Reviewerly/exHarmony huggingface dataset:
Reimagining the Indian Political Set-Up:A Political Branding Outlook

Politics is one area which the layman might not associate with the field of branding but with time this aspect of modern-day democracy has become synonymous with branding. Jevons (2005) is of the view that branding is flexible enough to include the realms of politics. The consumer-citizen concept is a step in this very direction. Today’s voter behaves more on the lines of a consumer who needs to convinced to buy into (read vote) the brand promises (read election manifesto and promises made during campaigning) put up by various political brands. Just like there are two aspects of a brand, successful and failed, political branding is no exception to the same. Modern times have seen the rise of many a political brands some of whom have had an ardent following while others have been shunned by the electorate for their disconnect with the voter. The western democracies such as US and UK are replete with political brands which have proven their mettle (or faded into oblivion) during various elections. However, the same has came to fore only in the past few years in India thanks to the information revolution. No other election witnessed more significantly the concept of political branding as did the last two general elections of 2014 and 2019. The concept of political branding and political participation have shown quite strong relationship between them in those countries where it is applicable. Through this paper, the author has attempted to establish a relationship between political branding and political participation along with what characterizes the successful making of a political brand in a conceptual way.
Research on the Application of VR Technology in the Cultivation of Double Innovation Talents

Shuangchuang talents refer to talents with innovative thinking and entrepreneurial abilities. This is also the main goal of training talents for education and teaching in my country’s higher education institutions. In the process of training and teaching innovative and entrepreneurial talents, there are problems such as imperfect training facilities and insufficient teachers, which have seriously affected the training of innovative talents in universities. The rise of VR technology has provided a new way for the training of entrepreneurs and entrepreneurs, which not only greatly eases the resource input of talent education in colleges and universities, but also effectively improves the efficiency of talent training. This article conducts detailed research on the application of VR technology in talent education and training from multiple perspectives.
Algorithm of Information Embedding into Digital Images Based on the Chinese Remainder Theorem for Data Security

With the huge transfers of data involved in the modern world, it is both crucial and challenging to maintain the security of data. This paper proposes a novel algorithm of information embedding into digital images that could be used to protect confidential information. The presented algorithm makes use of the Chinese remainder theorem and adaptive embedding to achieve good imperceptibility along with the possibility of hiding a decent amount of confidential information. The algorithm is evaluated via computing experiments and evaluation results, as well as comparison with similar works, demonstrate good imperceptibility qualities of the proposed scheme.
Constructing trading strategy ensembles by classifying market states

Rather than directly predicting future prices or returns, we follow a more recent trend in asset management and classify the state of a market based on labels. We use numerous standard labels and even construct our own ones. The labels rely on future data to be calculated, and can be used a target for training a market state classifier using an appropriate set of market features, e.g. moving averages. The construction of those features relies on their label separation power. Only a set of reasonable distinct features can approximate the labels. For each label we use a specific neural network to classify the state using the market features from our feature space. Each classifier gives a probability to buy or to sell and combining all their recommendations (here only done in a linear way) results in what we call a trading strategy. There are many such strategies and some of them are somewhat dubious and misleading. We construct our own metric based on past returns but penalising for a low number of transactions or small capital involvement. Only top score-performance-wise trading strategies end up in final ensembles. Using the Bitcoin market we show that the strategy ensembles outperform both in returns and risk-adjusted returns in the out-of-sample period. Even more so we demonstrate that there is a clear correlation between the success achieved in the past (if measured in our custom metric) and the future.
Online blended learning in the digital environment

Abstract The article presents the results of a study of the processes of educational activity in the context of the digital revolution. The authors focus on the scale of the spread of digital technologies, the provision of users with electronic means of communication, and the availability of the Internet network for argumentation of the established global information society. It was noted that in the context of the digital revolution, the face of manufacturing industries is changing. Market engagement platforms facilitate the diffusion of innovation and transformation of business models. In the context of the analyzed processes, the requirements for personnel are changing. The demand for professionals trained to work in a digital environment is expected to grow. It is hypothesized that personnel capable of research work, management of the processing of large data arrays and relevant information on the controlled or investigated object will have a high value. It is suggested that within the framework of courses on in-depth study of the use of tools of modern information systems, students should acquire the practice of independent work in the functional areas of information systems of business organizations. These can be separate information subsystems serving individual functions, processes, departments, for example, information systems and technologies of procurement, production, sales, processes for developing and implementing business development goals and strategies. The development and implementation of online blended learning courses aimed at organizing the learning environment can speed up the processes of training personnel to work in a digital environment. The authors express the point of view-network blended learning will be relevant for the training of developers and users of information systems, the development of engineering and technical and humanitarian competencies.
IMPLEMENTASI KUNJUNGAN RUMAH DALAM PEMBELAJARAN PADA MASA PANDEMI

