Reviewerly/exHarmony huggingface dataset:
Comprehensive Information Support of Urban Planning on BIM-based Design

The article is devoted to comprehensive information support of urban planning design based on BIM-technology.The study is based on a systematic approach to the process of developing urban planning documentation at the pre-design stage of construction, based on the current modern trend of transition to the digital economy.Information model of the territorial cluster of urban planning design is proposed in the study.The content of each layer of territorial cluster information model is described in detail.The conceptual model of spatial data storage for solving problems of general planning of the territorial cluster is presented in the form of three main blocks.Block 1 is data sources that are taken from the operating system and external sources.Block 2 is a data store, which operational and external sources supply spatial data or metadata.Block 3 is consumers of information that generate requests for data to the means of presenting information.The structure of Unified Information Support Center (UISC) and performers for comprehensive information support of the territorial cluster is presented in the study.As the results of the study are shown summary plan of engineering networks, made using BIM-based design software and digital 3D model of the consolidated plan of engineering networks, made using AutoCAD Civil 3D.The use of BIM technologies at the stage of urban planning design is a new direction of its development.
Area and Delay Efficient Compressor Based Montgomery Multiplier

Modular multiplication plays an important role in public-key crypto-systems. It first performs integer multiplication and then the costlier division operation is done. Due to this, the computation time and resource requirements will be high. In order to overcome these limitations, Montgomery Modular Multiplication (MMM) method is widely used. As integer multiplication is the most important operation in the Montgomery Multiplication algorithm, it becomes mandatory to enhance the speed of Integer Multiplier (IM) so that it can increase the overall efficiency of Montgomery Multiplier (MM). This work is mainly focused on compressor based MM to improve the performance in respect to propagation delay and area. In this paper, MM using 3:2, 4:2 and 5:2 compressors based Array Multiplier (AM) are designed for performing Integer Multiplication in MM and their performance are evaluated. The modules are synthesized using Xilinx ISE 14.7 and targeted on FPGA family Artix-7. Finally, comparative analysis is made in terms of delay and area
OBTAINING THE VOCABULARY OF DOWN SYNDROME CHILDREN BASED ON INDONESIAN VOCABULARY CLASSES IN SLB C1 AKW KUMARA 1 SURABAYA

Vocabulary is a language component that contains all information about the meaning and use of words in the language. The word class is the basis for the discussion of languages. In this study aims to analyse "child vocabulary grade Down Syndrome based on the Indonesian word in SLB C1 AKW Kumara 1 Surabaya". In the discussion and descriptives regarding the acquisition of vocabulary based on the Indonesian word class are included in psychocholinistic studies in morphological scope. The study discusses the acquisition of basic vocabulary forms classified by verb classes, noun classes, and adjectives.The focus on this study aims to describe and analyze the acquisition of basic vocabulary form based on Indonesian word class in SLB C1 AKW Kumara 1 Surabaya. The collection of data in this research is using the method of the free Libic hearing capable of directly recording the event of the speech of teachers and students in the learning activities with the device in the form of handphone, and the method of reading proficient see that in conducting interviews to class teachers.Based on the results of the research that has been done, it is derived data in the form of children with Down Syndrome who are classified into basic vocabulary based on basic verb classes and derived verb classes, basic noun classes, and basic noun classes.
On Predicting Rediscoveries of Software Defects

The same defect may be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. One solution is forcing clients to install a fix for every defect. However, this approach is economically infeasible, because it requires extra resources and increases downtime. Moreover, it may lead to regression of functionality, as new fixes may break the existing functionality. Our goal is to find a way to proactively predict defects that a client may rediscover in the future. We build a predictive model by leveraging recommender algorithms. We evaluate our approach with extracted rediscovery data from four groups of large-scale open source software projects (namely, Eclipse, Gentoo, KDE, and Libre) and one enterprise software. The datasets contain information about ⇡ 1.33 million unique defect reports over a period of 18 years (1999-2017). Our proposed approach may help in understanding the defect rediscovery phenomenon, leading to improvement of software quality and customer satisfaction.
Unmanned Ariel Vehicle Sorts with Societal and Security Applications

