Reviewerly/exHarmony huggingface dataset:
Visualizing Semantic Analysis of Text Data with Time and Importance through an Interactive Exploratory System

The main purpose of this visualization is for developing a visualization system to help users navigate their text data so that users can easily identify the main topics of data. In addition, the visualization system allows users to set options, such as text data processing pipelines, or provides proper interactions, giving them more flexible and diverse user experience of viewing data.
How to Write and Get Published: A Practical Guide for Librarians

"How to Write and Get Published: A Practical Guide for Librarians." Technical Services Quarterly, 37(2), pp. 210–211
An Analysis on Characteristics of Negative Association Rules

Association rules are one of the data and web mining techniques which aim to discover the frequent patterns among itemsets in a transactional database. Frequent patterns and correlation between itemsets in datasets and databases are extracted by these interesting rules. The association rules are positive or negative, and each has its own specific characteristics and definitions. The mentioned algorithms of the discovery of association rules are always facing challenges, including the extraction of only positive rules, while negative rules in databases are also important for a manager’s decision making. Also, the threshold level for support and confidence criteria is always manual with trial and error by the user and the proper place or the characteristics of datasets is not clear for these rules. This research analyses the behavior of the negative association rules based on trial and error. After analyzing the available algorithms, the most efficient algorithm is implemented and then the negative rules are extracted. This test repeats on several standard datasets to evaluate the behavior of the negative rules. The analyses of the achieved outputs reveal that some of the interesting patterns are detected by the negative rules, while the positive rules could not detect such helpful rules. This study emphasizes that extracting only positive rules for covering association rules is not enough.
A Time-Based bi-Objective Virtual Machine Placement Algorithm in Cloud Computing Platform

As the user's task arrives randomly in cloud computing platform, the system resource state and the task resource requirements are dynamic as well. Most of the existing scheduling algorithms are static so that they have low flexibility and energy efficiency. On the basis of the problems mentioned above, firstly, the task request dynamic simulation model was established by sampling Gaussian model of CPU and RAM, which could describe the tasks with different resource requirements and real-time changes. Based on the established model, to construct the virtual machine(VM) placement model under multi-constraints and bi-objective, the time-based genetic algorithm(T-Gene) was proposed, which introduced temporal dimension into the genetic algorithm. In order to get better performance on dynamic scheduling, fitness function was designed with the power consumption and the number of physical machines(PMs). Finally, comparing T-Gene algorithm with First Fit Descending(FFD), Random and Genetic Algorithm(GA), the power consumption decreased by 16.6% at most, the number of PMs used was reduced by 14.50% maximally. The results indicated that T-Gene algorithm can better resolve the configuration problem of virtual machines(VMs) under dynamically changing tasks.
Influence of Personality-based Features for Dialogue Generation in Computational Narratives

In this paper, we present an approach for generating dialogues for characters within the context of computational narrativesusing personality-based features for deep neural networks. The approach integrates the requirements of both narrative genres and personality traits for the definition of character-based stylistic models.The modelling of characters’ features from existing datasets of complete stories permits the generation of personality-rich character dialogues. We present early results from an evaluation based on a sample of characters’ personality traits across different narrative genres,demonstrating variability in the resulting dialogues
Word Orders of Korean Adnominals.

The purpose of this study is to define the relative word orders of Korean adnominals. In order to accomplish this aim, I subclassify adnominals into nominal-adnominals and predicative-adnominals at first, then into the traditional subclassifications as demonstrative, numeric and attributive adnominals. I argue that my subclassification gives more accurate explanations for some exceptional word order problems among many adnominals which are not solved till now. That is, while nominal-adnominals have relatively fixed syntactic positions as demonstratives - numerics - attributives respectably in their order, predicative-adnominals are not the same as that. Some predicative-adnominals observe the relative word order, but others do not. They are free in their syntactic positions, and these kinds of adnominals also show peculiar syntactic behaves which are not mentioned till now. That is, they can be conjugated with adjectives, be replaced by proform, and be modified by adverbs. These extraordinary phenomena are explained also.
Investigating the Methods of Management in Education with Taking the Case of a Teacher at the Stage of University

