Reviewerly/exHarmony huggingface dataset:
An enhancement of planned random algorithm applied on an online questionnaire

Like many other innovations, randomization has been a key factor in various fields such as games, science, art, statistics, and other areas. But although treated as common knowledge, randomization is often misunderstood by users when they start to perceive relationships or connections between randomly distributed data, this tendency is known as apophenia. It is observed mostly when a randomized dataset shows the same elements in a row or in multiple repetitions, an occurrence that is plausible given the nature of randomization. Nevertheless, this may appear as biased or non-random to humans, thinking that since an element had appeared once or a couple of times then it should not appear next to or within a set amount of time, another user misunderstanding known as gambler’s fallacy.The Planned Random algorithm (PR algorithm) was created as a solution to this problem, as it introduces a non- random process to lessen the repetitions of data in the returned dataset and making the result less random to appear more random.This study aims to enhance the Planned Random algorithm by increasing its apparent randomness by further minimizing the repetition of data in a resulting dataset. 5 final test simulations were done for both the existing PR algorithm and enhanced PR algorithm wherein the enhanced algorithm showed a promising 22.22% decrease in both total and average repetitions compared to the existing algorithm.In conclusion, the enhanced algorithm had seen a significant increase in apparent randomness when compared to the existing PR algorithm.
An Online Predictive System for Mapping Visual Scenes of Fraudulent Behaviour

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.
The Production and Dissemination of Hate Speech through the Media: Focusing on Journalism Practice and Feminist Ethics

This article seeks to reveal that the existing legacy media and social media outlets are playing a role in disseminating hate speech, and to explore solutions to this issue. Currently, the media are indiscretely reproducing online community postings and employing them to get more views. The legacy media reduce blatant discriminations to merely controversial issues and the social media continues to circulate hate speech by way of algorithm arrangements. Likewise, users are contributing to the spread of hate discourse through the uses of memes, and through their participation in cyber bulling. There are more instances where negative emotions are shared on social media scenes, and users themselves are creating meme-like forms that allow for the easier sharing of hate and discrimination. Throughout this type of processes, the anti-feminism sentiment emerges through the online space to make feminism a system of thought that must be rejected in Korean society. The media reportings convey hate sentiments produced sub-culturally in the online communities in their rawest forms, and thereby play a role in circulating antifeminist discourse in the public discourse sphere. The legacy media’s adherence to communal journalism, the social media’s voluntary restraint on overcommercialization, and the improvement of media literacy of users are suggested as solutions.
Llaimas Volcano Seismic Event Classification Using The Cross-Correlation Function

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.
Feature Selection and Ensemble Method Analysis for Breast Cancer Datasets

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.
Weighted polygamy inequalities of multiparty q-expected quantum entanglement

Abstract Based on q -expected entanglement measure for <?CDATA $q\geqslant1$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>q</mml:mi> <mml:mo>⩾</mml:mo> <mml:mn>1</mml:mn> </mml:math> , we generalize the polygamy inequality for multiparty entanglement in arbitrary-dimensional quantum systems. By using the β th-power of the q -expected entanglement of assistance for <?CDATA $0\leqslant \beta \leqslant1$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>0</mml:mn> <mml:mo>⩽</mml:mo> <mml:mi>β</mml:mi> <mml:mo>⩽</mml:mo> <mml:mn>1</mml:mn> </mml:math> and the Hamming weight of the binary vector related with the distribution of subsystems, a class of weighted polygamy inequalities in arbitrary-dimensional quantum systems is established. We further demonstrate that our class of weighted polygamy inequalities can be improved even into tighter inequalities, under some conditions, with auxiliary entanglement in bipartite subsystems. Our results may provide new ideas for studying the polygamy constraints of multiparty entanglement and better characterizing the entanglement distribution.
Project W.A.T.C.H: Its Contexts, Inputs, Processes and Products in the Department of Education