The goal this paper aims to detail exploration about the Unmanned Ariel Vehicle and its types and various application use cases of its. Discuss the Unmanned Ariel Vehicle market growth and regulations. Unmanned Arial Vehicle – generally called as UAV are the cutting edge technology and buzz word in the recent years because of its various potential strength. UAVs are usually called as Drone. As the name implies UAV is the aircraft without a human pilot on the board. Drones are controlled from the ground control system (GCS) or designed to fly autonomously using the defined flight path and flight plan.
Efficient Load Balancing and Service Broker Policy Using Local and Global Representatives in Cloud Computing

Cloud computing is a technology in the field of computing which offer services to the customer from anywhere at any time [1]. In the cloud, resources are shared all around the work for quick servicing to the customer. The aggregation of two terms is referred as cloud computing. The term “cloud” is a pool of different resources offers services to the end customers and “computing” is done based on the Service Level Agreement (SLA) to make the resources efficiently to the customers. Load balancing is an important challenge in the environment of the cloud to increase the utilization of resources [3]. Here we proposed an algorithm which is based on load balancing and service broker policy. We user two representative thin the proposed approach local representative and global representative Local user representative is used to predict the parameters of user task and based on priority it allocate the task to the Virtual Machine (VM). Then for scheduling the task and provide the services to the users based on the available cloud brokers global user representative used Dynamic Optimal Load-Aware Service Broker (DOLASB).we used two scenario with different no. of user requests , in these scenario result of our proposed method is better as compared with the other existing methods in terms s of Execution Time, Makespan, Waiting Time, Energy Efficiency and Throughput.
FAKTOR-FAKTOR YANG MEMENGARUHI KEBERHASILAN BELAJAR MAHASISWA PADA MODEL PEMBELAJARAN STUDENT CENTERED LEARNING DI STIKES JENDERAL ACHMAD YANI YOGYAKARTA

Background: Learning is an effort to obtain intelligence or knowledge, changing behavior or responses caused by experience. There are many factors that influence the success of learning. Two main factors that affect the success of one's learning are the factor of the internal (internal factors) and other factors that come from outside the individual (external factors). External elements (environmental factors and instrumental factors) and internal elements (physiological factors and psychological factors) also play a role in influencing learning processes and outcomes.&#x0D; Objective: To identify the factors that influence the success of student learning on SCL model in Stikes Jenderal Achmad Yani Yogyakarta.&#x0D; Methods: Research descriptive correlation with cross sectional approach. The population in this study were all students of Stikes Jenderal Achmad Yani Yogyakarta who obtained the SCL model. Data retrieval method used simple random sampling.&#x0D; Results: There is a relation between student's attention and learning achievement (P value = 0,000), there is correlation between fatigue with learning achievement (Pvalue = 0,000). There is no relation between family factor and learning achievement (Pvalue = 0,300), no correlation between school factor and achievement (Pvalue = 0,130), and no relation between environmental factor and academic achievement (Pvalue = 0,476)&#x0D; Conclusion: Students' attention in learning influences learning achievement, with positive relationship direction (r = 0,814), where each addition of student’s attention for 1 hour will improve student’s achievement as much as 2.21 points.&#x0D; Keyword: SCL model, learning.
Role of Education in Social Adjustment of Adolescents

Change might be characterized as a course of modifying conduct to arrive at an amicable relationship with the climate. Social change implies an amicable relationship with the general public, legitimate comprehension of social necessities, prerequisites and gathering objectives and meeting individually to the social necessities of the home, peer gatherings, culture and the local area. These days, it is seen that the young people of our general public are dealing with various issues at various levels and the foundation of such issues is found to have close connection with behavioural condition of them. As indicated by the advanced idea of schooling, best change is a definitive objective of training. On the off chance that the data about the change issues of young adult understudies is accessible and their necessities and sentiments are thought of and perceived, the educator and direction faculty will be in a superior situation to give satisfactory training to understudies. Educators can assume a fundamental part in forming the eventual fate of society by focusing on the youths are shared with their consideration. Social change is an effort made by an individual to adjust to rules, characteristics and prerequisites of an overall population to be recognized. It will in general be described as a psychological cycle. It incorporates adjusting to new standard and worth. In the particular language of mind science "coinciding with the populace nicely well" is called change. Clinicians oftentimes use the term change as per portray various kinds of social and social relations in the public eye. Thusly, change can be suggested as the reaction to the solicitations and loads of a group environment constrained upon the individual. The current paper is an endeavour to explore the social change of optional school understudies comparable to their schooling.
Quantifying the Probabilistic Distribution of Power Flows

