Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT OF LEADERSHIP POTENTIAL OF DEPARTMENTS AS AN INSTRUMENT FOR INSTITUTIONAL LEADERSHIP IMPLEMENTATION OF THE UNIVERSITY

The current development of higher education in Ukraine is conditioned by such key requirements as professionalization of university management and staff development of the university (new staff policy). Purpose of the article: to research and to justify the development system of departments leadership potential as an instrument for professional management of higher education. Methods: theoretical methods: theoretical and terminological analysis, strategic sessions, interviews, Thomas PPI method (International Certified Test) by R. Belbin; mathematical methods for analyzing empirical data.The development system of University departments leadership potential includes the following vectors: designing of the departments development strategy; analysing of internal and external resources; team - building; strategy implementing; results monitoring. Planning, implementing, evaluating and reflecting are the stages of departments leadership development. Planning: defining of strategic and operational goals; implementing: analysing of PESTLE and human resources; evaluating: identifying of strengths and weaknesses, responses to changes, cohesion; reflecting: educational quality assesing by round-up survey.Leadership’s potential development of departments of the university is a complex and non-linear educational system related to the university’s leadership potential. The attempt to explore it is made in our research. The units, goals, values and university development are realized by developing the leadership’s potential. The leadership’s potential of the university is an actual product of the article. It is determined that the scientific basis of the problem underlined in the research is sufficient to select the appropriate methodology (systematic approach), definition of the content, stages of the research, conclusions formation. The readiness to change, subordinate personal goals to team tasks, learn new and form actual competencies, help others, destroy stereotypes and accept challenges need the development. It is possible in terms of team leadership. It is grounded that the professionalization of university management is an actual and unresolved problem. It requires further research and implementation of European experience in the practice of higher education in Ukraine.The professionalization of university management is an urgent and unresolved problem. It requires further research and implementation of European experience in the practice of higher education in Ukraine. The presented development system of departments leadership potential in higher educational institutions is value-oriented. It is based on trust and responsibility. The implementation in university practice will provide the institutional leadership of higher education of Ukraine and its further integration into the European space.
Toward a More Open, Trusted and Efficient Research Environment

Open science is becoming increasingly popular. Both funders and publishers require data be made public. The goal is to make research easier to validate, more trusted and to hasten the speed of discovery. However, due to lack of training, lack of resources and lack of time, researchers often fail to make much of the content they generate public, and also fail to adequately document and organize it. Here I make an argument that researchers should try to make all their research content public. I briefly describe best practices that should both result in a better product and be less burdensome on the researcher. I also argue that if done properly, opening up their research can have multiple benefits for the research and career.
Utilization of social media by agricultural extension officers in Tamil Nadu

Social media is the medium for social interaction which uses ICT tools. With the growth of internet a wide range of ICTs have transformed social relationships, education and the dissemination of information. The present study was conducted to assess social media utilization behavior of agricultural extension officers. The study was conducted in Coimbatore district on 30 agricultural extension officers selected randomly. Most of the extension officers utilized social media like WhatsApp (100.00%) followed by YouTube (66.66%) and Facebook (63.33%) for sharing information, for entertainment and to interact with other extension officers. All the extension officials were using the social media through smart phones. The study revealed that social media may be used by the agricultural scientists to disseminate the new technologies among agricultural extension officers.
DARI INSPIRASI HINGGA APRESIASI

Although the birth of film art is the youngest form of art, but in its work has shaken the world by seizing a spectacular position. When film is recognized as a work of art, film also has the potential for communication that can deliver messages uniquely, so that it can be said as a manifestation of the representation of the lives of its people. However, how can the film be appreciated by the audience? Of course the stages of the process must go a long way starting from the inspiration to the embodiment of appreciation. There are several stages in the process, namely the stage of idea finding, development, packaging and formation until tangible to be appreciated. The idea-seeking stage is the stage of absorption of inspiration stimulated by aesthetic experiences. The development phase is to motivate the theme and the problems to be expressed in its realization. After that it is then packaged based on literary rules into a scenario. Furthermore, the interpretation of the manuscript is done to form through several components of creative workers. Compiled based on cinematic elements to the form of film packaging that can be appreciated.
LibGuides: Earth, Atmospheric & Aquatic Science Collection: ProQuest Results

