Reviewerly/exHarmony huggingface dataset:
Web Service Selection Approach Based on Agent and Fuzzy Logic

The context of this work is the selection of the services among a list of similar services.To differentiate between similar web services, the best approach to use is the one based on service quality (QoS) criteria.However, these criteria most of the time are imprecise and sometimes uncertain and ambiguous because they are based on discrete numerical data.In some situation, we need to apply the concept of partial truth, where the partial truth values are between two numerical values.The fuzzy logic can be applied to support the representation of imprecise, uncertain and ambiguous representation.It is based on the observation that people make decisions based on imprecise and nonnumerical information.In this work, we propose an approach for selecting web services based on the fuzzy logic.Indeed, we use fuzzy logic by translating the QoS values that are attributed to services into linguistic terms.In addition, we also allow the service client to formulate its requests in the form of linguistic terms.In this process, the system selects and render the desired web service to the client.Our solution is represented as three layers, i) User Layer, that receives functional or fuzzy requests from clients which treats and forward them to the next layer, ii) Basic Layer that implements the service-oriented architecture and also, obtains the QoS values from service repository; and iii) Fuzzy Layer that takes as input the quality criteria of each web service then proceeds to their fuzzification, ranking and finally assign the scores to the different web services.To validate our solution, we implemented it as a multi-agent system.The use of the notion of agent for web services is, therefore, a major challenge to equip web services with interesting capabilities of software agents and also improve the performance of the services selection system.
Accelerating GPU computing at runtime with binary optimization

Nowadays, many applications use GPUs (Graphics Processing Units) to achieve high performance. When we use GPU servers, the idle CPU resource of the servers is often ignored. In this paper, we explore the idea: using the idle CPU resource to speed up GPU programs. We design a dynamic binary optimization framework for accelerating GPU computing at runtime. A template-based binary optimization method is proposed to optimize kernels, which can avoid the high cost of kernel compilation. This method replaces determined variables with constant values and generates an optimized binary kernel. Based on the analysis results of optimization opportunities, we replace the original kernels with optimized kernels during program execution. The experimental results show that it is feasible to accelerate GPU programs via binary optimization. After applying binary optimization to five convolution layers of deep neural networks, the average performance improvement can reach 20%.
Meta classifications for Acute Inflammations Data Set

This research work presents a decision making of healthcare operational system by using machine learning classifiers algorithm to predict the decision making in comparison to the actual decision making.This model may help to doctor for making the best decisions.This model helps us to predict Acute Inflammations.The results show that Bagging, logitBoost and Multiclassclassifier for this case study generates highest accuracy of 48.75%.I. INTRODUCTION Machine learning in today's healthcare is unavoidable.Today's healthcare needs effective methods and research methodologies to save lives, reduce the cost of the healthcare services and early discoveries of contagious diseases.Now a day's instances in healthcare such as medical image processing and analyzing, predicting healthcare operational decisions, dosage trials for intravenous tumor treatment detection and management of prostate cancer.In this research work applied in weka 3.8.3version for Meta classification method by applying various kernels namely Polykernel, Normalized Polykernel, Puk, and RBF Kernel were applied to calculate for predicting caesarian section operational decisions.In this paper organizes section one has related works and brief introduction of this fields, section two presents Materials and Methods, the section three describes results and discussions and the section four presents conclusion.
A provably secure delegated authentication scheme and its applications

In a proxy signature scheme, an original signer can delegate his/her signing capability to a proxy signer, so that the proxy signer can sign on behalf of the original signer. Proxy signature is an important technology in delegated authentication schemes, so it is important to design provably secure proxy signature schemes. Boldyreva et a1. (2012) gave the definition of proxy signature and formalised a model of security for proxy signature schemes. They not only formalised a model of security for proxy signature schemes, but also specified the adversary's capabilities and goals. In this paper, we propose a new provably secure proxy signature scheme under this model, which is more efficient than that of the existing ones. Furthermore, we use this signature scheme to construct a proxy blind signature scheme, and give the security analysis of the new scheme. Proxy blind signature can be applied in cloud computing.
Forensic opinion in questioned document based on scientific techniques

The current scenario of criminal activities has rapidly changed due to excessive use of internet facility through computer.The present trend in forensic science education and research is emphasized towards quality research in order to standardized methods and techniques to solve critical criminal cases.Document examiners always play an important role in criminal justice system, however many at times they are often encountered with number of random questions which really do not relate with the actual matter, and they are also forced to give answer during court testimony.The role of forensic document examiner while giving any opinion becomes more significant as they produce detailed scientific evidence which is better referred to as forensic evidence based on scientific principles and methodology, presented to convince the court in favour of justice.
Design knowledge in the artistic–aesthetic development and transformation of the world

