Reviewerly/exHarmony huggingface dataset:
Aplikasi Pengelolaan Data Arsip Di Kelembagaan Kantor Kecamatan Bojongsoang

Abstrak Aplikasi Pengelolaan Data Arsip di Kelembagaan Kantor Kecamatan Bojongsoang merupakan sebuah aplikasi yang berfungsi untuk melakukan pendataan arsip-arsip yang ada di Kantor Kecamatan Bojongsoang. Tujuan dari dibangunnya aplikasi ini adalah untuk membangun sistem yang dapat memfasilitasi pegawai dalam mengelola data arsip serta mengurangi resiko hilangnya dokumen dan mengefisiensikan waktu dalam melakukan pencarian dokumen sehingga tidak perlu ke tempat penyimpanan dokumen arsip untuk mencari apabila terdapat suatu dokumen arsip yang akan dipinjam. Metode yang digunakan dalam aplikasi ini adalah metode waterfall dengan framework pemrograman CodeIgniter, tools perancangan Unified Modelling Language, serta pengujian aplikasi secara Black Box Testing dan User Acceptance Test. Penelitian yang dilakukan ini diharapkan dapat memudahkan pegawai kecamatan mengatasi masalah-masalah yang terjadi dalam mengelola kearsipan dokumen yang ada. Kata Kunci: Arsip, Arsip Elektronik, Aplikasi, Pengelolaan Arsip. Abstract Application of Data Archive Management in Institutional Office of Bojongsoang Sub-District is an application that serves to collect records in the Bojongsoang District Office. The purpose of the construction of this application is to build a system that can facilitate employees in managing archived data and reduce the risk of document loss and time efficiency in searching documents so there is no need to store archival documents to find if there is an archive document to be borrowed. The method used in this application is the waterfall method with the CodeIgniter programming framework, tools to design the Unified Modeling Language, and application testing in the Black Box Testing and User Acceptance Test. The research carried out is expected to facilitate sub-district employees to overcome the problems that occur in managing existing document archives. Keywords: Archives, Electronic Archives, Applications, Archives Management
Computer Prediction of Adsorption Water Purification Process in Rapid Cone-Shaped Filters

In the paper a mathematical model for computer predicting the process of adsorption purification of water from impurities in rapid filters taking into account changes in the temperature of the filtration flow along the height of the filter while observing the constant filtration rate is formulated. Analgorithm for numerically-asymptotic approximation of solution of the corresponding nonlinear singularly perturbed boundary value problem for a model region of a conical shape, bounded two equipotential surfaces and a surface flow, is developed. The proposed model allows through computer experiments to investigate changes in the characteristics of porous loads (filtration coefficients, active porosity), to predict the optimal variants for using adsorbents, and increasing the duration of the filters operation due to the choice of their shape, taking into account the effect on the process of adsorption purification ofwater not only changes in the filtration rate flow along the height of the filter, but also the temperature.
Discussions on Social Stabilization of a Drone and Expansion of Its Potential - A Focus on Drone Law Enactment Process and Practices by Media, Citizens and Artist

This study examines the problems caused by the process of drones becoming absorbed into society and gaining social acceptance from the perspectives of medium stabilization and the expansion of potential. Two problems caused by drones are the invasion of privacy and the threat to public safety. The key issue related to these problems is whether drones can be regulated by existing aviation laws. The ICAO and FAA intended to regulate drones according to aviation laws by changing the definition of an aircraft to include the concepts of remote communication and wireless control, thereby defining drones as aircrafts. However, changing the legal definition of an aircraft was insufficient because the problems caused by drones originate not only from their operation but also from the cameras mounted onto them. In order to regulate illegal drone shooting, the division between private and public territories and the definition of ownership thereof had to be changed. Moreover, geographical boundaries were converted into technically interpreted boundaries. Attempts to operate drones freely outside of government control continue, and drone journalism is a representative practice. Overturning information asymmetry, drones have achieved positive expansion as a medium that balances the power between individuals and the authorities in the realm of drone journalism. However, although drones are securing their ground as a tool for journalism, they are not free from the conflicts between the value of the freedom of expression and the provision of information and such issues as public safety and privacy. In Trevor Paglen's work, a drone is an automated visual machine that transforms humans, the main agents of image production, into data and objects of surveillance, and separates the sky from the ground as the realm of the surveillant. Hence, the medium of photography is not a tool for the objective recording of the world but is converted into a tool for data collection and interpretation
A Resource-saving Job Monitoring System of High Performance Computing using Parent and Child Process

