Reviewerly/exHarmony huggingface dataset:
An Empirical Study of Source Code Detection Using Image Classification

The detection of programming language for a source code file has achieved high accuracy using the machine learning techniques. On the other hand, for a piece of software (called snippet), the detection of programming language is required to append tags automatically in a question and answer site such as Stack Overflow. However, the detection of programming language for a snippet is still a challenge since snippets is not a complete source code. Usually, experienced developers can detect the language of such snippet at a glance. It is considered that such a task that a human being easily solves can be solved by the image classification method using deep learning technique. Therefore, we propose a programming language detection method using a deep learning based image classification method. By using the data from actual Q&A site, we evaluate our proposed model. The results of experiment demonstrate that we can successfully detect the correct programming language for snippets with over 90% accuracy.
“Go360”-A Fall Risk Assessment Smartphone Application for Older Adults

BackgroundGlobally, falls are the second leading cause of death and early identification of fall risk among older adults is very important to plan preventive measures. The literature has shown that a smartphone (SP) can be used for fall detection and fall risk assessment.ObjectiveTo develop a smartphone application (SA) for older adults to assess their fall risk based on clinical practice guidelines (CPG) and to pilot test the application.Material and MethodA SA named “Go360” was developed with three main built-in sensors of the phone to assess the fall risk using Timed Up and Go Test (TUG), 30-Second Chair Stand Test (30SCST), and Four Stage Balance Test (4SBT) along with body sway and gait speed data. The SA was pilot tested with 8 older adults concurrently with standard manual tests.ResultsThe results showed that SA overestimated the TUG, 4SBT stage 2 and 4SBT stage 3 test values. Conversely, there was no difference in 30SCST, 4SBT stage 1 and 4SBT stage 4 values. The fall risk matched with the manual test results.ConclusionThe newly developed Go360 SA detects the fall risk using 3 evidence-based functional tests in agreeable level with the standard manual test and it can be used by older adults for self-checking.
Encouraging Faculty Adoption of Virtual Reality Tools in Engineering Education

Virtual reality is one of the widely emerging technologies and is anticipated to play a substantial role in the future of education. Though many research studies have been conducted on its application in various disciplines, less investigations focused on its integration in engineering higher education. This work, thus, aims to identify the major opportunities and challenges of virtual reality adoption in various areas of engineering. To do so, solicited engineering faculty participants from four different departments at the University of Idaho attended demos to examine a virtual reality technology – namely Leap Motion desktop controller. They were then asked to respond to a survey that collected their feedback on virtual reality possible applications, educational uses, and challenges in their respective disciplines. The survey also collected responses related to their perception, acceptance, and recommendations on ways to encourage virtual reality implementation. Results show a majority of participants being in favor of adopting virtual reality, suggesting areas and classes/labs that would best benefit from such technology. This paper also proposes professional development activities and suggestions for virtual reality applications’ developers.
Nonlinear Model Predictive Real-time Control of Aircraft in Collision Avoidance

For collision avoidance problem, some methods have been researched in autonomous control field. However it is difficult to apply them to an aircraft because there are many practical issues such as calculation problem, infeasibility, complex dynamics of aircraft and so on. In this paper, we apply MPPI(Model Predictive Path Integral Control) to an aircraft. MPPI has optimal control algorithms based on stochastic sampling of trajectories and can perform in real-time with GPU computing. Finally, some simulations of collision avoidance illustrate the safety and efficiency of this method and prove the usefulness in aeronautical field.
Multi-target multi-Bernoulli filtering based on propagator method for DOA tracking

Aiming at the problem of Direction of Arrival (DOA) tracking for multiple target, this paper proposes a DOA tracking algorithm based on Propagator Method (PM) under Multi-Bernoulli filtering framework. The proposed algorithm uses particle filter to approximate the posterior distribution of target, where the calculation of likelihood function is the key of the update step. The eigendecomposition of the covariance matrix is needed when the likelihood function is replaced by MUSIC spatial spectrum function. In order to reduce the computational complexity of the matrix eigendecomposition, we use the spatial spectral function of PM to replace the pseudo-likelihood function of particle filter, and further exponential weighting is used to enhance the weight of particles at high likelihood area and make resampling more efficient. The simulation results show that the proposed algorithm can effectively track the DOA and estimate the number of multiple maneuvering target.
Art as General Education of University

