Reviewerly/exHarmony huggingface dataset:
EFEKTIVITAS PENGGUNAAN E-LEARNING BERBASIS SCHOOLOGY DENGAN MENGGUNAKAN MODEL DISCOVERY LEARNING TERHADAP PRESTASI BELAJAR SISWA PADA MATA PELAJARAN SISTEM KOMPUTER KELAS X MULTIMEDIA SMK NEGERI 6 SURAKARTA PADA TAHUN PELAJARAN 2015/2016

The purpose of this study was to determine (1) differences in student achievement between the experimental class and control class which given a treatment the use of e-learning-based Schoology using discovery learning models; (2) the effectiveness of the use of e-learning-based Schoology using a model of discovery learning in improving student achievement. The population of this study was students of X grade multimedia in SMK Negeri 6 Surakarta. The sampling technique that is used was random sampling. This research method is using quasi experimental. Data collection techniques in this study is using observational methods to determine the management of learning before and after treatments the use of e-learning-based schoology using a model of discovery learning. Methods of documentation to determine the list of names, the number of students, daily value and research evidence were taken by picture. The test method to determine the results of pretest and posttest. Analysis of the data used is non parametric test using the Mann Whitney test and the Wilcoxon signed rank test. Based on this research, first, there is a difference between the posttest value between control class and the experimental class after being given treatment such as the use of e-learning-based schoology using discovery learning models, sig value is smaller than the significance level 0,05 which is 0,000 &lt;0.05. Second, the use of e-learning based schoology using discovery learning is more effective, with an increase in the value of gain of 0,94. While conventional learning provides increased in the value of gain of 0,74.
APPLICATION OF PROMOTION, MAP AND EXISTING TOURISM INFORMATION SYSTEMS IN SOLOK SELATAN DISTRICT USING ANDROIDJAVA PROGRAMMING LANGUAGE

The development of technology and information is felt very rapidly and this affects aspects of work that make work easier, one of which is the development of mobile technology, information media can now be made in the form of mobile applications, using mobile technology in the form of tourist applications, which provide information - information about tourism in the district of Solok Selatan, the search for tourism information in the district of Solok Selatan will be more practical to use and users can use this application wherever they are, this application can be used as a medium of knowledge about tourism in Solok Selatan district. This Solok Selatan tourist application is expected to be able to provide more knowledge about Solok Selatan tourism to the wider community, especially the people of Solok Selatan District
A Hybrid Privacy Preserving against Multi-attacks for Network Data Publication

Network trace data provides valuable information which contributes to model network behavior, defends network attacks, and develops new network protocols. Therefore, releasing network trace data is highly demanded by researchers and organizations to promote development of network technologies. However, due to the sensitivity of the network track data, it is a potential risk for organizations to publish the original data which may expose their commercial confidentiality and customers’ privacy within their networks. Several methods have been proposed to prevent network track attacks, such as statistical fingerprinting and injection. Unfortunately, they are not sufficient to protect privacy because adversary can use more background knowledge to reach the intended attack, and this kind of attack is proved to be used. This paper proposed an attack model named Multi-Attacks by using more background knowledge. For this attack model, it extracts the inherent graphics structure between the source and destination IP addresses in the network trace data and proposes a solution, data swapping, to prevent the target host from being recognized, which is based on k-anonymity. Combined with other protection techniques, our method can effectively prevent this Multi-Attacks model while preserving the data utility and providing formal guarantees of confidentiality protection. And using data swapping method for privacy protection can provide a more perfect solution, reach a higher level of privacy protection and guarantee good data utility related to the anonymity-based approach. Lastly, our proposed algorithm is applied to different real datasets and demonstrate its effectiveness over several existing network trace data anonymization techniques.
Contradiction Management in Intent-driven Cognitive Autonomous RAN

&lt;div&gt;Intent Based Networks (IBNs) are mainly used to transform a user's intent into network configuration, operation, and maintenance strategies. IBN is a prominent feature for designing the AI-enabled next generation networks. In this paper we propose intent-driven orchestration of cognitive autonomous RAN for managing network control parameters.&lt;/div&gt;&lt;div&gt;Our proposed design enables the Controller to detect and remove contradiction, which may arise from a single intent, in the runtime. We also provide a brief overview of existing standards on this aspect and standardization impact of our research to show that it conforms with the worldwide mobile network management standardization efforts.&lt;/div&gt;
Editorial for Volume 9 Issue 2

