Reviewerly/exHarmony huggingface dataset:
Identifikasi Dampak Penggunaan Sistem Informasi Rumah Sakit (SIRS) Terhadap Pelayanan Kesehatan Menggunakan Hot-Fit Model 2006

Hospital Information System (SIRS) is an integrated information system that aims to handle all hospital management processes, ranging from diagnostic services, medical data measures, medical records, pharmaceuticals, pharmaceutical warehouses, billing, personnel databases, payroll, and accounting to the control management. Based on Indonesian Constitution No. 44 Article 52 year 2009, paragraph 1 states that "Indonesian hospitals are required to record and report all activities that occur within a hospital". On the Indonesia ministry regulation, PERMENKES No. 1171 year of 2011, Article 1 paragraph 1 states that "Each hospital is required to apply SIRS". Therefore Dr. Samratulangi Tondano District Hospital of Minahasa Regency in the North Sulawesi uses SIRS to improve employee performance in providing health services to the community. The paper discussed how to identify the impact of the use of Hospital Information Systems (SIRS) on health services. The purpose of this study is to look at the impact of the use of the SIRS system based on four indicators contained in the 2006 Human Organizational Technology (HOT-Fit) method in addition to the DeLone and McLean Success 2003 methods. By taking 150 respondents of SIRS users randomly, data were collected and analyzed using SPSS and AMOS software.The four hypotheses derived from three components namely "Technology", "Human" and "Organization" have a positive impact and provide a net benefit to the use of the system. In short, the majority of users SIRS only focuses on functions for registration and administration rather than clinical functions. The availability of IT units and IT personnel influences the use of SIRS as well.
THE CORRELATION BETWEEN STUDENTS’ MOTIVATION AND READING COMPREHENSION OF THE FIRST YEAR STUDENTS OF SMPN 1 CISARUA BANDUNG BARAT

The objective of this study is to know the correlation between students’ motivation and their achievement in reading comprehension. The research used quantitative method and correlational research as design. The population of the study was the seventh grade students of Junior High School 1 cisarua, Kabupaten Bandung Barat in academic year 2017/2018 with total number 395 students and the sample in this study is 32 students. Instruments for data collection were the questionnaire to find out students’ motivation and the reading comprehension test. Pearson Product Moment was used to analyze the data and the hypothesis testing was computed by applying SPSS version 22. It was found that there is a significant correlation between students’ motivation and their achievement in reading because the correlation coefficient was 0.658. It was classified into high correlation . Thus, there is a significant correlation between reading motivation and reading motivation. The result can be interpreted that students’ motivation had strong effect to reading comprehension skill. It is suggested the English teachers have to create teaching strategies that will motivate the students to read in class.Keywords: Correlation, students’ motivation, reading, achievement.
PEMANFAATAN MEDIA CERITA PENDEK DALAM MENULIS NASKAH DRAMA SISWA SMP KELAS 8

This study aims to describe the use of short story media in writing  play scripts for 8th grade junior high school students. This research included the process of planning, writing, and editing. The type of this research was classroom action research (CAR) with a two-cycle design. The data in this research were process data and result data. Data collection was done by using observation, field notes, and students' work. The subjects in this study were 39 students. The research results showed that the number of students who achieved the criteria of success in the first cycle was 74.3% and the second cycle increased to 89.7%. The conclusion of this study is that the planning step of the use of short story media in writing play scripts can stimulate the students to be able to develop ideas and imagination to construct a framework. In the process of writing play scripts based on the script planning, the students have been able to develop themes, characters and characterizations, plots, settings, and dialogues. In the editing process, the students have been able to use punctuation, spelling, and the use of capital letters.
Risk Assessment in IT Infrastructure

Due to large-scale digitization of data and information in various application domains, the evolution of ubiquitous computing platforms and the growth and usage of the Internet, industries are moving towards a new era of technology.With this revolution, the IT infrastructure of industries is rapidly undergoing a continuous change.However, the insecure communication channel; intelligent adversaries in and out of the scene; and loopholes in the software and system development add complexity in deployment of the IT infrastructure in place.In addition, the heterogeneous service level requirements from the customers, service providers, users, along with implementation policies in industries add complexity to this problem.Hence, it is necessary to assess the risk associated with the deployment of the IT infrastructure in industries to ensure the security of the assets involved.In this chapter, we present an efficient risk assessment mechanism in IT infrastructure deployment in industries, which ensures a strong security perimeter over the underlying organizational resources.
Widening and Squeezing: Towards Accurate and Efficient QNNs

