Reviewerly/exHarmony huggingface dataset:
PENGARUH SISTEM INFORMASI AKUNTANSI TERHADAP EFEKTIVITAS PENGENDALIAN PIUTANG DAN KOLEKTABILITAS PIUTANG TAK TERTAGIH PADA BPRS BHAKTI SUMEKAR CABANG PAMEKASAN

The purpose of this study is to determine whether the sales accounting information system influences the effectiveness of receivables control and the effectiveness of collectibility of uncollectible receivables in BPRS Bhakti Sumekar, Pamekasan Branch. This type of research uses descriptive quantitative methods. Data collection is done using a questionnaire. From the results of the study it is known that there is a significant relationship between accounting information systems and the effectiveness of accounts receivable control and collectability of uncollectible accounts. The simple correlation coefficient (R) for the effectiveness of receivables control is 0.826, which means that the accounting information system has a close or strong relationship to the effectiveness of accounts receivable control, which is 0.826 or 82.6%. While collectibility of uncollectible accounts of 0.847 means that the input variable consisting of accounting information systems has a close or strong relationship to collectability of uncollectible accounts of 0.847 or 84.7%. The coefficient of determination for the effectiveness of accounts receivable control is obtained value ( R 2 ) = 0.683 which means that 68.3% of the effectiveness of the control of accounts receivable can be explained by the accounting information system while the remaining 31.7% is influenced by other variables outside the model studied. uncollectible obtained value ( R 2 ) = 0.717 which means that 71.7% collectability of uncollectible accounts can be explained by accounting information systems while the remaining 28.3% is influenced by other variables outside the model studied.
Designing an English course for tourism at State Amazonian University

The purpose of the investigation were to propose an ESP course for students at “Universidad Estatal Amazonica” in the Department of Life Sciences in Tourism Engineering Puyo, Pastaza- Ecuador. This proposal consists in a Communicative Syllabus with specific topics and grammar structure, which will allow the learners to develop their abilities in English communication. It was organized in four units with the same structure divided into four lessons:  a vocabulary lesson, a grammar lesson, a professional lesson and a case study. It was designed to be taught in 64 hours face-to-face and 4 weekly practical hours. he proposal was created  to ensure the students get the necessary vocabulary and grammar focused on tourism in English linguistic structures and  that they can improve their and  oral  and written expression speaking  as well as them to perform activities related to their field of specialization. As a form of evaluation, the continuous evaluation and final exam were proposed to determine academic progress.
Analisis Kerentanan Blok Bangunan Terhadap Kebakaran di Kecamatan Jebres Kota Surakarta

Jebres Subdistrict is one of the sub-districts in Surakarta City, Central Java, Indonesia.Jebres sub-district is famous for an area that has a high density of buildings. The firedisaster in Jebres Sub-District was recorded in 2017 as having 13 fire incidents and witha loss of Rp 904,500.00. This study aims to, 1) Determine the characteristics of buildingblocks in Jebres Subdistrict, Surakarta City, 2) Know the level of vulnerability of buildingblocks to fire in Jebres Subdistrict, Surakarta City, and 3) Analyze the dominant factorsthat are vulnerable to fire in Jebres Subdistrict, Surakarta City. The method used in thisresearch is spatial analysis using ArcGIS software to explain the level of vulnerabilityand multiple linear regression analysis using SPSS software to explain the dominantfactors affecting fire rates. The results of this study are fire vulnerability maps in JebresSubdistrict consisting of 3 classes, namely low vulnerability, medium vulnerability, andhigh vulnerability. Based on these results the distribution of building block vulnerabilityto fire, for the distribution of low vulnerability has a number of building blocks as manyas 21 building blocks or 3.66%. The average distribution of vulnerability has 433building blocks or 75.56%. While those with high vulnerability have 119 building blocksor 20.76%. Dominant factors that influence the level of fire vulnerability in JebresSubdistrict are Building Density and.
Machine Translation with Cross-lingual Word Embeddings

Learning word embeddings using distributional information is a task that has been studied by many researchers, and a lot of studies are reported in the literature. On the contrary, less studies were done for the case of multiple languages. The idea is to focus on a single representation for a pair of languages such that semantically similar words are closer to one another in the induced representation irrespective of the language. In this way, when data are missing for a particular language, classifiers from another language can be used.
Predicting Solar Irradiance in Singapore