Background. Active power flow capacities are used to monitor the compliance with power system stability requirements while configuring and running the system. The grid is modeled mathematically for such design. The projected daily load curve and its associated magnitudes are calculated per rules, i.e. set specifically for specific time intervals. However, actual loads are not constant and can generally be represented by an interval that contains the actual values. Grid parameters are also seasonal, as they are affected by accidents, weather, etc. In other words, a grid model uses a number of assumptions. This paper proposes Monto-Carlo simulation to simulate the parameters of a power system as affected by changing the initial loads at grid nodes as well as the line resistance values per Gaussian distribution. The method can find how these values affect power flows in grid branches as well as determine the margin of static stability. Materials and methods: Monte Carlo Method (method of statistical testing). Results. This methodology has been applied to a base-generator/base-load two-node system as well as to a base-load-generator three-node system; besides, it has been applied to the model of Radkino-Arlansky District, Republic of Bashkortosan’s power system. For these models, the team calculated the active and reactive power flows for each successfully computed operating mode that would not compromise static stability. The obtained values were used to plot distributions and to find the range of their variation. Then the static stability factors were calculated and their dependences on the interval length of initial grid parameters changing were constructed. Conclusions. Changing the range of power flows in the branches of the analyzed grid helped researchers find which of them had the greatest fluctuation range and which nodes would affect the flows the most if altered in capacity. Thus, the capacities of these nodes are subject to more accurate adjustment.
A Curricular Strategy for Information Security Engineering

Existing textbooks and training materials in basic information security do not reflect the actual problem solving techniques and practices in the field of information security engineering.In general, texts focus on memorization of a broad range of facts related to modern information security practice.Analytical techniques, when present, often focus on mathematical foundations of cryptography, the inner workings of security protocols, and perhaps the logical derivation of formal security policy statements.In practice, information security engineering involves a life cycle starting with requirement analysis, progressing through design analysis and deployment, and repeating the cycle following a period of system monitoring and incident response.A fundamental activity in the practice of information security engineering is the assessment of security perimeters that divide a system into more-trustworthy and less-trustworthy components.This type of analysis is applied at every level of an information security system to yield an overall assessment of its security.Perimeter assessment requires that a student learn fundamental features of computer systems at the hardware, operating system, application, and network level.This yields a coherent curricular strategy that incorporates certain classical elements of cryptographic analysis (e.g.assessment of key strength), engineering requirements analysis, and fundamental elements of computer engineering.
Large receptive field networks for accurate high-scale image super-resolution

This thesis presents a novel convolutional neural network architecture for high-scale image super-resolution. In particular, we introduce two separate modifications that can be made to the convolutional layers in the network: one-dimensional kernels and dilated kernels. We show how both of these methods can be used to expand the receptive field and performance of super-resolution networks, without increasing the number of trainable parameters or network depth. We show that these modifications can easily be integrated into any convolutional neural network to improve performance. Our methods are especially effective for the challenging high scale super-resolution due to the expanded network receptive field. We conduct extensive empirical evaluations to demonstrate the effectiveness of our methods, showing strong improvements over the state-of-the-art.
Ontological model for evaluating the effectiveness of scientific institutions

The article presents an approach to assessing the quality of functioning of scientific institutions based on ontologies. Today, there are a large number of scientific institutions and specialized organizations whose efficiency depends on the quality of the services they provide. In the course of their operation, institutions accumulate a large amount of information (scientific articles, reports, employee ratings, economic indicators, etc.) that can be used to evaluate them automatically by national criteria. This study proposes to use an ontological model to store, present and manipulate with such information. Ontologies are new intelligent tools for finding resources on the Internet, new methods for representing and processing knowledge and queries. They are able to accurately and efficiently describe the semantics of data for a certain domain and solve the problem of incompatibility and inconsistency of concepts. The ontological approach allows the continuous improvement of the model based on basic ontologies by completing and developing them The ontology will allow not only to structure and systematize the data of scientific institutions, but also to perform the procedure of quality assessment through the mechanism of ontological logical inference. A general ontology for describing the activities of scientific institutions is represented by a system of five connected components. In the paper the structure of such a system is described, basic elements of its ontologies and the connections between them are highlighted. The ontology of the scientific institution activity is developed using specific technological platform TEDAOS - “Transdisciplinary Educational Dialogues of Applications’ Ontology Systems”.
Masterbot

