Reviewerly/exHarmony huggingface dataset:
De-Noising of Corrupted Fluoroscopy Images Based on a New Multi-Line Algorithm

Fluoroscopic images are a field of medical images that depends on the quality of image for correct diagnosis; the main trouble is the de-nosing and how to keep the poise between degradation of noisy image, from one side, and edge and fine details preservation, from the other side, especially when fluoroscopic images contain black and white type noise with high density. The previous filters could usually handle low/medium black and white type noise densities, that expense edge, =fine details preservation and fail with high density of noise that corrupts the images. Therefore, this paper proposed a new Multi-Line algorithm that deals with high-corrupted image with high density of black and white type noise. The experiments achieved images with a high quality and effectively preserved edge and fine details against black and white type noise densities depending on Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), and Image Enhancement Factor (IEF) measures.
Contour Sparse Representation with SDD Features for Object Recognition

Slope difference distribution (SDD) is computed for the one-dimensional curve. It is not only robust to calculate the partitioning point to separate the curve logically, but also robust to calculate the clustering center of each part of the separated curve. SDD has been proposed for image segmentation and it outperforms all existing image segmentation methods. For verification purpose, we have made the Matlab codes of comparing SDD method with existing image segmentation methods freely available at Matlab Central. The contour of the object is similar to the histogram of the image. Thus, feature detection by SDD from the contour of the object is also feasible. In this letter, SDD features are defined and they form the sparse representation of the object contour. The reference model of each object is built based on the SDD features and then model matching is used for on line object recognition. The experimental results are very encouraging. For the gesture recognition, SDD achieved 100% accuracy for two public datasets: the NUS dataset and the near-infrared dataset. For the object recognition, SDD achieved 100% accuracy for the Kimia 99 dataset.
Human-Machine Interactions for on the Fly Free Text Input Processing

Information in machine-readable form has to be entered by users of information systems in various situations. In the input process, forms with a number of individual fields are commonly used. For the creator, this input can be cumbersome and potentially counterintuitive. For this reason, free text components are becoming increasingly important. Information in the form of free text is not machine-readable as such, and extracting information is complex. The accuracy of existing approaches used to extract information from free text components depends directly on the quality of the used internal model. These models have to be created by experts or trained in advance using the appropriate machine learning methods. The main objective presented in this paper is extracting information as well as enhancing the underlying model on the fly. This implies that the information extraction algorithms apply directly to the user’s input and that the user is enabled to correct possible deficiencies in the model as they arise.
Readability measurement of Japanese texts based on levelled corpora

This book presents empirical methodologies and insights into the field of spoken and written discourse, in syntax, lexis, in corpus-based research and its applications to Japanese language education, and an exploration of the differences across time and register in diachronic Japanese language corpora. As such, it is divided into four parts, which are presented below with a brief overview of each chapter.
Pre-Proceedings of the 28th International Workshop on Functional and Logic Programming (WFLP 2020)

This volume constitutes the pre-proceedings of the 28th International Workshop on Functional and Logic Programming (WFLP 2020), organized by the University of Bologna, Italy, as part of Bologna Federated Conference on Programming Languages 2020. The international Workshop on Functional and (constraint) Logic Programming (WFLP) aims at bringing together researchers, students, and practitioners interested in functional programming, logic programming, and their integration. WFLP has a reputation for being a lively and friendly forum, and it is open for presenting and discussing work in progress, technical contributions, experience reports, experiments, reviews, and system descriptions.
Filter Construction for Real-Time Processing

Virtual environments should be multimodal and interactive. The technology used for simulation and reproductions must take into consideration the aspect of several sensory inputs in real time and the interaction with the person who is embedded in the virtual environment. In order to achieve a real-time performance, specific runtime conditions must be taken into account in order to stay within acceptable limits for latency and update rates. For the acoustic component of VR, we can use information from psychoacoustics on these limits. In this chapter, the implementation of software and hardware tools is introduced which provide real-time performance and interaction: head tracking and adaptive filtering.
Neural Networks Probability-Based PWL Sigmoid Function Approximation

In this letter, a piecewise linear (PWL) sigmoid function approximation based on the statistical distribution probability of the neurons' values in each layer is proposed to improve the network recognition accuracy with only addition circuit. The sigmoid function is first divided into three fixed regions, and then according to the neurons' values distribution probability, the curve in each region is segmented into sub-regions to reduce the approximation error and improve the recognition accuracy. Experiments performed on Xilinx's FPGA-XC7A200T for MNIST and CIFAR-10 datasets show that the proposed method achieves 97.45% recognition accuracy in DNN, 98.42% in CNN on MNIST and 72.22% on CIFAR-10, up to 0.84%, 0.57% and 2.01% higher than other approximation methods with only addition circuit.
Breast Cancer Biomarker Prediction Model Based on Principal Component Extraction and Deep Convolutional Network Integration Learning