The implementation of the home visit is one of the efforts made by the teachers in optimizing student learning activities in the middle of online online learning during the Covid -19 pandemic. This study aims to describe the application of the home visit method in increasing student motivation. This type of research approach used is a qualitative approach. The location of this research was carried out in MI Muhammadiyah Program Khusus Sindon 1. Data collection was carried out by interview. The result showed that:1) home visits were carried out at the encouragement of parents and the school officials. 2) Thr home visit program was very effective in implementing learning activities during the Covid-19 pandemic, even though teachers experienced problem with the infrastructure in the program.Keywords:Â Home Visit; Covid-19 Pandemic;Â Learning
F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration

Deformable image registration (DIR) is essential for many image-guided therapies. Recently, deep learning approaches have gained substantial popularity and success in DIR. Most deep learning approaches use the so-called mono-stream "high-to-low, low-to-high" network structure, and can achieve satisfactory overall registration results. However, accurate alignments for some severely deformed local regions, which are crucial for pinpointing surgical targets, are often overlooked. Consequently, these approaches are not sensitive to some hard-to-align regions, e.g., intra-patient registration of deformed liver lobes. In this paper, we propose a novel unsupervised registration network, namely the Full-Resolution Residual Registration Network (F3RNet), for deformable registration of severely deformed organs. The proposed method combines two parallel processing streams in a residual learning fashion. One stream takes advantage of the full-resolution information that facilitates accurate voxel-level registration. The other stream learns the deep multi-scale residual representations to obtain robust recognition. We also factorize the 3D convolution to reduce the training parameters and enhance network efficiency. We validate the proposed method on a clinically acquired intra-patient abdominal CT-MRI dataset and a public inspiratory and expiratory thorax CT dataset. Experiments on both multimodal and unimodal registration demonstrate promising results compared to state-of-the-art approaches.
Psychological aspects of ensuring the efficiency of professional activity of a project engineers

The article presents the results of theoretical and empirical research of the problem of psychological aspects of ensuring the efficiency of professional activity of a Project Engineers in the context of the theory of general and special abilities, the need to take into account the general and individual-typological in the mental development of the subject of labor. The importance of considering professional skills in connection with the intellectual readiness of the subject to the activity and individual style of its implementation is theoretically substantiated. The empirical study revealed the presence of correlations between the efficiency of professional activity, psychological readiness and individual style of activity. The most referent in the description of the professional skills of project engineers are the time of labor tasks performance and individual style of activity, and the organizing factor in the unity of these indicators is the generalization of mental activity, which forms the core of intellectual readiness for work. Correlation analysis of the data allowed us to identify the presence of clear links between: 1) the efficiency of activity by time indicator and ISA: the more ISA corresponds to the reference method, the less time is spent on solving the labor task, and vice versa; 2) between ISA and intellectual readiness for activity; the higher the level of complexity of labor tasks, the higher the level of correlation between these phenomena.
Case Testing as a Tool of Control in the Process of Future Teachers’ General Pedagogical Training

The expediency of using practice oriented technologies in training teachers, the potential of case technologies as a type of interactive educational technologies for solving problems of forming professional knowledge and skills of students of teaching specialties, and sources of cases (primary, secondary) have been characterized in the article. The essence and the main types of pedagogical cases appropriate to be used in the process of professional training of future teachers have been elucidated. The authors have presented the peculiarities of implementing testing as one of the types of students’ academic performance. Modern approaches to the use of case technologies in the process of assessment of the professional competence of specialists in different fields have been characterized. The practicability of using case testing as a tool to monitor the knowledge of future teachers in the process of general training has been substantiated. The primary sources for the preparation of teachers’ training case tests (a teaching situation, a piece of a scientific or fiction text, statistical materials, etc.) have been determined. The examples of case tests used in the process of studying pedagogical disciplines for 2nd and 3rd year students in the context of the modules «Pedagogy», «History of Pedagogy» and «Fundamentals of Pedagogical Excellence» have been given. The advantages and disadvantages of using case testing have been analysed in comparison with traditional testing used to determine the level and quality of general training of future teachers.
THE TEACHERS’ OPINION ON EFFICIENCY OF DISTANCE EDUCATION