The result of project activities is the adoption and implementation of decisions on the development and transformation of the world. Two related forms of project knowledge have a special influence on this process of project transformation: descriptive and prescriptive. This article contains the author’s interpretation of the concept of "project knowledge" as a set of developed historical experiences, scientific knowledges and peoples’ skills, abilities, ways, means andindividual project actions in the aesthetic transformation of the world. The purpose of this article is to consider the theoretical foundations of the formation of project knowledge in the aesthetic development and transformation of the world. An epistemological approach was implemented as the study’s methodology.
UPAYA PENINGKATKAN HASIL BELAJAR SISWA DALAM MATA PELAJARAN IPS MELALUI METODE FEEDBACK PARTNER (UMPAN BALIK) PADA SISWA KELAS IV SDN 18 BATANG GASAN

Based on the learning outcomes of Class IV students at SDN 18 Batang Gasan in social studies subjects it was found that student learning outcomes in social studies subjects were still very low. The average student learning outcomes are still under the KKM. The purpose of this study is to describe and obtain information about efforts to improve student learning outcomes in sub-social studies subjects. Explain the relationship between structure, function, and processes and disorders / diseases that can occur in the excretion system in humans and animals (fish and insects) through the method Feedback Partner in Class IV SDN 18 Batang Gasan. This research is a classroom action research. The procedure of research in this study includes planning, action, observation and reflection. This study consisted of two cycles with four meetings. The subjects of the study consisted of 30 students of Class IV SDN 18 Batang Gasan. Research data was collected using observation sheets and daily tests. Data were analyzed using percentages. Based on the results of research and discussion that have been put forward, it can be concluded that the Feedback Partner Method (Feedback) can improve student learning outcomes in sub-social studies subjects Explain the relationship between structure, function, and processes and disorders / diseases that can occur in the excretory system in humans and animals (fish and insects) at SDN 18 Batang Gasan. Student learning outcomes from cycle I to cycle II. The learning outcomes of students in the first cycle were 55.33 (Enough), increasing to 84.43 (Good) with an increase of 29.10%.
A Survey on-Confidentiality Preserving in Instant Runoff Voting Method

The E-voting promises the chance of convenient, straightforward and economical.Recently in cryptography some modifications guaranty to allow us to run difficult algorithms within the encrypted domain.During this state of matter, Majority technique may be a new scheme for a brand new electoral system.This system is with lots of mark able advantages, means a lot of concerned tallying method than first-past-the-post selection.To protect voter's privacy, a method must be done b solely manipulating encrypted knowledge by Instant-runoff selection (IRV).Generally IRV referred to as hierarchic order selection, permits voters to rank their preferences for a specific workplace among multiple candidates.Though the precise strategies of vote calculations will vary, within the finish the system is determined to make sure that the winner has the support of a majority of voters.This scheme will effectively ensure confidentiality and integrity of ballot in instant runoff voting method.
KOMPRESI MULTILEVEL PADA METAHEURISTIC FOCUSED WEB CRAWLER

Focused Web Crawler is a method for finding websites that match the search properties desired by the user.This method is slower than the method for web crawlers in general, namely the DFS (Depth First Search) algorithm and the BFS (Breadth First Search).To overcome this, the Focused Web Crawler search is enhanced with the metaheuristic cuckoo search.This method combined with the search on history search data stored in the system.But it stores more data every time the link searches, which increase the required space for stored data.A data compression method is proposed, which reduces data size and keeps the value of stored information.This proposed compression method is a multilevel compression which uses two compression methods, namely reducing prefix and postfix words, and string-based dictionary compression by making dictionary index words.The results of the word dictionary string compression are encoded data.The performance of this data compression is evaluated by comparing the results of search links using the KMP (Knutt Morris Pratt) method of uncompressed data with compressed data.The result shows the maximum precision with a value of 1 while the recall is 0.73.It is also found that the average file compression ratio is 36.4%.
ON THE ROLE OF THE LEADER IN MANAGEMENT PSYCHOLOGY

The problems and specificity of the use of psychological methods in management activities are considered. Analyzed the possibility of applying the psychological competencies of managers to stimulate labour and manage employee motivation. Special attention is paid to the analysis of the personality of the leader and his role in reducing conflicts in the workplace. In conclusion, the conclusion is made about the need to improve the level of psychological education of managers.
A decision system based on active perception and intelligent analysis for key location security information