우리나라 대학의 예술 관련 교양교과목은 한국교양기초교육원의 분류에 따르면 인문학으로 간주되어 교양교육의 영역에 속하기도 하고 동시에 정서적 체험교육으로 간주되어 소양교육에 다시 포함되기도 하는 상황이다. 예술의 속성상 창작과 체험, 그리고 그 결과물을 둘러싼 감상과 비평의 작업이 이론적 내용과 서로 뗄 수 없는 관계임을 인지한다면, 예술교육에 대한 이 같은 이중적인 분류 체계는 결코 적합하다고 볼 수 없다. 대학 교양교과목 중 예술 분야의 교과목에서 행해지는 실습과 실기 프로그램에 대하여 학술성이 부족하거나, 교육 목표가 흐릿하다는 인식이 사라지지 않고 있다. 본 연구는 이와 관련하여, 교양교육의 본질에 비춘 예술교육이란 무엇인가를 논의한다. 우선 대구가톨릭대학교에 개설된 <예술의 이해와 탐구> 교과목의 운영사례를 통하여, 다양하게 진행되는 모둠 활동과 개별 실습 활동이 창의성 교육과 연결되는 지점을 제시하고, 실습으로 구성된 교과목이 어떻게 학술성을 갖추게 되고, 전인적 발달을 지향하는 교양교과목의 목적에 부응할 수 있는지 밝힌다. 그렇게 함으로써, 예술교육이 대학의 교양교육에서 담당하는 역할과 위치를 조명하고, 사회를 변화시키는 인재를 길러내는 데 있어서의 중요성을 재확인한다. 본 연구는 특별히 창의성 계발과 관련하여 예술교육의 실천적 방안을 <예술의 이해와 탐구> 교과목을 중심으로 제시하였다. 무언가를 만들어 내는 행위는 창의성의 가장 근본적인 발현 양상이기에, 예술 작품 활동은 창의성 교육과 밀접한 관계를 맺기 때문이다. 새로움과 참신함, 그리고 문화를 가로지르는 타당성을 창의성의 특성이라고 한다면, 예술교육을 통한 창의성 계발은 다른 어느 분야의 교육보다 효율적일 것이다. 예술의 속성이 새로움과 참신함, 그리고 타당성에 있는 까닭이다. 교양교육이란 “인간, 사회, 자연에 대한 폭넓은 이해를 바탕으로 올바른 세계관과 건전한 가치관을 확립하는 데 기여하는 교육”이라는 정의에 비춰볼 때, 교양교육으로서의 예술교육은 매우 분명한 위치에 있음을 알게 된다.The Korea National Institute for General Education classifies general education art courses in university as humanities, while, at the same time, they are considered emotional experiential education. Art creation, experience, appreciation, and criticism are inseparable from the theoretical contents of art; therefore, such a dual classification system in art education is never suitable. Still, many believe that the practical programs associated with general education art courses are lacking in academics or that their educational goals are blurred. This study discusses what arts education is suitable in terms of general education. First, based on operational examples from the Understanding and Inquiry of Arts curriculum established at Daegu Catholic University, we will clarify how various activities and individual practice are connected with creativity education. In addition, we will consider how a practical curriculum can become academic and also achieve the purpose of the liberal arts curriculum, which targets overall development. In doing so, this study highlights the role and position of art courses in general university education and reaffirms their importance for the cultivation of talent that can change society. This study presents practical art education measures, especially those related to the development of creativity, focusing on the topic of Understanding and Inquiry of Arts. The act of creating something is the most fundamental manifestation of creativity, since the work of art is closely related to creativity education.
DRFM interrupted sampling repeater jamming suppression algorithm based on clustering

Interrupted sampling repeater jamming (ISRJ), which is generated by digital radio frequency memory (DRFM), has become a hot topic about electronic counter measures (ECM). The paper has proposed an ISRJ suppression algorithm based on numerical statistical characteristic analysis and clustering. First, preprocess the echo data to improve signalnoise ratio according to the numerical statistical characteristic analysis. Next, apply the algorithm of clustering to the echo so as to identify ISRJ and obtain the parameters of ISRJ. Then, reconstruct the jamming based on the ISRJ information from previous step. Finally, use the reconstructed jamming to suppress ISRJ. The simulation result shows that the proposed method can identify ISRJ successfully when SNR of echo is higher than -10dB.
INFORMATIONAL AND PSYCHOLOGICAL TECHNOLOGIES DEVELOPMENT OF EDUCATIONAL COMPETENCIES IN MEDICAL E-EDUCATION

