Reviewerly/exHarmony huggingface dataset:
Efficient PatchMatch Algorithm to Detect False Crowd in Digitally Forged Images

The authenticity and reliability of digital images have become one of the major concerns recently due to the ease in manipulating and modifying these images. Similar manipulation in crowded images gives rise to the false crowd, where a person or group of persons is copied and pasted in the same image. Thus, the detection of such false crowds is the focus of current research. In this paper, false crowd detection in forged images is carried out using modified and improved PatchMatch algorithm which can even detect multiple copies of the same instance. To sperate humans from non-human objects a human detection algorithm is used in the post-processing phase. A benchmark database consisting of false crowd images has also been developed. Experimental results confirm that the technique is capable of detecting the false crowds successfully and even robust for multiple cloning problem.
Enabling the Latent Semantic Analysis of Large-Scale Information Retrieval Datasets by Means of Out-of-Core Heterogeneous Systems

Latent Semantic Analysis (LSA) has already been widely and successfully applied in many applications for Natural Language Processing (NLP), usually working with fairly small or average sized datasets and no actual time constraints. Even so, LSA is a high time and space consuming task, which complicates its integration in real-time NLP applications (as, for example, information retrieval or question answering) on large-scale datasets. For this reason, an implementation of LSA that can both allow and accelerate as much as possible its execution on large-scale datasets would be most useful in these data-intensive, real-time NLP scenarios. However, to the best of our knowledge, such an implementation of LSA has not been achieved so far. Towards this end, a new, out-of-core, scalable, heterogeneous LSA (hLSA) system has been built and run on the clinical decision support large-scale dataset from the Text REtrieval Conference (TREC) 2015 competition. Results show that the out-of-core hLSA system can process this large-scale dataset (that is, 631,302 documents) with a full-ranked term-document matrix of 566 GB fairly fast and, besides, with a better precision (at least for one of the topics) than the TREC 2015 competing systems.
Spindle Torus Asymmetric Key Cryptosystem

A novel cryptosystem is created and tested for multimedia. It can be used in video conferencing, telemedicine, drone, cloud and military. Any node can enter or exit the network at any instant. Because of the nature of cloud networks, key generation and distribution is a great challenge. It is addressed by making it easier and faster to change keys. Generally, public key cryptosystems are slow as compared to private key cryptosystems. However, the novel algorithm proved to be faster than even symmetric key cryptosystems. Encryptions of multimedia are found to be comparatively more vulnerable to side channel attacks. This problem is addressed in the design of spindle torus cryptosystem. The cryptosystem also had inbuilt feature of compression. The algorithm can be modified to work as both stream and block cipher. Spindle torus cryptosystem proved to be at least 23.8 percent faster when compared with other cryptosystems.
The effect of organisational culture on students' cognitive, skill-based, and affective learning outcomes in higher education in Saudi Arabia [El efecto de la cultura organizacional en los resultados de aprendizaje cognitivo, basado en habilidades y afectivo de los estudiantes en la educación superior en Arabia Saudita]

The current study aimed to analyze the effect of organizational culture on students cognitive, skill-based and affective learning outcomes in Saudi higher education institutions. It has been conducted a quantitative research methodology by distributing questionnaires which contained 95 items to faculty members at two Saudi higher education institutions. 496 responses were further analysed using the SPSS (V23) and PLS-SEM. Results indicated that organisational culture has a direct and significant positive effect on students’ cognitive, skill-based, and affective learning outcomes in the context of Saudi higher education. The present study has a potential to reflect positively on the Ministry of Education, academic leaders, as well as support the higher education institutions. © 2019, Universidad del Zulia. All rights reserved.
Crowdsourcing for Urban Laborers and Time Optimization

The job opportunities in metro cities are immense but finding people with required skillset becomes difficult. Similarly, the worker’s migrating to these cities finds it difficult to get jobs and spend a considerable amount from their wages to reach the job location. Our system helps to ease these difficulties by providing jobs to the workers using recommendation systems and finding cost-efficient routes from the worker’s present location to the job site. The recommender system exploits the worker’s job history to provide recommendations by using the concept of real Boltzmann machine along with matrix factorization, and the location services take into consideration of various local transport services like shared-autos and taxis apart from trains and buses to suggest a cost-efficient path to ease the worker’s travel in a new city. The deep learning approach further enhances the recommender system efficiency by approximating rank for each job before recommending them to the worker.
Teachers' Perceptions on Mobile Pedagogy in China's Higher Education