This study aimed 1.) to describe how the teachers live or manifest the core values of honesty and punctuality in implementing Project WATCH along with Advocacy, Training/Orientation, Curriculum Integration, WATCH Club Activities, and Awards and Recognition using the CIPP Model of Evaluation. 2.) to develop an advocacy and implementation model on how Project WATCH core values could build punctuality and honesty among public school teachers. Regarding Project WATCH implementation, On the Context level focused on Advocacy, most of the respondents were not well informed about the goal, mission, and vision of the WATCH program. On the Input level, investigated the training/orientation and curriculum Instruction. Project WATCH activities were not well implemented because there was no budget allocation from the MOOE; they did not include it in the Annual Implementation Plan or School Improvement Plan. Most of the respondents said they have no specific training for Project WATCH. The process level focused on the description of the WATCH Club Activities. Most schools had WATCH Club for pupils only to manage the activities in school guided by the School Project WATCH Coordinator and the School Head. When it comes to teachers, there was no Organized WATCH Club. There was no Training and Orientation on Project WATCH, which was supposed to be one of the essential activities to be managed or spearheaded by WATCH Club Officers. The product level described the Program's outcome, which is awards and recognition. From the findings, most schools did not give awards to teachers. Most schools implemented Project WATCH, They did Advocacy through the hanging of tarpaulin inside the school premises, but most of the schools launch in June or any month of the year to implement the project. There was no budget allocated for this Program teacher and parents shared the expenses for the activities, and they did no evaluation done at the end of the year.
Bayesian Composite Quantile Regression with Composite Group Bridge Penalty

We study composite quantile regression (CQReg) with composite group bridge penalty for model selection and estimation. Compared to conventional mean regression, composite quantile regression (CQR) is an efficient and robust estimation approach. A simple and efficient algorithm was developed for posterior inference using a pseudo composite asymmetric Laplace distribution which can be formulated as a location-scale mixture of normals. The composite group bridge priors were formulated as a scale mixture of multivariate uniforms. We assess the performance of the proposed method using simulation studies, and demonstrate it with an air pollution data. Results indicated that our approach performs very well compared to the existing approaches.
Modelling a Conversational AI Chatbot for Academic Websites

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.
Automatic Composition of Machine Learning Models as Web Services across Data Sets

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.
Natural rubber components fatigue life estimation through an extreme learning machine

In engineering applications, natural rubber components are subjected to continuous alternating loads, resulting in fatigue failure. Although some theoretical models are used for the fatigue life estimation of rubber materials, they do not comprehensively consider the influence of multiple factors. In the present study, a model based on the extreme learning machine is established to estimate the fatigue life of natural rubber specimens. The mechanical load, peak engineering strain, ambient temperature, and shore hardness of natural rubber specimens are used as the input variables while the measured average fatigue life is used as the output variable of the extreme learning machine model. The performed analyses reveal that the regression results and predicted life of the established extreme learning machine model are encouraging. The backpropagation neural network model and the support vector machine model are implemented to evaluate the performance of the established model. It is concluded that the extreme learning machine model is superior to the backpropagation neural network and support vector machine models in accuracy and efficiency. The extreme learning machine model provides an effective means for accurately predicting the fatigue life of natural rubber components.
A Comparative Study of LSB based Statistical Steganalysis and Gray Level Co-Occurrence Matrix based Blind Image Steganalysis

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.
COVER (PMS 180&amp;K) (p/u from previous issue w/updates)

Artificial intelligence (AI), including deep learning methods that leverage neural network-based algorithms, hold significant promise for dermatopathology and other areas of diagnostic pathology in research and clinical practice. There has been significant progress over past several years in applying AI to analyzing digital histopathology images for diagnosis. While much work in AI analysis of histopathology data remains investigational, recent regulatory agency approval in Europe and United States of AI-assisted tools for clinical use in histopathologic diagnosis of prostate and breast cancer herald broader movement of AI into the clinical diagnostic realm of anatomic pathology, including dermatopathology. However, significant challenges remain in translating AI from research into clinical practice, including algorithmic real-world performance, robustness to variation in data sets and practice settings, effective integration into clinical workflows, and cost effectiveness. This review introduces core concepts and terminology in AI, and assesses current progress and challenges in applying AI to dermatopathology.
Spatiotemporal Distribution for Precipitable Water Vapor and Precipitation Over Iraq during the Period (1979-2019)

