Reviewerly/exHarmony huggingface dataset:
PENGEMBANGAN MEDIA PEMBELAJARAN E-MODUL MATERI SISTEM PEREDARAN DARAH PADA KELAS XI MIPA SMAN 6 BARRU

Abstract: This research is a research and development, which aims at developing e-modul learning media of Blood Circulatory Systems material, which is valid, practical, and effective. The research and development phase refers to Hannafin and Peck development model, which consists of 3 stages: namely (1) needs assessment, (2) design, (3) development and implementation. The assessment instrument consists of five instruments, namely (1) validity instrument of research instrument, (2) media validity instrument, (3) practicality test instruments by the teacher, (4) practicality test instruments by the students, and (5) learning outcomes instruments. Based on data analysis, the average of media validity obtained by two assesors is 4.3 in a valid category. The practicality of the media obtained from the teacher's response of 100% with a very strong category and the students response is 100% with a very strong category. The effectiveness of the media obtained 86.96% of students achieving learning mastery value. the conclusion based on the results of the study is the product of emodul learning media of Blood  Circulatory System material developed is valid, practical, and effective. Keywords: media, e-module, learning, circulatory system
Transaction Security in Energy Trading System using Block chain

Transaction Security (TS) is a framework that intercepts real-time Sales force events and applies appropriate actions and notifications based on security policies we create.In the earlier system of transactions all the nodes in the network are connected using centralized approach in which a node act as a server and all other nodes are connected to it.It is similar to client server model.All the information are stored in the centralized node.When the centralized node is been hacked by the hacker then it provides entire details about the transaction and doesn't provide enough security.Since the privacy of these data is very less we proposed to have more secured system.The proposed system uses a decentralized network that doesn't rely on a central point of control.A lack of a single authority makes the system fairer and considerably more secure using block chain and multi signature.A block chain is a public ledger of information collected through a network that sits on top of the internet.It is how this information is recorded that gives block chain its ground breaking potential and it is extremely important that the information being stored is honest and accurate.The main aim of this system is to provide transaction security without using a trusted third party since it reviews all the critical transaction communications between the parties, based on the ease of creating fraudulent digital content.This system provides high security and the hacker meets the difficulty level to retrieve the data..
Unveiling middle-level concepts through frequency trajectories and peaks analysis

Natural language development and learning begins with a few terms, often related to concepts associated to perception, in general neither too general nor too specific, gradually specializing and extending to abstract concepts. A linguistic middle-level can be considered as a lexical base on which a language oriented towards more complex communications develops in adulthood. Learning can extend from generic to specific terms (usually a child learns first the term "dog", then the term "dachshund"), or from specific to generic ("dog" → "mammal"). Thus, a middle-level includes all those terms that are halfway, in the taxonomic sense, between generic and specific concepts. In this paper we propose a computational approach to identify a middle-level relying on Wikipedia as input corpus and WordNet as lexical-semantic resource. An experimentation based on graded readings shows favourable results. The impact of this work could touch different fields, e.g., the automatic evaluation of the complexity of a text by computational approaches, rather than psychological and linguistic studies related to the language use.
Optical Flow Estimation with Occlusion Detection

The dense optical flow estimation under occlusion is a challenging task. Occlusion may result in ambiguity in optical flow estimation, while accurate occlusion detection can reduce the error. In this paper, we propose a robust optical flow estimation algorithm with reliable occlusion detection. Firstly, the occlusion areas in successive video frames are detected by integrating various information from multiple sources including feature matching, motion edges, warped images and occlusion consistency. Then optimization function with occlusion coefficient and selective region smoothing are used to obtain the optical flow estimation of the non-occlusion areas and occlusion areas respectively. Experimental results show that the algorithm proposed in this paper is an effective algorithm for dense optical flow estimation.
Reservation Policy for Multi-Sharing Resources in Heterogeneous Cloud User

The concept of cloud computing is focused on how to maximize the usage of multi-sharing in heterogeneous cloud user. At present, the cloud service providers are offering outstanding reservation and on-demand plans with restrictions. It restricts sharing of multiple resources with multiple users. There was no provision for user coalition and no option was provided to carry forward the unused resources. In this paper, the improvised model reservation policy for multi-resource sharing model (RPMRS) is proposed. RPMRS takes care of reservation provisioning policy (RPP) and multi-sharing of resource accountability for the end user and it can also carry forward the unused resource. The experimental results show that it is a promising model for carry forward of unused resources (CFUR) for both cloud provider and cloud ultimate user. The results emerged was of 98% efficient by way of resource provisioning with least user collision at a limited cost.
PENYEWAAN ONLINE WEDDING ORGANIZER BERBASIS WEB