Differential privacy is a promising approach to privacy-preserving data analysis that provides strong worst-case guarantees about the harm that a user could suffer from contributing their data, but is also flexible enough to allow for a wide variety of data analyses to be performed with a high degree of utility. Researchers in differential privacy span many distinct research communities, including algorithms, computer security, cryptography, databases, data mining, machine learning, statistics, programming languages, social sciences, and law.&#x0D; Two articles in this issue describe applications of differentially private, or nearly differentially private, algorithms to data from the U.S. Census Bureau. A third article highlights a thorny issue that applies to all implementations of differential privacy: how to choose the key privacy parameter ε,&#x0D; This special issue also includes selected contributions from the 3rd Workshop on Theory and Practice of Differential Privacy, which was held in Dallas, TX on October 30, 2017 as part of the ACM Conference on Computer Security (CCS).
Needs Assessment of the Participants of Computer Literacy Program (CLIP) in Partner Community

Determining the needs of the participants in a community extension program prioritizes the topics that they will be interested to attend. This ensures that participants are motivated and interested in various topics presented in the program. The study assessed the needs of participants from Village Looc, Mandaue City, Cebu, Philippines, on the computer literacy program (CLIP) offered by the UCLM College of Computer Studies. The findings of the study were the basis for a proposed annual extension program plan for June 2018 to May 2019.Findings revealed that the top ten needs were: computer assembly, computer troubleshooting, Microsoft Word, Microsoft Powerpoint, Internet cable termination, game development, web design, mobile application, keyboarding, and hard disk installation.Determining the needs of the participants prioritizes the topics that they will be interested to attend. This ensures that participants are motivated and interested in various topics presented in the computer literacy training program.Keywords: Computer assembly; computer troubleshooting; Microsoft Word; Microsoft Powerpoint; Internet cable terminationRecommended citation: Semblante, J. A. &amp;amp; Amparado, M. A. P. (2020). Needs Assessment of the Participants of Computer Literacy Program (CLIP) in Partner Community. Cebu Journal of Computer Studies, 2(1), 91-100.
Speech Encryption using Advanced Encryption Standard for Secured Communication

Securing speech communication is a great challenging task and interesting research area in recent years. Transmission of voice data over untrusted networks leads to attack the confidential information. Various speech encryption algorithms are in progress and even though speech data have been encrypted some additional features are still getting compromised to the eavesdroppers which are a get setback for security attacks. The state-of-art of Advanced Encryption Standard (AES) algorithm when compared to other encryption algorithm it has different types of cipher key length such as 128,192 and 256 bits respectively. Advanced Encryption Standard is analyzed statistically for revealing its superiority based on confusion and diffusion properties for evaluating the robustness against statistical attacks. A novel approach is developed for encrypting speech data using Advanced Encryption Standard (AES). Encrypted and the decrypted signal are evaluated based on some quality analysis for immunity checking against frequency-domain attack, brute force attack and statistical attack etc.
Algorithms for Detection Gender Using Neural Networks

In this paper, we investigate two neural architecture for gender detection tasks by utilizing Mel-frequency cepstral coefficients (MFCC) features which do not cover the voice related characteristics. One of our goals is to compare different neural architectures, multi-layers perceptron (MLP) and, convolutional neural networks (CNNs) for both tasks with various settings and learn the gender -specific features automatically.
Selfie phishing

Phishing websites are increasingly asking victims to upload selfies as well as copies of identity documents, according to a new report by Kaspersky. This is because many services now require users to provide an ID photograph for registration and identity purposes.
A Conceptual Dependency Graph Based Keyword Extraction Model for Source Code to API Documentation Mapping

Natural language processing on software systems usually contain high dimensional noisy and irrelevant features which lead to inaccurate and poor contextual similarity between the project source code and its API documentation. Most of the traditional source code analysis models are independent of finding and extracting the relevant features for contextual similarity. As the size of the project source code and its related API documentation increases, these models incorporate the contextual similarity between the source code and API documentation for code analysis. One of the best solutions for this problem is finding the essential features using the source code dependency graph. In this paper, the dependency graph is used to compute the contextual similarity computation between the source code metrics and its API documents. A novel contextual similarity measure is used to find the relationship between the project source code metrics to the API documents. Proposed model is evaluated on different project source codes and API documents in terms of pre-processing, context similarity and runtime. Experimental results show that the proposed model has high computational efficiency compared to the existing models on the large size datasets.
Intellectual Property Enforcement Program (DOJ)