Introduction: The article analyses systematized ideas on е-education as informational-psychological technology of educational competencies development applied to medical education. In the widest sense, е-education is interpreted as use of internet for learning. Such aspects of this informational-psychological technology, as virtual educational environment and subjects of educational process (е-student, educational technologist, librarian, teacher) are examined in the article. The aim. On the basis of the above information, one can formulate the purpose of the article, which is to present systematized representations of e-learning as an informational and psychological technology for the development of educational competencies in the process of postgraduate medical education.Materials and methods: In the work is used a range of methods: content analysis, bibliosemantic, systematic approach, analysis of products of activity.Review: Features of e-education are explored as an adaptive educational technology in the process of medical education and retraining. Target-orientation is emphasized as key important principle of effective informational-psychological technology of educational competencies development. Virtual educational environment is researched as the computer-integrated е-learning, which typically includes wide set of various tools for effective delivery of e-educational content to the audience, which improves co-operation and management. The article proves that structural and contentual dimensions of е-teaching make fundamental influence on what can or can't take place within e-educational process and even on how teachers and students build their own knowledge within e-courses, build that they what do (not) know, and the process of this construction. It is mentioned that the role of content within the е-educational environment can acquire many various forms, including educational materials, reference sources, as well as any practice-related materials, like scientific articles or clinical protocols and instructions. Some most typical functions, instruments and services, usually available in a virtual educational environment, are described in the article.Conclusion is made about considerable potential of е-education as an effective informational-psychological technology of educational process in medical education.
Global Graph Curvature

Recently, non-Euclidean spaces became popular for embedding structured data. However, determining suitable geometry and, in particular, curvature for a given dataset is still an open problem. In this paper, we define a notion of global graph curvature, specifically catered to the problem of embedding graphs. We theoretically analyze this value and show that the optimal curvature essentially depends on the dimensionality of the embedding space and loss function one aims to minimize via embedding. We also review existing notions of local curvature (e.g., Ollivier-Ricci curvature) and conduct a theoretical analysis of their properties. In particular, we demonstrate that the global curvature differs significantly from the aggregations of local ones. Thus, the proposed measure is non-trivial and it requires new empirical estimators as well as separate theoretical analysis.
Iterative Image Deblurring Algorithm using Complementary Pair of Filters

In this paper, an iterative algorithm for image deblurring is proposed. The algorithm is based on the complementary pair of filters. The modified Tikhonov regularization is used to control the optimized iteration of the deblurring process. Several sizes of Gaussian blur are applied to produce the degraded images in our experiments. The Peak Signal to Noise Ratio (PSNR) is used to measure the image deblurring quality. The results show that the proposed algorithm is superior to the traditional Lucy-Richardson algorithm and regularized filter both visualized observation and a quality metric. It performs well on any size of the blur kernel and can be applied in the non-exact blur kernel. Moreover, the edge ringing and boundary artifact are unnoticeable.
Online-Diagnosis with Organic Computing based on Artificial DNA

Organic Computing leads to significant advantages for complex dynamic systems like reduced development efforts, increased adaptability and robustness. However, for safety-critical systems which have to maintain functionality even in the presence of faults or failures (fail-operational) further properties are necessary. This includes the maintenance of the major core functionality even if non-redundant system resources fail, the Organic Computing runtime environment is harmed or the remaining resources are insufficient to maintain all services. These failure scenarios require semantic knowledge of the system combined with fault-diagnosis and adaption techniques to properly degrade and reconfigure the system.This paper highlights the research gaps towards active diagnosis based on artificial DNA and proposes solutions including semantic description methods, optimization algorithms for diagnostic models and adaptation techniques. Semantic description methods for Organic Cmputing systems with artificial DNA are the foundation for higher semantic-based failure detection and adaptation techniques. Diagnosis techniques for Organic Computing systems with artificial DNA can exploit the semantic descriptions to automatically build diagnosis models. Furthermore, these models can be optimized by evolutionary algorithms to improve their failure detection rates. Adaptation techniques modify the artificial DNA based on the recognized failures and the semantic description to realize the reconfiguration and degradation concepts.
Existing enabling technologies and solutions to maintain privacy and security in healthcare records

Electronic health record (EHR) is a repository of a patient medical record stored in digital format. MR is accessible by different healthcare professionals, administrative staffs, patients, and their relatives. The key highlight of EHR is that it is possible to exchange health information of patients between different healthcare providers. This MR property supports patients with efficient and high -quality healthcare delivery. MR has several advantages in improving efficiency, lowering costs, and medical errors. Usually, MR is outsourced to the third party such as cloud or fog. These third party service providers facilitate unlimited resources for storage and computing. This information technology infrastructure enables the medical record of a person to be stored in one place is accessed from any part of the world. Despite EBR&apos;s numerous advantages, it poses many security issues because EHR is exposed to third -party service providers and users of different kinds. Infringement of data privacy, data integrity, and user privacy are the main security issues. Researchers have come up with many ideas since 1982 to improve EHR&apos;s security. Then they concluded that these breaches of security might be confined by encrypting EHR before being out sourced to the third party. Researchers have used different encryption techniques to encrypt EHR, such as symmetric key encryption, public key encryption, and identity based encryption. All of the above techniques of encryption fall with their common disadvantages. Currently, researchers apply attribute -based encryption (ABE) in EHR because it provides additional security requirement of fl exibility and control unauthorized access. The ABE scheme allows the MR owner to choose authorized users to access various parts of the MR, and the MR owner can enforce write access control and read user access control policies. Multiauthority ABE is developed to provide efficient key management and to avoid key escrow. Authentication of users can also maintain EHR&apos;s privacy and security. We discuss existing encryption techniques and authentication techniques in this chapter to maintain the privacy and security of EHR being outsourced to the third party. In addition, the advantage of enabling blockchain technology is also discussed in securing EHR
Role of organizational aspects in requirements engineering processes of a socio-technical system: Insights from E-Governance case studies

