Reviewerly/exHarmony huggingface dataset:
Various Recommender Systems and Their usage in the Domains of Mobile Based and Online Applications

The activities of the users are surrounded by online shopping, online content fetching and online payment of the various bills. The important point is in case of the online shopping with Amazon, Flipkart and many other online shopping sites provides some sort of intelligent assistance to the user. Based on the past history, based on the user profile. Such kind of the applications were named as recommender systems. The most common categories of recommender systems involves, the collaborative filtering, content-based filtering, multi-criteria recommender systems, risk-aware recommender systems, mobile recommender systems and Hybrid recommender systems. The current work dealing with the process followed by the recommender systems along with various key factors embedded in the usage. The suggestions given by the application to the user depends on user profile, and content searched by the user and the collaboration of other products with the current product. The work focus on the implementation algorithms existing in the process of recommender systems, the above listed categories of recommender systems follow certain key mechanisms depending on the user query. The work also deals with the performance aspects of the recommender systems in case of accuracy and reproducibility in recommender system research. Especially the mobile recommender systems there are certain limitations of region and accuracy of the results. Overall the outcome of the work is to describe the importance of the recommender systems and the internal mechanism followed by various recommender systems.
Chatbot System

For a student interface web applications can come in a different of formats, ranging from command-line, graphical, web application, and even voice.While the most popular user interface include graphical and web-based applications, occasionally the need arises for an alternative interface.Whether due to multi-threaded complexity, concurrent connectivity, or details surrounding execution of the service, a chat bot based interface may suit the need.Chat bots provide a text-based user interface, allowing the user to type commands and receive text as well as text to speech response.Web application using Chat bots are usually a form full services, remembering previous in order to provide functionality.When chat bot technology is integrated with popular web services it can be utilized securely by an even larger audience.
Students Perceptions towards Distance Learning with Online Collaborative Platforms: A Case Study

In view of the COVID-19 pandemic and government policy to carry out distance education by employing full online learning. The research explores the EFL students perception toward distance education during Covid19 Pandemic with online collaborative platforms which employed in EFL Students of English Department of a private college in Indonesia. This research used a descriptive case research using purposive sampling techniques by taking 27 respondents from English Department at STKIP PGRI Jombang. The online questionnaire used to collect data on the perception of students by employing online collaborative platforms. The questionnaire are adapted from the technology acceptance model (TAM) constructed by Davis, 1989 with little modification as it excludes the external factors such as the availability of the internet access, and the support from the administration. TAM is possibly the most widely-used framework for measuring technology acceptance, and its high validity has been proven empirically in many previous studies (Basri &amp; Paramma, 2019 and Wiyaka et.al., 2018). The quantitative data was collected using an online questionnaire posted in Google form. The method of descriptive case research in terms of percentage has been used for data processing. The result of this research indicates the positive perception those EFL students of English Department at STKIP PGRI Jombang who took Critical Reading by using online collaborative platforms held on the use of online collaborative platforms. Further research can refer to this Acceptance Model in determining a suitable ICT integrated learning program betien various platform and the user expectations of the online platforms used.
Big Data Analytics and Visualization for Hospital Recommendation using HCAHPS Standardized Patient Survey

In Healthcare and Medical diagnosis, Patient Satisfaction surveys are a valuable information resource and if studied adequately can contribute significantly to recognize the performance of the hospitals and recommend it.The analysis of measurements concerning patient satisfaction can act as a valid indicator for giving recommendations to the patient about a specific hospital, as well as can provide insights to improve the services for healthcare organizations.The primary objective of the proposed research is to carry out an in-depth investigation of all the measurements in HCAHPS survey dataset and distinguish those that contribute considerably to the hospital suggestions.This work performs predictive analysis by building multiple classification models, each of which examined and evaluated to determine the efficiency in predicting the target variable, i.e., whether the hospital is recommended or not, based on specific set of measurements that contribute to it.All the models built as a part of research specified the same list of measure id is that help in deriving the target.It provides an insight into how caregiver interaction, emphasizes on the services rendered by the caregiver and overall patient experience makes a hospital highly valued and preferred.An in depth-analysis is conducted to derive the implementation results and have been stated in the later part of the paper.
A Novel Method for Feature Extraction using Color Layout Descriptor (CLD) and Edge histogram Descriptor (EHD)

