Reviewerly/exHarmony huggingface dataset:
THE ORGANIZATIONAL SECURITY INDEX: A TOOL FOR ASSESSING THE IMPACT OF NATIONAL CULTURE ON INFORMATION SECURITY ATTITUDES IN SLOVENIA AND THE UNITED STATES

This study seeks to enhance understanding of the role that national culture plays in influencing employee attitudes and behaviors with respect to information security.Commercial firms and governmental organizations are increasingly dependent on a variety of relationships with foreign organizations staffed by individuals raised and socialized in their own national culture.Information security professionals agree that people, rather than technology, pose the greatest threat to information within an organization.As commercial organizations recognize the importance of establishing an effective information security culture, the importance of understanding the security-related attitudes of the workforce becomes apparent.The impact of national culture on information security attitudes and behavior has relevance not only in the commercial world, but also in the public sector, as government entities engage with foreign partners in activities ranging from information exchanges to multinational, coalition military operations.One of the most widely-used theoretical models used to assess and describe national culture, and to compare one national culture to another, is the framework developed by Hofstede (1980).This study employs an explanatory sequential mixed methods model to examine how national culture influences the attitudes of employees in an insurance company in Slovenia and a maritime industry firm in the United States.Building upon Hofstede's work, this study proposes an Organizational Security Culture Index, or OSCI, as a tool for helping gauge how national culture influences information security-related attitudes in a workforce.
Radiocarbon “Distraction”

The existence of the radiocarbon dating technique is rather known, if for no other reason than it is cited in the explanation cards of some artifacts exposed in museums; sometimes writing says “artifact dated using radiocarbon method.” The out-of-the-blue assignation of a medieval date to the Shroud upset both the scientific community and the world public opinion. Some scholars, such as Eric Jumper, belonging to the famous Shroud of Turin Research Project and blindly trusting in science and in the radiocarbon dating method, quit their studies on the Turin relic. The statistical calculations of the results related to radiocarbon test published by the review in Nature were double-checked, and serious mistakes had been found. The American researcher R. Villarreal, analyzing a thread declared coming from the Shroud, provided by R. Rogers and extracted by Professor Luigi Gonella Gonella from the sample taking in 1988, discovered that one end was made of linen but the other end was made of cotton.
Machine Control Using Hand Gesture Recognition

Human to machine collaboration is an important game changer in industries as well as in daily lives.Hand gesture recognition assists this interaction by automating the process.This collaboration is supported by proposing system which can recognize human hand gestures and perform tasks based on those gestures.This paper presents the system that uses hand gesture recognition to control machine.The machine executes programmed task according to gestures recognized.The hand gestures are recognized using vision-based approach.The defined gestures are static and carried out by bare hands.The recognition of the system involves hand segmentation, feature extraction, and classification.The hand is segmented using bounding box in webcam preview, and features are extracted by determining signature of hand and histogram of signature.The classification process uses supervised feed forward neural network system to train some samples of different gestures.Once gesture is recognized, the programmed tasks start to execute.The proposed system has found to have an average accuracy of 92.6% for the classification of gestures.
Dealing with categorical missing data using CleanerR

Missing data is a common problem in the world of data analysis. They appear in datasets due to a multitude of reasons, from data integration to poor data input. When faced with the problem, the analyst must decide what to do with the missing data since its not always advisable to discard these values from your analysis. On this paper we shall discuss a method that takes into account information theory and functional dependencies to best imput missing values.
Preface

The International Virtual Conference on R obotics, A utomation, I ntelligent S ystems and E nergy (IVC RAISE2020) focused on the latest technologies, researches and challenges in R obotics, A utomation, I ntelligent S ystems and E nergy fields. The conference is held on December 15, 2020 in Perundurai, India. The purpose of IVC RAISE 2020 is to provide opportunity to share the most recent research outcomes in the areas of R obotics, A utomation, I ntelligent S ystems and E nergy. It is aimed to create a professional network among researchers, academicians, professionals, engineers, and industry on the focused and related research areas of the entire energy infrastructure related to SMART CITY development with aid of R obotics, A utomation, I ntelligent S ystems and E nergy. List of Organisers, Advisory Committee, Organizing Committee and this titles are available in this pdf.
DESIGN AND IMPLEMENTATION OF A COLLABORATIVE PLATFORM MODEL FOR EPIDEMIC AND COLLECTIVE HEALTH SERVICES