Ubiquitous learning facilitated by mobile technology accelerates learning and teaching inside and outside the classroom. This study investigates how teachers perceived mobile pedagogy in their teaching experience. Qualitative data were obtained through 35 interviews from North Minzu University in China. Content analysis is conducted to analyze teachers' perceptions on their understandings of mobile pedagogy to digital natives. The study implicates that teachers have different understandings towards mobile pedagogy, though the majority showed a positive attitude that mobile pedagogy is an essential supplement for teaching in the digital era. Teachers' perception of mobile education and their technological background are important factors influencing their teaching practice with mobile technology. Teachers need to improve pedagogical approaches integrated with technology to meet the demand of today's generation.
Design and FPGA prototype of modified Blum-Blum-Shub pseudorandom sequence generator

The algorithm of the Blum-Blum-Shub, BBS, generator is cryptographically secure pseudorandom number generator. The paper investigates the design and FPGA prototype of modified Blum-Blum-Shub pseudorandom sequence generator. The goal of the design is to have number of cycles for modified BBS algorithm close to classic BBS algorithm. Since BBS algorithm based on large integer modular multiplication, the FPGA prototype uses the Montgomery multiplication algorithm. It was established that it is possible to generate sequence with modified BBS algorithm, which has better repetition period and statistical characteristics, for the same number of cycles in compared to classic BBS algorithm, but with additional number of circuits.
Presentational Advances in User-Based Design Processes in Architecture and Civil Engineering: Virtual Reality Dimension

Virtual Reality has been acquired in certain fields where the interaction is important such as the Architectural-Engineering-Construction field. This paper aimed to investigate the impact of using Virtual reality in Designing Process on improving the communication between Designers and Users. Using Qualitative research methodology, the findings agree that the major disadvantage is difficult software workflow for specific industries. It has been concluded that the increased interest in VR and immersive environments is allowing better understanding and identification of problems and is offering more accurate visualization and better project communication.
THE DEVELOPMENT OF STUDENTS’ CRITICAL THINKING IN LEARNING A FOREIGN LANGUAGE

&#x0D; &#x0D; &#x0D; This article deals with the issue of working out and incorporating in educational process of higher educational institutions of the innovative technology for developing skills of critical thinking for the future Management specialists. The research is aimed at revealing both theoretical and practical ideas about critical thinking development in English language teaching. To enhance critical thinking in learners, foreign language teachers use various methods and techniques, consequently there have been described the following methods such as “Lead-in”, “Socratic Questioning”, “Business role play”, “Active reading”, and “Translation”. The use of the above methods by foreign language teachers in classes contribute to the development of critical thinking among students and motivate them for learning a foreign language, as well as making the study process be possible to turn from routine work into interactive, interesting and challenging activities.&#x0D; &#x0D; &#x0D;
Interefernce Reduction in Embedded Medical Image

Patient file Number and finding is embedded inside the medical image provide significant information which should be unavailable to a un-authorized person who does not have an access to the image. The medical image effect by variant type of noise corrupt the image quality when it comes to protecting information in the medical image. In this project, we will present a method to interference reduction in the embedded medical image. A method Encrypt the patient file number and findings by using RSA and then embedding in a medical image by Discrete Wavelet Transform (DWT) technique. For reduction noise, we filter the medical image after the previous process by Median filter. With this system, any medical image that will be transferred will have the patient file number and findings hidden and embedded in the image with better quality.
Graph-Related Properties for Comparing Dynamic Call Graphs

Software systems produce long sequences of call graphs, in particular, if the graphs are generated during runtime and not revision by revision. Visualizing, analyzing, and interacting with such long dynamic graphs with respect to different properties is a challenging task. In this article we describe an interactive visualization technique for dynamic call graphs that supports the observation of the data in vertex, edge, and time dimensions based on properties related to the graph topology, inherent vertex hierarchy, involved links, and graph-theoretic problems. Moreover, we provide a time-aligned view on several dynamic graphs with the goal to compare them visually. We also provide standard node-link diagrams for individual graphs or aggregated dynamic graph subsequences as a details-on-demand technique and for supporting graph comparisons on different temporal granularities. We illustrate the usefulness of the dynamic graph visualization by applying it to the call relations at runtime of the open source software project JHotDraw. We evaluated the interactive visualization by reflecting on the static and dynamic patterns we could identify in the dataset by changing the graph properties under exploration. Moreover, we conducted a controlled user study with 20 participants investigating three typical tasks like finding graph sequences, identifying a complete graph, and exploring the reason for a change in a shortest path algorithm. Finally, we discuss scalabilities and limitations of our approach.
Expert Nutritional System for Military Athletes Based on Fuzzy Logic and Inferential Statistics

