seemingly varying devotion. However, despite recent improvements, much is left to be done in both countries if they are to permanently break with systemic corruption, particularly to ensure an impartial and independent judiciary.
Concurrent Transaction Logic with Priority and Timing Constraints

&lt;p&gt;Concurrent Transaction Logic (CTTZ) is a deductive language for programming database transaction applications that integrates queries, updates, and transaction composition in a complete logical framework. The language supports all the properties of classical trans­actions and the properties found in some new transaction models, e.g., sub-transactions, transaction rollback, and concurrent transactions. &lt;/p&gt; &lt;p&gt;The contributions of this thesis are twofold. First, it extends CTTZ to account for timing-event-based prioritized concurrent systems in which transactions may have pri­ority and timing constraints. This extension of CTTZ, here called TV-CTTZ, provides a high-level logic programming framework for specifying and simulating executions of timed transactions and trigger-events commonly present in real-time concurrent appli­cations. Second, it describes a Prolog implementation of TV-CTTZ. The implemented TV-CTTZ prototype supports the translation from TV-CTTZ to CTTZ. Underlying this protocol, we use a simplified Rate-Monotonic algorithm [10] to schedule the execution of constraint concurrent transactions and built-in timing predicates to handle transaction time-relations.&lt;/p&gt;
Using C++ with R and Maxima

One of the advantages of code implemented in C++ is that it can be used as part of native libraries or stand-alone applications and also integrated as a component of other development and modeling environments. In the financial industry, for instance, it is common to have lower-level modules implemented in C++, with high-level analysis being performed in more user-oriented environments such as Excel, Mathematica, Matlab, Maxima, R, and Octave.
Augmenting Code Review Experience Through Visualization

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Obscure image classification and restoration using Support Vector Machines

A restoration and classification computation for blurred image which depends on obscure identification and characterization is proposed in this paper. Initially, new obscure location calculation is proposed to recognize the Gaussian, Motion and Defocus based blurred locales in the image. The degradation-restoration model referred with pre-processing followed by binarization and features extraction/classification algorithm applied on obscure images. At this point, support vector machine (SVM) classification algorithm is proposed to cluster the blurred images. Once the obscure class of the locales is affirmed, the structure of the obscure kernels of the blurred images are affirmed. At that point, the obscure kernel estimation techniques are embraced to appraise the obscure kernels. At last, the blurred locales are re-established utilizing nonblind image deblurring calculation and supplant the blurred images with the restored images. The simulation results demonstrate that the proposed calculation performs well.
Reversible Data Hiding on Image Encryption with Index Boundary for Partial Confidential Documents

An efficient data hiding method is proposed in the smart cyber-attacks such as data theft, virus attacks on the transmitting of whole confidential data, partial confidential data via private and government networks. The transmitting data over the internet is one of the better solutions to make a work easy and fast even though protecting data from the smart hackers is vital role in the cyber-crimes. There are various protection techniques of confidential data like digital watermarking, digital signals with embedding data into images, audio and videos. The existing watermarking techniques using RSA is a time consuming process for number of iterations to be performed even in signal decryption of image. These complexities of iterations to be overcome by the Least Significant Bits, DWT transformation and Arnold transformation were failing in all aspects of security requirements. The proposed method of reversible data hiding has an efficient encryption in medical images, health care image and data transmitting in various organizations.