Requirements engineering (RE) contributes to developing products of a socio-technical system. External triggers cause transitions in socio-technical systems; to manage transitions the products need to form stable designs. During RE and software development, organisations interact with rulesets (interoperations) and the organisational aspects influence interoperations. When we extend interoperations from socio-technical transition theory, it assists product development, including RE, and contributes to the stabilisation of product designs. With an approach that analyses inter-organisational interactions, the author extended one of the existing transition theories and identified improvements to organisational aspects. With diverse heuristics and analytic views, we can examine the phenomenon (interoperations) and requires studying it in its settings; so, used a multi-case study method to represent diverse interoperations. Selected traditional software development cases of e-governance and represented all socio-technical transition trajectories. The author extended socio-technical transition theory and contributes to inter-organisational body-of-knowledge by adding additional categories to inter-organisational approach.
Improved Anomaly Detection in Experimental Wind Tunnel Data using PCA

Conformal mapping is shown to improve anomaly detection with Principal Component Analysis (PCA) for wind tunnel measurements. Experimental data from tests evaluating the performance of a series of two-dimensional airfoils are compiled. These data include multiple sensor system types and various conditions to generate a historical data set. Proper selection and interpolation to a standard distribution of sensors is shown to be critical in compiling the historical data for this PCA anomaly detection scheme. Principals of ideal flow aerodynamics and conformal mapping are used to reduce airfoil geometry dependent deterministic variance in airfoil surface pressure measurements. An eigendecomposition of the covariance between all sensor measurements are used to determine principal components that separate expected sensor covariance from unexpected covariance and noise. This reduction of deterministic variance improves the ability of the PCA scheme to detect anomalies.
Content and Functions of Independent Work of Students

The paper shows that independent work of students in current conditions has acquired the status of one of the critical forms of organization of students' activities aimed at the development of graduates' readiness for permanent self-development as a necessary condition for successful adaptation in a continuously changing educational, professional, and social environment.The structural components of the independent work of students as a type of educational activity carried out by students as indirect management from teachers are also revealed.The pedagogical conditions for increasing efficiency of independent work of students also include a clear definition of places, goals, and objectives of independent work in the structure of educational process; use of methods for motivation of students to perform independent work; design and application of a system of successive complicating level of problems of competence-oriented educational tasks; as well as creation of information and educational environment.
HMM-Based Person Re-identification in Large-Scale Open Scenario

This paper aims to tackle person re-identification (person re-ID) in large-scale open scenario, which differs from the conventional person re-ID tasks but is significant for some real suspect investigation cases. In the large-scale open scenario, the image background and person appearance may change immensely. There are a large number of irrelevant pedestrians appearing in the urban surveillance systems, some of which may have very similar appearance with the target person. Existing methods utilize only surveillance video information, which can not solve the problem well due to above challenges. In this paper, we explore that pedestrians’ paths from multiple spaces (such as surveillance space and geospatial space) are matched due to temporal-spatial consistency. Moreover, people have their unique behavior path due to the differences of individual behavioral. Inspired by these two observations, we propose to use the association relationship of paths from surveillance space and geospatial space to solve the person re-ID in large-scale open scenario. A Hidden Markov Model based Path Association(HMM-PA) framework is presented to jointly analyze image path and geospatial path. In addition, according to our research scenario, we manually annotate path description on two large-scale public re-ID datasets, termed as Duke-PDD and Market-PDD. Comprehensive experiments on these two datasets show proposed HMM-PA outperforms the state-of-art methods.
An Investigation on the Selection of Filter Topologies for Passive Filter Applications by Neural Network

This project presents an alternative way in designing 5th, 7th and 11th harmonic filters by creating a neural network program that can calculate harmonics which are generated in the system by ac or dc drives and it can verify the result using the simulation in verification program. Our program can choose the right harmonic filter and help designing harmonic filter faster, easier and more accurate by concerning the cause of other factors that exclude the formulas such as limitation of the devices in a suitable cost. It will be more and more accurate every time the users use this program. Our program will train itself after inputting new data. The more we use the program, the more accurate it will be. We created the program with easy understandable user interface to facilitate any harmonic filter designers with low experiences to have an ability as an expert harmonic filter designer because our program has a memory of an experienced designer and ability to train itself. Furthermore, our program will help supporting the development in harmonic filter designing for any kinds of future research.