Reviewerly/exHarmony huggingface dataset:
Optimization of Air Traffic Management Efficiency Based on Deep Learning Enriched by the Long Short-term Memory(LSTM) and Extreme Learning Machine(ELM)

Abstract Air traffic management refers to the activities required for the efficient and safe management of the national air system (NAS) for each country. This concept has been widely assessed due to its complexity and sensitivity for the beneficiaries, including passengers, airlines, regulatory agencies, and other organizations. To date, various methods (e.g., statistical and fuzzy techniques) and data mining algorithms (e.g., neural network) have been used to solve the issues of air traffic management (ATM) and delay the minimization problems. However, each of these techniques has some disadvantages, such as overlooking the data, computational complexities, and uncertainty. The present study aimed to increase ATM efficiency using the deep learning approach. The main research objective was to propose a deep learning model with the application of a long short-term memory-based deep learning model in order to increase the predictive accuracy in short daily and long-term annual windows by enhancing deep learning (two-dimensional). In addition, the deep model output was transferred to the extreme learning machine fast learning deep neural machine in order to calculate the estimated time of arrival real-time based on other similar input data, including the NAS data, bureau of transportation statistics system, and automatic dependent surveillance-broadcast system. The final results indicated the increased accuracy of ATM compared to other studies.
Managing Cyber-Risk: Contracts, Litigation, Acquisitions &amp; Procurement

&lt;i&gt;An analysis of twenty (20) &lt;b&gt;C&lt;/b&gt;ommercial-&lt;b&gt;O&lt;/b&gt;ff-&lt;b&gt;T&lt;/b&gt;he-&lt;b&gt;S&lt;/b&gt;helf (COTS) Technologies was executed in order to investigate how they may be applied to minimise the Cyber-Threats associated with ‘undefined requirements’ pertaining to &lt;b&gt;C&lt;/b&gt;ontracts, &lt;b&gt;L&lt;/b&gt;itigation, &lt;b&gt;A&lt;/b&gt;cquisitions &amp; &lt;b&gt;P&lt;/b&gt;rocurement (CLAP). However, our analysis concludes that only one (1) COTS Technology is capable of achieving this objective (Testimation Technology); as demonstrated utilising four (4) Simplified Examples. One (1) Simplified Example pertaining to &lt;b&gt;C&lt;/b&gt;ontracts, demonstrates Cyber-Threat minimisation by precisely &amp; unambiguously specifying the minimum level of Cyber-Confidence to be delivered &amp; the maximum level of Cyber-Risk to be tolerated. Three (3) Simplified Examples pertaining to &lt;b&gt;L&lt;/b&gt;itigation, &lt;b&gt;A&lt;/b&gt;cquisitions &amp; &lt;b&gt;P&lt;/b&gt;rocurement respectively, demonstrate Cyber-Threat minimisation by the application of a &lt;b&gt;D&lt;/b&gt;ecision &lt;b&gt;A&lt;/b&gt;ssistance &lt;b&gt;T&lt;/b&gt;able (DAT) generated by this COTS Technology. All four (4) Simplified Examples presented, demonstrate how it is possible to Manage Cyber-Risk utilising a scientifically formulated tool which has been experimentally verified to Predict &amp; Measure all forms of Cyber-Risk to greater than 98.07% accuracy.&lt;/i&gt;&lt;br&gt;
The Model of English Teaching Material for Elementary Schools Teacher Education Based on Contextual Approach

The aim of this research was to develop a model of English teaching material for elementary school teacher education based on the contextual approach.This was conducted at the elementary school teacher education department of Universitas Negeri Jakarta from July 2016 to December 2017 using the research and development models of Borg and Gall, and Dick and Carey.The data were collected using questionnaires, interviews, and tests (cloze tests and formative tests) instruments and analyzed using both quantitative methods with Paired T-Test and Cohen's Kappa Coefficient and qualitative method with Miles and Huberman's model.The results showed that the developed model had practicality and that it effectively met the needs of the students in the department.
The Relation of Competency Interpreting Data and Evidence Scientifically and Visual Intelligence

The goal of this research is to gain the relation of competency interpreting data and evidence scientifically and visual intelligence. It reveals that they has positive correlation.
Epistemic Logics

Abstract Standard possible-worlds epistemic logic gives rise to the problem of logical omniscience. There are attempts to deal with the problem without using impossible worlds. A number of these approaches are discussed in this chapter and all are found wanting. The impossible worlds approach is immediately more successful, but faces a deep problem: how should impossible worlds be constrained, so as to give adequate models of knowledge and belief? One option is to take impossible worlds to be closed under some weaker-than-classical logic. But this approach does not genuinely solve the problem of logical omniscience. A different approach is the dynamic one, whereby epistemic states are not closed at any one time, but nevertheless evolve towards closure in a dynamic way.
Studying Developmental Processes in Accelerated Cohort-Sequential Designs with Discrete- and Continuous-Time Latent Change Score Models

