Reviewerly/exHarmony huggingface dataset:
Ring-Topology Echo State Networks for ICU Sepsis Classification

Sepsis is a life threatening condition that can be treated if detected early. This paper presents a study of the application of a Ring Topology Echo State Network (ESN) algorithm to a sepsis prediction task based on ICU records. The implemented algorithm is compared with commonly used classifiers and a combination of both approaches. Finally, we address how different causal strategies on filling missing record values affected the final classification performances. Having a dataset with a limited number of time entries per patient, the utility score U = 0.188 obtained (team 51: PLUX) suggests that further research is needed in order for the ESN to capture the temporal dynamics of the problem at hand.
Securely Exposing Machine Learning Models to Web Clients using Intel SGX

Machine Learning (ML) methods are applied frequently to predict outcomes or features, that would otherwise require tedious manual work. ML models are usually deployed on Web servers, where end user can query them providing the input data. Server side deployment's shortcoming is that users' data must be sent to a server on each query, increasing network usage and leading to privacy/legal issues.In this paper we present a system which aims to ease the deployment of ML models on the client side of Web applications, while protecting the Intellectual Property (IP) of the model owner. Protection of the ML model is realized with Intel SGX which assures that a loaded model cannot be inspected by the end-user.
Developing Training Applications for Hydrogen Emergency Response Training

Virtual Reality (VR) has been evolving over the years, becoming more and more accessible, in a wide area of applications. One of these areas where VR can have a major impact is training and certification. Hydrogen vehicles are becoming a reality and first responders still lack proper tools and resources to train emergency responses for the purpose. VR can play here a crucial role in ensuring a proper hydrogen emergency response training due to the advantages associated with VR training programs such as resource optimization, repeatability, and replicability. This paper proposes using VR for hydrogen emergency response training by developing a solution composed of three components: tutorial mode, training mode, and certification mode. A usability study is further conducted to evaluate its usability and user satisfaction. The results show that the use of this application regards usability and user satisfaction were extremely positive.
Effort Estimation in Agile Software Development Using Deep Learning Model

Software effort estimation is a major activity in the process of software development that permits managers and software engineers to accurately estimate the schedule and budget.Although traditional effort estimation approaches are used to estimate effort for agile software projects but they mostly result in inaccurate estimates.According to standard surveys, 30% to 40% of software projects failed because of inaccuracy of software effort predictions.To improve the accuracy and efficiency of effort estimation, an agile software development process is introduced and substitutes the traditional methods in the software industry.One approach of calculating effort of agile projects is the Story Point Approach.Software industries have adapted the Agile model where effort is estimated using Story Points.The goal of this study is to provide a detailed overview of the effort estimation techniques in Agile Software Development based on Story Points.In this paper, we propose a prediction model for estimating story points based on long short-term memory and recurrent network.This model has been applied to a dataset composed of issue reports mined from JIRA repositories.The proposed work uses three different performance metrics i.e. mean magnitude of relative error, mean square error, and prediction to evaluate the performance of the model.The results of the proposed models are compared to the existing models in the literature.
Automatic segmentation of the left ventricle myocardium by a multi-view deformable model

Nowadays magnetic resonance images (MRI) are being used to calculate important clinical parameters such as ejection fraction (EF), left ventricle myocardium mass (MM), and stroke volume (SV) which are crucial to estimate the cardiac function, surgical planning and create patient-specific heart models, therefore for quantifying accurately these parameters it is also necessary a good delimitation of cardiac structures. The proposed approach presents an automatic segmentation of the left ventricle (LV) and basically is composed by three steps: first, heart structure localization with template matching technique in coronal and sagittal view that is used to restrict axial analysis. Second, ellipsoidal approximation using the axial projection of previous coarse segmentation. Third, a conventional snake algorithm is performed to refine external myocardium boundaries in axial view. The strategy was evaluated using 100 cardiac MRI volumes provided by the ACDC 2017 MICCAI challenge which is composed of 4 different heart diseases, the strategy had an average Dice Score of 0.79.
Correlation between Game Experience and Presence in immersive virtual reality games

Virtual Reality (VR) technologies have evolved to the point where it is being used in various areas (entertainment, medicine, education, etc.). One of the metrics that allow the evaluation of the virtual experience is Presence. In this work, we conduct an exploratory study that studies which factors of VR games correlate to presence. Various components of games are also shared between other VR applications allowing the results to be applicable not only in VR games. A study with 78 participants divided into 5 groups was conducted where each group played a different VR game. Presence and Game Experience were evaluated. The results indicated multiple positive correlations between subscales of Presence and Game Experience.
School Management in the Midst of Educational Technology Advancement