Water vapor plays an important role in transporting sensible heat and latent heat and is important in cloud fashioning, and precipitation fashioning, it’s one of the more important greenhouse gases so it plays an essential role in climate change. To strengthen understanding of climate change, it is necessary to analyze the spatial and temporal PWV and P distribution and variations and association between them. This research aims to calculate Precipitable Water Vapor and Precipitation Conversion Efficiency and spatial and temporal PWV and P distribution and association between them for Iraq for the period (1979-2019). In this research temperature and dew point temperature and precipitation has been downloaded from ECMWF to calculate saturation vapor pressure and actual vapor pressure and mixing ratio and that’s necessary to calculate Precipi table Water Vapor and Precipitation Conversion Efficiency. spatial distribution and temporal variation of monthly and total annual and a seasonal average of PWV and P have been studied for twelve stations covering north, east, west, central and southern (Sulaymaniah, Zakho, Kirkuk, Mosul, Erbil, Khanaqine Baghdad, Rutba, Karbala, Smawa, Nasiryia, Amarah). The results showed that larger Precipitable water vapor does not necessarily correspond to larger PCE, as well as the Precipitable water vapor increases in the station that characterizes high temperature and location near a water source so its increase in south station and decrease in the northeast stations . While precipitation increase in stations that located in mountains region and characterize by low temperature so its increase in Sulaymaniyah, Erbil and Zakho stations. And there is a negative relation between P and PWV.
Research on College English Teaching Evaluation System Based on Data Mining Technology

with the vigorous advancement of information technology in the Internet age, various industries have been greatly affected, and the trend of combining Internet models with multiple industries is being promoted gradually. Therefore, connecting the Internet and education has slowly become popular, and data mining technology plays a central role in this process. Data mining technology analyzes the Internet information generated by students in class, extracts relevant features, and explores the relationship between students' performance in college English classrooms and the various classroom elements. At first, this article summarizes data mining and college English teaching at home and abroad. On this basis, the scenes of the students in the college English classroom are imagined, the students' habits are modeled to establish the evaluation system of college English class.
Discernment of Malaria-Infected Cells in the Blood Streak Images Using Advanced Learning Techniques

Protozoa infection, which is recognized as one of the foremost fatal diseases in the world, is a dipteran-borne illness caused by the anopheles mosquito. The parasites in mosquitoes that are known to be the cause of this deadly disease belong to the Plasmodium genus. Reliable and accurate detection of the disease at an early stage thus becomes an important task at hand. This should be done so that proper medical treatments and healthcare can be provided to the patients for a full recovery. The manual methods using a microscope, involved in the detection of the parasite often lead to inaccurate and unreliable results as they depend on the skills of the pathologist as well as the conditions of the clinic and the facilities available. Hence, automation of the process is essential so that the errors in the manual methods can be rectified and meticulous results can be yielded. Our method involves cleaning up the blood smear images obtained from the laboratories, extracting the parasite features, and then training the preprocessed dataset using Convolutional Neural Networks (CNNs). The CNN is a deep learning calculation that soaks up associations in data images, allots significance (learnable masses and inclinations) to different perspectives/protests within the image, and has the choice to separate one from the opposite. Numerous filters were used to preprocess and eliminate noise from the images obtained using the dataset. We aim to reduce the time and labor involved while simultaneously improving the accuracy so that medical staff in the less-developed areas, which are more prone to malarial infections, can use this to make a faster diagnosis.
BlockCloud: Blockchain as a Cloud Service

Blockchain-Cloud hybrid applications confirmed their usefulness in day-to-day activities; it provides more data security and safety. Now, many industries started using hybrid services of Blockchain-Cloud. This hybrid combination provides more flexibility in storage with validation of data. Authorization of transactions is monitored and increases the network elasticity. Cloud technology is a well-known, very low-cost solution for resources availability. If blockchain technology is added with cloud data and services, the cloud data security will be improved significantly. Once a valid block is created, this secured block will be sent to all other network nodes. The blockchain data uses protected blockchain cloud storage. This hybrid combination of blockchain with cloud technology provides data security, protection and transparency, definitely enhancing the service quality. This BlockCloud model will be available to the customer as a cloud service with blockchain security, i.e. cloud-based BaaS: Blockchain as a Cloud Service.
JQuery Software Architecture of University Scientific Research Management Information System Based on Web Hierarchical Data Heterogeneous Mining

This paper discusses the function design and realization idea of college student information management system using jQuery framework and AJAX technology and using multi-layer architecture, in which factory pattern, dependency injection and reflection mechanism are applied in the multi-layer architecture. Then, the SSH (Struts, Spring, Hibernate) combined architecture is used to realize the development of the scientific research funding management system in colleges and universities, and effectively solve the problem of data heterogeneity between the scientific research funding management system and other systems. It explores a low-cost and reliable way of middleware heterogeneous database to realize the integration of the original management information system. The updated data of each subsystem database is converted into XML messages through XML parsing tools, and then the JMS message service provided by the middleware application server is used.