Reviewerly/exHarmony huggingface dataset:
AN OPTIMIZED PAGE RANK ALGORITHM WITH WEB MINING, WEB CONTENT MINING AND WEB STRUCTURE MINING

With the rapid increase in internet technology, users get easily confused in large hypertext structure. The primary goal of the web site owner is to provide the relevant information to the users to fulfill their needs. In order to achieve this goal, they use the concept of web mining. Web mining is used to categorize users and pages by analyzing the users‟ behaviour, the content of the pages, and the order of the URLs that tend to be accessed in order. Most of the search engines are ranking their search results in response to users' queries to make their search navigation easier. With a web browser, one can view web pages that may contain text, images, videos, and other multimedia, and navigate between them via hyperlinks. It is very difficult for a user to find the high quality information which he wants. Page Ranking algorithm is needed which provide the higher ranking to the important pages. In this paper, we discuss the improvement of Page ranking algorithm to provide the higher ranking to important pages. Most of the search engines are ranking their search results in response to user’s queries to make their search navigations easier.
MODEL OF HISTORY EDUCATION LABORATORY MANAGEMENT

The background of this research is based on the importance of forming professionalhistory teacher candidates in accordance with the above mentioned expectations,the Department of Historical Education needs to empower and develop the HistoryLaboratory as a superior program. The History Education Laboratory is centered onthe field of science, a place of authority and academic integrity. The HistoryEducation Laboratory was formed in order to meet the needs of the department andthe development of academics. The main limitation of this research problem is"what is the model of Management of Historical Education Laboratory in HigherEducation from the Organization and Administration aspects? Qualitative researchmethods are research procedures that produce descriptive data in the form ofwritten or oral words from and observable behavior. The objective of the researcherto use a qualitative approach is to look for a complex and holistic description of thesubject matter studied in this regard regarding the management model of theHistorical Education laboratory in tertiary institutions.
A Neural Network Language Document Representation Technique for Web-Page Classification

The task of assigning a web page to the correct category is getting cumbersome because of the influx of digital documents on the World Wide Web.The performance of applications such as web directories, question and answering system, web content filtering systems depends on the key performance of automatic web page classification systems.From extant literature, the performance of web page classification system depends on adequate textual representation of the web content.Several statistical document representation techniques such as bag of words models, ngrams models and topic models have been proposed by authors to capture the real semantics of web documents but are fraught with several challenges such as semantic mismatch, multiple meanings of words.Thus, this paper proposes a recent neural network language model (Doc2Vec) which utilizes document embedding's to solve the document representation problem of web page classification system.Results obtained confirms the earlier assumption that Doc2Vec performs robustly on very high dimensional text such as web documents, it also capture the real semantics of the web document.
ZEBRAFISH MODEL IN THE DEVELOPMENT OF COVID-19 RAPID TEST

In order to search for new alternatives for rapid tests, our research group prospected a strategy to develop a rapid COVID-19 patient detection and tracking kit, using zebrafish model
Enhanced Particle Swarm Optimization for Path Planning of Unmanned Aerial Vehicles

This paper presents an enhanced particle swarm optimization (PSO) for the path planning of unmanned aerial vehicles (UAVs). An evolutionary algorithm such as PSO is costly because every application requires different parameter settings to maximize the performance of the analyzed parameters. People generally use the trial-and-error method or refer to the recommended setting from general problems. The former is time consuming, while the latter is usually not the optimum setting for various specific applications. Hence, this study focuses on analyzing the impact of input parameters on the PSO performance in UAV path planning using various complex terrain maps with adequate repetitions to solve the tuning issue. Results show that inertial weight parameter is insignificant, and a 1.4 acceleration coefficient is optimum for UAV path planning. In addition, the population size between 40 and 60 seems to be the optimum setting based on the case studies.
Using OCLC WorldCat to Survey Government Publications in a Library’s Collection

A method to evaluate a library’s government information collection using OCLC’s WorldCat is described. By searching material type codes for government publications, and limiting the search to an owning library, it is possible to find the number of cataloged government publications in a library’s collection. The system can be used to identify the age of government publications in a library, the number of items on a given subject, and find publications on a topic from a specific time period. This method of analysis is especially useful for analyzing government information collections when publications are cataloged into a library’s main collection. The search technique can be used to generate statistics on government publication collections which can be used to prepare reports on library collections and materials.
Comparative study of red blood cell morphology in peripheral smear and automated cell counter

