Reviewerly/exHarmony huggingface dataset:
Building the Predictive Scale for the Psychological Efficiency of the Athletes Students at Al-Furat Al-Awsat Technical University

The objectives of the research focused on the preparation of a questionnaire to build a predictive measure of psychological efficiency for the students of the athletes of the University of the Middle Euphrates technical, as well as “the recognition of predictions of psychological efficiency, and applied research on a group of athletes at the University of the Euphrates Middle Tech for the period of 22/11/2017 and The researcher used the descriptive method in the survey method. The most important steps of the research are to limit the number of athletes in Al-Furat Al-Awsat Technical University from the students. The main questionnaire was composed of (48) Building a collective and individual scale, as required (325) questionnaires were returned (301), (24) of which were excluded due to lack of complete answer.
Formal Modelling and Verification of Spinlocks at Instruction Level

Spinlocks have been widely used as a solution for synchronous accesses to shared resources, and their correctness is critical to guarantee the consistency of concurrent processes. This paper presents formal models and machine-checked verification of the correctness of spinlocks at instruction level. We present the formal verification of two spinlocks, which are spinlocks implemented based on the ARM instructions and the x86 instructions, respectively. Our model formalizes the lowlevel instructions that are necessary to capture the execution of spinlocks, characterizes the processor hardware mechanisms related to each instruction, and considers the context switches on processors and two-level scheduling of processors and processes. We specify the correctness property of our models, that is, accesses of a critical section satisfy mutual exclusion, and verify that the models satisfy the property using the theorem prover Isabelle/HOL. With the verification experience, we give some suggestions on how to implement spinlock leveraging the ARM ISA.
Detection of Proper Form on Upper Limb Strength Training Using Extremely Randomized Trees for Joint Positions

Learning how to perform a workout usually requires a little bit of research for people without experience, especially if it's in strength training or a workout that uses an equipment. Having an experienced instructor guide a trainee to perform such activity is enough, but with the advancement of computer vision, it opens up an opportunity to use technology to teach us without human intervention. In this study, Kinect V2 will be used to detect the joints of the subject and capture the starting and the end position of the workout. By tracking the position of the joints through the RGB-D sensor, the model will determine if the posture was performed correctly by the subject of these 5 (five) workouts: dumbbell lateral raise, dumbbell shoulder press, barbell front raise, dumbbell shrug, and barbell upright row. The data will be collected using the Java language and the KinectPV2 library to get the coordinates of the joints for each subject. Scikit-learn will be the chosen platform in the model creation for training and testing the datasets. Extremely Randomized Trees is a tree-based ensemble method for supervised classification and regression that will randomize. ERT will be used to the model proposed and compare it to the KNN.
Property-Directed Inference of Relational Invariants

Property Directed Reachability (PDR) is an efficient and scalable approach to solving systems of symbolic constraints also known as Constrained Horn Clauses (CHC). In the case of non-linear CHCs, which may arise, e.g., from relational verification tasks, PDR aims to infer an inductive invariant for each uninterpreted predicate. However, in many practical cases this reasoning is not successful, as invariants should be derived for groups of predicates instead of individual predicates. The article describes a novel algorithm that identifies these groups automatically and complements the existing PDR technique. The key feature of the algorithm is that it does not require a possibly expensive synchronization transformation over the system of CHCs. We have implemented the algorithm on top of a up-to-date CHC solver Spacer. Our experimental evaluation shows that for some CHC systems, on which existing solvers diverge, our tool is able to discover relational invariants.
Introduction to Software Design

Software design is introduced by describing what is and what is not software design. Approaches for creating a software design are then discussed, along with some examples to help you better understand the concept of abstraction. Software design is then described within the context of a software development process (SDP). Finally, three generic SDPs—waterfall, incremental, and agile—are described to emphasize the similarities and differences between these three approaches and how software design fits within each approach.
DYNAMICS OF ART AND SCIENCE AS TRANSFORMATION OF MENTALITY OF THE EUROPEAN CULTURE

Dynamics of art and science is shown as transformation of mentality of the European culture. The problem of stability and variability as vision of existence and time is illustrated by the analysis of human essential characteristics manifested through descriptions of the surrounding world. The analysis is based on the conception “mentality”. The mental method is understood as analysis of archetype dynamics. Parallelism in the process of changing archetypes established in art and science is interpreted as similarity of their existential foundations represented in mentality of the European culture. Using the mental method, the author identifies common foundations of tradition and innovation in the European culture.
Law Is Order: Protecting Multimedia Network Transmission by Game Theory and Mechanism Design

