Reviewerly/exHarmony huggingface dataset:
ФОРМИРОВАНИЕ НАУЧНО-ИННОВАЦИОННОГО ПОТЕНЦИАЛА ВУЗА: ИНОСТРАННЫЕ ГРАЖДАНЕ В РОССИЙСКОЙ АСПИРАНТУРЕ

The article analyzes the main indicators of the activities of the Russian postgraduate studies in the period from 2014 to 2018, analyzes the dynamics of the number of organizations involved in postgraduate training. One of the criteria for raising the status of a higher education at the international level is the development of academic mobility of students. Since 2014, the increase in the number of foreign citizens in universities has been significantly growing. This entails the need to introduce and implement measures to revise organizational policies regarding the activities of the postgraduate departments of higher educational institutions. The article provides the reasons why foreign citizens choose Russia postgraduate programs, what was revealed by means of a survey. The organization faces difficulties, mainly due to flaws in the organization of scientific and educational activities of foreign postgraduates. Academic mobility, as an indicator that brings the university to a new quality level, requires special attention. The efficiency of postgraduate studies as per the existing methods does not take into account the peculiarities of training foreign postgraduates. According to the analysis of official ranking agencies, the leading universities in Chelyabinsk were identified and analyzed as per four key criteria of the efficiency of postgraduate studies. The results of the analysis emphasized the need to revise the organizational policy of an educational institution in terms of the activities of the postgraduate department. Attention is focused on the key problems of the head of an educational organization and suggests appropriate solutions to problems. As an additional criterion for assessing the efficiency of the postgraduate study activity in the framework of the development of academic mobility, an additional indicator “Accessibility of Postgraduate Education for Foreign Citizens” has been proposed and considered.
RTI : A CHECK ON CORRUPTION AND A SYMBOL OF JUSTICE DELIVERY IN THE MODERN DEMOCRATIC ERA

In our Judicial and justice delivery system, if something has revolutionized and completely changed the perspective of common people towards the ability and capability of Indian Judiciary system to dispense and deliver justice after Public Interest Litigations in the recent decades, then it has to be Right to Information Act and the accessibility and ease of the filing an RTI. Right from revealing India’s National Sport to be Hockey, asking for validity of picture of Mahatma Gandhi on Indian currency to questioning use of black and white election symbols on electronic voting machines, Right to Information has emerged as a savior and rather a tool to ensure that justice prevails in the society. The vigilant and leading role played by Right to Information in revealing and bringing into limelight some major scams of all time like Adarsh Housing Society scam, 2G scam, Commonwealth scam, Red Cross Society scam etc. is not unknown to anyone. At extreme local like Village Panchayat, it won’t be an exaggeration to state that Right to Information has come up as a weapon to combat exploitative, baseless and corrupt practices prevailing at administrative and other departmental levels. Once the access and awareness regarding the Right to Information successfully reaches till the extreme remote and backward areas of the country, a complete developed nation won’t be a mere dream any longer. Thus, the Right to Information Act, 2005, which provides power to any individual of the country to enquire regarding various matters, is one of the highlighting success stories of Indian Judicial and Justice Delivery system in the recent decade. With even better enforcement of the Right to Information Act, 2005 and ensuring the practical reach of the tool to the remotest areas of the country, RTI can emerge as an even bigger beneficiary and boom to our democracy.
Deep learning-based computational histology staining using spatial light interference microscopy (SLIM) Data (Conference Presentation)

Histological staining of tissue samples is one of the most helpful tools in diagnosing and prognosing various cancers. However, in order to prepare the slide for a histopathologist to examine, the tissue must first undergo a series of time-consuming processes, such as a staining technique to visually differentiate features in the sample. In this study, we use a label-free method to generate a virtually-stained microscopic image using a single spatial light interference microscopy (SLIM) image of an unlabeled tissue sample, therefore eliminating the need for standard histochemical administration. This novel approach will render histopathological practices faster and more cost-effective, while providing medically relevant dry mass information associated with SLIM images.
Exploration and Practice of Teaching Reform of Computer Public Courses Under Big Data Environment

Computers are the necessary professional knowledge of modern talents, and universities offer computer public courses to meet the needs of social talents development. At present, there are many problems existing in the computer courses teaching in colleges and universities, such as loose content, lagging mode, slow feedback, etc., and the classroom teaching is not efficient. Based on the big data environment, applying information technology to the teaching of computer public courses can re-plan the course, improve the teaching mode, collect students’ teaching evaluation, and improve the teaching effect. The article will analyze the problems existing in the teaching process of computer public courses in China, and propose corresponding reform strategies, aiming at promoting the development of teaching in colleges and universities, improving the quality of talents and meeting the development needs of the times.
VEHICLE CLASSIFICATION BASED ON BACKGROUND SUBTRACTION WITH DEEP LEARNING IN TRAFFIC SCENE