The aggregation and visualization of data are part of one of the most important fields of Data Science's application today.This class of tools evidences its importance in the area of public health, especially in the context of epidemics and pandemics.However, there are several issues in accessing reliable data, such as diverse sources, economic interests, and technical difficulties.This work proposes and explores the technological choices for the implementation of a system in which, collaboratively, users provide health information, which are made available through panels with scalability in access and flexibility in the analysis, allowing a macro view of the situation.Also, with the use of these visualizations and mobile application technologies, users can take advantage of services such as monitoring health status and sending alerts of emergency situations.
Djibouti

An external sector statistics (ESS) mission visited Djibouti from January 26–30, 2020. This was the fourth mission under the JSA/AFR project to improve ESS in 17 Francophone African countries. The mission found that significant data on direct investment (DI) have not been incorporated in either the balance of payments or international investment position (IIP) statistics since 2017.
Predicting Mouse Cursor Target using Backpropagation Neural Network

Many solutions were proposed in the past decades to assist the people with disability in the movement to interact with personal computers. Various results were proposed to simulate the mouse cursor movement and click operations through facial expressions captured by the camera. Tracking and converting accurately the facial expression of the user to the mouse operation is still acknowledged as a research challenge and opportunity. The proposed system introduces a prediction of items to be selected by the user in the GUI based system applying the backpropagation neural network techniques to improve the performance of the overall selection process.
CLEANLINESS INSPECTION OF THE ABLUTION SPACES OF THE FEDERAL TERRITORY MOSQUE

Muslims go to mosques to congregate in prayers; some Malaysian mosques carry historical value, whereas some are simply fine works of art. The term "Iconic Mosque" has been defined by the Islamic Tourism Centre in Malaysia as “having a design which represents the modern architecture and the cultural identity of the country”. Some evidence shows that the ablution spaces in Malaysian Mosques encountered many issues regarding their cleanliness. Three methods of study were used to analyse the Federal Territory Mosque ablution spaces: physical observation, architectural drawing analysis, and interview. The research aims to improve the cleanliness of the ablution areas by studying their design aspects. The study’s significance is to evaluate the cleanliness of ablution spaces at the Federal Territory Mosque. The findings of this research revealed that using a natural ventilation system could significantly improve the cleanliness of the ablution areas if accompanied by a mechanical system. The investigation analysis discovered that a smaller ablution room design could result in an unhygienic space. The users’ abuse is one of the crucial factors that impact the ablution room cleanliness.
Spectro-temporal features for audio replay attack detection

Speaker verification can be viewed as a process of verifying the person using his/her utterance. The major challenge to implement automatic speaker verification in security applications is spoofing attacks. Speaker verification systems can be spoofed using pre-recorded speech, synthetic and voice conversion speech. Hence, there is a need to develop spoof detection system in order to make voice biometrics viable for security applications. This paper proposes to explore time-frequency representations obtained using gammatone filterbank and constant Q transform for detecting presentation attack for automatic speaker verification. The experiments are carried out for ASV spoof 2017 database and the results are compared with state-of-art replay speech detection systems based on cepstral features.
AJAX

In this chapter, you learn to implement AJAX (i.e., exchanging data with a web server in the background) and update the web page asynchronously. This chapter covers the following recipes.
Advanced Clustering Technique to Handle Multi-word Expressions for Descriptive Documents

Expressive clustering comprises of naturally sorting out information occurrences into groups and creating a graphic outline for each group. The portrayal ought to advise a client about the substance regarding each group moving forward without any more assessment of the particular occasions, empowering a client to quickly filter for pertinent bunches. Choice of portrayals frequently depends on heuristic criteria. We model graphic grouping as an auto-encoder organize that predicts highlights from bunch assignments and predicts bunch assignments from a subset of highlights. We present an area free bunching based methodology for programmed extraction of multiword expressions (MWEs). The strategy consolidates factual data from a universally useful corpus and writings from Wikipedia articles. We fuse affiliation measures through elements of information focuses to bunch MWEs and after that process the positioning score for each MWE dependent on the nearest model doled out to a group. Assessment results, accomplished for two dialects, demonstrate that a mix of affiliation estimates gives an improvement in the positioning of MWEs contrasted and basic checks of co event frequencies and simply factual measures.
Less Sparse Feature Set With Meta Heuristic Weighted Classifier for Tweet Sentiment Classification