Background: Automated cell counters are a very important part of pathology laboratory for evaluation of complete blood count (CBC). They also provide RBC histograms to interpret differentmorphological variations of Red Blood Cells.These histograms and other parameters have been found veryuseful in diagnosing various hematological conditions and Red Blood Cell disorders if they are correctly interpreted.Examination of peripheral smears is still the gold standardfor diagnosing some of the RBC disorders which might not be diagnosed otherwise by automated cell counters. They play an important role in quality check of automated analyzers. Materials and Methods:In this prospective study we have taken 200 samples over a period of 6 months. We did comparative study between RBC histograms obtained by automated hematology analyzer and peripheral blood smears stained by field stain. We have discussed morphological variations of red blood cells and their characteristic changes in respective RBC histograms. Result:Out of 200 samples of RBC histogram interpretation, 138 cases showed correlation with peripheral smear findings while 62 cases showed discrepancies. Conclusion: Microscopic examination of peripheral blood smear still remains gold standard for diagnosis of various hematological conditions.
QR based management system for plants shopping center

&lt;span&gt;It is well known that the development in the life style requires a robust enhancement in the provided services based on technologies. This paper suggests a mobile application under android environment that manages the information and sale systems regarding plants shop. The proposed application uses the Quick Response (QR) codes as identification of an object (plant). The proposed system includes two parts: server and client. The server side contains the most software application, such as database, while the client (mobile) side runs the website based interface between the application and users. QR tag is attached to each plant on the farm to be read by visitor’s mobile camera and sent to the server side using the designed web application. The received QR code is processed by the server and preparing the response with full information of a plant to be sent back to the mobile for user viewing. In addition, the proposed system offers a sale service to the user after performing registration. The proposed system is tested over different case studies and the obtained results show the efficiency of its performance.&lt;/span&gt;
On the Reversibility of Discretization

“Discretization” usually denotes the operation of mapping continuous functions to infinite or finite sequences of discrete values. It may also mean to map the operation itself from one that operates on functions to one that operates on infinite or finite sequences. Advantageously, these two meanings coincide within the theory of generalized functions. Discretization moreover reduces to a simple multiplication. It is known, however, that multiplications may fail. In our previous studies, we determined conditions such that multiplications hold in the tempered distributions sense and, hence, corresponding discretizations exist. In this study, we determine, vice versa, conditions such that discretizations can be reversed, i.e., functions can be fully restored from their samples. The classical Whittaker-Kotel’nikov-Shannon (WKS) sampling theorem is just one particular case in one of four interwoven symbolic calculation rules deduced below.
INCREASING TEACHERS’ ICT-COMPETENCY LEVEL IN THE AFTER-GRADUATE EDUCATION PROCESS

ПІДВИЩЕННЯ ІКТ-КОМПЕТЕНТНОСТІ ВЧИТЕЛІВ У ПРОЦЕСІ ПІСЛЯДИПЛОМНОЇ ОСВІТИThe relevance and problems of improving levels of non-informational teachers ' ICT competencies are presented in the article.The researches and publications, which consider various competencies concept aspects concerning the use and possession of information and communication technologies and these competencies levels are analyzed.The advanced training courses "Implementation of Information Technologies in the Educational Process" are conducted at Sumy Makarenko State Pedagogical University, which acquire the basic skills of using information technologies, global network services and the theoretical knowledge.The program content of the indicated courses is presented in the article.The motivation problems analysis concerning the teachers' use of information technologies in their own professional activity was conducted.The courses urgency and demand is explained by the fact that adult people spend much time developing new technologies and soon lose their already acquired skills due to the irregular practice, which requires repetition of working methods with technical means and applications, are unsure working with technical means, feel fear of doing wrong actions, in many cases, require individual training under constant assistant's presence, which reduces the self-employment effectiveness.The courses purpose is to form the students' ability to solve professional problems and problems through the information technology introduction in the educational process.Also important is the inverse cooperation with students after such course's completion.During the survey and questionnaire, it was found out that during further self-training some teachers, who had attended time courses, improved their knowledge and skills.Thus, the next ICT competence level was formed.In this case, Moodle -educational content environment was used in teachers' practical work; computer testing programs, authors' blogs, cloud data storages, multimedia presentations for lectures, seminars, speeches at departments meetings; scientific repository of the university scientific library and the science-research base of Google Scholar was updated and more.
The Fuzzy Multiple Correlation and Its Application to Determine the Correlation of Math Anxiety with Math Self-Efficacy and Attitude