Intelligent traffic surveillance system plays a vital role in modern day traffic analysis. Numerous ways have been developed to streamline the process of analyzing traffic. The counting and classification of the vehicle during some period of time in an area require more effort even the couple of proximity sensors can calculate the track of moving the vehicle, but they are not economical. Therefore this paper proposes a framework for vision-based moving vehicle counting and classification system by combining background subtraction, proposal generation network and iterative refinement Convolution Neural Network (CNN). These approaches are applied in a cascade way to obtain the classification and counting. The experiment results show that the proposed approach has the best classification accuracy on the MOT dataset.
Power optical transmission network, reliability analysis, cloud model, evidence theory

In order to solve the problem that the qualitative indicators in reliability analysis of the power optical transmission network can not be accurately measured, this paper proposes a reliability evaluation method based on the evidence cloud droplets model.The model uses the cloud model to achieve the conversion between qualitative concept and quantitative value.Considering the correlation between the cloud droplets, it deeply excavates the interaction between cloud droplets combined with the evidence theory, and obtains the support of qualitative indicators to each reliability level.Finally, all indicators are used to give the analysis results of the reliability of the power optical transmission network in the form of ranks.By comparing with the traditional cloud model similarity algorithm, the proposed method has the advantages of objective science and high sensitivity, and can provide reliable decision-making basis for reliability evaluation of power optical transmission network.
Computer Aided Diagnosis of Early Breast Cancer by Multimodal Imaging

Breast cancer is one of the common tumors threatening women’s health, early detection and treatment is an important way to improve the cure rate of breast cancer and save the lives of patients. In recent years, with the development of sequencing technology and pathological image technology, a large number of multimodal data of omics and pathological image have been accumulated. The introduction of the above multi-modal data in early breast cancer research can greatly improve the cure rate of breast cancer. Therefore, how to effectively integrate the above multi-modal data is an urgent problem in the field of early breast cancer diagnosis. In addition, computer-aided diagnosis is one of the important applications of medical imaging. It helps doctors to draw conclusions on reading films through automatic detection and recognition, effectively solves the problem of easy fatigue and uneven professional skills of doctors, and has great application value in medical diagnosis. So based on related literature, technology and academic research on the basis of the analysis, combining the multimodal imaging and computer aided, used in the diagnosis of early breast cancer, and to analyze the results, aims to improve the diagnosis of early breast cancer rate and quality, providing certain theoretical basis for related research.
Investigating the potential of a gist-sensitive computer-aided detection tool

This study explored the possibility of using the gist signal (radiologists’ first impression about a case) for improving the performance of two recently developed deep learning-based breast cancer detection tools. We investigated whether by combining the cancer class probability from the networks with the gist signal, higher performance in identifying malignant cases can be achieved. In total, we recruited 53 radiologists, who provided an abnormality score on a scale from 0 to 100 to unilateral mammograms following a 500-millisecond presentation of the image. Twenty cancer cases, 40 benign cases, and 20 normal were included. Two state-ofthe-art deep learning-based tools (M1 and M2) for breast cancer detection were adopted. The abnormality scores from the networks and the gist responses for each observer were fed into a support vector machine (SVM). The SVM was personalized for each radiologist and its performance was evaluated using leave-one-out cross-validation. We also considered the average reader; whose gist responses were the mean abnormality scores given by all 53 readers to each image. The mean and range of AUCs in the gist experiment were 0.643 and 0.492-0.794, respectively. The AUC values for M1 and M2 were 0.789 (0.632-0.892) and 0.814 (0.673-0.897), respectively. For the average reader, the AUC for gist, gist+M1, and gist+M2 were 0.760 (0.617-0.862), 0.847 (0.754-0.928), 0.897 (0.789-0.946). For 45 readers, the performance of at least one of the models improved after aggregating its output with the gist signal. The results showed that the gist signal has the potential to improve the performance of adopted deep learning-based tools.
Exploring specific learning difficulties in primary schools: an empirical research

This study attempts to identify students with specific learning difficulty at inclusive primary school and to construct a model of assessment of specific learning difficulty. The data were collected by using observations, tests, interviews, and questionnaires and the data analysis used a descriptive quantitative and qualitative approach. The research results indicate that 85 (18.27 %) of 465 research subjects are identified as those having specific learning difficulty with the male ones among those so identified being greater in number than the female ones (their percentages being respectively 55.3 % and 44.7 %). The distribution of the types of their specific learning difficulty could be shown as follows: of the 85 research subjects, 26 (22.10 %) have difficulty with reading; 23 (19.55 %) have difficulty with writing; and 36 (30.60 %) have difficulty with mathematics. The model of assessment applied was as follows: difficulty in learning reading was assessed by using the Fernald, Gillingham, and Glass-Analysis methods, difficulty in learning writing was assessed by viewing students’ activities of writing by hand (or beginning writing), spelling, and expressive writing, and difficulty in learning mathematics was assessed by using formal and informal assessment models.
Electro-optic perceptron towards 10^18 MAC/J-efficient photonic neural networks (Conference Presentation)