Quantization neural networks (QNNs) are very attractive to the industry because their extremely cheap calculation and storage overhead, but their performance is still worse than that of networks with full-precision parameters. Most of existing methods aim to enhance performance of QNNs especially binary neural networks by exploiting more effective training techniques. However, we find the representation capability of quantization features is far weaker than full-precision features by experiments. We address this problem by projecting features in original full-precision networks to high-dimensional quantization features. Simultaneously, redundant quantization features will be eliminated in order to avoid unrestricted growth of dimensions for some datasets. Then, a compact quantization neural network but with sufficient representation ability will be established. Experimental results on benchmark datasets demonstrate that the proposed method is able to establish QNNs with much less parameters and calculations but almost the same performance as that of full-precision baseline models, e.g. $29.9\%$ top-1 error of binary ResNet-18 on the ImageNet ILSVRC 2012 dataset.
Engineering Top-Down Weight-Balanced Trees

Weight-balanced trees are a popular form of self-balancing binary search trees. Their popularity is due to desirable guarantees, for example regarding the required work to balance annotated trees.While usual weight-balanced trees perform their balancing operations in a bottom-up fashion after a modification to the tree is completed, there exists a top-down variant which performs these balancing operations during descend. This variant has so far received only little attention. We provide an in-depth analysis and engineering of these top-down weight-balanced trees, demonstrating their superior performance. We also gaining insights into how the balancing parameters necessary for a weight-balanced tree should be chosen — with the surprising observation that it is often beneficial to choose parameters which are not feasible in the sense of the correctness proofs for the rebalancing algorithm.
Data Mining in Programs

Software exists in various control systems, such as security-critical systems and so on. Existing program clustering methods are limited in identifying functional equivalent programs with different syntactic representations. To solve this problem, firstly, a clustering method based on structured metric vectors was proposed to quickly identify structurally similar programs from a large number of existing programs. Next, a clustering method based on similar execution value sequences was proposed, to accurately identify the functional equivalent programs with code variations. This approach has been applied in automatic program repair, to identify sample programs from a large pool of template programs. The average purity value is 0.95576 and the average entropy is 0.15497. This means that the clustering partition is consistent with the expected partition.
A supervised multimodal search re-ranking technique using visual semantics

The multimedia content in a webpage is usually given least importance in webpage ranking. A better user satisfaction could be achieved if the web pages are ranked based on multiple modalities rather than just depending on the textual content. A better ranking of the web pages is proposed using natural language descriptions of images along with the textual content in a webpage is being proposed. The inter-modal correspondences between text and visual data are learned using the convolutional neural network assisted by the datasets of images and their sentence descriptors. The model is based on convolutional neural networks over images to generate the image descriptor and Dandelion API for their similarity measure with the query. The image description is algorithmically generated rather depending on the image annotations present. Finally, it has been proven that the re-ranked web pages using the generated descriptions significantly outperform the state of art retrieval models.
Unsupervised Bilingual Lexicon Induction Across Writing Systems

Recent embedding-based methods in unsupervised bilingual lexicon induction have shown good results, but generally have not leveraged orthographic (spelling) information, which can be helpful for pairs of related languages. This work augments a state-of-the-art method with orthographic features, and extends prior work in this space by proposing methods that can learn and utilize orthographic correspondences even between languages with different scripts. We demonstrate this by experimenting on three language pairs with different scripts and varying degrees of lexical similarity.
PENGARUH PENDIDIKAN KARAKTER KEPANDUAN HIZBUL WATHON TERHADAP PRESTASI BELAJAR SISWA DI SMP MUHAMMADIYAH 7 YOGYAKARTA

Based on the results of simple regression analysis with summary models obtained R = 0.608 or rh = 0.608. It aims to find out the hypothesis rejected or accepted with N = 40 while rt = 0.312 then obtained 0.608 ,3 0.312 from these results it can be concluded that Hα is accepted. So it can be concluded that there is an influence between Hizbul Wathon's Scout Character Education with learning achievement.&#x0D; Regression equation, obtained from the determinant coefficient value R ² = 0.370 with the meaning that the character education of Hizbul Wathan contributed to the learning achievement of 37%. So it can be concluded that learning achievement is influenced by Hizbul Wathan's Character Education by 37% while the remaining 63% is influenced by factors outside this study.&#x0D; The simple regression analysis test results obtained by the regression equation: Y = 46.257 + 0.459 X. Based on the simple regression equation can be obtained a constant (α) of 46.257 with the understanding that if the Character Education Hizbul Wathan (X) or equal to zero (0) then the level of achievement learning (Y) of 46,257 units, the variable Hizbul Wathan Character Education (X) obtained a coefficient value of 0.459 which means that if the value of Hizbul Wathan Character Education (X) increases by one unit then the learning achievement (Y) will increase by 0.459 units.&#x0D; Hypothesis testing is done through testing the significance of the regression coefficient of Hizbul Wathan's Character Education variable. With the hypothesis of Hizbul Wathan's Character Education influencing student achievement. The analysis shows that the regression coefficient is 0.459 with a significance level of α = 5%, then the regression coefficient is significant because ρ = 0,000&gt; 0.05.
Consciousness Technicalization Problem in Philosophical Thought: Origins and Effects