High performance computing has been more important in the past decade. In the present day, data used for processing becomes enormous. Where a high performance computing resource is needed to help process the data. Some scientific experiments involving big data. Which requires high speed data processing cannot be done by an ordinary computer system. Also, there is a need for support of parallel processing. The solution starts by dividing the job into a number of sections to be processed into parts and the processing unit each processing unit of data at the same time. Then, the system sends the calculated result back to the compiled. This mechanism will speed up the processing time to complete the task and generate more output at the same time. Therefore, a solution in this study is to maximize efficiency when using the resources of the computer which involves the processing power of the processor (CPU Cores).When the HPC system has a large number of concurrent users and requests processing resources that do not match the actual usage. Therefore requires a system to detect job requests that use inefficient computing resources to help users and system administrators to work effectively.
Pengaruh Jurusan, Biaya dan Kualitas terhadap Keputusan Siswa Untuk Masuk SMK Negeri 2 Batanghari

This study aims to determine the Effect of Department, Cost and Quality on Student Decisions to enter Kujuruan Middle School (SMK). This research is descriptive quantitative with the number of respondents as many as 110 people from students of SMK Negeri 2 Batanghari. The analysis used is multiple regression, partial test (t test), simultaneous test (f test), and determination test (R2). The results showed that the most dominant independent variable or a positive influence was the Cost variable (X2) with tcount (10,969)&gt; t table (1,65936). For F Test it is known that Fcount = 101.212&gt; Ftable = 2.69 This means that together the Department, Cost and Quality influence the Student's Decision to enter SMK Negeri 2 Batanghari because the calculated f value of 101.212 is greater than the f table 2.69 (101.212 &gt; 2.69). While seen from the coefficient of determination. Department, Cost and Quality influence the Decision of Students to enter SMK Negeri 2 Batanghari by 73.4% and the remaining 2.66% is influenced by other factors not examined in this study.
Noisy $\ell^{0}$-Sparse Subspace Clustering on Dimensionality Reduced Data

Sparse subspace clustering methods with sparsity induced by $\ell^{0}$-norm, such as $\ell^{0}$-Sparse Subspace Clustering ($\ell^{0}$-SSC)~\citep{YangFJYH16-L0SSC-ijcv}, are demonstrated to be more effective than its $\ell^{1}$ counterpart such as Sparse Subspace Clustering (SSC)~\citep{ElhamifarV13}. However, the theoretical analysis of $\ell^{0}$-SSC is restricted to clean data that lie exactly in subspaces. Real data often suffer from noise and they may lie close to subspaces. In this paper, we show that an optimal solution to the optimization problem of noisy $\ell^{0}$-SSC achieves subspace detection property (SDP), a key element with which data from different subspaces are separated, under deterministic and semi-random model. Our results provide theoretical guarantee on the correctness of noisy $\ell^{0}$-SSC in terms of SDP on noisy data for the first time, which reveals the advantage of noisy $\ell^{0}$-SSC in terms of much less restrictive condition on subspace affinity. In order to improve the efficiency of noisy $\ell^{0}$-SSC, we propose Noisy-DR-$\ell^{0}$-SSC which provably recovers the subspaces on dimensionality reduced data. Noisy-DR-$\ell^{0}$-SSC first projects the data onto a lower dimensional space by random projection, then performs noisy $\ell^{0}$-SSC on the projected data for improved efficiency. Experimental results demonstrate the effectiveness of Noisy-DR-$\ell^{0}$-SSC.
The {\alpha}{\mu} Search Algorithm for the Game of Bridge.