Non-van Neumann compute engines such as neuromorphic electronics have shown to outperform CPUs by 3-4 orders of magnitude in terms of ‘weighted addition’, namely multiply-accumulate (MAC)-per-Joule. Here, we discuss experimental devices for a photonic neural network (NN) with an energy efficiency targeting10^18 MAC/J. We consider an electro-optic perceptron consisting of a photodetector (summation) coupled to an EO modulator (nonlinear activation function, NLAF) [George et al, Opt.Exp. 2019]. The perceptron’s efficiency is proportional to the electronic charge at the NLAF; in case of Silicon MZI modulators, this is ~10^6 charges hence the MAC/J is similar to TrueNorth. However, co-integration of emerging EO materials such as ITO into Si MZIs enables efficient modulation (e.g. VpL=0.5 V-mm [Armin et al, APL Phot. 2018]. Here we discuss latest results of a ITO-Silicon MZM with a record-low VpL=0.06 V-mm, and show noise-based NN training results of our in-house software PhotonFlow.
IMPLEMENTASI MODEL DELONE DAN MCLEAN TERHADAP KESUKSESAN PENERAPAN DATABASE REPLIKASI PADA DIREKTORAT JENDERAL BEA DAN CUKAI

Data presentation is one of the main performance indicators for agencies of the Directorate General of Customs and Excise, especially the Echelon II unit, namely the Directorate of Customs and Excise Information at the Subdirectorate of Data Management and Services. The large number of data requirements required makes the server load on the database even greater, for this purpose a replication database is called a database report as a database that is used as a database for data retrieval. This study aims to analyze the factors that influence satisfaction in the use and utilization of the database report as a source of data in presenting data using the Delone and McLean models. In measuring the success of the system there are variables in information quality, system quality, service quality, usage, and user satisfaction that are associated with the net benefits received by individuals or organizations. The research method used is by distributing questionnaires through the Google Forms link to employees in the Data Management and Service Subdirectorate, the results of the questionnaire were processed using SEM-PLS techniques using SmartPLS 3.0 tools. Based on the results of the analysis, the percentage of success in using the database report is 75.7% at level 4 between 61% - 80%, which is success, but there still needs to be a lot of improvement to become a better government agency.
PERBANDINGAN KEMAMPUAN MEMBACA PERMULAAN ANTARA METODE SAS (STRUKTURAL ANALITIK SINTETIK) DENGAN METODE GLOBAL BERBANTUAN MEDIA GAMBAR DI KELAS II SDN 045 TARAKAN

This study aimed at determining if there was a difference in early reading ability between learners taught with the Structural Analytic Synthetic (SAS) method which was assisted with image media and those taught with global method which was also assited with image media. This quasi-experimental research was conducted in August 2019. The population was the second grades students of SDN 045 Tarakan. The sample consistedof two classes, class IIA as the experimental group and class IIB as the control group. The independent sample t-test results showed that the value of calculated t was 0,193, the significance level was 0,05, the df was 56, and the critical t was 2.00. it was known that the value of the calculated t was equal or less than that of the critical t. Thus, it was concluded that there was no difference in the result of initial reading ability between second grade learners taught with image media assisted SAS methodand those taught with image media assisted global method at SDN 045 Tarakan.
Human-Robot Interaction in a Manned Space Flight: An Ontological Approach.

The use of robotic systems (RSs) in future manned space missions requires the creation of the cosmonaut-researcher a holistic view on the forms of interaction within the “human – robot” system (HRS) under the adverse environmental conditions. For these purposes, educational and reference materials (ERMs) are needed in fields of ergonomics and its representation in the design of human-machine interfaces (HMI). The paper considers the application of the ontological approach in the actual subject area – the ergonomics of the HMI, as the way of interdisciplinary integration various scientific fields – Informatics, ergonomics, psychophysiology, etc.
Методика организации SPOC курса по обучению планиметрии будущих учителей математики

The article presents using the van Hiele theory of geometric thinking for the organization of mixed training of students of the pedagogical Department of the N.I. Lobachevsky Institute of mathematics and mechanics KFU on the basis of SPOC course «Elementary mathematics: Plane geometry». Training includes the use of various IT-techniques and tools that can improve the quality of learning and form the necessary professional competence of the future teacher of mathematics. The course implements the technology of project-modular and inverted learning.
Fuzzy Logic based Enhanced Healthcare System for Elderly People (EHSEP)