The paper reveals the problem of the professional formation of a future teacher, training a teacher with a high intellectual level of self-awareness, being capable of conceptual thinking, creativity and being ready to independently managing one’s own professional activity, which will allow interacting more effectively with the learning environment, being an active subject of professional and pedagogical activity.
The Relationship Between Faculty Members' Perception of Emotional Blackmail and their Organizational Trust in Jordanian Universities

Purpose - this study aimed to determine the faculty members' perception of emotional blackmail (EB) and relationship to organizational trust (OT) in Jordanian Universities.Research Methodology - A quantitative approach used a correlational design with a convenience a random sample of a total of 289 faculty members in public Jordanian universities. EB Scale with three subscales; fear, obligation and guilt, with 25 items, and OT with a total of 12 items used in this study.Findings - the results revealed that participants perceived EB and OT at medium level. No significant differences in EB level according to participants' gender and college. There are significant differences in EB level according to teaching experiences in favour to less five years, 5-10 years, and more than 20 years. There are significant differences in EB level according to academic rank variables in favour to associate and assistant professors. No significant differences in OT level perceived according to participants' gender, college and teaching experience, while there are significant differences in OT level perceived according to participants' academic rank in favour to associate, assistant, and tutor. There is a negative correlation between EB, and OT perceive by faculty members.Practical implications - the researchers recommended that the Jordanian universities should pay attention to the (EB) and (OT) in their universities.Originality/ Value - This study is important for several reasons. EB influences the OT at any given organization, specifically universities. The findings of this study will contribute to the knowledge of EB and OT, revealing strategies that will help leaders establish organizational trust among faculty members.
Pengaruh Pendekatan Realistic Mathematics Education terhadap Hasil Belajar Matematika

This study aims to determine the positive and significant influence of the RME approach on mathematics learning outcomes. This study uses a type of experimental research with research designs non-equivalent group control design. The population of this study was fourth grade students of SDN 1 Mulyosari. The study was determined by  purposive sampling. The results of the study showed that the average N-Gain value in the experimental class was 0.55 (medium category). While the average N-Gain value in the control class is 0.35 (medium category). The results of the study concluded that there were positive and significant effects indicated by the calculation of the value of the posttest of the experimental class and the control class with the value of t count > t table that is 2.59> 2.00 (with α = 0.05). Penelitian ini bertujuan untuk mengetahui pengaruh positif dan signifikan pendekatan RME terhadap hasil belajar matematika. Penelitian ini menggunakan jenis penelitian eksperimen dengan desain penelitian non-equivalent control grup design. Populasi penelitian ini adalah siswa kelas IV SDN 1 Mulyosari. Penelitian ditentukan dengan  sampling purposive. Hasil penelitian diperoleh  nilai rata-rata N-Gain pada kelas eksperimen sebesar 0,55 (kategori sedang). Sedangkan nilai rata-rata N-Gain pada kelas kontrol sebesar 0,35 (kategori sedang). Hasil penelitian menyimpulkan terdapat pengaruh yang positif dan signifikan ditunjukan dengan perhitungan nilai posttest kelas eksperimen dan kelas kontrol dengan nilai thitung > ttabel yaitu 2,59 > 2,00 (dengan α = 0,05). Kata kunci : hasil belajar, matematika, RME.
IMPLEMENTASI TATA KELOLA TEKNOLOGI INFORMASI MENGGUNAKAN FRAMEWORK COBIT 5 PADA DIREKTORAT JENDERAL BEA DAN CUKAI

Directorate General of Customs and Excise needs a breakthrough by using audit to manage information technology around it. Managing information technology are urgently needed for Directorate General of Customs and Excise in order to correct the past mistake, improve, and evaluate itself. The method that we were used to measure capability level in this study are COBIT 5 framework which develope by ISACA. This COBIT 5 focused on Deliver, Service, and Support (DSS) which cover Services, Security Management, Continuity, Services Support for Stakeholders, Data Management, and Operational Facility. This study are based on qualitative research and data sample. Data sample gained by doing survey on selective respondents whis is first hand user who involve at managing information technology process. The research indicate that the level of capability DJBC at domains DSS is 2.09, which means still at the level 2 (managed process), it means that the process has been implemented regularly, there is planning and monitored. So, it needed recommendation the target level to be achieved level 3 with by improving the documentation of the processes manage information technology and compile requirements, classification, and prioritization in service delivery and incident handling
Blockchain Based Data Structure for Travel Entourage Tracking System