A guide to all aspects of Earth, Atmospheric & Aquatic Science Collection including content, searching, and viewing results on the new ProQuest platform.
MATHEMATICAL TASKS AS A MEANS OF FORMING PROFESSIONAL COMPETENCIES OF FUTURE TEACHERS

An important result of the preparation of the future teacher of mathematics is the formed professional competences. The process of formation should be carried out systematically, starting from the first year. While studying at the university, the foundations of modern mathematical knowledge should be laid, the need for professional self-development and self-education should be formed. The purpose of the study: the development of tools that contribute to the formation and development of professional competencies of students, future teachers of mathematics, in the study of mathematical disciplines. The study analyzed the professional competencies of a mathematics teacher, the components of mathematical culture and established their relationship. The competencies that can be formed during the first year of study are defined. Identified the need to convert standard mathematical problems. Based on the research, a technology for creating special complex problems based on standard mathematical problems has been developed. Tasks consist of two parts: subject (mathematical) and professionally-oriented. Tasks can be used to form subject and professional competencies, diagnose their formation. The article presents the requirements for them, types and examples of tasks. The result of the assignments from the point of view of the formation of subject and professional competences is described.
Effect of Image View for Mammogram Mass Classification – An Extreme Learning Based Approach

Mammogram images are broadly categorized into two types: carniocaudal (CC) view and mediolateral oblique (MLO) view. In this paper, we study the effect of different image views for mammogram mass classification. For the experiments, we consider a dataset of 328 CC view images and 334 MLO view images (almost equal ratio) from a publicly available film mammogram image dataset [3]. First, features are extracted using a novel radon-wavelet based image descriptor. Then an extreme learning machine (ELM) based classification technique is applied and the performance of five different ELM kernels are compared: sigmoidal, sine, triangular basis, hard limiter and radial basis function. Performances are reported in terms of three important statistical measures namely, sensitivity or true positive rate (TPR), specificity or false negative rate (SPC) and recognition accuracy (ACC). Our experimental outcome for the present setup is two-fold: (i) CC view performs better then MLO for mammogram mass classification, (ii) hard limiter is the best ELM kernel for this problem.
Hiding Text Using Album Art in the MPEG Audio Layer 3

Today privacy of data is a big concern. Security is defined as the degree of protection against danger, damage, loss, and criminal activity. Particularly when a sensitive message is to be delivered to a destination authentication and confidentiality are required. Providing security for electronic documents is an important issue.So the attractive solution for this problem is Steganography. Steganography is the art and science of writing hidden messages in data so that no one except from the sender and intended recipient even realize that there is a hidden message. The hidden message may be text, image, audio, video, etc. In this paper, we mainly discuss about how to hide text  in album art.
Developing Joyful Story Sheets (JoSS): an Effort to Build Character for EYL Learners in Indonesia through Reading JoSS

In response to character education stated in Indonesian Curriculum 2013, to build characters for students of early ages is significant. This can be built through establishing reading habits and building character education to young learners living in urban and suburban areas simultaneously. However, there is lack attention paid to those living in suburban areas. Thus, this research is intended to provide them with some appropriate character-based reading materials. In order that they enjoy reading, the reading materials should be joyful and arouse imagining. This research employs Research and Development (Borg and Gall, 1983 &amp; Ari, et.al., 1985) with the data were collected through doing need analysis by means of distributing questionnaire to EYL in suburban areas in East Java Indonesia, interviewing EYL teachers and parents having children at elementary schools. The results of the data collecetd in Need Analysis were used to develop the product. This R and D produced collection of Joyful Story Sheets (JoSS) for EYL of the 3rd, the 4th, the 5th, and the 6th graders with each grade consists of 40 joyful story sheets written based on some characters, i.e. hard working, independence, discipline, honesty, and tolerance. The research reveals that the product of this research-namely JoSS- is proved to inspire the students’ moral values, to build love of reading, and to encourage learning English. This research result is pedagogically implemented not only as a means of character education but as supplementary materials for reading class as well. To prove its effectiveness, it is suggested for further researchers to experimentally investigate.
Towards Understanding Industry’s Perspectives on the Software Quality Characteristics: A Survey