Nowadays, the computer network plays as the most important medium in the transmitting of multimedia. Correspondingly, the orderliness of network is the protection of multimedia transmission. However, due to the Packet Switching design, the network can only provide best-effort service, in which the multimedia applications compete for its network resource. In the lawless competition, the applications are obliged to be greedy and deceptive driven by their best self-interest. As a result, the transmission of multimedia applications becomes disorderly and inefficiently, and we lose the protection of multimedia network transmission. In this paper, we first investigate the behaviors of multimedia applications with Game Theory, and summarize the disorderly transmission as a Prisoner’s Dilemma. The lost of law leads to the disorderly transmission in multimedia network. Then, we investigate the relationship between application’s media-attribute and its required transmission service, and resolve this Prisoner’s Dilemma with Mechanism Design. Specifically, a novel Media-attribute Switching (MAS) is proposed, where the network allocate the transmission resources according to the application’s claimed media-attribute. In MAS, differentiated services are provided to applications with different claimed media-attribute. We design MAS to have the honesty application gets compatible service while the deceptive application gets incompatible service. Therefore, the MAS can provide incentives for multimedia applications to label their data media-attributes honestly and allocate the network resources according to their attributes, thus to protect the multimedia network transmission. The theoretical analysis and experimental comparison both prove our MAS’s protection to the multimedia network.
A Secure Key Scheduling Operation for International Data Encryption Algorithm using Serpent Key Schedule Operation

The International Data Encryption Algorithm (IDEA) is one of an encryption algorithm that uses a cyclic process in producing sub keys from secret key using its key schedule but generates large weak keys. GISKOP is a modified IDEA that uses the concept of serpent key scheduling operation to address the weak keys found on the original IDEA. Randomness test was used to identify the dependence and correlations between generated sub-keys of a key scheduling operation. Statistical evaluation was done to analyze and compare key distribution and exchange operations of the modified key scheduling operation. The GISKOP key scheduling operation obtained an increase of 8% randomness using frequency test in the sub-key independence level. Also, it was able to maintain its 100% randomness under the sub-key level independence. Thus, proving that each generated sub keys are not correlated with each other. With this, many attacks on systems that implement IDEA can be mitigated. Furthermore, the findings will take advantage of independency or nonlinear relationship between sub-keys and prevent breaking the whole cipher.
Data Mining Algorithms for Knowledge Extraction from Web Log Files

Web log files contain visitor activity information on a website. They are automatically created and maintained by a web server. The raw web log file format is essentially one line of text for each visit of the web site, each time a visitor requests a page (HTML document, image, etc.), information about the request (including client IP address, request date/time, page requested, HTTP code, bytes served, user agent, and referrer) are added to the current log file. The web maintains a standard format the CLF (Common Log Format) for web server log files. Analysis of server log file can provide significant and useful information, data extracted from log files could be stored in a database, allowing various uses when needed. Data Mining is the process of extracting and discovering patterns and knowledge from large amounts of data. Web Mining is the extraction of interesting and potentially useful patterns and implicit information from artifacts or activity related to the Web. Web Usage Mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. It is the application of data mining techniques to discover usage patterns from web data. In this paper, we present an analysis and extraction of useful information and patterns from web data based on a deep analysis of web log files, first we start with the presentation of different formats of web log files, then we present the different preprocessing used methods, finally the demonstration of the system “Web content and Usage Mining’’ for extracting knowledge from web data and web site analysis using several Data Mining Algorithms Apriori, FPGrowth, K-Means, KNN, and ID3.
Location histogram privacy by Sensitive Location Hiding and Target Histogram Avoidance/Resemblance