Blockchain has attracted many people from various industry as the expectation is it can address several computing issues especially in decentralized environment. However, the blockchain technology has yet to be fully understood where implementations such as in the area of travel entourage tracking has yet to be fully considered. This paper will look at blockchain implementations in various fields and look at the requirements for implementation in travel entourage system. Based on evaluations, it is shown that blockchain has the potential to be implemented for travel entourage system.
Sistem Informasi Pendataan Pasien Jamkesda Pada Puskesmas Aras Kabu Kecamatan Beringin

Information on the data collection of JamKesDa Aras Kabu patients that has been done using Ms.word, even then it is only the creation of the copy, while for the data input is still done by writing in a book, thus causing considerable time to obtain the desired information and also less effective in archival storage. The problem faced in handling patient information systems is the length of data collection because it still uses a system that is not adequate. Therefore the author tries to design a new system that is expected to help in reducing existing problems so far. In this study the authors used a computerization of the Kabu Aras Health Center by using the Visual Basic 2008 programming language as an interface, Mysql for the database and and Crystal Report for reporting and are expected to be an alternative for adjusting the data collection problems of JamKesDa patients in the Aras PusKesMas Aras Kabu.
Research Guides: Coronavirus & Library Resources: Need Help?

A guide to help you with the shift to online classes. Featuring: news, information, library & educational resources
A Study on the Numerical Analysis Classes Using the Flipped Learning Teaching Method

The purpose of this study is to cultivate talented people with integrated and creative thinking during the fourth industrial revolution. The existing traditional lecture teaching-learning method have various problems that the dropout rates of the student is high and the creative problem solving ability is hindered. In particular, there is a limit to the practical application based on the theory. In the case of engineering school, it is necessary to apply effective teaching methods to increase students" participation and academic achievement because most of them need to apply to actual software based on theory. In this paper, we proposed a new teaching method that uses the advantages of flip learning to increase students" learning motivation and self-directed learning. Also, this study analyzes the learning effect by applying it to the numerical analysis class of the engineering class and suggests the problem and application method based on the result.
Anthropogenic Disturbance by Domestic Extraction of Gold Mining in Mongolia

Mining, husbandry, and construction activities are consuming a large amount of natural resources. These processes have multiple impacts on the environment, including the excavation of large areas. This research focuses on gold mining in Mongolia, and aims (1) to identify the gold mining activities and allocated them on a map, and (2) to quantify the material flows related to gold mining. Statistical datasets, sourced by the Mineral Resources of Mongolia and the National Statistical Office of Mongolia, were used to account for domestic extraction. Two methods were used for mapping mining activities: firstly, the degraded areas were identified through a geographic information system (GIS) software; secondly, the domestic extraction of gold mining was estimated by the standardized method of material flow accounting. Results indicate the Mongolian gold mining activities exploited 9,812 ha of land across 18 different provinces. In addition, 745,300 m3 of soil was excavated to produce 132 tons of gold in 2007-2017. Particularly, during this period 100.8 tonnes of green gold was extracted which means the gold extraction that does not include any chemical process and just washing soil to obtain gold. "Green Gold" is recognized as less environmental impact by the European market.
High speed roughness measurement on blank silicon wafers using wave front phase imaging

In this paper we introduce a new metrology technique for measuring wafer geometry on silicon wafers. Wave Front Phase Imaging (WFPI) has high lateral resolution and is sensitive enough to measure roughness on a silicon wafer by simply acquiring a single image snapshot of the entire wafer. WFPI is achieved by measuring the reflected light intensity from monochromatic uncoherent light at two different planes along the optical path with the same field of view. We show that the lateral resolution in the current system is 24μm though it can be pushed to less than 5μm by simply adding more pixels to the image sensor. Also, we show that the amplitude resolution limit is 0.3nm. A 2-inch wafer was measured while laying on a flat sample holder and the roughness was revealed by applying a double Gaussian high pass filter to the global topography data. The same 2-inch wafer was also placed on a simulated robotic handler arm, and we show that even if gravity was causing extra bow on the wafer, the same roughness was still being revealed at the same resolution after a high pass filter was applied to the global wafer geometry data.
Penerapan Strategi Poster Session Pada Materi Kerucut Siswa Kelas VIII SMPN 2 Ndona