The ISO SQuaRE software quality standard categorises software quality into eight different characteristics: functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability and portability. Each quality characteristic is further considered in terms of a cohesive set of sub-characteristics. In this paper, a survey has been conducted with the goal of understanding which software quality characteristics are popular in industries and any modeling languages and tools used for analysing the software quality. The survey has been performed with 16 experienced practitioners, who work for a Turkish software company and have been requested to answer a pre-determined set of questions. The survey results lead to many interesting outcomes, some of which are as follows: (i) maintainability and performance efficiency are the top-popular characteristics, while portability is the least, (ii) time behaviour is the top-considered performance sub-characteristic, (iii) interoperability is the top-considered compatibility sub-characteristic, (iv) learnability and appropriateness recognisability are the top-considered usability sub-characteristics, (v) availability is the top-considered reliability sub-characteristic, (vi) confidentiality and integrity are the top-considered security sub-characteristics, (vii) modularity and reusability are the top-considered maintainability sub-characteristics, (viii) none of the participants use any modeling languages for analysing the software quality early on, and (ix) the participants use COTS tools for analysing the software implementation.
Block chain as a secure platform for storing IoT based data

Block chain, a promising technology is emerging as a boon for many sectors. IoT, at the same time has brought about a tide of innovation with its wide range of applications. However, the problem with IoT is ensuring the security of the sensor based data storage. The possible and feasible solution for this problem can be formulated using Block chain. Block chain has begun to have a significant influence in the Internet of Things by enhancing security, empowering the incorporation of an increasing number of devices into the ecosystem. The improvements in IoT gadget security encourage quicker appropriation of this progressive advancement, and will open up an extensive variety of potential outcomes for endeavors in the days to come. Hereby we aim to propose a new IoT server platform by introducing a block chain. This system can be a radical departure from traditional processes of storing data and it can also remove the bottlenecks associated with the traditional cloud based data storing systems. It aims at retrieving sensitive data from the IoT devices and securely storing as well as maintaining it in the block chain and controlling the access to this data.
AMIS: Programmable Privacy-Preserving Network Measurement for Analysis and Troubleshooting

1Network measurement and monitoring are instrumental to network operations, planning and troubleshooting. However, increasing line rates (100+Gbps), changing measurement targets and metrics, privacy concerns, and policy differences across multiple R&E network domains have introduced tremendous challenges in operating such high-speed heterogeneous networks, understanding the traffic patterns, providing for resource optimization, and locating and resolving network issues. There is strong demand for a flexible, high-performance measurement instrument that can empower network operators to achieve the versatile objectives of effective network management and resource provisioning. In this demonstration, we present AMIS: Advanced Measurement Instrument and Services to achieve programmable, flow-granularity and event-driven network measurement, sustain scalable line rates, to meet evolving measurement objectives and to derive knowledge for network advancement.
Demo Abstract: A Tool to Detect and Visualize Malicious DNS Queries for Enterprise Networks

This demo presents our web-tool to access and visualize real-time detection of malicious DNS queries for an enterprise network of a large university campus in Sydney, Australia. We showcase two aspects: (1) how to access and process our open data-set containing more than one million DNS queries pertaining to data exfiltration we generated in our campus network, enabling insights into the attributes of such malicious queries; and (2) visualizing our real-time learning-based detection engine operational on 10 Gbps traffic streams from the network border of the university campus.
LibGuides: Agricultural Science Collection: My Research

A guide to all aspects of Agricultural Science Collection including content, searching, and viewing results on the new ProQuest platform.
Emotion recognition from facial expression

The aim of image (photo) based emotion recognition system emotion is to detect and classify the emotion from the human face from an image. The automatic system mainly has two components i.e. extraction of facial feature and classification of facial feature. To classify the feature precisely effective feature classification methods should be applied. Many recent systems uses additional information from classification which reduces accuracy as well as increase execution time. In this system Double Local Binary Pattern (DLBP) is used for feature extraction which is a variant of Local Binary Pattern (LBP). Since DLBP has small dimension size which reduces the detection time. To handle local illumination problem Logarithmic Laplace-Domain is proposed (LoL-Domain). Finally, Convolution Neural Network (CNN) is used for an obtained feature for classification.
Power of Predictive Analytics: Using Emotion Classification of Twitter Data for Predicting 2016 US Presidential Elections