The article is devoted to analysing the bibliography of the problem of technicalization of individual and public consciousness within the framework of the basic trends of philosophical thought of the Early Modern and Modern Periods including materiallism and idealism, psychoanalysis, phenomenology, existentialism, post-structuralism, trans-humanism, etc. in the context of studying the key issues of ontology and civilization evolution. The authors reveal the content of the concept “consciousness technicalization” and trace evolution in philosophical-theoretical understanding of the technicalization problem, from the mechanistic approach where the emphasis is on dominance towards interpreting a wide spectrum of trends and manifestations of technicalization and revealing a potential of technicalization of different spheres, levels and forms of consciousness and psyche. The conclusions are made that the bibliography of the problem basically covers the following issues: tendencies for correlation of technicalization and value relativization processes, fatalistic recognition of their inevitability, considering an average individual as a simulation object of consciousness.
Selecting Quality Broiler Chicken using Data Mining Technique

One of the keys of the Broiler farm is in the initial process of choosing the chicken seeds or known as the day DoC. Some criteria are free special diseases of the mushroom, derived from good quality chicken and so on. The problem is that many electoral processes can make it difficult for farmers and companies to choose good quality broiler chickens. Plus the limited ability of farmers to choose broiler chickens, because they still choose them manually. The research is divided into 3 phases i.e. using AHP to sort the criteria of weights that exist among them the first order free of disease with a weight of 0.207, normal body with a weight of 0.174, weight according to the standard with weights 0.172 and Beyond. While Fuzzy CMeans is used for cluster processes in monitoring the quality level of each chicken nursery process by dividing 3 clusters of cluster 1 as much as 410 breeders (96.70%), a cluster of 2 as many as 12 breeders (2.83%) and cluster 3 as many as 2 farmers (0.47%). The second phase is used by the Decision Tree C 4.5 to process the classification of the selection process whether it enters the category A (good), B (Enough) and C (less). While the third phase is still in development research. The result of this classification process gives the info that the Decision Tree C 4.5 works well marked with a validation accuracy value of about 92.03% with a RoC value of about 0881. This research provides a solution for companies to be able to monitor from 3 parts, they are the inputs, processes and outputs of the farmer's chicken nursery. Contributions for the company are able to reduce losses caused by the fault of the three sections so that the company's profits will increase.
A Primer on Domain Adaptation

Standard supervised machine learning assumes that the distribution of the source samples used to train an algorithm is the same as the one of the target samples on which it is supposed to make predictions. However, as any data scientist will confirm, this is hardly ever the case in practice. The set of statistical and numerical methods that deal with such situations is known as domain adaptation, a field with a long and rich history. The myriad of methods available and the unfortunate lack of a clear and universally accepted terminology can however make the topic rather daunting for the newcomer. Therefore, rather than aiming at completeness, which leads to exhibiting a tedious catalog of methods, this pedagogical review aims at a coherent presentation of four important special cases: (1) prior shift, a situation in which training samples were selected according to their labels without any knowledge of their actual distribution in the target, (2) covariate shift which deals with a situation where training examples were picked according to their features but with some selection bias, (3) concept shift where the dependence of the labels on the features defers between the source and the target, and last but not least (4) subspace mapping which deals with a situation where features in the target have been subjected to an unknown distortion with respect to the source features. In each case we first build an intuition, next we provide the appropriate mathematical framework and eventually we describe a practical application.
IMPROVING ENGLISH SPEAKING ABILITY USING THE SNOWBALL THROWING GAMES TECHNIQUE

Abstract In this study, the researcher used method Classroom Action Research (CAR) to improve the quality of the learning and teaching processes as well as to detect and solving the problems that found in the teaching and learning process. The subjects of this research were the 34 students in SMK Budi Bhakti Utama Padalarang. The researcher used collaborative action research with some English teachers in the school. In this study, the researcher using the instruments interview and questionnaire test to collecting the data. The test that given to students is pre test and also post test in the and of the class or after the students has a treatment. In this result of the study showed the mean score of pretest is 62.02 to 64.00 and post test’s score reached up to 79.00. It is important to describe that there is a significant improvement of the test. Therefore, the criteria of success had been determined. It is crucial to remember that communicative games have contributed and positive impact on teaching and learning process. The communicative games like snowball throwing game expected to enhance students’ motivation and enthusiasm in learning English. Clearly, It gives positive improvement on students’ confidence and their fluency in speaking skill. In short, communivative games can be describing that the strategy of teaching-learning creates good, enjoyable circumstances and reduces the stress level and boredom in learning process. Keywords: Snowball Throwing, Speaking ,Car How to Cite: Last name-1, Initial First and Middle name-1., Last name-2, Initial First and Middle name-2., &amp; Last name-3, Initial First and Middle name-3. (2017). Title Title Title Title. Infinity, X (X), XX-XX.
The Signal Private Group System and Anonymous Credentials Supporting Efficient Verifiable Encryption.