This qualitative study has been intended to explore school management practices in the midst of educational technology advancement.Case study research design has been employed to have an in depth look at practices of a selected school on adopting technology driven school management in a way that addresses the type of technologies introduced and how they have contributed for school management.Accordingly, the school has so far introduced different educational technologies within short period of time.Though positive roles of the introduced educational technologies on improving the existing school management have been recognized by regulatory bodies, further content and context based studies and assessments need to be initiated in a way that enables expansion of the school's best practices to other private and public schools in the metropolitan.
Research of the labor resource redeployment by mathematical methods of optimal management

Abstract The problem statement of labor resource redeployment to ensure the sustainability and balance of positive territorial transformations is due to the necessary in order to study the socio-economic factors of the labor resource development in modern economic conditions. The paper presents mathematical models of the labor resource redeployment. In the dynamic model of staff resource redeployment, the speed of redeployment, the dynamics of inter-resource composition and the limitations of the dynamic characteristics of the redeployment process are studied. The model of the territorial labor resource redeployment is a solution to the problem of placing workers with their multi-agent interaction and any finite number of employers on the network with a given set of vacancies for each employee that he wants to receive.
Adaptive Cluster based Model for Fast Video Background Subtraction

Background subtraction (BGS) is one of the important steps in many automatic video analysis applications.Several researchers have attempted to address the challenges due to illumination variation, shadow, camouflage, dynamic changes in the background and bootstrapping requirement.In this paper, a method to perform BGS using dynamic clustering is proposed.A background model is generated using the K -means algorithm.The normalized γ corrected distance values and an automatic threshold value is used to perform the background subtraction.The background models are updated online to handle slow illumination changes.The experiment was conducted on CDNet2014 dataset.The experimental results show that the proposed method is fast and performs well for baseline, camera-jitter and dynamic background categories of video.
CBNAAT Study of Extra-Pulmonary Tuberculosis among Population of North Andhra Pradesh

Background & Objectives: Extra pulmonary tuberculosis (EPTB) constitutes 15 to 20% of total cases of tuberculosis in India.It is high in incidence among HIV and Pediatric group and involves almost all systems of the body.Cbnaat (Catridge-based nucleic acid amplification test) is of definitive value in its diagnosis.The present study aims at knowing the prevalence of EPTB among the population of Visakhapatnam of North Andhra.Material & Methods: 12,372 cases of EPTB out of total cases (old & new) of 67,017 are studied from the data at District Tuberculous Center, Visakhapatnam for the period 2007 to Aug 2018.Results & Discussion: FNAC samples of lymph nodes and others reported highest (177) among EPTB followed by pleural effusion (28) and pus & abscess (30) showing similar and bronchial wash ( 26).In the present study EPTB showed overall prevalence of 18.80 similar to Indian average of 15 to 20%.PTB: EPTB is 4: 1 in males and 2 : 1 in females showing more in incidence in the latter.Hence the target group for EPTB is more of female population as they are vulnerable due to anaemia, malnutrition and low immunity.Conclusions: Though the emphasis is more on PTB case finding, EPTB is also significant and has to be paid attention in the control of tuberculosis.
Analysing underlying Cognitive Process in Reading and Spelling among Dyslexic Students

The idea of individual's study is one of the major considerations of the modern theories in education.The aim of this study is to analyse underlying cognitive process in reading and spelling among dyslexic students, over a sample of 60 children belong to private and government schools in Chennai.Schonell spelling test and Schonell reading test were administered to measure the reading and spelling age.F-test is used to analyse the data and the result indicate that there is significant difference in actual age between reading and spelling age.
Growing Threat of Cyber Crime in Indian Banking Sector

In the dictionary of criminal terminology, cybercrime is a relative a new term; it has emerged mainly after the introduction of technology in financial sector in late 90’s. The present article focuses on the current scenario and technical aspects of cybercrimes concerning the banking sector and their related challenges and impcats.it also highlights the measures to combat the resulting cyber-attacks for better enhanced security.
Website evaluation using cluster structures

Since the early 1990s, when frequent commercial use of the Internet started, academic researchers and website practitioners have actively conducted research on websites.The research's three broad categories are Web content mining, Web structure mining, and Web usage mining; apart from those, some research on coloring, placement technique of images, texts, and links on each page.This paper focuses on the difference between two cluster structures of websites, one induced from the link-based property and the other from the term-based property.The link-based property is stable until a new link is added, but the term-based one varies depending on the items for searching.We propose an evaluation method for the website by comparing the structures of clusters resulted from these properties.Here we adopt kernel k-means method as the clustering method and compare partial clusters derived from term-based property depending on the given sequence of particular terms to deinite partial clusters from the link-based property.To distinguish them, we try to adopt spectral analysis.
Distinguish Markov Equivalence Classes from Large-Scale Linear Non-Gaussian Data