Athletic performance seeks to enhance the physical and mental state of the athlete, and it is implicit to systematize sports training; for this reason, managing the monitoring of the physical state of athletes implies relating variables such as initial physical performance, hydration, types of nutrition, and training to take successful strategic actions. Among the innumerable factors that promote success in sport, training, motivation and, above all, resistance to bodily injury is limited since the time to test the athlete in respect to his talent and training the margin of risk between victory and defeat is minimal, nutrition is a fundamental element in the physical preparation of a specific athlete of those who are very disciplined because the diet benefits or affects sports performance and therefore the desired result. It must be taken into account that each athlete must be aware of the nutritional objectives to be achieved and how they can improve a feeding strategy to comply with the expert’s guidance and in this way shape their long, medium and short term goals. This study was a focus on planning and training of military athletes and proposes the structure of an expert nutritional system to reach better standards. The system is available through the use of web services focused on new technologies based on inferential statistical systems and fuzzy logic applying a statistic analysis aimed at decision making. The web services are aimed at improving the monitoring of the physical condition of the athletes to provide nutritional support for the maintenance of a healthy lifestyle with good physical performance, that is to say, it simplifies the information contained in the original variables, looking for the interrelations between the numerical variables defined simultaneously in a set of elements. The results achieved show an improved performance in the physical evaluation of athletes.
Peer Ratings of Grade 11 Students Using Technology and Traditional Materials in Their Oral Presentations

This study aims to investigate the peer ratings of 72 Grade 11 students in their report presentations in English for Academic and Professional Purposes (EAPP) where they used technology and traditional materials. Selected through purposive sampling, they were asked to submit the ratings given by their peers in the following categories: presentations using technology, presentations using traditional materials, and presentations using combined technology and traditional materials. Findings showed that regardless of the type of instructional materials used, males and females did not differ in their performance. However, a significant difference existed between using traditional materials and using a combination of technology and traditional materials, which indicates that there is a significant effect in the performance of students (F-value=6.642; p-value=.002). Students obtained the lowest performance with the use of traditional materials alone, but highest with the combination of technology and traditional materials. Focus group discussions with six students and eight teachers were conducted. Themes generated from both groups include delivery of report presentations, materials used, strengths and weaknesses of traditional and technology materials, and performance of students using technology. From the semi-structured questionnaire, 70 out of 72 students claimed that they performed better with the combination of technology and traditional materials. Thus, both technology and traditional materials still play an important role in a Filipino learning environment.
Blockchain-based Sensor Data Validation for Security in the Future Electric Grid

This paper explores the feasibility of using blockchain technology to validate that measured sensor data approximately follows a known accepted model to enhance sensor data security in electricity grid systems. This provides a more robust information infrastructure that can be secured against not only failures but also malicious attacks. Such robustness is valuable in envisioned electricity grids that are distributed at a global scale including both small and large nodes. While this may be valuable, blockchain's security benefits come at the cost of computation of cryptographic functions and the cost of reaching distributed consensus. We report experimental results showing that, for the proposed application and assumptions, the time for these computations is small enough to not negatively impact the overall system operation. From this we conclude that it is indeed worthwhile to further study the application of blockchain technology in the electricity grid, removing the assumptions we make and integrating blockchain in a much more extensive manner. To the best of our knowledge, this is the first instance where blockchain is used to validate the measured sensor data in the electricity grid, thus providing security to other system operations.
Maximum Entropy Based Urdu Part of Speech Tagging

This paper represents results for a part of speech tagger based on Maximum Entropy model on Urdu corpora. We discussed the specialized features/parameters of the model and their impact on tagger performance. We also discussed the complexity of Urdu language for a tagger to predict correct tag and inconsistencies in corpora found during experiments. For the purpose of detailed experiments, two different corpora are used in this paper. The maximum accuracy recorded for tagger is 93.24% overall and 69.89% on previously unseen data.
Genetic Ant Colony Algorithm Improves Resource Scheduling in Cloud Computing

When a large number of users request cloud computing resource services, rational organization of resources and task scheduling is one of the key technologies of cloud computing. Aiming at the problems of low efficiency and slow convergence speed of existing cloud computing resource scheduling algorithms, combined with the characteristics of global search ability of genetic algorithm and positive feedback convergence of ant colony algorithm, a resource scheduling algorithm is proposed. The initial pheromone distribution is generated by the genetic operator, and the exact solution is obtained by the bidirectional convergence ant colony operator. The experimental results show that the proposed algorithm is superior in solving accuracy and convergence speed, and it is an effective cloud computing resource scheduling algorithm.
Quantum Mechanics Formalism for Modeling the Flux of BitCoins