[Published in Psychological Methods]. Studying the time-related course of psychological processes is a challenging endeavor, particularly over long developmental periods. Accelerated longitudinal designs (ALD) allow capturing such periods with a limited number of assessments in a much shorter time framework. In ALDs, participants from different cohorts are measured repeatedly but the measures provided by each participant cover only a fraction of the time range of the study. It is then assumed that the common trajectory can be studied by aggregating the information provided by the different converging cohorts. We conducted a Monte Carlo study to evaluate the practical relevance of using discrete- and continuous-time latent change score models for recovering the trajectories of a developmental process from ALD data under different sampling conditions. We focused on exponential trajectories typically found in the development of cognitive abilities from childhood to early adulthood. The results support the appropriateness of ALD designs to study such processes under various conditions of sampling. When all cohorts are drawn from the same population, both discrete- and continuous-time models are able to recover the parameters defining the underlying developmental process. However, discrete-time models yield biased estimates when time lags between observations are not constant. When cohorts are not from the same population and, thus, lack convergence, both types of models show bias in various parameters. We discuss the findings in the context of developmental methodology, encourage researchers to adopt continuous time models to analyze data from ALDs, and provide recommendations about how to implement such research designs.
The Ontology of Documents, Revisited

Three contributions are made to understanding the nature of documents. A survey of definitions of "document" from the last century shows that those definitions which most accurately reflect the ways in which the term "document" is used in practice are typically compound definitions, consisting of two or three elements that each refer to a different function of documents: medium, message, and meaning. Locating documents in E. J. Lowe's four-category ontology results in consideration of documents as universals rather than as particulars. Analysis of B. Smith's theory of document acts suggest that all documents, not just the ones that are involved in declarations, are creative in the special sense that they are generative of quasi-abstract entities of the kind that collectively comprise social reality.
Addressed Challenges

In this chapter, we discuss the diverse set of challenges, from different perspectives, that we face because of our aim to incorporate knowledge in software and processes tailored for software and systems evolution. Firstly, the discovery and externalization of knowledge about requirements, the recording and representation of design decisions, and the learning from past experiences in evolution form the human perspective, including developers, operators, and users. Secondly, performance and security induce the software quality perspective. Thirdly, round-trip engineering, testing, and co-evolution define the technical perspective. And fourthly, formal methods for evolutionary changes provide the foundation and define the formal perspective.
SP Case Study: Use Program Design Criteria and Simple Models

The Address Book Application (ABA) is introduced as a case study. After a few ABA requirements are described, three versions of a structured programming (SP) solution are described. Each SP solution is described using source code, a hierarchy chart, a Nassi–Shneiderman diagram, and a statechart. The three program design criteria described in Chap. 2 are used to evaluate each solution.
Effective Search Engine Spam Classification

Search engine spam is formed by the spam creators for commercial gain. Spammers applied different strategies in web pages to display the first page of web search results. These strategies may avoid displaying good quality web pages in the top of search engine results page. Nowadays there are numerous devised algorithms available to identify search engine spam. Even though search engines are still affected by search engine spam. There is a necessity for search engine industry to filter search engine spam in the best way. The proposed study identifies spam in web search engine. Spammers try to use most popular search keywords, popular links and advertising keywords in web pages. This strategy helps to increase ranking to display the top of search results. The proposed method is used important features to detect spam pages which are classified using decision tree C4.5 classifier. This method produces better performance when compared with existing classification methods.
Penentuan Level Depresi Mahasiswa Tingkat Akhir Menggunakan Sistem Inferensi Fuzzy dengan Metode Sugeno