In the problem of causal discovery, conditional independence (CI) tests are generally used to detect the causal relationships among observed data. Due to the curse of dimensionality and the limitation of causal direction learning based on V-structure learning, it is difficult for constraint-based methods to distinguish the actual graph from a set of Markov equivalence classes. To alleviate this problem, in this work, a novel regression-based method to test CIs over linear Non-Gaussian data is proposed. The main purpose of this proposal is to relax the CI test of x⊥y|Z to two unconditional independence tests x - f (Z) ⊥y - g (Z) + ΣH (Z) and x - f (Z) + ΣH (Z) ⊥y - g (Z), wheref and g can be estimated by linear regression independently. In addition, we further show that x -f (Z) ⊥y-g (Z)+ΣH (Z) ( or x -f (Z)+ΣH (Z) ⊥y- g (Z) ) can lead to x ← Z ( or y ← Z ). According to this regression-based method, we design a causal structure learning algorithm to learn the actual graph instead of a set of Markov equivalence classes over the observed data. Experiments indicate that our method can detect much more causal relationships than other existing methods, especially in large-scale cases.
Energy-Domain State Divergence Effect in Quantum Optoelec/Elec-Tronics, Logicism Physics and Novel Concepts of Numbers

Research advances on the energy-domain state divergence effect itself and its typical manifestations in quantum optoelec/elec-tronics are reported. The principle of logicism physics is seriously suggested and some novel concepts of numbers are described.
The Using of Partnership Technology in the Group Educational Activities of Future Primary Classes Teachers

The article clarifies that partnership is a collaboration constructing all activities, communication and behavior on the basis of voluntary responsibility and equality in achieving common goals and outcomes. It is proved by the author that the technology of cooperation acquired new features in the process of its development, but some of its originally incorporated elements lost their significance. This technology evolved into a technology of partnership, new approaches and methods of achieving results appeared in its structure. The definition of «technology of partnership in education» is specified. It is a system of use in a certain sequence of methods, techniques, strategies and means of subject-subjective interaction of participants in the educational process on the basis of tolerance and creativity. It has been determined that it is important for the partnership technology that it is based on the use of the group work method as the most common form of cooperation. The basic principles of partnership business relationships are the respect for a personality; benevolence, conscious management of the course of interaction, a distributed leadership, a social partnership. The advantages of using partnership technology in students education is to develop their autonomy and reflexivity; to feel freedom in decision making; the opportunity to proceed from own motives, values, ideals, interests and needs in the ways of its activity; for teachers – exemption from continuing care for students, control of each step.&#x0D; The author believes that the most effective in the formation of partnership relations is the using of methods of intensive learning as a way of cognition, which is carried in the forms of students’ common activities, their interaction and information exchange, the common solution of different problems. The intensive teaching of future teachers includes the using of interactive methods, heuristic conversations, and multimedia presentations, discussion of special videos of lessons, using computer-assisted methods, trainings, practical group and individual exercises, modeling of educational processes or situations, group work with author’s manuals. The intensive training is carried in the following forms: meetings with well- known teachers, master classes, competitions in creative works with their discussions.
Interpolation-based outlier detection for sparse, high dimensional data

Abstract The clustering-based approach has always been an important research direction of outlier detection technology. The current detection approaches based on clustering of outliers are able to overcome the shortcoming of traditional test approach of outliers, however, most of the existing approach based on clustering to improve the choice of initial clustering center, this does not solve poor due to the sparse data clustering effect, and so cannot be radically improve the accuracy of detecting outliers. The data in the outlier detection problem can be regarded as a high degree of mixing between the normal point and the abnormal point. On the premise of reducing the loss of normal points, the set of outliers is the N samples farthest from the clustering center containing the most outliers. Inspired by this idea, an outlier detection approach based on genetic clustering for high-dimensional sparse data was proposed. By applying genetic algorithm based on traditional k-means, this approach processed the difference of original data and solved the problem of poor clustering effect caused by high-dimensional data sparsity. The experimental results show that compared with several improved k-means-based clustering approaches and outlier detection approaches, the proposed approach can reduce the loss of normal points and distinguish normal data and outlier more accurately.
PENGEMBANGAN BAHAN AJAR PENGAYAAN KONSEP KEANEKARAGAMAN HAYATI SMP KELAS VII BERBASIS PENELITIAN KEANEKARAGAMAN JENIS MOLLUSCA DI PERAIRAN DESA BATANJUNG, KECAMATAN KAPUAS KUALA, KABUPATEN KAPUAS