The article presents the findings of large-scale sociological survey titled ‘Assessment of the distance learning mode in the self-isolation conditions by educators of Rostov Region.’ The survey reflects the opinion of 8,079 teachers, including 7,608 women and 470 men, who work in general education. The relevance of the study is significant given that the entire general education system of the Russian Federation was urgently transferred to the distance learning mode due to the rapid spread of novel coronavirus in first-half 2020. The respondents assessed their own technical and material conditions in which they carried out the educational activities. The survey included analyses of the financial capabilities necessary to ensure the educational process in distance learning from home and the state of health of teachers working in the distant mode. The presented findings indicate that the teaching community negatively assessed the transition. The health of teachers suffered due to long hours in front of the computer, the effectiveness of teaching decreased, and transferability of learning deteriorated due to deficiencies in technical equipment. The article draws a general conclusion that for the present distance education cannot be a full-fledged alternative to general education in its traditional form.
Encoder-Decoder Attention ≠ Word Alignment: Axiomatic Method of Learning Word Alignments for Neural Machine Translation

The encoder-decoder attention matrix has been regarded as the (soft) alignment model for conventional neural machine translation (NMT) models such as RNN-based models. However, we show empirically that this is not true for the Transformer. By comparing the Transformer with the RNN-based NMT model, we find two inherent differences, and accordingly present two methods of capturing word alignments in the Transformer. Furthermore, instead of focusing on the Transformer, we present three axioms for the attention mechanism that captures word alignments, and propose a new attention mechanism based on these axioms that we have termed the axiomatic attention mechanism (AAM), and which is applicable to any NMT models. The AAM depends on a perturbation function, and we apply several perturbation functions to the AAM, including a novel function based on the masked language model (Devlin, Chang, Lee, and Toutanova 2019). Using the AAM to guide the training of an NMT model improved both the translation performance and the learning of word alignments of the NMT model. Our research sheds light on the interpretation of sequence-to-sequence models on neural machine translation.
Integrating Human Hand Gestures with Vision Based Feedback Controller to Navigate a Virtual Robotic Arm

This paper reports the design and development of a real-time IMU-Vision-based hybrid control algorithm to interact with a 6-DOF Kinova virtual robotic arm. Human Robot Interaction (HRI) control scheme proposed in this paper utilizes an embedded gyroscopic sensor from a Myo Gesture Control Armband's inertial measurement unit and an 800*600-pixel resolution from a Microsoft HD camera. The algorithm exploits the mathematical features of a numerical discrete time integrator and a mean filter to process the raw angular velocity data from the gyroscope. The processed data further provides the angular displacements to the end-effector of the robotic arm during clockwise or counterclockwise actions along x, y, and z axes from the user. This also facilitates the end effector (gripper) motion which was also controlled simultaneously by the roll action through threshold comparison in the algorithm. A vision based feedback system was designed using a computer vision toolbox and blob analysis technique in order to make the system more reliable and to control the distance of the end-effector while reaching to desired objects. The results demonstrated a significant control of the 6-DOF virtual robotic limb using the gyroscopic information and user inputs. The virtual robotic arm stopped the movement after reaching 320 mm from the desired object as expected. For three different objects, the maximum error between the real and the measured distance was calculated as 15.3 cm for cylindrical object. Due to its smooth control and arm gesture controller, this technology has the potential to assist people with either physical impairments or neurological disorders to perform activities of daily living using assistive robotic arm in the near future.
NoFish; Total Anti-Phishing Protection System

Phishing attacks have been identified by researchers as one of the major cyber-attack vectors which the general public has to face today. Although many vendors constantly launch new anti-phishing products, these products cannot prevent all the phishing attacks. The proposed solution, “NoFish” is a total anti-phishing protection system created especially for end-users as well as for organizations. This paper proposes a machine learning & computer vision-based approach for intelligent phishing detection. In this paper, a realtime anti-phishing system, which has been implemented using four main phishing detection mechanisms, is proposed. The system has the following distinguishing properties from related studies in the literature: language independence, use of a considerable amount of phishing and legitimate data, real-time execution, detection of new websites, detecting zero hour phishing attacks and use of feature-rich classifiers, visual image comparison, DNS phishing detection, email client plugin and especially the overall system is designed using a level-based security architecture to reduce the time-consumption. Users can simply download the NoFish browser extension and email plugin to protect themselves, establishing a relatively secure browsing environment. Users are more secure in cyberspace with NoFish which depicts a 97% accuracy level.
Violence Detection Through Surveillance System