Solar irradiance is the primary input for all solar energy generation systems. The amount of available solar radiation over time under the local weather conditions helps to decide the optimal location, technology and size of a solar energy project. We study the behaviour of incident solar irradiance on the earth's surface using weather sensors. In this paper, we propose a time-series based technique to forecast the solar irradiance values for shorter lead times of upto 15 minutes. Our experiments are conducted in the tropical region viz. Singapore, which receives a large amount of solar irradiance throughout the year. We benchmark our method with two common forecasting techniques, namely persistence model and average model, and we obtain good prediction performance. We report a root mean square of 147 W/m^2 for a lead time of 15 minutes.
RANCANG BANGUN SISTEM INFORMASI PENYEDIAAN AIR MINUM DAN SANITASI BERBASIS MASYARAKAT (PAMSIMAS) DENGAN METODE EXTREME PROGRAMMING

Pamsimas or Penyediaan Air Minum dan Sanitasi Berbasis Masyarakat, is a government program for rural communities that greatly helps the village government to provide water and sanitation needs for society. Therefore the management of Pamsimas becomes very necessary and important. But unfortunately the management of Pamsimas at the village level still uses manual methods. It really requires a lot of time and energy, given the large amount of data that must be managed in Pamsimas. This research has the purpose of creating a digital system that is able to makes management process of Pamsimas more effective and efﬁcient of time, effort and costs, with web base PHP programming language and MySQL database. The development method used in this study is extreme programming method. This method was chosen because it has good feedback or communication between the developer and client. Furthermore this methods whose stages are simple and also more ﬂexible to the changes that occur. The results of this research are a web-based digital information system that could make the process of managing data in Pamsimas more effective and efﬁcient, because this system is able to make reports and calculate bills automatically. So that the previous time spent by many managers becomes less, and because of that the energy spent is more effective.Keywords : Web Application, Information System, PAM System, PAM System Information, Laravel, Extreme Programming.
LibGuides: College Research Literacy Summer 2019: Presenting Research & Conclusion (Week 8) 7/29--8/4

Course content to complete readings, learning activities and quizzes for College Research Literacy Readings, activities, and quizzes to be completed in week eight.
Depth Completion via Deep Basis Fitting

In this paper we consider the task of image-guided depth completion where our system must infer the depth at every pixel of an input image based on the image content and a sparse set of depth measurements. We propose a novel approach that builds upon the strengths of modern deep learning techniques and classical optimization algorithms and significantly improves performance. The proposed method replaces the final $1\times 1$ convolutional layer employed in most depth completion networks with a least squares fitting module which computes weights by fitting the implicit depth bases to the given sparse depth measurements. In addition, we show how our proposed method can be naturally extended to a multi-scale formulation for improved self-supervised training. We demonstrate through extensive experiments on various datasets that our approach achieves consistent improvements over state-of-the-art baseline methods with small computational overhead.
MODEL PEMBELAJARAN COOPERATIVE INTEGRATED READING AND COMPOSITION (CIRC) UNTUK MENINGKATKAN PRESTASI BELAJAR

Implementation of this study aims to determine the improvement of learning achievement of Indonesian students class III Semester II SD No. 3 Abiansemal 2015/2016 Academic Year after applying the Cooperative Integrated Reading And Composition (CIRC) learning model in the learning process. The initial problem that occurs is that the learning process has not been maximized by the teacher in improving student achievement due to the use of the Cooperative Integrated Reading And Composition (CIRC) learning model that still uses a model that is constantly being asked without adequate theory. After the data was collected using tools in the form of student achievement tests from an initial average of 67.38 with learning completeness of 26.92%, increased to 71.81 with learning completeness 57.69% in cycle I and rose to 78.54 with learning completeness 96.15% in cycle II. The results in the second cycle are in line with the expectations of the research success indicators therefore this study is not continued to the next cycle. With the acquisition of these data it can be ascertained that the application of the Cooperative Integrated Reading And Composition (CIRC) learning model method in the implementation of the learning process is able to improve the achievement of students' Indonesian learning so that the proposed hypothesis can be accepted.
Research Guides: Art of STEM Competition & Exhibit: Judging Rubric

Homepage for the Art of STEM Competition at Kelvin Smith Library, Case Western Reserve Library.
Where Design and Implementation Meet

In the previous chapters, you learned all about a chatbot’s design and how Extreme Hiking Holidays designed their Digital Assistant, Travvy. The actual implementation of this Digital Assistant can be done by developers by coding all the flow logic, but Oracle Digital Assistant (ODA) offers a feature that can be used by both business users and designers to set up the initial version of a Digital Assistant after which the developer can take over to finish the implementation. With this feature, the Conversation Designer, you can quickly build a proof of concept for a conversational design concept without any need to code OBotML, nor do you need to create intents or entities. The Conversation Designer allows you to focus on the user experience by setting up a conversation between the bot and a user. After the conversational user experience is created as explained in Chapter 2, the Conversation Designer can be used to create a prototype/mockup of the Skill Bot. From that mockup, the actual Skill Bot can be generated by the click of a button. Then the chatbot can be trained and tested. Figure 4-1 shows where the Conversation Designer fits in the design and development process.
Human Understandable Interpretation of Deep Neural Networks Decisions Using Generative Models