Wedding organizers help prospective brides and families in the planning and implementation of a series of wedding events in accordance with the schedule and budget that has been set by offering various concepts of marriage but prospective brides have difficulty knowing the WO is constrained by a number of things such as lack of information, difficulties in ordering and takes time to visit WO places. Constraints The website is a forum for wedding organizer promotions to brides that can be accessed at any time where the system is designed using the PHP programming language and MySQL database. The aim of the research is to design a web-based Wedding Organizer (W0) information system so that prospective brides can find wedding concepts desired is adjusted based on the number of invitations, finance, catering, buildings, and bridal aisle decorations while for service providers is the promotional media WO has so that it runs a wedding organizer business process that connects service providers with consumers through electronic transactions using the internet.
Cloud Computing Security Threats and Attack Detection Issues

Cloud computing is the group of services for software network and hardware, which are provided to users. Cloud storage provides users with the facility to store, access and manipulate data according to user's convenience regardless of time and location along with providing the pool of resources such as network, storage and services on the basis of demand. Cloud computing is highly demanded among users because of its features such as high computing power, less cost of services, high performance, scalability, reliability, accessibility and availability. Security is still posed as a critical challenge in the cloud computing paradigm. As cloud computing demand increases, securing the cloud becomes more difficult from different threats and attacks. Particular attack can primarily focus on different layers of cloud architecture and attack on one layer makes upper layers unstable and prone to easy attacks. In this survey paper, we will study different threats or attack on cloud data and cloud layer to prevent data theft, data leakage, breach and data modification by applying user authentication, user access rights and admin authentication, and access rights from internal threat point of view to eliminate from insider and outsider attack on data in cloud environment.
Dual-Precision Acceleration of Convolutional Neural Network Computation with Mixed Input and Output Data Reuse

Memory access dominates power consumption in hardware acceleration of deep neural networks (DNN) computation due to the movement of huge data and weights. This paper design a DNN accelerator using mixed input and output data reuse scheme to achieve balance between internal memory size and memory access amount, two contradictory design goals in resource limited embedded systems. First, analytical forms for memory size and accesses are derived for different data reuse methods in DNN convolution. After comparing the analysis results across different convolutional layers of the VGG-16 model with different levels of hardware parallelism, we implement a low-cost DNN hardware accelerator using mixed input and output data reuse scheme with 32 processing elements (PEs) operating in parallel. Furthermore, the design supports two precision modes (8-bit and 16-bit) allowing variable precision requirements across DNN layers, resulting in more efficient computation compared with single-precision designs through sharing of hardware resource.
Hitting Time of Stochastic Gradient Langevin Dynamics to Stationary Points: A Direct Analysis.

Stochastic gradient Langevin dynamics (SGLD) is a fundamental algorithm in stochastic optimization. Recent work by Zhang et al. [2017] presents an analysis for the hitting time of SGLD for the first and second order stationary points. The proof in Zhang et al. [2017] is a two-stage procedure through bounding the Cheeger's constant, which is rather complicated and leads to loose bounds. In this paper, using intuitions from stochastic differential equations, we provide a direct analysis for the hitting times of SGLD to the first and second order stationary points. Our analysis is straightforward. It only relies on basic linear algebra and probability theory tools. Our direct analysis also leads to tighter bounds comparing to Zhang et al. [2017] and shows the explicit dependence of the hitting time on different factors, including dimensionality, smoothness, noise strength, and step size effects. Under suitable conditions, we show that the hitting time of SGLD to first-order stationary points can be dimension-independent. Moreover, we apply our analysis to study several important online estimation problems in machine learning, including linear regression, matrix factorization, and online PCA.
A Probabilistic Learning Approach for Predicting Application Launches in Cloud Computing Architectures

Desktop and application virtualization suffers from delay. Opening sessions and remote applications implies to load a non-negligible amount of data, parameters and services. This can be solved by predicting the future activities of the users and pre-loading the required resources. We thus propose a complete approach that automatically discovers the periodical patterns of the users and that automatically builds a probabilistic model of user's behaviour. A kernel density estimator is exploited to estimate the probability density function of an application to be launched by a user. Using the probabilistic approach allows to predict the application a user will open and to reduce the launching time. The efficiency of the proposed approach has been verified by an implementation in a virtualization tool under real operating conditions.
Lack of effects of gender on the reading rate of long texts