Depression is a disease whose main symptoms are unclear and ambiguous. Depression has a wide influence on health, lifestyle and economic losses. Causes of depression can be seen from sleep disorders, uncomfortable environment, and excessive use of antidepressant drugs. This research determines the level of depression in the final year students who are in the thesis work phase, especially in the mathematics department of FMIPA UNESA, and implements it into fuzzy logic.This type of research is qualitative and quantitative. The inputs us&#x0D; Depression is a disease whose main symptoms are unclear and ambiguous. Depression has a wide influence on health, lifestyle and economic losses. Causes of depression can be seen from sleep disorders, uncomfortable environment, and excessive use of antidepressant drugs. This research determines the level of depression in the final year students who are in the thesis work phase, especially in the mathematics department of FMIPA UNESA, and implements it into fuzzy logic.This type of research is qualitative and quantitative. The inputs used are body mass index, systolic blood pressure and physical health questions. And the output produced is the severity of depression. Data collection techniques used by researchers by asking a number of questions that were asked to 40 final year students. And the processing stage uses the Sugeno fuzzy method.&#x0D; The results of this study can help improve medical services by determining the level of depression in students. This study uses the MATLAB application. The results of this system give an accurate valued are body mass index, systolic blood pressure and physical health questions. And the output produced is the severity of depression. Data collection techniques used by researchers by asking a number of questions that were asked to 40 final year students. And the processing stage uses the Sugeno fuzzy method.&#x0D; The results of this study can help improve medical services by determining the level of depression in students. This study uses the MATLAB application. The results of this system give an accurate value
1658-838X

The study aimed to identify the levels of credibility of Jordanian government and private television channels, and their degrees of commitment to the criteria of credibility, during the Coronavirus (COVID-19) crisis. It also aimed to reveal the degrees and types of changes in the credibility ratings of these channels before and during the crisis. The study relied on surveying the media audience as a research method, and it used a questionnaire as a data collection tool. The study sample represented a cross section of all Jordanians who were 18 years of age or older; a quota sample of 420 respondents was selected, divided equally among the three regions of Jordan (North, Central, and South). The results of the study showed that the most important credibility criteria adhere to by Jordanian government and private television channels were these: ‘depending on media professionals with experience and high competence’, ‘working for the public good’ and ‘relying on professional and ethical principles’. The government channel AlMamlaka topped the list of Jordanian television channels with the highest credibility among respondents. Roya Channel was shown to be the Jordanian television channel with the highest change in credibility ratings during the Coronavirus crisis.
Editorial 2021

Editorial 2021 Authors André Knops Laboratoire de Psychologie du Développement et de l'Éducation de l'Enfant (LaPsyDÉ), UMR CNRS 8240, Université de Paris, Paris, France Abstract No abstract available. PDF HTML XML Article info Impact Citations How to Cite License Published at 31. March 2021 https://doi.org/10.5964/jnc.6203 Issue: Vol. 7 No. 1 (2021) Section: Editorial Share: Z Knops, A. (2021). Editorial 2021. Journal of Numerical Cognition, 7(1), 1-3. https://doi.org/10.5964/jnc.6203 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX This work is licensed under a Creative Commons Attribution (CC BY) 4.0 International License. PlumX Dimensions Views: Total Abstract PDF HTML XML 525 238 213 46 28
Tempting Facades of the Cannabinoid Market on the Russian Darknet: Designing Quality as the Key to Social Normalization of Demand

The article discusses the problem of sociopolitical control over the market for illicit psychoactive substances (PAS) on the Russian darknet in light of the needs that this market, on the one hand, promises to satisfy and, on the other hand, constructs itself, stimulating consumption communities. The transformation of goods into market commodities is conceptualized as a social process. Market intermediaries sharply detect the deficits and consumers’ cultural attitudes and, relying on them, firstly, normalize the demand for their product and, secondly, invest in the development of consumer capital, which helps buyers make informed choices even where the quality of market product is uncertain, unpredictable, and hard to assess prior to consumption. To reconstruct and evaluate the marketing efforts of online stores selling illicit substances, the article analyzes 1,000 descriptions of products available on the cannabinoid market, collected using the parsing method from an online marketplace on the Russian darknet, as well as consumer reviews of these products. The article demonstrates that the shadow market for natural surfactants normalizes its product by categorizing it as a natural medicine that allows consumers to influence their physical and psychological conditions not just for individual hedonistic purposes but to achieve positive social effects. Cannabinoid products are marketed as a source of new experiences that contribute to self-knowledge, creativity, emancipation, and substantive interaction with other people. In a medicalized society of emotions, the consumer is offered the image of a taster and gourmet, able to appreciate the results of the art of cannabis growing. Article in Russian
Peer Review Teman Sejawat Sebidang Karya Ilmiah - Washback of Broadcast Project-based assesment fot Tourism 4.0 on Student Learning

Peer Review Teman Sejawat Sebidang Karya Ilmiah - Washback of Broadcast Project-based assesment fot Tourism 4.0 on Student Learning - Angesti Palupiningsih
A Complete Research on Techniques &amp; Technologies of Big Web Data Preparation to Web User Usage Behaviour