Abstract A location histogram is comprised of the number of times a user has visited locations as they move in an area of interest, and it is often obtained from the user in the context of applications such as recommendation and advertising. However, a location histogram that leaves a user’s computer or device may threaten privacy when it contains visits to locations that the user does not want to disclose ( sensitive locations ), or when it can be used to profile the user in a way that leads to price discrimination and unsolicited advertising (e.g., as “wealthy” or “minority member”). Our work introduces two privacy notions to protect a location histogram from these threats: Sensitive Location Hiding , which aims at concealing all visits to sensitive locations, and Target Avoidance/Resemblance , which aims at concealing the similarity/dissimilarity of the user’s histogram to a target histogram that corresponds to an undesired/desired profile. We formulate an optimization problem around each notion: Sensitive Location Hiding ( $${ SLH}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>SLH</mml:mi></mml:mrow></mml:math> ), which seeks to construct a histogram that is as similar as possible to the user’s histogram but associates all visits with nonsensitive locations, and Target Avoidance/Resemblance ( $${ TA}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>TA</mml:mi></mml:mrow></mml:math> / $${ TR}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>TR</mml:mi></mml:mrow></mml:math> ), which seeks to construct a histogram that is as dissimilar/similar as possible to a given target histogram but remains useful for getting a good response from the application that analyzes the histogram. We develop an optimal algorithm for each notion, which operates on a notion-specific search space graph and finds a shortest or longest path in the graph that corresponds to a solution histogram. In addition, we develop a greedy heuristic for the $${ TA}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>TA</mml:mi></mml:mrow></mml:math> / $${ TR}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>TR</mml:mi></mml:mrow></mml:math> problem, which operates directly on a user’s histogram. Our experiments demonstrate that all algorithms are effective at preserving the distribution of locations in a histogram and the quality of location recommendation. They also demonstrate that the heuristic produces near-optimal solutions while being orders of magnitude faster than the optimal algorithm for $${ TA}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>TA</mml:mi></mml:mrow></mml:math> / $${ TR}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>TR</mml:mi></mml:mrow></mml:math> .
Video stalling detection method

Abstract ISP providing network access services has a huge user group; therefore the competition between the ISP providers is extremely fierce. Under the situation that video occupies the most of network flow, providing high satisfaction network services for video users can effectively improve the competitiveness of ISP, in which video Stalling plays an important index. For protecting the privacy of users, most video websites use HTTPS as the application layer protocol for video transmission, so ISP could not get the playback of video users by parsing HTTP packets, and could not directly detect the video users. In this assay, a new method, protocol transport layer Video Stalling Detection Method based on HTTPS is proposed. This method can effectively match the YouTube, Youku, Letv, Tencent video and other major video sources of the stalling event.
Simulation application of virtual reality technology in legal education

Abstract The virtual simulation teaching of law is a systematic practice course of judicial case handling. This course introduces VR technology, enabling testers to play the role of a judicial officer in a virtual environment to handle cases. This design is realized through the intersection of the teaching design by the arts and sciences, the construction of virtual models, and man-machine interaction. Through this design, students can improve their ability to handle cases, develop students’ thinking, and enhance students’ ability to use their knowledge comprehensively. In order to ensure better experimental results, it is necessary to provide technical support from scene simulation, case simulation, mechanism simulation and so on.
Context-Aware Residual Network with Promotion Gates for Single Image Super-Resolution

Deep learning models have achieved significant success in quantities of vision-based applications. However, directly applying deep structures to perform single image super-resolution (SISR) results in poor visual effects such as blurry patches and loss in details, which are caused by the fact that low-frequency information is treated equally and ambiguously across different patches and channels. To ease this problem, we propose a novel context-aware deep residual network with promotion gates, named as G-CASR network, for SISR. In the proposed G-CASR network, a sequence of G-CASR modules is cascaded to transform low-resolution features to high informative features. In each G-CASR module, we also design a dual-attention residual block (DRB) to capture abundant and variant context information by dually connecting spatial and channel attention scheme. To improve the informative ability of extracted context information, a promotion gate (PG) is further applied to analyze inherent characteristics of input data at each module, thus offering insight for how to enhance contributive information and suppress useless information. Experiments on five public datasets consisting of Set5, Set14, B100, Urban100 and Manga109 show that the proposed G-CASR has achieved averagely 1.112/0.0255 improvement for PSNR/SSIM measurements comparing with the recent methods including SRCNN, VDSR, lapSRN and EDSR. Simultaneously, the proposed G-CASR requires only about 25% memory cost comparing with EDSR.
ФОРМУВАННЯ УРБАНІСТИЧНОГО ПРОСТОРУ СЛОБОЖАНЩИНИ ХVIII ст. (НА ПРИКЛАДІ ТВОРЧОСТІ Г.С. СКОВОРОДИ)