This project aims to deliver a system which detects violence in the crowd. The model does not need human intervention to detect violence as it is automated. A dataset has been collected for detecting whether violence is taking place or not. The dataset includes both the scenarios, the ones which contain violence and ones which does not. Then, the model is trained to analyze whether the scenario contains violence or not. To detect scenarios which contain violent instances, various deep learning algorithms are applied on the dataset. CNN and LSTM-based architectures are experimented separately and in combination on this dataset. The model can be easily implemented in CCTV camera systems because it is lightweight.
Innovative potential of "digital methodology" in the training of personnel of nuclear industry enterprises

The article considers the first stage of designing diversification of professional retraining programs for employees of the nuclear industry in the conditions of digital transformation of the industry. The article justifies the new digital approaches to personnel training. At the project development stage, the general methodological foundations of digital disciplines in knowledge production were established in the form of a "digital methodology," the core of which is the knowledge paradigm of technoscience. The potential of "digital methodology" leads to the development of the mental, social, organizational resources of workers. The worldview platform of the project made it possible to formulate guidelines for the formation of competencies in the diversification of the professional retraining program: the development of critical and analytical thinking, technological literacy, personal growth, communicative initiative, and social responsibility. The authors note that the recognition of the methodological reflection of digital technologies is presented in the publications of researchers in various scientific fields, while the practice of foreign research is more advanced in the development of a quantitative assessment of qualitative indicators, and the domestic tradition is focused on the cognitive aspect of digitalization. But the convergence of approaches is manifested in the diversity of digital learning practices.
Random Assignment with a Smile: How to Love “TheRandomiser”

Abstract Objectives This note describes a free online portal ( www.therandomiser.co.uk ) that allows researchers to design randomised controlled trials and then delegate the random assignment process to pracademics delivering the experiment. Methods Observation of the use of this tool in repeated randomised trials in police agencies. Findings Researchers are able to design RCTs using the online portal, which offers many ways to customise the experimental design. Results are downloadable in excel or plain text format. Researchers can grant access to treatment providers, enabling them to log in securely, enter identifiers for cases, and assign different treatments to each case. Email notifications of assignment can be sent to designated list of recipients who can track the allocation of treatments. This tool delivers this functionality at zero cost and at the time of writing is being used by 78 researchers, who have set up 70 experiments that have processed 5778 randomisations. Conclusions TheRandomiser has been used in multiple experiments with feedback suggesting it is a powerful and user-friendly tool. The ability to deliver trickle-flow randomisation with high degrees of researcher control are attractive, as is the ability to edit an unlimited number of qualification questions prior to randomisation.
Insights on the Indian Ocean Tectonics and Geophysics Supported by GMT.

This paper presented analyzed and summarized data on geological and geophysical settings about the tectonics and geological structure of the seafloor of the Indian Ocean by thematic visualization of the topographic, geophysical and geological data. The seafloor topography of the Indian Ocean is very complex which includes underwater hills, isolated mountains, underwater canyons, abyssal and accumulative plains, trenches. Complex geological settings explain seismic activity, repetitive earthquakes, and tsunami. Understanding and prognosis of the disastrous and catastrophic geological events is strongly based on correct data analysis, modelling and visualization. An important feature of this paper is mapping multi-source high-resolution data by GMT. Data include raster grids in NetCDF and GRD formats: ETOPO1, geologic and marine free-air gravity data, EGM96, age, spreading rates, and spreading asymmetry of the ocean crust by NOAA, total sediment thickness. Data were visualized by GMT modules to compare and analyze geophysical and geological settings of the Indian Ocean. Visualization reveled correlations between high bathymetric variations of the oceanic seafloor, distribution of main geological seafloor fabric: Southwest, Southeast, Mid and Carlsberg ridges. Tectonic maps were plotted to perform comparative analysis of several variables: crust age, spreading half rates (mm/yr), asymmetries in crustal accretion on conjugate ridge flanks (%), variations in the geopotential and gravimetric models. Being the warmest of the world’s ocean, Indian Ocean has specific climatic conditions (repetitive monsoons, tsunamis, cyclones and storms), complex geologic seafloor structure with triple junction and unique geographic settings. Presented paper contribut ed to the regional studies of the Indian Ocean.
Designing a predictive guidance and control system for maneuverable ground moving target tracking in 3D space using a Hexarotor

Designing a predictive guidance and control system for maneuverable ground moving target tracking in 3D space using a Hexarotor