The rapid advancements in data digitization, the most powerful inventions of learning methodologies in data collection and reduced cost of data storage further enabled the World Wide Web with immense amount of data at significant rate in all the key domains. The generated web data is non-scalable, high dimensional, widely distributed, heterogeneous, dynamic in nature and having useful insights, and thus, it evolved as big data. This situation creates inevitably increasing opportunities in extracting structured solutions from unstructured weblog data for the present big data researchers. Moreover, to provide value addition to any key domain and derive actionable knowledge for various applications, such as, web usage analysis for improvements in fraud detection, product analysis and customer segmentation, got the focus in big data era by the web analysts. To improve operational performance and to discover hidden insights accurately, a comprehensive process is required to investigate the web user usage behavior by analyzing big web data. Towards this, the authors concentrate on reviewing the techniques and technologies of web data collection and preparation for investigating web user usage behavior effectively. In the present paper, the researchers initially pay an attention to explore web log data preparation methods in the traditional approach. Later, the review emphasizes on Hadoop approach for big data preparation and processing. This approach able to concentrate comprehensively on both the stages: distributed data storage and parallel processing of weblog data and to leverage the strengths of techniques and technologies of individual stages. Moreover, the authors deliberately review the possible potential research paths that results in an improved methodologies for data storage and optimized processing speed in the era of big web data
Optimized Task Scheduling for Cloud Computing using PSO and GA

Cloud computing started with risk-free concept: Let someone else take the ownership of setting up of IT infrastructure and let end-users tap into it, paying only for what is been used. A service offering computation resources is frequently referred to as Infrastructure as a Service (IaaS) and Software as a Service (SaaS). An environment used for construction, deployment, and management of applications is called PaaS (Platform as a Service). With the advent of cloud computing, resizable infrastructure for data analysis is now available to everyone via an on-demand maybe free model. Cloud computing totally depends on the internet to deliver its services to the users. In the modern computing environment where the amount of data to be processed is increasing day by day, the costs involved in the transmission and execution of such amount of data is mounting significantly. So there is a requirement of appropriate scheduling of tasks which will help to manage the escalating costs of data intensive applications. In this paper, we propose an algorithm that uses particle swarm optimization to schedule the tasks to get maximum benefits from the resources. The benefit can be expressed in terms of increased resource usage, minimized response time, minimize overall cost incurred. We will then schedule the tasks using genetic algorithm and compare the results given by particle swarm optimization as to what extent they are similar and which gives better results. Both algorithms are heuristic algorithms hence result may vary
Administrasi Keuangan

The world of education is a world where there are learning activities between teachers and students, these two components cannot be eliminated in an educational process because if one of them is lost there will never be a learning goal. However, on the other hand there are components that also play a role as supporting learning activities both directly and indirectly. No less important components are facilities and infrastructure. Administration of educational facilities and infrastructure is very supportive of achieving a goal of education, as a personal education we are required to master and understand the administration of facilities and infrastructure, to improve work power effectively and efficiently and be able to respect the work ethics of personal education, so harmony, comfort can create pride and a sense of belonging both from the school community and the residents of the surrounding community
Three Keys to Finding The Right Event Speaker

Special Events GaloreVolume 19, Issue 2 p. 6-6 Event Speakers Three Keys to Finding The Right Event Speaker First published: 15 January 2019 https://doi.org/10.1002/speg.31041Read 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. Volume19, Issue2February 2019Pages 6-6 RelatedInformation
An Exploration of the Various Dimensions of Organisational Citizenship Behaviour

This study is an attempt to explore the various aspects of organisational citizenship behaviour among employees. In a world where employee’s morale and loyalty are under the scanner, citizenship behaviour offers bright hope for the organisation.A country’s citizenship does not merely come by just living in that country; it is gained by meeting the legal requirements of a nation. A country is benefitted by citizens who voluntarily contribute in their ways towards the growth of the nation. Same way when the employees give their best, as they feel responsible along with a strong sense of belongingness for the organisation, they reflect organisational citizenship behaviour. Organisational Citizenship Behaviour (OCB) is the voluntary actions and behaviour by the employees, which are not a part of the job description but benefits in the efficiency of the organisations. The paper’ first objective would be to study what induces citizenship behaviour among employees. Personal characteristics and attitudes could play a big part in determining the employee’s behaviour. On the other hand, the organisation’s policies and environment also is a crucial factor in determining OCB. The next objective of the study is to analyse the impact of OCB. Though the positive effect is always favoured, this research explores if there could be any negative impact of citizenship behaviour on the employees. The study is based on the views of 100 respondents who belong to private corporate firms within Chennai city only. The influencers and impact of OCB are discussed as the various dimensions in the study.