Deep Neural Networks have long been considered black box systems, where their interpretability is a concern when applied in safety critical systems. In this work, a novel approach of interpreting t ...
Peningkatan Hasil Belajar Materi Bangun Datar Menggunakan Papan Berpaku SD Negeri 2 Tlogopucang Tahun Ajaran 2017/2018

The results of preliminary observations at SD Negeri 2 Tlogopucang found problems in learning Mathematics in Flat Build Material. Teachers dominate more and involve students less in the learning process. If we observe the current learning, the teacher has not managed the class well. The teacher has not used the right learning model. Students are less active in learning, the research used is Classroom Action Research which consists of two cycles. In each cycle two meetings were held. Data collection uses observation sheets and by conducting evaluation tests. Data analysis techniques use qualitative and quantitative analysis. The results of the pre-cycle research, the average grade of 61 with a percentage of graduation 50%, students complete learning 8 children, students have not completed 8 children, the percentage of 50%. In cycle 1, it was obtained the average grade of 76, the percentage of completeness 65.75% the number of students who had completed learning 11 children, not yet completed learning a total of 5 children with a percentage of 35.25%. In cycle 2, all students meet the minimum completeness criteria, a percentage of 100% is obtained with an average grade of 96.25. The conclusion is the use of nail board media can improve the learning outcomes of students in class II of SDN 2 Tlogopucang in the academic year 2017/2018.
Output PV power prediction using an artificial neural network in Casablanca, Morocco

Optimal use of renewable energy requires its characterization and prediction to size detectors or estimate the potential of power plants [20-21]. In terms of prediction, electricity suppliers are interested in different horizons to manage power plants and predict their production [1-2]. This paper proposes a model for predicting the output power in photovoltaic (PV) panels installed on the rooftop of the Ben m'sik faculty at Hassan II University, Casablanca, Morocco, and this model is based on a multilayer perceptron (MLP) model. In this work, different combinations of weather variables were used to develop this model and for validate the proposed model results different practical measurement methods are used, such as mean square error (MSE), mean absolute error (MAE), correlation (R) and coefficient of determination (R2). The determination coefficient of the proposed model is 0.98501 with an RMSE value of 30.663. The proposed model was tested on new data, the results showed that the model works with a good preferment and that the prediction quality depends on the time of year with a determination coefficient of 0.9972, 0.9856, 0.9487 and 0.9942 for summer, autumn, winter and spring respectively.
Short-term effect of the demonstration of human dissection and excursion on students´ ideas about the human organ systems: a Slovak experience

Excursions in natural sciences education are justified in the current school system and within the scope of subject focus. The research aimed to observe the immediate impact of demonstration of the human dissection and excursion on the formation of ideas of students about the human body systems.The experiment involved the first Slovak demonstration of a real human autopsy for students of the Biology Teaching Department (PdF TU in Trnava). Concepts of the structure of the human body were analyzed before and after experimental impact by a projective technique. The evaluation included the representation, description, and abundance of organs in the view of various systems. The subject of the research were also the questions focused on the use of illustrative procedures and tools in the educational process.Significant statistical differences were found in the group affected by human autopsy in understanding of the digestive, urinary, and locomotor systems. Conversely, the skin, endocrine glands, and lymphatic system were the least represented by the experimental groups.Considering the presented results, using different organizational forms and aids (real and virtual) is essential for bringing a positive educational effect on the studied problem (Tab. 1, Fig. 5, Ref. 20).
GIS based Emergency Response System for Mandalay

Urban fire plays one of the most important problems that causes disturbing conditions not only for developing countries but also for developed countries. In spite of the modern techniques of fire prevention and suppression, urban fires continue to damage properties and lives. It is required to develop an effective response system on a regional scale to tackle this problem. Therefore, this system intends to establish a system that can identify the best route from any fire incident to the nearest or closest rescue places such as fire emergency services, hospitals, police stations and so on. In this system, GIS-based technology applies for finding the best route by considering traffic data. Both graph theory and network analysis tools in GIS are supplied for modeling and analyzing transportation networks. A transportation network is a valued graph that contains a set of vertices, and edges. To compute the length of the shortest path from the source to each of the remaining points in the graph, the system uses Dijkstra's algorithm. Comparing to other simple shortest route, the algorithm in this system can provide an optimal route that consumes less time but the average speed is higher.
Hybridization of Facial Features and Use of Multi Modal Information for 3D Face Recognition