Because bitcoins processes depend on Internet transactions, one can argue that the dynamics of flux and volume of bitcoins might be subject to stochastic instead of a pure determinism event. By knowing that Quantum Mechanics describes well physics in the microscopic level and it is capable to calculate exact measurements of physical observables, we apply the concept of amplitude of probability to model the success probability of any transaction involving the new monetary unit so-called bitcoins. In this manner we focus on the description of the potential transactions using entirely the formalism of quantum mechanics. In addition we use also the concept of Green’s function that appear along the construction of the amplitude. Although not any direct correspondence can exist between the dynamics of flux of bitcoins and the purpose of a quantum theory, the modeling is limited to the extent of the interpretation of the success probability to complete any bitcoin-based transaction. For a transaction of $$\mathcal{N}$$ US dollars, we found that the bitcoin flux might reach up to a 90% of the completion of the transaction.
A Binary I-Ching Divination Evolutionary Algorithm for Feature Selection

Feature selection is used to extract the most essential features from the data without degrading the performance of an algorithm, especially a classification algorithm. Various evolutionary algorithms (EAs) combined with classification algorithms are commonly used for feature selection. This paper suggests an innovative feature selection algorithm based on I-Ching Divination Evolutionary Algorithm, called binary IDEA (BIDEA). The main idea is to use a series of hexagrams encoded as binary vectors, which is called the hexagram state to represent the solutions of selected features. After three flexible operations, intrication, turnover and mutual, the transformed hexagram state can be obtained as candidate solutions. Then the optimized hexagram state can be searched to form the new state in the next iteration by evaluating candidate solutions. Experiments checked out with standard datasets reveal that the proposed BIDEA performs better in terms of classification accuracy, precision, recall and feature reduction than the competing feature selection methods.
Personality Development in the Information Society Engineering Education

Contradictory goals of the educational process such as to bring up a student as a personality or as a professional cause disputes among scientists whether education is a service or value, and lead professors to frustration regarding the ways of training and personal development of students due to reduced number of class hours and human sciences, especially in engineering and technical universities.Human development is at the same time humanistic and pragmatic, it can be realized through education at different levels, it is in demand both by the society and the state; its peculiarities are connected with a person’s individual experience.In the theoretical part of the study, analysis of the discussion on the problems of humanization and humanitarization of higher engineering and technical education in Russia is provided. Modernization of the education system through humanitarization and humanization, along with the competency-based approach, will help overcome the dehumanization of education by changing its content, which requires the integration of humanities and natural sciences knowledge.In the practical part of the study, an important component with a significant humanistic and humanitarian potential in a multi-disciplinary technical university is defined as liberal arts education, aimed at developing culture of interaction, communication, and interpersonal relations.The authors propose a model of interactive communication learning, which was successfully implemented in the distance and full-time education in humanities with undergraduate, master’s, and PhD students. Classes were conducted in the form of pair, group and project activities using role-plays, business games and case studies.
AR Flashcards for Asian Language Learning

Bilingualism has been reported to improve significantly the quality of life of individuals in varying age groups, especially the elders. Therefore, this paper demonstrates an augmented reality framework to render 3D objects over corresponding Chinese or Japanese words, with or without the respective pronunciation. The application can identify 5 different logograms from their doubles, making it a potential auxiliary tool in the second language learning process.
Classification of Social Media Users Based on Disagreement and Stance Analysis

Analyzing conversational behavior is a primary task in the field of sentiment analysis. Different researchers have proposed their models to perform the sentiment analysis of social media discussions. Existing approaches mainly studying the conversational behavior based on the text in the conversation. In any discussion, the users could have different viewpoints about the topic of conversation. A user can agree or disagree on the topic of discussion. Agreement of a user to the topic is called a stance, and if the user disagrees to the topic, we refer it as disagreement. The classification of the users based on stance and disagreement is not a well-researched area, and need to be explored further. In this work, we have proposed a computational model to classify the members according to stance or disagreement. The proposed model uses the novel approach, and it is a hybrid of topic modeling and VADER (Valence Aware Dictionary and sEntiment Reasoner). To evaluate the proposed model, we have conducted an experiment, and we did use the WhatsApp group discussion, Facebook comments as a dataset. We also compared the proposed model with two baseline approach, topic modeling, and VADER. From the results, we can conclude that the proposed model can effectively classify social media users based on disagreement and stance.