Now days, Image processing finds diversified applications in almost all field of life. The success of any image processing application is depends on proper feature extraction technique. To extract good and proper features is very interesting and challenging task in the development process. It is used to describe the image based on its contents. These extracted features are used to compare, analyse and/or search the analogous images. There are various feature extraction techniques are found in the literature to design various applications. However any image processing application generates images with high dimensionality, which will be results in the low efficiency of an application. This paper provides an approach to extract features from the images using MPEG-7 feature extraction techniques. The approach discussed in the paper uses two popular MPEG-7 visual content descriptors; they are namely Edge Histogram Descriptor (EHD) and Color Layout Descriptor (CLD). The concept results in reduction of dimensions of an image to improve the efficiency of the application. It can be used as a heart to design any image processing application as well as provides strong foundation to develop variety of applications.
Goalpost Detection Using Omnidirectional Cameras on ERSOW Soccer Robots

The ERSOW robot is a soccer robot developed by Politeknik Elektronika Negeri Surabaya, Indonesia. One important ability of a soccer robot is the ability to find the goal in the field. Goal Post is often used as a sign by soccer robots in a match. The mark is a reference robot in the field to be used in determining the strategy. By knowing the location of the goal in a field, the soccer robot can decide to maneuver in the match to get the right goal kick. There are various methods of detecting goals. One of them is to detect goal posts using vision. In this study, the radial search lines method is used to detect the goalposts as markers. Image input is generated from an omnidirectional camera. The goal area is detected on the front side of the goal area. With experiments from 10 robot position points in the field, only 1 position point cannot detect the goal. The robot cannot detect the goal because what is seen from the camera is the side of the goal, so the front side of the goal area is not visible.
State of art on efficient document co-editing in cloud collaboration

Cloud collaboration is an important technique which helps distant users to share their work, information and files over the cloud at the same instant of time.The focus of this study is to remove the problem of the deadlock or long time waiting zone condition for requests edit threads, by the users in collaborative structure.The 'co-authoring' or 'co-editing' process generates a major problem in the form of writing confliction in concurrent and single user editor system in cloud collaboration process, hence multi-version approach is implementing as a solution to ensure no confliction in cloud collaboration environment.In this study cloud collaboration architecture is discussing which describes the efficient working of central cloud, remote cloud and local cloud in collaborating environment.The involvement of central cloud helps to minimise the storage space of data in the cloud environment with reduced redundancy factor.
Optimizing the Effect of Cropping and Rotation Attacks on Watermarked Images using Back Propagation Neural Network in DWT Domain

Hiding an image in another image is the technique used for copy write protection. In this proposed work, the watermark is inserted into blue plane of the cover image, In this watermark extraction and embedding process, the back propagation neural network in conjunction with biorthogonal wavelets is utilized to improve the efficiency. The performance is tested by normalized correlation coefficient. The imperceptibility of the watermark is tested by cropping and rotation attacks effectively.
Problems of digitalization of higher education in Russia

Researched is the process of undergoing great changes, caused by the transition of all universities in the country to online education in the context of the coronavirus pandemic. The article deals with specific problems, risks and challenges related to the digitalization of higher education: digital inequality, closely related to digital literacy, the lack of a unified way of communication between students and teachers, the lack of generally accepted platform solutions for conducting classes online; the actual growth of the teacher’s workload in the conditions of digitalization of education, which is not yet taken into account in the system of rationing of remuneration, professional burnout in a sufficiently large number of teachers, lack of motivation and self-discipline of students, increased bureaucratization of the higher education system. The experience of implementing digitalization into education during the pandemic dispelled myths about the benefits of an immersive education model and individualized learning based on online technologies. Digitalized learning is focuses primarily at memorization and reproduction, and not at comprehension and critical perception. A comprehensive solution to these problems is the introduction of new models of educational programs.
Vector Generation of Reflection and Shearing of 2D Objects: Sequencing in Column Major and Row Major Pattern

Transformations are the best and effective techniques of producing changed objects in terms of Displacement, Enlargements and Orientations. In other words the Transformation are the most challenging way of shifting or changing the dimensions and orientations of images in the most effective way.But This modifying and repositikoning of the existing images is calculated by a standard convention of Matrix Calculations.The usual practice of doing so is straight forward. The transformed object can be obtained by coupling (Matrix Multiplication) original object Matrix with the transformation vectors. The main challenge is how to evaluate it. The usual practice is standard Column Major Pattern. The alternative Row Major Pattern is also known approach but what matters is the sequence of operations that make these both approaches worth mentioning.Visualization can be enhanced if either of the approach is adopted. But what makes it more exciting is the calculations that come with both of these approaches. A normal practice is to use the standard Column Major Pattern for processing objects .An Alternative to this Technique is Row Major Pattern which equates to the same result only if sequence of operations are not compromised. This paper describes the transformation (Reflection and Shearing) in both Column and Row Major Pattern and at the same time aims in putting down clear semantics in justifying the sequence of operations.
Efektivitas Konseling Behavioral Model Krumboltz untuk Mengembangkan Keputusan Karir Siswa