Effective extraction of characteristic information from sequencing data of cancer patients is an essential application for cancer research. Several prognostic classification models for breast cancer sequencing data have been established to assist patients in their treatment. However, these models still have problems such as poor robustness and low precision. Based on the convolutional network model in deep learning, we construct a new classifier PCA-1D LeNet-Ada (PLA) by using principal component extraction method, Le-Net convolution network, and Adaptive Boosting method. PLA predicts three biomarkers for breast cancer patients based on their somatic cell copy number variations and gene expression profiles.
Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)

Any obstacle-free path planning algorithm, in general, gives a sequence of waypoints that connect start and goal positions by a sequence of straight lines, which does not ensure the smoothness and the dynamic feasibility to maneuver the MAV. Kinodynamic-based motion planning is one of the ways to impose dynamic feasibility in planning. However, kinodynamic motion planning is not an optimal solution due to high computational demands for real-time applications. Thus, we explore path planning followed by kinodynamic smoothing while ensuring the dynamic feasibility of MAV. The main difference in the proposed technique is not to use kinodynamic planning when finding a feasible path, but rather to apply kinodynamic smoothing along the obtained feasible path. We have chosen a geometric-based path planning algorithm “RRT*” as the path finding algorithm. In the proposed technique, we modified the original RRT* introducing an adaptive search space and a steering function that helps to increase the consistency of the planner. Moreover, we propose a multiple RRT* that generates a set of desired paths. The optimal path from the generated paths is selected based on a cost function. Afterwards, we apply kinodynamic smoothing that will result in a dynamically feasible as well as obstacle-free path. Thereafter, a b-spline-based trajectory is generated to maneuver the vehicle autonomously in unknown environments. Finally, we have tested the proposed technique in various simulated environments. According to the experiment results, we were able to speed up the path planning task by 1.3 times when using the proposed multiple RRT* over the original RRT*.
PEDAGOGICAL CONDITIONS FOR THE FORMATION OF ART-THERAPEUTIC COMPETENCE OF A FUTURE MUSIC TEACHER

The article explores the features of pedagogical conditions for the formation of art-therapeutic competence of a future music teacher. The scheme of the art-therapeutic composition of professional competence is given, and the substantial composition of its components is described.The author comes to the conclusion that the art-therapeutic competence of a music teacher is a combination of professional and personal qualities necessary for a successful pedagogical activity of a future specialist. She emphasizes the importance of a cultural component, since students must form an integral cultural and musical personality.Art therapy is an effective process for individuals who have communication problems or suppressed conflicts. When the words fail, art is an excellent means of communication. Then art therapies are usually more beneficial for these children in helping them develop and enhance their interpersonal communication and socialization skills. Art therapy session may look like an art class on the surface, but the goals and purposes are different. The focus in art therapy is on analyzing the inner experiences, one’s own feelings, perceptions, and imagination. Art therapy is an excellent process as an outlet for inner as well as outer expression. It substantiates the art therapeutic competence that is a tool for improving vocational training, since it reflects in its composition all the components of the professional competence of a music teacher. Formation of art-therapeutic competence of a future music teacher in a pedagogical university will be effective when implementing a set of pedagogical conditions, such as:1. organization of music-creative activity for students on the basis of a task technology;2. dialogue in the process of the art-therapeutic competence formation;3. providing a reflexive and positional determination of the future music teacher in professional and creative activity.
Software Project Management Systems Using Kanban Method in the CV. Primavisi Globalindo

Reducing the risk of failure in working on software projects is one of the successes for the company. It can be done by implementing project planning management properly. One important aspect of project management planning is scheduling. Scheduling includes recording human resources and tasks in the project. The Kanban method is one of the methods used to overcome problems in controlling project schedules. This study aims to develop a project scheduling system that applies the Kanban method. In this research, project management and scheduling system will be developed using the Kanban method. This system expected to be able to assist companies in handling projects. Kanban was chosen because it can easily respond to project changes, easily implemented, and company needs. In this study, unit testing was performed on the system's three main features and tested the validity of the system's 49 functional requirements. The usability test produces a value of 76. Based on the validation and usability test results, it can be concluded that the system is included in the acceptable category.
UIC High-Speed Days held on 14 and 15 February 2019 – UIC Communications