{\alpha}{\mu} is an anytime heuristic search algorithm for incomplete information games that assumes perfect information for the opponents. {\alpha}{\mu} addresses the strategy fusion and non-locality problems encountered by Perfect Information Monte Carlo sampling. In this paper {\alpha}{\mu} is applied to the game of Bridge.
GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors

The lack of large-scale datasets has been a major hindrance to the development of NLP tasks such as spelling correction and grammatical error correction (GEC). As a complementary new resource for these tasks, we present the GitHub Typo Corpus, a large-scale, multilingual dataset of misspellings and grammatical errors along with their corrections harvested from GitHub, a large and popular platform for hosting and sharing git repositories. The dataset, which we have made publicly available, contains more than 350k edits and 65M characters in more than 15 languages, making it the largest dataset of misspellings to date. We also describe our process for filtering true typo edits based on learned classifiers on a small annotated subset, and demonstrate that typo edits can be identified with F1 ~ 0.9 using a very simple classifier with only three features. The detailed analyses of the dataset show that existing spelling correctors merely achieve an F-measure of approx. 0.5, suggesting that the dataset serves as a new, rich source of spelling errors that complement existing datasets.
Framework of Software Testing Based on Cloud Computing

Abstract For the problem that efficiency is low and cost is high existing in the traditional software testing method, this paper tested software using cloud testing technology. It introduced related technologies including cloud testing, and described the design of overall architecture for the system in details, designed and implemented the scheduling module using a high priority first scheduling based on dynamic priority. The MATLAB simulation results are that the total turnaround time of the scheduling algorithm in this paper is short when the same tasks are scheduled and increase slowly when the number of tasks is increased than traditional FCFS. This shows that this scheduling algorithm could reduce test cost and realize the automation of software testing under the condition of significantly improving test efficiency and resource utilization.
KRM-based Dialogue Management

A KRM-based dialogue management (DM) is proposed using to implement human-computer dialogue system in complex scenarios. KRM-based DM has a well description ability and it can ensure the logic of the dialogue process. Then a complex application scenario in the Internet of Things (IOT) industry and a dialogue system implemented based on the KRM-based DM will be introduced, where the system allows enterprise customers to customize topics and adapts corresponding topics in the interaction process with users. The experimental results show that the system can complete the interactive tasks well, and can effectively solve the problems of topic switching, information inheritance between topics, change of dominance.
Fighting Detection Based on Analysis of Individual’s Motion Trajectory

Fighting is a typical malignant event that endangers social security. Video surveillance is a common and effective solution to detect fighting in public places. The conventional method of detecting the fighting events is to analyze the limb movements of each individual in the video. From the theoretical point of view, the conventional approach is more accurate, however, it will be very hard to make it to be practical in a short time. In order to develop a practical system for detecting the fighting events, we put forward an effective method by analyzing the trajectory of each individual instead of analyzing the individual’s limb movement. In our proposed method, the key is to find the different laws of trajectories between normal movements and fighting. There are three basic steps in the proposed method: firstly, MobileNets is used as the basic network model of SSD to extract targets to improve the efficiency and accuracy of individual detection; secondly, KCF algorithm is used to achieve real-time tracking of multi-individual in different behavior modes; thirdly, the extracted motion trajectory is preprocessed and the information entropy of the trajectory is calculated to realize the detection of the fighting behavior. The experiment demonstrates that the proposed method is simple and practical, and can efficiently identify the behavior of fighting in real time.
P4_1 Maximum Power Generation From Solar Panels