Among various linguistic and extralinguistic factors which may affect speech tempo, the gender of the speaker has received considerable attention. In a number of publications it has been reported that women tend to read at a slower rate than men. However, other studies cast doubt on these findings and the issue needs further investigation. This paper attempts to compare the reading rate of male and female speakers of English on the basis of selected chapters from audiobooks. The recordings analysed are considerably longer than the samples used in previous research. The rate of speech has been measured using phonemes per second, syllables per second and words per second. The results consistently indicate that gender does not affect reading tempo. They are directly applicable in text-to-speech (TTS) software development and may be useful in other disciplines, such as forensic linguistics, clinical linguistics or education.
Organizational Maturity: The Elephant Affecting Productivity

The maturity of an organization’s software development environment impacts the productivity of its developers and their teams. Consequently, organizational attributes should be measured and factored into estimates of cost, schedule, and quality. This chapter presents an evolutionary model of organizational maturity, how the model can guide productivity and quality improvements, and how its practices can be adapted to evolving development methods.
Application of Game-Based Learning in the Teaching Process of Disaster Medicine for Medical Students

Introduction: Classroom instruction of disaster medicine for medical students is complicated and lacks attraction. Nowadays a novel method, which is named Game-Based Learning (GBL), has been used in other fields and received good feedback. Aim: To apply GBL to the teaching process of disaster medicine and discuss the effect of its application. Methods: A computer game was devised based on a syllabus of disaster medicine and employed it in classes of disaster medicine for medical students. Then a questionnaire about the application of GBL in education was used inquiring the demands of medical students for the designing of GBL in disaster medicine, including their platform and game mode preferences. Feedback was collected and data was analyzed after the class. Results: 201 questionnaires were issued, and the valid rate was 100%. From the responses, 77% of medical students considered the application of GBL in education on disaster medicine was necessary, and 73% of the respondents thought it was practical. Furthermore, over 90% of medical students expressed their expectation for the adoption of GBL. According to another survey of 51 medical students we conducted, after attending a class about knowledge of injury classification with one board game adopted, most of the students believed GBL was better than traditional methods of teaching. Discussion: There is a high approbation degree among medical students to the adoption of GBL in the teaching process of disaster medicine, which suggests a great possibility for the application of GBL in medical education. It is concluded that GBL can be used in the teaching process of disaster medicine.
Trends and Prospect of the Market for Veterinary Medical Devices in Korea

This study reviewed the trends and prospect of the market for veterinary medical devices in Korea. The registration of veterinary medical devices has sharply increased since 2013, and a total of 2,133 products from 348 companies were registered by 2018. Of these products, the proportion of the instrument, in vitro diagnostic (IVD) reagents, medical only used for animal and supplies were 51.6%, 35.7%, 7.6% and 5.1%, respectively. The sales amount of veterinary medical devices is approximately 95.8 billion won in 2017. The sales of domestic consumption and imports were 53.9 and 41.9 billion won, respectively. They are increasing 14.9% (CAGR) in the domestic consumption, and 44.0% (CAGR) in the export from 2011 to 2017, respectively. The proportion of IVD reagents, instrument, medical only used for animal and supplies were 54.2%, 41.0%, 3.8%, and 1.0%, respectively. The top 10 items with high sales were IVD reagents for clinical immunochemistry, visceral function testing instrument, hematological testing apparatus, syringes, IVD reagents for molecular genetics, etc. They are widely used from 3,926 animal hospitals in 2017. This study suggested that registration and sales of veterinary medical devices have gradually increased since 2013 as the demand of health care services for various animals. Therefore, the veterinary medical devices industry is expected to grow in the future.
Home Visit Effectiveness on Students’ Classroom Behavior and Academic Achievement

Home visits have a large influence on the academic achievement of students and the relationship between teachers and students. The purpose of the study was to investigate the effectiveness of home visits on students’ academic success and behavior in the classroom. This study investigated the parent involvement of the students who were visited by teachers compared to students who were not visited by teachers. An explanatory mixed research method was used to determine the influence of the home visits on the academic achievement and classroom behavior of students compared to students whose homes were not visited. The first phase of the study was a survey instrument to measure the perspectives of teachers regarding the academic success and behavior of students. The second phase of the study included interviews with teachers to investigate their perceptions of the home visits. The total sample size of the study was 128 for the survey, and 10 of the 128 later participated in interviews. The results of the study indicate that home visits and family engagement have positive impacts on students’ academic achievements and attitudes in school. The results of the study are applicable broadly in education and can assist teachers in improving the academic performance of their students
Automated tableau generation using SPOT (Syntax Prosody in Optimality Theory)