Federal Grants & ContractsVolume 44, Issue 7 p. 4-5 Grant Alerts Intellectual Property Enforcement Program (DOJ) First published: 29 February 2020 https://doi.org/10.1002/fgc.30945Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume44, Issue75 March 2020Pages 4-5 RelatedInformation
PENGGUNAAN MODEL POE2WE DALAM MATERI ELEKTROMAGNETIK UNTUK MENINGKATKAN PEMAHAMAN KONSEP DAN MOTIVASI BELAJAR SISWA

The goal of this research is to increase the understanding of the concept and students' learning motivation using POE2WE model. And this research is using qualitative approach in the form of theoretical data with descriptive method and literature review. It means, the researcher takes the data through read literature activity which relevant with the context that needed. Through this method, the researcher can elaborate the problems which discussed clearly and comprehensive. POE2WE model (Prediction, Observation, Explanation, Elaboration, Write, Evaluation) are education model development that was found by Dr. Nana, M.Pd. in his dissertation during S3 in Universitas Sebelas Maret. The education with this model provide a stimulus to students to identify a problem by predicting the problem given. The next step, students will do the experiment or observation, explaining the results of observation, and linking theoretical concept to everyday life. After that, the students can write the conclusion and self-evaluation as the last step in this learning model. The results of the research shows that the use of POE2WE model is capable to increase the understand of concept and students' learning motivation, because with this model the students are capable to provide stimulus to other students in identifying the problems.
Prospects for the use of criteria for assessing the effectiveness of the development of information and library institutions

The article examines the ongoing reforms in Uzbekistan, in particular, analyzes the decrees, concepts and programs for the development of the information and library sphere. The author examines research conducted abroad on the development of special criteria for assessing the effectiveness of information and library activities, the creation of statistical databases. Taking into account international experience, a solution to this issue is proposed.
Information Security

Information is a valuable asset.Information includes both in electronic and physical forms such as paper, video or knowledge .With the development of the network and information technology, information security has become the key of information technology in 21 st century.Today we are living in "Information world" because information is present everywhere and it's so important for us.If we are in education world or business world then we all want the required information is it's "security".If we want to handling and doing any work we always want to updated according to current scenario.So first of all we have to check that the information is wrong or not and the information is totally secure
Disruptive Technology Enabled Healthcare 4.0 Model for Lesion Identification with Reduced Latency

Advancement and innovations in technology have resulted in ease of accessibility and availability of resources, resulting in an increased liability on health-care services. However, the application of healthcare services in rural and undeveloped areas remains a foremost challenge, despite the investments made, largely due to unreliable communication infrastructures. Machine learning (ML) has witnessed a terrific amount of attention over the last few years in the field of medical imaging research for the lesion detection through a biomedical application such as Magnetic Resonance Images (MRI), CT scan, X-rays and Ultrasound etc. Normally, an MRI or CT scan are used by the experts to produce images of the soft tissue of the human body. Early detection of the lesion is a crucial part of follow-up care after completion of primary treatment. The goal is to reduce the mortality rate by early detection and treating the disease while it is still curable assuming a more effective salvage surgery and treatment. This paper presents a comprehensive review of the automated classification learning algorithms to identify lesion; indicates how learning algorithms have been applied to biomedical applications from data acquisition to image retrieval and from segmentation to disease prediction. This paper provides a brief overview of recent innovations and challenges associated with learning algorithms applied to medical image processing and analysis. Lastly, the paper concludes with a concise discussion and tries to predict direction for upcoming trends on more advanced research studies on lesion detection.
Същност и практически измерения на лидерството в международния мениджмънт