In this paper the web application will be shown that can classify URL using Naïve Bayes and chatbot which is combination of rule-based chatbot and artificial intelligence (AI).Chatbot can answer to user's queries based on URL corpus.Web application is developed for users regardless of their technical knowledge.The paper presents my solution and opens questions for further development in this scientific field..
An After-action Review: Creating a Matrix Organizational Design Model for Online Education at a Tier-1 Research University

He has over thirty-five years of theoretical and defense industry-based practical
Hybrid Classification Technique for Sentiment Analysis of the Twitter Data

Sentiment can be described in the form of any type of approach, thought or verdict which results because of the occurrence of certain emotions. This approach is also known as opinion extraction. In this approach, emotions of different peoples with respect to meticulous rudiments are investigated. For the attainment of opinion related data, social media platforms are the best origins. Twitter may be recognized as a social media platform which is socially accessible to numerous followers. When these followers post some message on twitter, then this is recognized as tweet. The sentiment of twitter data can be analyzed with the feature extraction and classification approach. The hybrid classification is designed in this work which is the combination of KNN and random forest. The KNN classifier extract features of the dataset and random forest will classify data. The approach of hybrid classification is applied in this research work for the sentiment analysis. The performance of the proposed model is tested in terms of accuracy and execution time.
Understanding User Customization Needs: Requirements for an Augmented Reality Lamp Customization Tool

Nowadays, people are willing to pay for personalized items that satisfy their preferences and distinguish them.Previous work has provided generic customization tool design guidelines.User requirements were gathered for the design of an Augmented Reality (AR) application for lamp customization in context.These are required to define a product configurator that allows users to meet their specific needs.The results of three user studies show that customers' needs are preference fit, inspiration and help; freedom and support during the customization process; and trustworthy visualizations.
SEFRA - Web-based Framework Customizable for Serbian Language Search Applications

This paper presents SEFRAa web-based framework for searching Web content written in Serbian.SEFRA is an easily customizable hybrid solution that can be a platform for new search applications and/or a service for already existing ones.The proposed architecture solves the problems of indexing, searching and displaying search results adjusted for Serbian.It unifies several web technologies and services into one product suitable for use in the Western Balkan's countries for helping e-Government citizens' services and other public-sector services, private company administration, solving specific search problems for academic institutions and scientific literature publishers, etc.The proposed solution uses advanced Serbian language services accessible over the Web.It is also implementable for any other language where the target language morphology service exists.In other words, architecture is also customizable in this direction.It should be noted that the proposed architecture is optimized from both backend and web front-end perspective.The source code can be pulled from https://bitbucket.org/mjovanov/pretraga/.The one application of the proposed architecture is experimentally demonstrated through the search of crime law documents of Serbia.The experimental usage of this implementation shows that the problem of search relevance, is well-solved and easily customizable.
Performance Analysis of Predictive Models using Generic Datasets

Today over 2.5 quintillion bytes of data is being created every single day where 753 crore people on this planet are creating 1.7mb of data each second. Most often than not, Researchers only scratch the surface when it comes to analyzing which algorithm will be best suited with their dataset and which one will give the highest efficiency. Sometimes, this analysis takes more computational time than the actual execution itself. Aim of this paper is to understand and solve this dilemma by applying different predictions models like Neural Networks, Regression and Decision Tree algorithms to different datasets where their performance was measured using ROC Index, Average Square Error and Misclassification Rate. A comparative analysis is done to show their best performance in different scopes and conditions. All data sets and results were compared and analyzed using SAS tool.
A Semi-Markov decision model-based brokering mechanism for mobile cloud market

As the multitude and complexity of cloud market increases the evaluation and selection of cloud services becomes a burdensome task for the users. With the increased rise of available services from various Cloud Service Providers (CSP), the role of cloud brokers becomes more and more important. In this thesis, the challenge of optimally allocating multiple cloud system resources to multiple mobile user’s requests with different requirements is investigated and an optimal Cloud Broker model is proposed. The cloud brokering mechanism is formulated as a Semi-Markov Decision Process (SMDP) model under the average system cost criteria, taking into consideration the cost of the occupying computing resources, the communication costs, the request traffic, and some security risk degrees and resource requirements from the multiple mobile users. Through minimizing the overall system cost, the optimal resource allocation policy is derived by using the Value Iteration Algorithm. Simulation results are provided, demonstrating the efficiency of the proposed Cloud Broker design.