Solar panels are a source of renewable energy that become less efficient as they heat up. The intensity of light from the Sun and temperature increases as the distance from it decreases. In this paper, we investigated how to maximise the power generated from a solar panel by moving it closer to the Sun. We determined the ideal distance from the Sun to be 0.258 AU, with a peak power generation of 1450 W.
A face reconstruction method based on fusion regression network and gradient descent

Three-dimensional (3D) face reconstruction refers to the restoration and reconstruction of 3D model of face from one or more two-dimensional (2D) images. It has been widely used in face recognition, expression migration, face editing and other aspects. In the current existing algorithms, there are still many shortcomings in how to reconstruct 3D face by parametric model in real time. In this paper, based on the convolutional neural network, we integrate the weight mask into the loss function, and then use the back propagation algorithm to calculate the parameter gradient error. Finally, the parameter self-renewal purpose of the loss function is achieved by gradient descent. It can be seen from the experimental results that this method can accurately reconstruct the 3D contour of the face, and the reconstruction results are complete and the topological structure is known. This is very important for the application after face reconstruction, such as face changing, expression changing and other aspects of accuracy has been greatly improved.
Data Mining Approaches in the Study of the Nigerian Informal Sector

The vast amounts of economic data currently being generated and collected calls for the application of new methodologies in order to make sense of them.It is for this reason that we have undertaken the analysis of some of data collected on the informal sector of the Nigerian economy using data mining and machine learning techniques.This is different from the traditional bare statistical methods hitherto being used in such analysis.In this work, we used data gathered by the National Salaries, Incomes and Wages Commission (NSIWC) on the informal sector of the Nigerian economy between the year 2014 and 2016.These data were subjected to analysis using WEKA data mining/machine learning tools and the Random Forest ensemble algorithm.The results show that the modal population age group of Nigerians working in the informal sector is in the age bracket of 30-44 years.Similarly, it was discovered that wholesale business is the dominant activity in the informal sector and women's participation in informal sector business is still low compared to their male counterparts.This study shows the relevance or implication of utilizing data mining methodologies over the conventional statistical analysis of data.
Moving Fast and Breaking Things: How to stop crashing more than twice

"Moving fast, and breaking things", instead of "being safe and secure", is the credo of the IT industry. In this paper, we take a look at how we keep falling for the same security issues, and what we can learn from aviation safety to learn building and operating IT systems securely. We find that computer security should adopt the idea of safety. This entails not only building systems that are operating as desired in the presence of an active attacker, but also building them in a way that they remain secure and operational in the presence of any failure. Furthermore, we propose a 'clean slate policy design' to counter the current state of verbose, hardly followed best practices, together with an incident handling and reporting structure similar to that found in aviation safety.
Pengaruh Model Pembelajaran CTL (Contextual Teaching Learning) dan Media Papan Tempel terhadap Hasil Belajar IPA Siswa Kelas IV

Nita Bella Silvia/A510150255. INFLUENCE OF MODEL CTL (CONTEXTUAL TEACHING LEARNING) AND TEMPEL BOARD MEDIA IN STUDENT LEARNING RESULTS IN CLASS IV. Essay, Faculty of Teacher Training and Education. Muhammadiyah University of Surakarta. Agustus 2019Education is essentially a conscious effort made by humans to develop their knowledge and personality. Education has an important role in fostering people who have knowledge and skills. Media learning is an intermediary tool to facilitate the teaching and learning process. Learning model as a guide in planning learning in class. After making observations it can be stated that elementary schools can be seen by teachers using the lecture method, without using models or media. This study aims to determine the effect of the use of the CTL model on the learning outcomes of fourth grade students of SD Negeri Karanganyar 3, to determine the effect of using CTL models and Sticky Media on student learning outcomes of grade IV SD Toyogo 1. The type of research used is quantitative experimental research, by using a one group pretest posttest experimental design. The results of this study are that there is an influence on the use of the CTL Model on the learning outcomes of science students in SD N Karanganyar 3, there is an influence on the use of the CTL Model and Sticky Media on student learning outcomes at SD N Karanganyar 3 and SD N toyogo 1.
Pervasive Data Science and AI