This research is an experimental study to cultivate student learning outcomes of grade XI Language of SMA N 1 Tabanan. Conditioning and user behavior are limited to those that can be used purely, can not be handled strictly. In this study, the control variables are Krumbotz counseling behavior, while the control class in this study is not given with the same as the experimental class. The sample of research, determined by random sampling technique is random sampling technique through drawing. Based on the First Hypothesis Testing the thitung value of -10.632 with df = (N-1) = (35-1) = 34 and 5% significance level then obtained the value of ttable of 2.032. Since it is larger than ttable, this proves that the first hypothesis in this study can be used and the behavior behavior of the Krumboltz counselor is effective for making decisions for grade XI Language of SMA N 1 Tabanan. Based on Second Hypothesis Testing The average tcount of 8,739 with df = (N1-1) + (N2-1) = (35-1) + (35-1) = 68 and 5% significance level hence the obtained ttable value of 2.011. Since it is larger than ttable, it proves that there are two factors in this study that can be used to determine the behavior of the Krumbolt behavior model (experimental group) with groups of students who are not. Based on these results it will be done counseling behavior Krumboltz behavioral model to develop decisions that can be categorized well and can provide a very effective contribution.
User Tagging Behaviors in an OPAC: An Analysis of Seven Years of I-Share User Tags

User tagging services are under-used in cultural heritage institutions despite existing for over a decade. This study considers seven years of user tags from university and public institutions by comparing service usage between institution types and qualitatively analyzing a selection of tags from the University of Illinois at Urbana-Champaign. Researchers found that, overall, few users are tagging items in the online catalogs, but tags being created are largely descriptive in nature, indicating the potential to improve discoverability for under-described materials. With improved education on their use and purpose, tagging and annotation services can become invaluable resources for cultural heritage institutions.
Classification of Facial Images into Adult or Minor Categories using Facial Features

Facial images have always been used for various analytical and research purposes as they contain abundant information about personal characteristics, including identity, emotional expression, gender, age, etc. A human image is often defined as a complex signal composed of many facial attributes such as skin colour and geometric facial features. Nowadays the real-world applications of facial images have brought in a new dawn in the field of biometrics, security and surveillance, and these attributes play a crucial role in the same. Unrestricted and unintended access to certain resources and information to the minors has a history of physical and psychological implications, which makes age, in particular, more significant among these attributes. Consider a scenario where users may require an age‐specific human computer interaction system that can estimate age for secure system access control or intelligence gathering. Automatic human age estimation using facial image analysis will come as a rescue with its potential applications in the field of Age Specific Human Computer Interactions and numerous real‐world applications which include human computer interaction and multimedia communication. Here, we aim to identify and classify images provided as input into two main categories, adults and minors. This classification would act as an access controller to the desired resources or information. MATLAB was used to identify the younger and older images. Initially we got the databases of features extracted from the input images using different feature extraction methods. Later we compared the several trained databases to get a specific range for younger and older images. This range then became the basis for identifying the young and the old.
Knowledge Systems and Risk Management: Towards a Risk and Threat Assessment Framework

Knowledge is the most important asset that a company can have.Thus, it is imperative that this asset is safeguarded just like generic information assets.However, knowledge management (KM) and knowledge systems are different than traditional information systems with different threats and different operational requirements.Information Security professionals recognize that risk assessment is the cornerstone to information security.We build on this perspective and propose that risk assessment techniques need to be applied to KM too to properly safeguard this asset.We discuss risk assessment frameworks and build on a KM/knowledge system specific risk assessment framework with a step-bystep guideline for KM/knowledge system specific threat assessment.
The Complex Method to the Solution of the Problem of Polychromatic Images Segmentation

The article touchs upon the problem of polychromatic images segmentation. It is a very urgent issue, because today the sphere of electronic mapping has rapidly been evolving. The research aims at developing a technique of adaptive segmentation and implementing it as a program for a PC. Aerial snapshots taking from the countryside are treated as objects of our research. The developed method combines background areas detection, edge detection and dimensions selection. The experiment has been carried out. It proves the effeciency of the developed technique.
An Adaptive Slide Window Security Method for Transaction Updation in Data Stream Mining