Despite of achieving good performance in controlled environment, the conventional 3D face recognition systems still encounter problems in handling the large variations in lighting conditions, facial expression and head pose The humans use the hybrid approach to recognize faces and therefore in this proposed method the human face recognition ability is incorporated by combining global and local information to develop a robust face recognition system.In this papers it is proposed that hybridization of global and local facial features and combination of 2D and 3D modality helps in improving performance of face recognition system. The main issue of existing face recognition systems is the high false accept rate which is not desirable when security is the main concern. Most of the existing face recognition techniques overcome these problems with some constraints. However, the proposed methodology has achieved better results and handled all the three issues successfully. Also the use of 2.5D images (Depth Map) and dimensionality reduced data (Eigen faces) has shown that the system is computationally reasonable.
Cluster validity indices for mixture hazards regression models

In the analysis of survival data, the problems of competing risks arise frequently in medical applications where individuals fail from multiple causes. Semiparametric mixture regression models have become a prominent approach in competing risks analysis due to their flexibility and easy interpretation of resultant estimates. The literature presents several semiparametric methods on the estimations for mixture Cox proportional hazards models, but fewer works appear on the determination of the number of model components and the estimation of baseline hazard functions using kernel approaches. These two issues are important because both incorrect number of components and inappropriate baseline functions can lead to insufficient estimates of mixture Cox hazard models. This research thus proposes four validity indices to select the optimal number of model components based on the posterior probabilities and residuals resulting from the application of an EM-based algorithm on a mixture Cox regression model. We also introduce a kernel approach to produce a smooth estimate of the baseline hazard function in a mixture model. The effectiveness and the preference of the proposed cluster indices are demonstrated through a simulation study. An analysis on a prostate cancer dataset illustrates the practical use of the proposed method.
The costs of cyberterrorism for the national economy: United States of America vs Egypt

Abstract In recent years cyber terrorism has become increasingly used with the globalization of technology and people’s access to high-speed internet. It takes place exclusively in the online environment, the advantage being that it offers an increased level of anonymity to users. Terrorist groups are targeting the misappropriation of social media accounts, focused on Distributed Denial of Service activities, exploiting communications services and banking services for fraudulent misappropriation of financial accounts. Cyberterrorism generates very high costs for the national economy, such as the involvement of specialists for detecting and correcting intrusion, declining productivity and income, costs of information theft, regaining the reputation of an institution or company, the costs relating to the resumption of production and the provision of services, the loss of information concerning intellectual property, financial manipulation using stolen information, the cost of securing computer networks and assuring them in the event of intrusion, costs generated by the time spent on recovering stolen data. In 2018 both the US and Egypt took action on these activities, the US modified its national cyber strategy and Egypt adopted the new law project to combat cybercrime. The main cyber threats they face are: threats of intrusion and sabotage of IT infrastructures, cyberterrorism and cyberwar, threats to digital identity and theft of private data, malware programs. The targets of the attacks were public sector entities, financial organizations, health care organizations, retail and accommodation. The reasons for why hackers attack these organizations are money-related, malware infected by emails, commercial and industrial espionage.
Research on Clustering Performance of Sparse Subspace Clustering

Recently, sparse subspace clustering has been a valid tool to deal with high-dimensional data. There are two essential steps in the framework of sparse subspace clustering. One is solving the coefficient matrix of data, and the other is constructing the affinity matrix from the coefficient matrix, which is applied to the spectral clustering. This paper investigates the factors which affect clustering performance from both clustering accuracy and stability of the approaches based on existing algorithms. We select four methods to solve the coefficient matrix and use four different ways to construct a similarity matrix for each coefficient matrix. Then we compare the clustering performance of different combinations on three datasets. The experimental results indicate that both the coefficient matrix and affinity matrix have a huge influence on clustering performance and how to develop a stable and valid algorithm still needs to be studied.
Using Augmented Reality Technology to Construct a Wood Furniture Sampling Platform for Designers and Sample Makers to Narrow the Gap between Judgment and Prototype

The production and design of wood furniture manufacturing includes manufacturing furniture parts and their assembly with appropriate finishing operations; the process requires repeated communication and discussions, as well as furniture sampling and trials, which are indispensable. However, in the sampling process, due to the different understandings of the designer and the sample maker in regard to the size of 2D drawings and the modeling of 3D furniture, the sampling results often differ greatly from the designer’s original concept; such errors appear mostly in the prototyping of wooden furniture. In this study, we focus on the wooden chair to explore whether augmented reality (AR) can contribute to the comparison between the virtual and physical shapes in the furniture prototyping process. We hope that by employing AR, the gap between the prototype and the finished furniture will be narrowed. By researching actual furniture prototyping with three furniture designers and two sample makers, this study has defined three furniture prototyping methods in the industry. Based on the basic principles, we recruited 38 designers to participate in the comparison experiments employing the above three different furniture prototypes. The results confirmed that applying the AR technology can effectively narrow the gap between judgment and prototype.