In various enterprises, the security data are manually entered by multiple security workers at different times, which can lead to disordered data in the system, and also, analysis decision files need to be manually processed. To solve these problems, this paper presents a decision system for key location security information based on active perception and intelligent analysis. First, the designed system is developed based on C/S framework. Then, a deep learning perception model is constructed. Experimental results show that this system can significantly reduce the heavy workload of security inspectors, and reduce the frequency of safety accidents.
Improving Reading Comprehension Through Think-Pair-Share (TPS) Technique Students of STIK Siti Khadijah Palembang

The objectives of this study were to find out : (1) the significant improvement on the third semester students’ reading comprehension before and after being taught using Think-Pair-Share technique at STIK Siti Khadijah Palembang, South Sumatera, Indonesia; and (2) the significant difference on students’ reading comprehension between the students who were taught by using Think-Pair-Share technique and those who were not. The population of this study was all the third semester students of STIK Siti Khadijah Palembang which consist of 56 students in academic year 2018/2019. The sample of this study was taken by using total sampling. Thus, the total number of the sample was 56 students. The sample was the third semester students at D.III Nursing Study Program (experimental group) which consist of 28 students and the third semester students at S1 Nursing Study Program (control group) which consist of 28 students. The test was given twice to both experimental and control group. True experimental design was used to analyzed the data. To verify the hypotheses, the data used only posttest design to analyzed by using paired sample t-test and independent sample t-test was 0.005 which was lower than 0.05.The result of this study showed that Reading Comprehension by using Think-Pair-Share technique gave significant improvement on the students’ reading comprehension and gave significant difference between students’ who were taught by Think-Pair-Share technique and those who were not.
IMPLEMENTING COLLABORATIVE STRATEGY TO IMROVE READING COMPREHENSION THE ELEVENTH GRADERS OF SMK KERTHA WISATA MALANG

ABSTRACT&#x0D; In this classroom action research, the researcher used the model of classroom action research developed by Kemmis and Mc Taggart (1999). There are four steps of teaching. Before doing those four steps, the researcher did reconnaissance step by observing the class situation and interviewing the class teacher and the students to know the problems. After knowing the problems, the researcher started to do the four steps of teaching they were planning, implementing, observing, and reflecting. The findings of this result showed that teaching reading comprehension using collaborative strategic reading improved the students` reading comprehension skill. In the first cycle the result was not satisfactory. The students were still passive in class because they did not understand about the method and many of them still found difficulty in understanding the texts. Their mean score of the first cycle was under the MMC. The criterion of success is when students give good response to this method, and also get the mean score that reach the MMC. After implementing the second cycle, the researcher found that the students were more enthusiastic because they knew about the topics of the texts and enjoyed comprehending the texts using CSR. They felt that the method was not boring. Besides that, the students` mean score was 72.85. The second cycle succeeded and proved that the students` mean score improved. It was above the MMC.
Microsoft Teams Approaches to Solve Collaboration Needs

Team collaboration in organizations is an effort to facilitate better work delivery and employee engagement.Most of organizations has emphasized on its employees collaborating at the work place.However, there are short comings from team collaboration which should be solved to facilitate better team work.Microsoft Teams collaboration facilitates bringing communication tools in one gathering and sharing working space.This paper will discuss, and elaborate approaches of Microsoft Teams have been using to solve collaboration problems experienced in different work teams.Team collaboration is an important aspect in ensuring teams will work better in collaboration.Team collaboration is important because it facilitates working better in the organization and builds team work among team members.Work and business management through team work is easy because members of the team corporate to instill change in the organization that helps to businesses to achieve their goal.
Dialectical Logic and Boolean Algebra

Dialectical logic was founded by German famous philosopher F. Hegel, but it has not been laid on mathematics for a long time. In this paper author explains the dialectical logic pure mathematically, and shows that the classic formal logic, its mathematical expression is Boolean algebra(includes multiple value system), is a special case from dialectical logic, and the true-valued function for dialectical logic is a continuous function valued on closed interval &amp;nbsp;and defined on time-space axes system. The Aristotle three laws of formal logic are expanded into expression of dialectical logic, and Russell paradox is expanded into the case of multiple order. Some new theorems for Boolean operators and the matrix expression for De Morgan&amp;rsquo;s theorem of multiple variables dialectical logic are given. At the end of the paper, linear or nonlinear dialectical logic are defined and analysis properties of dialectical logic true-valued function are pointed.&amp;nbsp;
Describing the Students’ Grammatical Errors on Spoken English