Twitter using Machine Leaning Techniques has been done. While consideration Bigram, Unigram,. SVM and naïve Bayes classifier which hybrid with PSO and ACO for effective feature weight. In Fig. 4.9 compare all experiment by on graph which shows that SVM_ACO and SVM_PSO better perform than SVM. NB_ACO and NB_PSO perform better than NB but if compare between hybrid approaches then SVM_PSO show 81.80% accuracy,85% precision and 80% recall. IN case of naïve Bayes NB_PSO 76.93% accuracy,76.24 precision and 82.55% recall, so experiments conclude that Naive Bayes improve recall and SVM improve precision and accuracy when use as hybrid approach.
Developing Augmented Reality Hybrid Marker using Pictorial Quick Response Code for Community Products

Applying augmented reality technology correctly helps businesses grow and attract more consumers, but using the marker that is the QR code does not directly interpret. On the other hand, if using pictorial markers, although they can convey meaning, it still takes time to process to extract the hidden information. This paper proposes to develop the hybrid marker for augmented reality by mixing the community brand image with the QR code for community product entrepreneurs, and develop the mobile application for scanning the hybrid marker then respond to the augmented reality content in several styles. The hybrid marker was generated into two modes. The opacity layer mode was set the opacity value of QR code to 55%. And overlapping mode is designed to invert the pixel color between pictorial band image and QR code. This system was evaluated in black-box testing. As a result, the efficiency of the hybrid marker and mobile application is the highest level of user acceptance while being used in this system.
Network Design

In this chapter, we apply copulas to network evaluation and design. The network is considered to be comprised of rain gauges that are located in the southwest (seven gauges) and east central (three gauges) parts of Louisiana. To select proper rain gauges for network design, the kernel density is applied to model the marginal rainfall variables as that studied for rainfall analysis in Chapter 10. For the simplicity of illustrating the copula-based network design, meta-elliptical copulas (i.e., meta-Gaussian and meta-Student t) are applied to model the spatial dependence among rain gauges. The network design case study shows the appropriateness of the copula-based network design.
Introduction

In the field of robotics and artificial intelligence, autonomous robot has been a highly active research area, which enables a robot to perform behaviors with a high degree of autonomy. With the continuing development in the field of mobile robotics, in particular, using multiple robots to autonomously explore and map an environment has caught the attention of many robotics researchers and practitioners (see Fig. 1.1). Utilizing a group of robots have found significant advantages compared to their single robot counterpart: robustness to single robot failure, quicker exploration of environments in time critical search and rescue missions, execution of tasks of high complexity, reduction of human risks, and costs associated to disaster response. Accurate localization and mapping is a crucial competency for enabling collaboration between multiple mobile robots.
Spam detection system: a new approach based on interval type-2 fuzzy sets

&lt;p&gt;Today, most Internet users use email to communicate electronically. They depend on the Internet to deliver their important emails safely and to the right recipients. However, the fast growth of Internet users and their use of email together with the exponential increase of unsolicited users sending spam have made the email system less reliable. An email can falsely be markedly a spam filter on its way to the recipient or even get buried among junk mailing the recipient’s inbox. There are several intelligent anti-spam filters which use different artificial intelligence methods to detect spam including neural networks and fuzzy logic systems. This paper presents an interval based type-2 fuzzy spam detection system. Our results show that interval type-2 fuzzy set is an effective technique for spam detection and email classification. The proposed system enables the user to have more control over the various categories of spam and allows for filter personalization.&lt;/p&gt;
Multinomial Classification of “Hete-Neurons” in Heterogeneous Information Networks

The real-world objects communicate and exchange data and can have meaningful relationships between them which lead to the field of research called Heterogeneous Information Networks.These object behaviour and attributes are modelled as "Hete-Neurons" which is proposed in this paper.To model this object interconnectivity and Multinomial Classification the cognitive level of mapping of the queries in the examination by using Bloom's Taxonomy is considered and interesting results are identified.The comparative study held on previous models which used the Bloom's Taxonomy showed an accuracy of 89 % but the proposed approach presented a higher accuracy and also gave a new insight into the perception of a neuron as "Hete-Neuron" which is heterogeneous.A multi-class Classification approach is experimented with a dataset which contains 1050 queries from well reputed university exam papers and showed a higher accuracy rate with 99.86 when tested with the sigmoid function.The same dataset is also experimented using the well-known softmax function which gave an accuracy of 100%.
JavaScript Variables