Teaching materials is one of the important components in the instructional process in addition to teachers and students. Learning success can also be determined by the materials which are used as students’ references so that the effectiveness of student learning increases even without the presence of a teacher. A good teaching material resulted from an environment-based research that combines the teaching materials contained in the textbook with the existing learning objects around the environment where the students reside. There are not many researches for developing teaching materials which are based on local potential, particularly mollusk-based ones. Concrete examples of various types of mollusca from the research results on Mollusca types found in the surrounding area can be used as a learning source to overcome the learning limitations, so that students learn more easily and get more information about the types of Mollusca. This study aims to (1) describe the validity of Biology teaching materials enrichment for Class VII in SMP based on the research result toward mollusca in the marine area Batanjung village. (2) to describe the practicality of teaching materials Biological material enrichment of Class VII in SMP based on the study of molluscs in the river area of Batanjung village, (3) to describe the effectiveness of Biology teaching materials enrichment for Class VII in SMP based on the research of mollusca in the river area of Batanjung village. The results showed that (1) teaching materials made were in the category of “very valid”, judging from the expert validation and the validation of teaching materials of a partner-teacher showed that the teaching materials were in “quiet sufficient” category, and the student readability test result showed that the teaching materials were feasible to be used, (2) The teaching materials created are quite practical, seen from the result of the use of the teaching materials which were classified as “good”, and also from the observations to students’ activities observed are assessed “adequate” and the students’ responses indicated positive responses to the instructional materials, (3) the teaching materials created were quite effective based on learning outcomes which improved after using these materials.
KESALAHAN EJAAN DALAM PENULISAN ARTIKEL WEB IAIN SURAKARTA DAN IMPLIKASINYA PADA PEMBELAJARAN BAHASA INDONESIA KURIKULUM 2013 DI SMP

The article is a written media that is used for information dissemination tools to the general public which are written based on the rules of the standard language, good and correct based on the applicable rules. This study analyzes the inaccuracy of spelling language in writing articles on the Surakarta IAIN Web as well as the implications in 2013 curriculum learning. The focus of discussion in this study is how the form of language errors in spelling in the article on Surakarta IAIN Web and the implications in 2013 curriculum learning. This is a description of the inaccuracy of spelling language in writing articles on the Surakarta IAIN Web and the implementation of learning based on the 2013 curriculum. The type of research used is descriptive qualitative. The method used is observation and documentation. Based on the results of the analysis of language errors in writing articles on the Surakarta IAIN Web, it was found that a form of error (1) the form of spelling errors included (a) a form of error in using standard language, (b) conjunctions, (d) repeated words and (e) the use of punctuation; and (2) Implementation of the 2013 curriculum in Learning includes activities (a) identifying text deficiencies based on applicable KD, (b) reviewing and revising texts based on applicable KD. The high school education unit includes text editing activities based on applicable KD.
A Preliminary Study of Multi-viewpoint Risk Assessment of IoT

With current global businesses extensively depending on data, Internet of Things (IoT) sensors have become the primary source of the real-time data that enable the digital transformation. According to Bain’s Insight, the market for the IoT will grow to more than $520 billion by 2021. The technology has been significantly adopted with an array of use cases, but due to the ever-expanding threat landscape, many customers show that security remains the primary barrier when it comes to acceptance of IoT. The current security risk management methodologies focus mostly on the cyber view. This paper identifies 29 risk factors that are extracted using the risk breakdown structure method by expanding the traditional view to include other views such as physical and psychological ones, which are critical to business operations. These, in turn, will help clarify the IoT security and the relation of non-cyber risk for proper implementation of IoT systems.
A comparison of structured data query methods versus natural language processing to identify metastatic melanoma cases from electronic health records

The relative efficacy of natural language processing (NLP) of text reports compared to structured data queries for identifying patients from electronic health records (EHRs) with metastatic cancer remains unclear.Such identification is critical for identifying and recruiting potential study candidates for cancer trials, particularly trials of cancer chemotherapy.For such purposes, we performed a direct comparison between NLP and structured data query methods for identifying patients with metastatic melanoma.Using EHR data from two large institutions, we found that NLP of text reports identified close to three times as many patients with metastatic melanoma compared to a structured data query algorithm (1,727 vs. 607 patients).Using an external tumour registry, we also found NLP had much higher sensitivity than structured query for identifying such patients (67% vs. 35%).Our results emphasise the importance of employing NLP criteria when identifying potential cancer study candidates with metastatic disease.