The use of the fuzzy number is not doubtful in psychological domain.The fuzzy number provides a more real and flexible conception of psychology variable.The correlation between two variable and its form of fuzzy data can't be determined by using Pearson correlation.The correlation analysis to analyse two fuzzy correlations has been majorly introduced by some experts.Meanwhile, this article is aimed at determining multiple fuzzy correlation formula based on multiple traditional correlations.Henceforth, to demonstrate the multiple fuzzy correlation formula, the three psychological variables are involved; those are the mathematical anxiety and efficacy as well as the attitude toward mathematics.These three variables were taken from 245 respondents; students of vocational high school 11th grade.The comparison analysis between fuzzy multiple correlation and traditional multiple correlation is finally discussed in this article.
Publisher Correction: Evolutionary transcriptomics of metazoan biphasic life cycle supports a single intercalation origin of metazoan larvae

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Knowledge Discovery: From Uncertainty to Ambiguity and Back

Knowledge Discovery in Databases is concerned with the development of methods and techniques for making sense of data. Its aim is to model the shapes of distributions and to discover patterns. During the knowledge acquisition process choices are made. Uncertainty and ambiguity hinder the process and “poor” choices cannot be avoided. Uncertainty corresponds to situations in which the choices are unclear and/or their consequences difficult to measure. Ambiguity arises from the lack of context, there is not sufficient information to assure the success of the choice, thus causing confusion. And decision making is hampered by perceptions of uncertainty and ambiguity. Medical diagnosis/prognosis is a complex decision making process. In this paper we present a comparative study of model ambiguity on breast cancer predictions. Automatic classification of breast cancer on mammograms using two models, logistic regression and artificial neural networks are considered. The models were trained and tested to separate malignant and benign tumors for two different scenarios. Ambiguity in the prediction was studied for the different models. The results show that a measure of uncertainty is practical to explain observable phenomena, such as medical data. Since model ambiguity can rarely be avoided, ordering alternative models by their degree of ambiguity is crucial in medical decision making processes. Furthermore, the levels of uncertainty and ambiguity are relevant in the knowledge representation process and open up new possibilities for richer Data Mining tasks.
Tree-Structured Correlation Filters for Robust Visual Tracking

In recent years, correlation filter based trackers have significantly advanced the state-of-the-art in visual tracking. However, most existing correlation filter based tracking algorithms update target object model assuming that target appearances change smoothly over time. This assumption may not be appropriate for handling more challenging situations such as occlusion, deformation, illumination variation, and abrupt motion, which may break temporal smoothness assumption. To address these issues, in this paper, we propose a novel treestructured correlation filters (TCF) for diverse target object appearance modeling, where multiple correlation filters collaborate to estimate target states and determine the desirable paths for online model updates in the tree. As a result, the proposed TCF tracker has the advantages of both CNNs and correlation filter based trackers. Furthermore, our TCF tracker can preserve model reliability by smoothly updating deep correlation filters along the path in the tree, and make the learned appearance models sufficiently diverse and discriminative. Extensive experimental results on two challenging benchmark datasets demonstrate that the proposed TCF tracking algorithm performs favorably against the state-of-the-art trackers.
PEDAGOGICAL TECHNOLOGY FOR THE FORMATION OF RESPONSIBILITY IN CHILDREN OF PRESCHOOL AGE

The success of responsibility formation will depend on the implementation of the pedagogical technology of responsibility formation, which implies the consistent implementation of such stages in the educational process of the preschool institution as the formation of ideas about responsibility and motivation of the activities performed, the development of practical skills for the manifestation of responsible behavior in various activities, the conscious independent use of the accumulated experience of responsible behavior in the process of own activities.
Iterative Controller Synthesis for Multirobot System