Abstract Much recent work on the syntax-prosody interface has been based in Optimality Theory. The typical analysis explicitly considers only a small number of candidates that could reasonably be expected to be optimal under some ranking, often without an explicit definition of GEN. Manually generating all the possible candidates, however, is prohibitively time-consuming for most input structures – the Too Many Candidates Problem. Existing software for OT uses regular expressions for automated generation and evaluation of candidates. However, regular expressions are too low in the Chomsky Hierarchy of language types to represent trees of arbitrary size, which are needed for syntax-prosody work. This paper presents a new computational tool for research in this area: Syntax-Prosody in Optimality Theory (SPOT). For a given input, SPOT generates all prosodic parses under certain assumptions about GEN, and evaluates them against all constraints in CON. This allows for in-depth comparison of the typological predictions made by different theories of GEN and CON at the syntax-prosody interface.
AIML and Sequence-to-Sequence Models to Build Artificial Intelligence Chatbots: Insights from a Comparative Analysis

A chatbot is a software that is able to autonomously communicate with a human being through text and due to its usefulness, an increasing number of businesses are implementing such tools in order to provide timely communication to their clients. In the past, whilst literature has focused on implementing innovative chatbots and the evaluation of such tools, limited studies have been done to critically comparing such conversational systems. In order to address this gap, this study critically compares the Artificial Intelligence Mark-up Language (AIML), and Sequence-to-Sequence models for building chatbots. In this endeavor, two chatbots were developed to implement each model and were evaluated using a mixture of glass box and black box evaluation, based on 3 metrics, namely, user’s satisfaction, the information retrieval rate, and the task completion rate of each chatbot. Results showed that the AIML chatbot ensured better user satisfaction, and task completion rate, while the Sequence-to-Sequence model had better information retrieval rate.
Development of communicative competencies of students in the context of blended learning

This article explores students’ communicative competencies development in the context of blended learning. The relevance of the work is the need of new conditions for students' communicative competencies development. The goal of the work is to prove the effectiveness of blended learning for the development of communicative competences. The article offers recommendations for teachers on competencies development in the implementation of blended learning, and also presents the levels of communicative competences development. In the process, the essence of the application of e-learning in higher educational institutions is revealed.
A Brief Overview of the Synergy Between Metaheuristics and Unconventional Dynamics

This brief review paper focuses on the modern and original hybridization of the unconventional dynamics and the metaheuristic optimization algorithms. It discusses the concept of chaos-based optimization in general, i.e. the influence of chaotic sequences on the population diversity as well as at the metaheuristics performance. Further, the non-random processes used in evolutionary algorithms, and finally also the examples of the evolving complex network dynamics as the unconventional tool for the visualization and analysis of the population in popular optimization metaheuristics. This work should inspire the researchers for applying such methods and take advantage of possible performance improvements for the optimization tasks.
Renkli Resimlerin Yüksek Boyutlu Kaotik Lineer Dönüşümlerle Şifrelenmesi

In this study, a well-known chaotic transformation namely Arnold’s CAT map is used to extend 2-dimensional mapping to a higher dimension. This extension is achieved by means of the planar extension and Multinacci series. The demonstration of a 3-dimensional Arnold’s CAT map is performed by RGB component substitution of a colored image. For this purpose, the colored image is converted from a standard RGB space into an intensity-hue-saturation (IHS) space. Consequently, both Chebyshev and Hadamard map is employed for encryption of the intensity component. Besides, CAT map is engaged to encrypt the hue and saturation components. According to the results, the proposed method has a great potential to be an efficient tool for data encryption.
Polarization and phase shifting interferometry

A novel interferometric approach for a full-field and simultaneous measurement of the phase and the polarization state of a light wave is introduced. The same procedure can be used for simultaneous analysis of the phase transmission and the polarization properties of a specimen.
The Swarm Satellite Trio Studies Earth and Its Environment

8th Swarm Data Quality Workshop; Frascati, Italy, 8–12 October 2018
Aspect-Based Sentiment Analysis with Minimal Guidance

Aspect-based sentiment analysis is an important tool to understand user opinions in a fine-grained manner. Although extensively studied, developing such a tool for a specific domain remains an expensive process. Most existing methods either rely on massive labeled data for training or external language resource and tools which are not necessarily available or accurate. We propose to study the aspect-based sentiment analysis with only a small set of aspect and sentiment seed words as guidance on a target corpus. We first expand the aspect and sentiment lexicons from the given seed words by features created by frequent pattern mining. Then, we develop a generative model to characterize the aspect and sentiment mentions based on their word embedding, and infer the sentiment polarity for sentiment words accordingly. The effectiveness of our method is verified by experiments on two real world data sets.