On 14 and 15 February 2019, the UIC Passenger Department held two “open days” at UIC headquarters dedicated to the topic of High-Speed. The aim of the event, organised for UIC staff, was to give an…
The agency in language and the professionals’ intercultural competences: A case study on the educators’“pivot move” in medical visits of unaccompanied minors

The presence of unaccompanied minors (UAM) in the Italian health care system represents a recent phenomenon, not fully investigated from a pedagogical perspective. The article reports findings from an exploratory study on medical visits involving UAMs with low communicative competence in the language of interaction, and their accompanying educators. Adopting a Conversation Analysis-informed approach to a corpus of video-recorded visits, we analyze the “problem presentation” and “history taking” phases. We singled out two resources (the ‘pivot move’ and the ‘oscillating addressivity’) respectively used by the educator and the physician to 1) pursue the “incompatible goals” of their agendas and 2) manage the UAM’s participation in the interaction by attributing him agency (or not). Focusing on the (inter)professional challenges of this triadic medical encounter, in the conclusion we advance that the awareness of the communicative details through which agency can be allocated or revoked is part of the intercultural competences of professionals working for UAM’s inclusion in the host society.
A Deep Learning Architecture for Recognizing Abnormal Activities of Groups Using Context and Motion Information

Currently, the automation of activity recognition of a group of people in closed and open environments is a major problem, especially in video surveillance. It is becoming increasingly important to have computer vision architectures that allow automatic recognition of group activities to make decisions. This paper proposes a computer vision architecture capable of learning and recognizing abnormal group activities using the movements of the group in the scene. It is based on the Activity Description Vector, a descriptor capable of representing the trajectory information of a sequence of images as a collection of local movements that occur in specific regions of the scene. The proposal is based on the evolution of different versions of this descriptor towards the generation of images that will be input of a two-stream classifier capable of robustly classifying abnormal group activities. Moreover, it includes context information to provide extra information to classify the activities including it as the third stream of the classifier resulting in a robust architecture for one class classification problems. The architecture has been evaluated and compared with other approaches using Ped 1 and Ped 2 datasets, obtaining a high performance in abnormal group activity recognition.
Optimizing Heuristic Search Algorithms using Neural Networks

At the opposite side of the uninformed search algorithms, performing a systematic search, heuristic search algorithms are based on multiple rules leading it to estimate, in a predictive way, the minimal cost of the path from the current state to the goal. In this sense, A* algorithm is an example of heuristics-based algorithms that can guarantee to find a least-cost path to a goal state if this algorithm is using an “admissible heuristic”. A heuristic is said to be “admissible” if it never overestimates the real path cost from the current state to the goal. Furthermore, if the condition h(x) ≤ d(x, y) + h(y) is satisfied by the heuristic h (d denotes that edge length), for every edge (x,y), then h is called consistent. And with consistent heuristics, finding an optimal path without processing any node more than once is guaranteed. The main idea consists on developing a Neural Network that can optimize those heuristics to further refine the A* algorithm results. Towards achieving that goal we must find the best synaptic coefficients, for that reason, a learning phase will be needed during which the network parameters are adjusted until the best admissible and consistent heuristic is obtained, dominating any other heuristic (h1 dominates h2 if for every node n (state), h1(n)>h2(n) ). During this learning phase, and as inputs, the neural network will have some representative examples in the form of pairs of several problems and heuristics ({P1,h1};{P2,h2}...{Pn,hn}), to finally be able to calculate the best heuristic regardless of the inputs.
HOME SCHOOLING AS AN ALTERNATIVE TO INSTITUTIONAL FORMS OF TEACHING DECORATIVE AND FINE ARTS IN UKRAINE IN THE XIX – EARLY XX CENTURIES