The synthesis problem is to construct a system fulfilling some specific requirements when interacting with the environment, which is one of the most crucial and challenging tasks in robotics. In comparison to the case of dealing with a single robot, synthesizing of a system constituted with multiple robots is, in general, much more involved. Actually, information is shared among robots in the latter case, and for a fixed robot, when fictively merging the rest ones into its environment, we are confronted with imperfect description of environments. In this article, we present an iterative controller synthesis approach to dealing with multirobot systems. In our model, the behaviors and outputs of one robot can be observed by the other ones, as a part of their inputs. To make our model more flexible, we allow the mechanism of “partial observation,” namely, only a part of outputs can be observed by other robots on some particular sensors. Our synthesis approach is conductive in an iterative manner. By analyzing the dependence among robots, we first try to synthesize controllers for some of them and then extract a set of invariants from the solved part to refine other ones. Repeatedly and iteratively using this way, we may arrive at a complete solution. Meanwhile, in comparison to the monolithic approach, using the iterative manner usually produces a much more compact result, which means that the size of the controller is smaller.
xTML: A Unified Heterogeneous Transfer Metric Learning Framework for Multimedia Applications [Application Notes]

Owing to the continual growth of multimodal data (or feature spaces), we have seen a rising interest in multimedia applications (e.g., object classification and searching) over these heterogeneous data. However, the accuracy of classification and searching tasks is highly dependent on the distance estimation between data samples, and simple Euclidean (EU) distance has been proven to be inadequate. Previous research has focused on learning a robust distance metric to quantify the relationships among data samples. In this context, existing distance metric learning (DML) algorithms mainly leverage on label information in the target domain for model training and may fail when the label information is scarce. As an improvement, transfer metric learning (TML) approaches are proposed to leverage information from other related domains. However, current TML algorithms assume that different domains explore the same representation; thus, they are not applicable in heterogeneous settings where the data representations of different domains vary. In this research, we propose xTML, a novel unified heterogeneous transfer metric learning framework, to improve the distance estimation of the domains of interest (i.e., the target domains in classification and searching tasks) when limited label information, complementary with extensive unlabeled data, is provisioned for model training. We further illustrate how our proposed framework can be applied to a selected list of multimedia applications, including opinion mining, deception detection and online product searching.
THE USE OF PRONUNCIATION BINGO GAME TO IMPROVE STUDENTS’ PRONUNCIATION

This research is mainly purposed to find out whether there is influence of using pronunciation bingo game to improve students’ pronunciation at first grade in MTs Alkhaeriyah Kepandean Ciruas Serang. The game is applied by experiment class and control class. The method of this research is true-experiment research. The population in this research is the first grade in MTs Alkhaeriyah Ciruas Serang. The writer took three classes with total number of the first grade are 132 Students. They are three classes, 44 Students from class VIIA and 44 Students from class VIIB and 44 Students from class VIIC. The writer took 60 students as sample and uses random sampling because the writer uses true-experiment method. To analyze this research the writer uses T-test method and to get the data the writer uses observation technique, and test as instrument of research. The observation is to know the students’ pronunciation at the first grade in MTs Alkhaeriyah Keoandean Ciruas Serang, while, test is to know the influence use of pronunciation bingo game to improve students’ pronunciation at the first grade in MTs Alkheriyah Kepandean Ciruas Serang. After having analysis data, there is influence using of pronunciation bingo game to improve students’ pronunciation between experiment class and control class, based on the calculation is know that t table with level significance 5 % = 2,00 and with level significance 1% = 2,65 so tobservation n = 20,34 &gt; t table = 2,00 or tobservation n = 20,34 &gt; t table = 2,65.the conclusion is that the writer reject H0 : to &lt; tt . It means there is no influence the use of pronunciation bingo game to improve students’ pronunciation at the first grade in MTs Alkhaeriyah Kepandean Serang and receive Ha : to &gt; tt. it means there is influence the use of pronunciation bingo game to improve students’ pronunciation at the first grade in MTs Alkhaeriyah Kepandean Ciruas Serang.
Random Forests with a Steepend Gini-Index Split Function and Feature Coherence Injection

Although Random Forests (RFs) are an effective and scalable ensemble machine learning approach, they are highly dependent on the discriminative ability of the available individual features. Since most data mining problems occur in the context of pre-existing data, there is little room to choose the original input features. Individual RF decision trees follow a greedy algorithm that iteratively selects the feature with the highest potential for achieving subsample purity. Common heuristics for ranking this potential include the gini-index and information gain metrics. This study seeks to improve the effectiveness of RFs through an adapted gini-index splitting function and a feature engineering technique. Using a structured framework for comparative evaluation of RFs, the study demonstrates that the effectiveness of the proposed methods is comparable with conventional gini-index based RFs. Improvements in the minimum accuracy recorded over some UCI data sets, demonstrate the potential for a hybrid set of splitting functions.