Recent years have seen an explosion in the use of data science and AI as a central tenant in numerous computing applications, products, research, and innovation. Examples of the success of data science abound—applying new machine-learning techniques to problems such as vision and speech recognition and translation has achieved commonplace levels of performance that would have seemed impossible a few years ago. In parallel, developments in pervasive computing increasingly enable us to instrument our physical environment with complex sensors and actuators and create an interconnected world that generates huge volumes of data. The importance of these trends can be seen in the growing momentum of exemplars such as the Internet of Things (IoT), smart environments, and augmented cognition. Pervasive data science is characterized by a focus on the collection, analysis (inference), and use of data (actuation) in pursuit of the vision of ubiquitous computing1 and raises multiple new challenges, demanding new approaches to how we capture, process, and use data in pervasive environments. Beyond the hype, it is clear that our world is becoming increasingly data centric, in which both physical and electronic services depend on the collection, analysis, and application of large volumes of heterogeneous data. In this Special Issue, we present a series of articles that cover different aspects of the exciting work that is currently carried out in this area.
In Memoriam: Brian John Skinner (1928–2019)

Brian John Skinner, professor emeritus in the Yale Department of Geology and Geophysics, passed away on 21 August 2019 at the age of ninety. Brian was a pioneer in mineralogy and economic geology a...
ANALISA KELAYAKAN USAHA MIKRO KECIL DAN MENEGAH (UMKM) UNTUK PRODUK KRASIDA PADA PT. PEGADAIAN MENGGUNAKAN METODE J48.

Currently, in the world of abundant and sustainable data, it can be utilized in data mining in order to better manage the feasibility analysis of Medium-Scale Micro Enterprises (UMKM) for the kraside products at Pt. A more effective pawnshop this research was conducted to utilize existing court ladies as a source of strategic informationfoUMKM In processing UMKM data and classifying the feasibility period for krasidan products to use data mining techniques. The eligibility period for UMKMrecruitment uses the J48 method. the attributes used consist of business groups owned by prospective nassabah, the high or low number of sales in the future is the average needed by UMKM.In this thesis the software used is Weka. Thus the interpretation of the results of the study indicates that the variables that need to be used as considerations are analyzed for the feasibility of UMKM.Keyword : Datamining, UMKM, Krasida, Method J48, Weka
MENYOAL AKSES TERPUSAT ONLINE DATABASE SEBAGAI BASIS KEGIATAN KEILMUAN PERGURUAN TINGGI

As the foundation of university scientific activities, the existence of information resources such as electronic databases is an urgent.There is a discourse about the need not for universities to subscribe to electronic databases independently, but rather to be subscribed by central institutions such as the National Library.This paper is intended to give consideration to the need for centralized electronic database access.With a variety of considerations, the government, through related agencies, should rethink the idea or idea of subscribing to electronic information sources centrally conducted by the ministry or the National Library.
Last year at #ncte18 (welwasn't there) created ...

Last year at #ncte18 (welwasn't there) created an RSS planet of folks blogging through the conference or decide to own their content from their own
Differentially Private Geo-Social Ranking

With the popularity of Geo-Social networks, the combination of social and spatial data facilitates Geo-Social data analyzing. One kind of such analyses is Geo-Social ranking. Given a query location q, the Geo-Social ranking problem is to rank the users in the Geo-Social network, based on their adjacency to q and their influential on their friends. However, the Geo-Social network contains massive privacy information of individuals, such as the relationships between users and the location information of users. Leakage of such information may cause serious impact on users. In this paper, we investigate the problem of privacy preserving Geo-Social ranking, which finishes the ranking task while protecting the social and spatial privacy of users. We solve the problem based on the notion of differential privacy. We define the differential privacy target in Geo-Social ranking and design a ranking algorithm that satisfies differential privacy. We evaluate our approach with real-world dataset to show the efficiency of our algorithm.