In this chapter, you will learn some basic JavaScript data types. When you want the computer to hold onto some information, that information is of a certain “type.” For example, an email address is a type called String. The computer recognizes that your email address is a series of letters, numbers, and symbols.
Metacognitive Strategy Preview, Question, Read, Reflect, Recite, and Review. (PQ4R) In increasing interest in BACA Blended Learning in Junior High School (SMP)

Reading is one of the important language skills that junior high school students have in today's digital age. Information on the development of science and technology that flows profusely in digital forms, requires the growth of high reading interest from junior high school students. The high interest in reading is characterized by the enthusiasm of students in wanting to understand reading material in a literal, inferential evaluative, and appreciative manner. This study aims to improve the reading ability of junior high school students through the Preview, Question, Read, Reflect, Recite, Review (PQ4R) based on blended learning strategies. Blended learning technology combines face-to-face and online learning activities in the process of reading and understanding reading material. The methods in experiments using digital reading material was read using the PQ4R metacognitive strategy. The results of the study indicate that students carry out reading activities (self-planning) with Preview and Question stages. Then, the students conduct reading monitoring (self-monitoring) with the three stages; Read, Reflect, and Recite. Finally, the students evaluate the progress of reading (self-evaluation) by conducting a review. Thus, it can be concluded that the students interest in reading increases by applying the blended learning based PQ4R metacognitive strategy.
A Novel Sorting Method for Real and Integer Numbers: An Extension of Counting Sort

Sorting is an essential conceptin the study of data structures. There are many sorting algorithms that can sort elements in a given array or list. Counting sort is a sorting algorithm that has the best time complexity. However, the counting sort algorithm only works for positive integers. In this paper, an extension of the counting sort algorithm is proposed that can sort real numbers and integers (both positive and negative).
Online Reviews &amp; Ratings Inter-contradiction based Product’s Quality-Prediction through Hybrid Neural Network

With the explosive growth of web usage, people feel comfort to use internet for their personal work such as shopping, sharing information etc. People are more interested in “what other thinks” so the comments and reviews on any online product, movie has huge effect on its earning. Sentiment analysis help people to judge quality by analyzing the reviews. In this era where everyone is so busy in their routine work, it feels like very difficult and time consuming task to check all available reviews on a product. As reviews on a product can be written by anyone so their certainty can be doubtful for example people can give fake reviews just for enjoyment. Another problem with reviews is that contradiction which exists between ratings and reviews of a product for example a person gives 5 star to a product but write a lengthy list of problem exists in that product. To deals with this problem, we are introducing a methodology that finds out contradiction of reviews and ratings of a product then finds out the actual score/quality of product which can save people’s time to read all the reviews or clear their confusion if they stuck between whether to trust on ratings or reviews.&nbsp; In this research we used CNN Hybrid model which gives 97.5% accuracy which is better than previous models. Dataset is collected from amzon.com. We have also applied CNN Hybrid model on different training and testing dataset ratio in both cases i.e. bigger and smaller dataset. We evaluate CNN hybrid model on both smaller and bigger dataset and experimental results conclude that increasing dataset will increase accuracy of CNN Hybrid Model.
Fast Facts

Streaming and vinylInterlibrary loanCollege graduates and academic challengeSmart speakers, voice assistants, and parentsAcademic library collections
Faculty Employment Conditions

Higher Education AbstractsVolume 56, Issue 3 p. 230-232 FACULTY EMPLOYMENT CONDITIONS Faculty Employment Conditions First published: 04 October 2021 https://doi.org/10.1111/hea.15_12174Read 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume56, Issue3July 2021Pages 230-232 RelatedInformation
Living in harmony with the nature

The experience in ecological education of the central district library and the diversity of related services and activities are discussed. Non-standard solutions for ecological and environmental problems awareness are proposed.
Dominion Energy announces $35 million education initiative to support minority students

Corporate Philanthropy ReportVolume 35, Issue 9 p. 2-2 News Briefs Dominion Energy announces $35 million education initiative to support minority students First published: 13 August 2020 https://doi.org/10.1002/cprt.30685Read 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 onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume35, Issue9September 2020Pages 2-2 RelatedInformation