This present study describes the students’ grammatical errors on spoken English based on the classifications of errors refer to Dulay, Burt and Krashen’s theories. Qualitative method was used in the study. Oral test was used as the research instrument. There were 25 participants of English education study program of Timor University who were chosen randomly as the research sample. The Tape Video Recording (TVR) was used to gain data of spoken English. There were five techniques in analyzing the data: transcription, codification, classification, analyses and discussion. The results of data analyses revealed that omission presented 40,87% of errors. Then; addition presented 31,74% and misformation presented 15%. The misorderning was categorized as the lowest score with 12,30%. In linguistic category; the data showed that verb was categorized as the highest errors which presented 19% of errors. The next error was preposition which presented 17%. Then pronouns category presented 14% of errors. The conjunction and article categories presented 11% of errors on spoken English. The singular/plural and negation categories presented 10% of errors for each category. The lowest error of linguistic category was word order which presented 8% errors. The findings showed that the students still make errors on linguistic category on spoken English. There was a phenomenon in this finding that the students tend to use verb-ing instead of using verb-1 in the spoken English. They dispose to add and omit any linguistic category unconsciously when they speak.
Image Feature Layered Indexing Method for Transparent Access

In the data transparent access process, it is often necessary to query the data accurately to find the location of the data that the user needs to access. This paper studies the image feature organization and indexing of image data based on image content retrieval, and uses the image plane position constraint relationship to propose an image feature layered index method. In the process of image transparent access, data storage management needs to detect and extract local feature information of the image (such as SIFT feature points), and then design appropriate data structures to organize and index massive high-dimensional feature vectors, and in a specific storage structure. Design an efficient and accurate feature search algorithm. The paper mainly includes two parts: LSH high-dimensional indexing algorithm for thumbnails and KD-Tree high-dimensional indexing algorithm based on improved position information.
A K-Means Based Multi-level Text Clustering Algorithm for Retrieval of Research Information

Academic researchers in institutions of higher learning and research institutes use research outputs and metadata throughout their research work and to help in identifying research collaborators as well as getting to know existing research.Research outputs range from academic theses, journal and conference articles, books and book chapters, and datasets while research meta-data includes authors, affiliations, research areas, and projects, among others.However, access and retrieval of relevant research outputs and metadata remains a major challenge.As a result there is duplication of research, fewer opportunities for networking, and difficulty in detecting scientific fraud.Efforts need to be made to make academic research outputs and meta-data readily available and easy to retrieve.The main purpose of this work is to develop a tailor-made approach to information retrieval for the retrieval of research information and related meta-data.Therefore, the paper presents a multi-level text clustering algorithm for retrieval of scholarly research outputs and metadata from a central repository through a web based interface.The algorithm first clusters SQL data records that represents meta-data at the first level, then retrieves and clusters text documents representing research outputs at the second level.The algorithm was tested on retrieving information in the areas of text clustering, cloud computing, banking, HIV/AIDS, food security and cancer.The results show that it enables researchers to retrieve relevant information according to their information needs.To enable further enhancements and improvements, the algorithm will be released to the public domain for use in similar application domains or extension by other researchers.
Data-Driven Approach to Multiple-Source Domain Adaptation

A key problem in domain adaptation is determining what to transfer across different domains. We propose a data-driven method to represent these changes across multiple source domains and perform unsupervised domain adaptation. We assume that the joint distributions follow a specific generating process and have a small number of identifiable changing parameters, and develop a data-driven method to identify the changing parameters by learning low-dimensional representations of the changing class-conditional distributions across multiple source domains. The learned low-dimensional representations enable us to reconstruct the target-domain joint distribution from unlabeled target-domain data, and further enable predicting the labels in the target domain. We demonstrate the efficacy of this method by conducting experiments on synthetic and real datasets.
Application of a New Segmentation Algorithm in Submarine Manganese Nodule Statistics

To solve the problem of particle overlapping in the statistics of submarine manganese nodules, a new algorithm is proposed in this paper. According to the natural round nucleus shape of manganese nodule particle, a substitution circle is used to replace the particle approximately. Firstly, the centroid of particle obtained by calculating is regarded as the center of the substitution circle. Then, the distance between the circleâ€™s center and the boundary of the particle is obtained, and the distance plus to a modified constant as the radius of the substitution circle. Finally, the intersection points of two substitution circles are looked upon as the pair of segmentation points, and the manganese nodule particles is segmented by connecting a line between the pair of segmentation points. From experiments results, itâ€™s shown that the accuracy of statistics is over 98% after processed by the new algorithm, which proved the proposed algorithm is effective.