With a tremendous advent of new technologies, the quality of human lives is changing day by day. The major focus is on how to improve the health care systems efficiency to help achieve greater life expectancy. Healthcare systems integrated with IoTs are built which generates timely results instead of going to hospitals just for a routine check up and can inform the near emergency care units in case of any anomaly. The elderly people are the ones who are in dire need of home based health assessment systems as they have a higher risk of getting diseases specially when they are living alone. The proposed home based improved health care system for the elderly people using fuzzy logic not only assess the physical health but it also assess the stress level of the patient which is often neglected. The data for physical health is collected using sensors and the data for mental health, in terms of stress level, is collected by taking different parameters into account. The proposed healthcare system can save the life of the elderly people by generating result at an early stage of physical illness or stress level so medical assistance can be timely provided.
Robust 6DOF measurement for non-overlapping multi-camera systems based on uncertainty-weighted space resection

This paper introduces an improved 6DOF measurement method for the non-overlapping multi-camera systems. In contrast to the existing equal-weighted bundle adjustment methods, the proposed method assigns an uncertainty based weight to each of the non-overlapping cameras. The measurement uncertainty evaluation framework is established based on the implicit function theorem. The weight assignment criterion enables the camera in a better observation condition to provide stronger constraints. The 6DOF parameters are obtained by optimizing the uncertainty-weighted space resection model with the nonlinear squares solver. The experiment results demonstrate the robustness of the proposed method to cope with poor observation conditions.
Convergence Technologies by a Long-term Case Study on Telepresence Robot-assisted Learning

The purpose of this paper is aimed to derive suggestions for convergence technology for effective management of distance education by analyzing a long-term case. The experiment was designed with notebook, smartphone or tablet based robot controlled by a remote instructor and a learner, who have experience of distance learning including robot assisted learning. The tablet based robot has the display system of feedback to speakers. During five months, three types of experiments were conducted randomly and a participant was interviewed thoroughly. The result, like the previous research, demonstrates that the task performance of the learner in telepresence robot-assisted learning was better than that in the notebook, and smartphone based. However, it is believed to be necessary to adjust the system for eye-contact and voice transmission for the remote instructor. The instructor required an additional sight by supplementing an extra camera and automatic direction control to source of sound.
An improved method for 3D reconstruction based on uniform point drift registration estimation

It is indispensable to obtain more information such as the 3D structure of the space target by detecting and identifying the target, when complete the on-orbit servicing and on-orbit control tasks. Both lidar and binocular stereo vision can provide three dimensional information of the environment. But it is very sensitive to the illuminance of environment and difficult to image registration at weak texture region, when we are using the binocular stereo vision in space. And lidar also has some defects such as the lidar data is sparse and the scanning frequency is low. So lidar and binocular stereo vision should be used together. The data of the lidar and binocular stereo vision are fused to make up for each others flaws. In this paper, uniform point drift registration method is used in the fusion of point cloud which is sampled by lidar and binocular stereo vision. In this method, the two groups of point cloud are considered as one which submit to mixed probability distribution and the other one which is sampled from the points submit to mixed probability distribution. The transformation estimation between the two groups of the point cloud is maximum likelihood estimation. The transformation is required to take overall smoothness. In other words, the point clouds should be uniformed. The uniform point drift method can solve the registration problem efficiently for 3D reconstruction. Usually the time can be compressed by 10%.
KEEFEKTIFAN MODEL STUDENT FACILITATOR AND EXPLAINING BERBANTU MEDIA PAPAN KARTU TEMPEL TERHADAP HASIL BELAJAR SISWA KELAS IV TEMA CITA-CITAKU SDN 01 GEMUHBLANTEN

This research aimed to determine the effectiveness of the Student Facilitator and Explaining models with the help of the Paste Card media on the learning outcomes of the fourth grade students on the theme of My Story SDN 01 Gemuhblanten. The population were all fourth grade students of SDN 01 Gemuhblanten Kendal academic year 2018/ 2019. This research was an experimental study with a quantitative approach. The design of this study was a pre-experimental study with the type of research used is one group pretest-posttest design that uses a sampling technique that is non probability sampling. Data collection techniques are carried out using interview, observation, documentation, and test techniques. Student learning outcomes are seen from the average pretest value of 59.00 and increase in the posttest value with an average of 83.37. From the calculation of t-test obtained tcount greater than ttable that is 20,391&gt;2,101, then H0 is rejected and Ha is accepted. The conclusion is that the Student Facilitator and Explaining learning model is assisted by the media of the Paste Card Board effective on the learning outcomes of the fourth grade students on the theme of My Story SDN 01 Gemuhblanten.