The article is devoted to the analysis of peculiarities of home schooling in the context of the history of development of institutional and non-institutional forms of teaching decorative, applied and fine arts disciplines in the territory of Ukraine, which in the XI -early XX century was part of the Russian Empire.It is found out that during the period under study home schooling was a common form of education among the wealthy layers of the population of Ukraine as part of the Russian Empire: nobles, landowners, officials, clergy.It is established that home tutors and home teachers carried out pedagogical activities in accordance with the legal framework of the Ministry of Public Education of the Russian Empire.Legal foundations of artistic disciplines formation were considered in the course of systematic analysis of a number of documents of the government department of education (statutes, decrees, orders, circulars, etc.), which were published on the pages of the popular at that time periodicals, such as: "Journal of the Ministry of Public education", "Provincial News" and others.It is found out that the education system reform by the efforts of the Ministry of Public Education was caused by inconsistency of the level of public school organization, necessity of updating of the pedagogical approaches, forms and methods, which significantly influenced expansion of the content of education (in particular artistic disciplines) both in the system of general education as a whole and in the system of home schooling in particular.It is stated that the normative-legal documents concerning introduction of the subjects of artistic and decorative cycle in general education institutions were obligatory for pedagogical work of home teachers and home tutors.The application of gender approach in home schooling is shown, which indicates the division of tasks of the cycle of arts and crafts with compulsory needlework lessons for girls (embroidery, carving, work with beads) and lessons of traditional handicrafts mastering for boys (woodworking, carpentry, working with metal).It is concluded that home schooling played a positive role in the formation of decorative arts teaching in the history of the national education development in the lands of Ukraine, which were part of the Russian Empire in the XIX -early XX century.
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE UNTUK MENINGKATKAN HASIL BELAJAR BAHASA INDONESIA PADA KONSEP MEMBACA PEMAHAMAN SISWA KELAS V SD INPRES LABUHA

This study aims to determine the increase in learning outcomes of students in class V SD Inpres Labuha on the concept of reading comprehension by applying the cooperative learning model of the Think Pair Share type and to determine the activities of teachers and students when implementing the type of cooperative learning model Think Pair Share in grade V SD students. Labuha's Inpres on the concept of reading comprehension. The type of research used is Classroom Action Research (PTK). The research was conducted on the fifth-grade students of SD Inpres Labuha. The subjects of the research were 14 students of class V SD Inpres Labuha. The observer consists of two teachers, each with one teacher observing the activities of the teacher and another teacher observing the activities of students in the learning process. The techniques used in this research are test and non-test techniques. The test technique was used to determine student learning outcomes by using questions in the form of essays totaling 4 questions in cycle I and 4 questions in cycle II with a maximum score of 16. both classically and individually. The learning process that has been implemented is in accordance with the learning model Think Pair Share, starting from the stage Think (thinking individually), the stage Pair (pairing with a peer), the stage Share (sharing answers with other partners) can be carried out well by researchers and students class V SD Inpres Labuha. After being analyzed using descriptive statistics, it was found that an increase in student learning outcomes in class V SD Inpres Labuha through the cooperative learning model Think Pair Share on the concept of reading comprehension and the number of students who completed classical learning in the first cycle there were 8 students or 57%, in the second cycle, it increased. to 13 students or 92%, the results of observations on student activity increased by an average of 63% in the first cycle and 77% in the second cycle, while the results of teacher activity observations increased from 85% in the first cycle to 92% in the second cycle.
Pola Rekrutmen, Seleksi, Pendidikan Dan Pelatihan Pengaruhnya Terhadap Pengembangan Karier Aparatur Sipil Negara Kejaksaan Tinggi Sumtera Selatan

The research objective was to find out the results of the analysis of how the influence of recruitment, selection and education &amp; training patterns both partially and simutaneously towards career development. The survey method applied research model, uses 165 samples from a population of 295 South Sumatra High Prosecutors' staff, using proportional random sampling Technical data analysis using descriptive statistics and inferential statistics. In this study, the type of data used is primary data and secondary data. Data collection techniques using questionnaires, interviews, observation and documentation. Testing the hypothesis through t test and F test using SPSS analysis tools The results of data processing using SPSS 23, using the t test that t count is 7.378&gt; with t table 1.9764 and 0.00 &lt;0.05 significance that there is a positive and significant pattern of recruitment on career development; that t count is 13,730&gt; with t table 1.9764 and 0.00 &lt;0.05 significance that there is a positive and significant selection effect on career development; that t count is 19.303&gt; with t table 1.9764 and 0.00 &lt;0.05 significance that there is a positive and significant effect of education &amp; training on career development; and use the F test that F count is 142.310&gt; with F table 2.6687 significance 0.00 &lt;0.05 that there is a positive influence and a significant pattern of recruitment, selection and education &amp; training together towards career development, with the magnitude of the coefficient of determination The remaining 74.6% is influenced by other variables. The conclusion of the study is that the pattern of recruitment, selection and education &amp; training has a positive and significant effect on career development both partially and simultaneously. The strategy for career development of the State Civil Service of South Sumatra's High Apparatus is very much determined by the opportunity given by the institution to the apparatus to attend education &amp; training. Â Keywords ; pattern of recruitment, selection, education &amp; training, career development