Predictive analytics using the twitter feeds is becoming a popular field for research. A tweet holds a wealth of information on how an individual expresses and communicates their feelings and emotions within their social network. Large-scale collection, cleaning, and mining of tweets will not only help in capturing an individual’s emotion but also the emotions of a larger group. However, capturing a large volume of tweets and identifying the emotions expressed in it is a challenging task. Different classification algorithms employed in the past for classifying emotions have resulted in low-to-moderate accuracies thus making it difficult to precisely predict the outcome of an event. Secondly, the presence of diverse emotion annotated datasets, none of which are specific to a particular domain, has limited the potentiality of supervised algorithms for classification purposes. In this study, we demonstrate the potentiality of a lexicon-based classifier, NRC , which can mine emotions and sentiments in tweets. Using the NRC classifier, we initially determined the emotions and the sentiments within the tweets and used that to predict the swing direction of the 19 US states towards the candidates of the 2016 US presidential election. Comparing the predictions from the NRC against with the actual outcome of the election, we observed a ~90% accuracy, a performance superior to the mainstream pollsters indicating the potential emotion and sentiment-based classification holds in predicting the outcome of significant social and political events.
Three-dimensional target monitoring technique based on a morphology correlation for high-power laser applications

Existing monitoring and target positioning systems used in high-power laser fusion experiments have a complex structure and size, making their operation slow and calibration difficult. A simple and accurate positioning technique is proposed here that is based on cross-correlation between the morphology of the target measured at various positions. The morphology of the target is obtained using a spectral interferometer at a video frequency, and its three-dimensional (3D) position is determined by the position of the maximum spatial correlation coefficient. This technique can determine the 3D position and orientation of the target at the sub-micrometer range using only a single compact optical head. The proposed technique is quite simple in its structure and very convenient in operation. The feasibility and performance of the proposed technique is demonstrated in experiments.
Hate Speech on Campus: Reframing the Discourse

College campuses have long grappled with the question of allowing controversial speakers on campus. In the half-century since the Free Speech Movement at Berkeley, such events have become a fairly typical aspect of campus life. In recent years, however, increasingly divisive public figures have been invited—and, on occasion, disinvited. Being “deplatformed” has become a badge of honor for public figures like Ben Shapiro, Ann Coulter, and Milo Yiannapolous.
Asymptotic approximation of statistics based on the sample of negative binomial distribution

The paper proves the theorem on the limit distribution of negative binomial random sums. The results of modeling negative binomial random sums using the R programming language are demonstrated. As is well-known, in classical problems of mathematical statistics sample volume is a known parameter. In these problems, the statistics of random sums usually converges to the distribution of Gauss. Additionally, it can be stated that mathematical expectations of independent random terms do not affect the structural features of the limit distribution itself, except mathematical expectations of the limit distribution. In case of random sums, where the sample volume is also a statistic, the limit distribution of random sums with the sums of terms with zero mathematical expectation from the limit distribution of random sums with the sums of terms with non-zero mathematical expectation may be different. The formulated theorem shows that if the accumulation of terms in random sums has the character of a negative binomial distribution, the structure of the limit  distribution depends on the symmetry of the random terms. To estimate the convergence rate, Lemma proved that negative binomial random sums are mixed Poisson random sums with a mixing gamma distribution. Therefore, accuracy of asymptotic models of negative binomial random sums can be estimated by estimating the convergence rate of mixed Poisson sums.
Investigating the effect of automation on user experience: enriching a task-modeling notation

This position papers presents a solution to allow to analyze the impact of automation on user experience by extending a task notation with the concepts of function allocation, authority and representation, and the ability to represent data from user experience evaluations.
Collaborative filtering content for parental control in mobile application chatting

Mobile phone is an important medium of communication for most people regardless their age. One of the most used mobile phone application is chat application. Since mobile users are across different age groups, from youngsters to senior citizen, each age level has their own ways or styles of communication when using mobile application chatting. Adult mostly used proper syntax with complete sentences while youngsters normally use short forms with incomplete sentences. In addition, improper communication styles, usage of bad and inappropriate words has become a trend among youngsters. This matter gives negative impact on the education system in a short-term and national language preservation in a long term. Hence, in this paper, researchers present a tool that provides word recommendations for mobile application chatting. This tool would be is an education material to younger generation users with subtle approach. Implementation of the tool is by adapting Collaborative Filtering approach with User-Based model which focusing on recommendation on similar interest between users. Collaborative filtering content tool is functioning well during the functionality testing and it is thriving as a mobile application chatting guidance.