The Nature and Practical Dimensions of Leadership in International Management International management and companies in particular are forced more and more to operate and develop in conditions of dynamism, uncertainty and high competitive pressure. Their management rests on the effective coordination of their activities by uniting the efforts of all members towards the achievement of common goals. Given the unpredictable and not entirely manageable changes in the international environment, the survival and success of companies depend precisely on their ability to develop leaders and their leadership skills. As a source of intellectual property and innovations, the human resource requires a special approach for activation, motivation and support. There is no question that effective management is impossible without leadership that is qualified to organize, unite and inspire a group of individuals under a common mission and goal. In that regard, the present work specifically clarifies the nature and practical dimensions of leadership in the context of international management. Through literary overview and critical analysis, the focus is placed on the fundamental leadership theories and styles, as well as on the role of the global leader as a prerequisite for the success of international companies. The fundamental leadership style of management developed in the USA, Germany and Japan as a manifestation of the cultural factor and inter-cultural differences is clarified. Its practical dimensions are illustrated through comparative analysis between international automobile companies Toyota and Audi.
Determinants of Financial Inclusion in Africa: Evidence on Holding a Current Account

The term "financial inclusion" implies access and use of banking services (current account, savings account, insurance, credit, payments, etc.) at a low cost for the disadvantaged and low-income population in a country. In fact, banking services constitute a public good. It is therefore necessary that the accessibility and equitable use of banking services by the entire population should be among the primary objectives of government policies and financial institutions. Indeed, this helps to meet the basic financial needs of the population in any given country. The main objective of our study is therefore to examine the determinants of current account holding, which is considered to be a basic dimension of the use of banking services and therefore of financial inclusion. In our paper, we adopt an empirical approach using cross-sectional data to analyze the determinants of current account holding in the African continent.
Design and Analysis of Multisource Logs Forensic With Lock Technique for Cloud Security Enhancement

Multisource cloud log forensics (MCLF) strengthens the investigation method by means of detecting the malicious behavior of hackers thru deep cloud log evaluation. But, the accessibility attributes of cloud logs thwarts accomplishing the purpose to analyze cloud logs. Accessibility consists of the productions of cloud log get admission to, selection of suitable cloud log file, cloud log information integrity, and cloud logs trustworthiness. Hence, forensic investigators of cloud log files are dependent on cloud provider vendors (CSPs) to get entry to of diverse cloud logs. Accessing cloud logs from outside the cloud without depending at the CSPs is once more a hard, whereas the boom in cloud assaults has improved the need for MCLF to research the malicious activities of attackers. Criminals are easily hiding incriminating files within the cloud system and altering the log contents. Hence lock mechanism has been added to MCLF technique. This paper reviews the MCLF with lock technique and highlights diverse challenges and issues involved in examining cloud log data. The logging mode, the importance of MCLF, and cloud multisource-log-as-a-service are introduced. The MCLF security necessities, weakness points, and experiments are recognized to tolerate altered cloud log susceptibilities. This paper represents the design and analysis details of MCLF with Lock technique.
Towards an Intelligent Personalized Persuasive Conversational System for Human Interaction on Divining the Future Event and Assisting by Using Artificial Intelligence

In the next wave of insurgence, humans may endeavour self-reflection which can lead to an effortless talk and to find out if an event will fructify. Training the system on how to make accurate prognostication with the help of machine learning and statistical models can lead to an intelligent personalized conversational system. The Chatbot industry is ever-growing and after the COVID-19 pandemic and rigorous lockdowns all around the world, people have realized the importance of human interaction in their lives. We are developing this model to create a more intimate relationship between the system and humans. For this purpose, many open-source platforms are available. Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up a conversational agent artificially. The success of this project will help the model in observing and understanding human emotions which will ultimately help it to form a more personalized relationship to delineate the future course of events.
Finding Page Rank using Transition Matrix and Random Vector

Today, the web is growing at a very fast and rapid rate. Also, there is afast growth in using of the internet compared with a past years. Due to the dynamic nature of web, the information on the internet in form of pages is added and removed in no time. The information on the web had become very important and a large amount of information is hidden inside the web. Getting the information, which is in need has become very difficult. Hence mining of the web data deeply in-terms of the content, structure, and usage is necessary. The search engines, in general, give us a list of web pages for user queries. For the users to move on that list comfortably a ranking mechanism is applied. Many of the rank basedmechanisms are based upon content-based or link-based. Analgorithm is proposed to find the rank of the mined web pages is presented in this paper. The proposed algorithm is compared and analysed with existing mining algorithms namely page rank and HITS algorithms. This paper highlights respective strengths, weaknesses, variations, and carefully analyses all the algorithms with an example. The added feature of the algorithm is that the most valuable page of the list, which is given by the search engine, is displayed at the top of the list.