In this paper we present a system for maintaining a membership list of users in a group, designed for use in the Signal Messenger secure messaging app. The goal is to support private groups where membership information is readily available to all group members but hidden from the service provider or anyone outside the group. In the proposed solution, a central server stores the group membership in the form of encrypted entries. Members of the group authenticate to the server in a way that reveals only that they correspond to some encrypted entry, then read and write the encrypted entries. Authentication in our design uses a primitive called a keyed-verification anonymous credential~(KVAC), and we construct a new KVAC scheme based on an algebraic MAC, instantiated in a group G of prime order. The benefit of the new KVAC is that attributes may be elements in G, whereas previous schemes could only support attributes that were integers modulo the order of G. This enables us to encrypt group data using an efficient Elgamal-like encryption scheme, and to prove in zero-knowledge that the encrypted data is certified by a credential. Because encryption, authentication, and the associated proofs of knowledge are all instantiated in G the system is efficient, even for large groups.
From Shakespeare to Li-Bai: Adapting a Sonnet Model to Chinese Poetry

In this paper, we adapt Deep-speare, a joint neural network model for English sonnets, to Chinese poetry. We illustrate characteristics of Chinese quatrain and explain our architecture as well as training and generation procedure, which differs from Shakespeare sonnets in several aspects. We analyse the generated poetry and find that model works well for Chinese poetry, as it can: (1) generate coherent 4-line quatrains of different topics; and (2) capture rhyme automatically (to a certain extent).
Motion Planning With Pose Constraints Based on Direct Projection for Anthropomorphic Manipulators

This paper presents an efficient planning algorithm, called Direct-Projection Rapidly-exploring Random Tree (DP-RRT), to address the motion planning with end-effector pose constraints for anthropomorphic manipulators. The key of this planning problem is to find constraint-satisfying configurations on the constraint manifolds and connect them to generate a collision-free and smooth path. In the previous works, the configurations that satisfy pose constraints are generally calculated by the numerical iteration methods based on Jacobian projection techniques. However, such approaches have many technical challenges, such as joint limits and singularity, many numerical iterations and much computing time. In this work, we propose a Direct Projection method based on the analytic inverse kinematics (IK) that can directly project configurations onto the constraint manifolds instead of the numerical iteration methods. The proposed DP-RRT algorithm combines the Direct Projection method with the Rapidly-exploring Random Tree (RRT) algorithm, where the RRT algorithm is employed to explore the ambient space by growing tree branches, and the Direct Projection method is used to project the tree branches onto the constraint manifolds for constructing a constraint-satisfying path. As the analytic IK solver is used to calculate the constraint-satisfying configurations, the DP-RRT algorithm is characterized by high efficiency and no numerical iteration. Besides, avoiding joint limits and singularity, as well as the smoothness of the end-effector and the joints trajectory are also considered. The effectiveness of the proposed algorithm is demonstrated on the Willow Garage's PR2 simulation platform in a wide range of pose-constrained cases.
Perencanaan Strategi Sistem Informasi Penjualan Menggunakan Pendekatan Togaf Adm (Studi Kasus : Three Sister’s House Of Beauty)

Three Sister’s House Of Beauty is one of the several business located at karangtengah cibadak sukabumi. This Business offers all things about skincare, makeup and fashion for youngest to the oldest especially for a man. In the process business activity, Three Sister's has implement strategic planning, but in this prospect the planning has a missed targeted so that it cannot be realized properly, the problems regarding data collection process of sold product and ordering data for customers sometimes just written, input into Ms.Word and Ms.Excel. In odd moment, Three Sister’s share and promotion product on social media, the community of beauty have every rules if want post on group. So that, Three Sister's House of Beauty must planning of ISand IT strategies to be good business proces in future. The conclusion, strategic planning for implementing Enterprise Architecture is one of the best solutions for supports a business or organization. So with this, the author conducts research with the study of the Togaf ADM to support Sales Information Systems that are integrated, right on target, and support business processes in Three Sisters' House of Beauty.