Data steam mining has gained large interest in current research domain. Where various information’s are retrieved based on the content of the context, the accuracy of the input stream with respect to its privacy is a major challenge. Windowing technique is used an effective approach in providing security measure in data stream mining. The recent develop windowing approach operates using sliding window, where anonymity is focused by different processing rules. The linear search sliding window has a constraint of search overhead and loss of generality under distributed information. In this paper, a new adaptive window approach for privacy coding in data stream mining is proposed. This presented approach is developed with the concern of minimize the search overhead and accuracy in search mining performance using adaptive window monitoring.
Partial Addition and Ternary Product based -so-semirings-1

A ternary  - SO semiring possess a “natural partial ordering”, an infinitely “partial addition and a ternary multiplication with a set of laws. In this paper we introduce the notions” of different structures of partially ternary  - ideals of ternary  - SO semi ring and characterize them. Mathematical subject classification: 16Y60
Elliptic Curve Blended Cross Chaos Based Secure Image Communication

Image encryption has proven a successful method to communicate the confidential information. Some of the images may or may not be confidential. So there is a need to secure the confidential images. Initially, symmetric encryption is used for security purpose. But it has the problem that if the key is revealed the interceptors can immediately decode it. To make the key transformation more secure, asymmetric encryption is introduced. In this two different keys are used for encoding and decoding. So even the interceptors hacked the key it cannot be possible to decode. In this project Elliptic Curve Cryptography (ECC) is utilized for generating the keys and the cross chaotic map used for generating the chaotic sequence. These chaotic sequences are utilized to encode the image for secure communication.
Simulating Manual Signature using Elman Back Propagation Model to Create Pseudo Digital Signature

Manual Signatures are used in authentication worldwide. But they are still not used in VANETs and in ad hoc networks for security. In our research we try to use manual signature in place of Digital Signatures for the security of message and stimulated the same by pattern recalling mechanism of Artificial Neural Network using Elman Back Propagation Algorithm to create pseudo digital signature. These pseudo digital signatures are now used as the identity of message sender in communication. We also maintained the speed of manual signature recognition and verification to stop the delay in identification of the sender.
The IoT: Uses and Applications

The Internet of Things (IoT) is a pervasive web in which each object or machine has a unique identity and is be able to use the Internet to link with other machine or send data; also known as the industrial Internet(Laudon, 2019). IoT makes it easier for people to communicate, collaborate with each other, and access educational resources, creating a multitude of opportunities for consumers, educators, and business owners to transform their lives. The following report defines the Internet of Things, provides several examples of how IoT technology is currently used, and explains the potential applications of IoT in an educational setting. The Internet-enabled devices used with the Internet of Things are useful in preschools, elementary and secondary schools, and colleges and universities, as they increase efficiency, facilitate better interactions between students and educators, and give educators more time to deliver instructional content. The report concludes with an overview of the barriers that make it difficult to implement IoT technology.
Real Time Face Recognition in Group Images using LBPH

Face recognition is a beneficial work in computer vision based applications. The goal of the proposed system is to provide complete face recognitions system capable of working a group of images. The faces are detected and verified the identity of an individual using a machine learning algorithm. The haar cascade detects the face from a group of images for training and testing dataset. The dataset contained positive and negative images for training and testing. The LBPH algorithm recognizes the faces from input images. The proposed system detects and recognizes faces with 98% accuracy.
Secured Information Sharing using Data Sanitization and restoration

This paper focuses on the issues face by the supply chain management industry for overall working.Block chain technologies can contribute to the operations and supply chain domain as well.Currently, supply chains are becoming more and more complex in structure, difficult in terms of task, and diverse in terms of stakeholders, and many organizations do not have an integrated view of the entire supply chain.In supply chain management multiple stakeholders are responsible for effective communication where data sharing from vendors, suppliers, managers by maintaining transparency and privacy is very difficult.In this paper two methods are introduced for dealing with issues mention above and the methods are data sanitization and restoration.
Data‐driven auditing: A predictive modeling approach to fraud detection and classification

J Corp Acct Fin. 2019;30:64-82. DOI: 10.1002/jcaf.22389 In the above-mentioned article, the author biography for Nitin Singh should read “Nitin Singh is Associate Professor of Operations Management & Decision Sciences at IIM Kashipur, India.” We apologize for this error.