The article considers the peculiarities of the formation of the urban culture of Slobozhanshchina during the eighteenth century in the conditions of the transformation of society, changes in the way of life guidance, and beliefs of various stratums of society. It is proved that the theme of the city occupies a special place in the creative heritage of anthropocentric philosophy of Skovoroda. The philosopher shares the notion of the city as"ghrad"(staroslav.) and "city," which distinguishes the idealized rustic that opposes the "city." The educational role of Skovoroda ideas in structuring the urban space of the Slobodsky Krai in the democratic field of European tradition is shown. The Ukrainian philosopher, along with Augustine and the Blessed Utopians of the Renaissance, described his vision of the foundations of a just society as his"ghrad"(staroslav.) . Determining the role of man in the world Frying pan carries out through the philosophical reflection of the ontological external through the internal monologue of the subject. Exit from the ontological situation of violence, war, confrontation of the philosopher through the collective image of the city sees in the moral integrity of man. The analysis of the topic is carried out in the retrospect of the temporal cut of the history of the region in a plurality of political, cultural, social and multinational factors. The policy of central government in Sloboda Ukraine during the XVIII century. from the decrees of Peter I to the transformations of Catherine II, is schematically traced in parallel with the philosophical thought of the Ukrainian thinker. The emphasis is on the peculiarities of the formation of the ethnic diversity of the region. The transformation of Ukrainian society by the example of Slobozhanshchyna under the influence of the centralization policy of the Russian Empire has no direct reflection in the philosophical work of Skovoroda. Being manifestations of society - politics, economics, state reforms - through the prism of anthropo-philosophical reflection appear in the Ukrainian philosopher the concept of a redefined "inner man" with a complete Christian morality. The preconditions of formation of the urban space of Slobozhanshchyna on the example of Kharkiv due to the features of settlement, the military-democratic Cossack system and external factors of influence are considered. A set of factors of the formation of the cultural center of the Sloboda region, which created the synergy of the creation of a pro-European city
A Fine-Grained Authorized Keyword Secure Search Scheme in the Cloud Computing

The development of the Internet and the Internet of Things has led to a sharp increase in the amount of data. The great advantages of big data have promoted the research and usage of a series of related technologies in various fields. In the field of government, data from various departments is being aggregated to acquire more value which can help to improve the efficiency and quality of public service. Cloud computing, as an infrastructure of big data, is also applied in government big data. However, the sensitivity of government data determines that the data stored in the cloud must be well protected. Meanwhile, fine-grained data sharing is also important for the public services of government. Recently, several searchable attribute-based encryption schemes have been proposed to achieve fine-grained data access control and search on ciphertext simultaneously. Unfortunately, each of them has some imperfections in efficiency or access policy. In this paper, we propose a fine-grained authorized keyword secure search scheme by leveraging the attribute-based encryption primitive, whose access policy supports AND, OR, and threshold gates. We give the concrete construction, rigorous verification of correctness, detailed security analysis, and prove that our solution is efficiency through several experiments.
Assessment and Elimination of Inflammatory Cell: A Machine Learning Approach in Digital Cytology

In automatic cytology image diagnosis, the false-positive or false-negative often come up with inflammatory cells that obscure the identification of abnormal or normal cells. These phenotypes are presented in the similar appearance in shape, color and texture with cells to detect. In this paper, to evaluate the inflammation and eliminate their disturbances of recognizing cells of interests, we propose a two-stage framework containing a deep learning based neural network to detect and estimate the proportions of inflammatory cells, and a morphology based image processing architecture to eliminate them from the digital images with image inpainting. For performance evaluation, we apply the framework to our collected real-life clinical cytology slides presented with a variety of complexities. We evaluate the tests on sub-images cropped from 49 positive and 49 negative slides from different patients, each at the magnification rate of 40×. The experiments shows an accurate profile of the coverage of inflammation in the whole slide images, as well as their proportion in all the cells presented in the image. Confirmed by cytotechnologists, more than 96.0% of inflammatory cells are successfully detected at pixel level and well-inpainted in the cytology images without bringing new recognition problem.
The Design Process for Enhancing Visual Expressive Qualities of Characters from Performance Capture into Virtual Reality

In designing performances for virtual reality one must consider the unique qualities of the VR medium in order to deliver expressive character performance. This means that the design requirements for participant engagement and immersion must evolve to address these new possibilities. To address the need for evolving an expressive character performance for VR, a five step production framework is proposed which addresses steps of directing, performance capture, the cyclical stages of retargeting and animation refinement and movement translation to avatars in VR.
A Certificateless Aggregate Signature Scheme Based on Blockchain for EMR

In this paper, a certificateless aggregate signature scheme for blockchain- based electronic medical record (EMR) is proposed, which has the characteristics of decentralization, security, credibility and tamper-proof. Performance analysis shows that the proposed scheme has constant communication cost and low computational cost. This scheme can be utilized to tackle difficult problems in regard to identity authentication in EMR. It can also preserve the integrity of EMR data.