The purpose of this study was to improve student learning outcomes using the Poster Session strategy. Based on observations made by researchers in class VIII before the study, it was found that the lack of activity of students and many students who had not achieved learning outcomes according to the minimal completeness criteria was 60. The reason is that students are not actively involved by the teacher in learning process. Efforts to solve this learning problem the author uses the Poster Session strategy. The level of success is viewed from 3 aspects, namely student learning completeness which is examined from the results of the cycle I and II tests, observation of teacher activities and student activities. Based on the results of the analysis after the implementation of the study, the researchers found that all student learning completeness in the first cycle was 48% and in the second cycle was 95% so there was an increase in student learning outcomes by 47%.  Observers' observations on the activities of students in learning cycle I were 57% and in cycle II 90% so there was an increase of 33%. Observer observation results on the first cycle teacher activities were obtained at 52.62% and in the second cycle it was 94.78% so that an increase of 42.16%
Learning to Recognise Objects and Actions for Intelligent Agents

Author(s): Agarwal, Nakul | Advisor(s): Yang, Ming-Hsuan | Abstract: Computer vision involves a host of tasks, such as boundary detection, semantic segmentation, surface estimation, object detection, image classification, action localization, to name a few. For a holistic understanding of a scene, which is required by a lot of real-world applications, many of these tasks need to be combined together. For instance, an autonomous car should not only be able to detect other cars (object) but also if a pedestrian is walking (action). The former requires localizing the object, which can either be at the pixel level or bounding box level. The latter requires localizing the action, and by extension the actor, in both space and time. These problems are best dealt with approaches involving supervised learning models which rely on large annotated datasets, and so the problem becomes even more challenging when there is lack of labeled data.In this thesis, we first tackle the problem of spatio-temporal action localization in an unsupervised setting. As the name suggests, it requires modeling of both spatial and temporal features. So, we propose an end-to-end learning framework for an adaptation method which aligns both spatial and temporal features and conduct experiments on the action localization task. To highlight the potential benefits for autonomous cars, we also construct and benchmark a new dataset which contains pedestrian actions collected in driving scenes. Then, for a holistic understanding of the scene, we shift our attention from localizing actions to recognising objects especially in a city street scenario. We do this by jointly dealing with the tasks of object detection and semantic segmentation. While the former localizes the individual instances of objects at the bounding box level, the latter provides pixel level distinction but at the category level. We explore a novel observation that connects the two tasks and provide an end-to-end learning framework to exploit this connection.
Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks

Verifying real-world programs often requires inferring loop invariants with nonlinear constraints. This is especially true in programs that perform many numerical operations, such as control systems for avionics or industrial plants. Recently, data-driven methods for loop invariant inference have shown promise, especially on linear loop invariants. However, applying data-driven inference to nonlinear loop invariants is challenging due to the large numbers of and large magnitudes of high-order terms, the potential for overfitting on a small number of samples, and the large space of possible nonlinear inequality bounds. In this paper, we introduce a new neural architecture for general SMT learning, the Gated Continuous Logic Network (G-CLN), and apply it to nonlinear loop invariant learning. G-CLNs extend the Continuous Logic Network (CLN) architecture with gating units and dropout, which allow the model to robustly learn general invariants over large numbers of terms. To address overfitting that arises from finite program sampling, we introduce fractional sampling—a sound relaxation of loop semantics to continuous functions that facilitates unbounded sampling on the real domain. We additionally design a new CLN activation function, the Piecewise Biased Quadratic Unit (PBQU), for naturally learning tight inequality bounds. We incorporate these methods into a nonlinear loop invariant inference system that can learn general nonlinear loop invariants. We evaluate our system on a benchmark of nonlinear loop invariants and show it solves 26 out of 27 problems, 3 more than prior work, with an average runtime of 53.3 seconds. We further demonstrate the generic learning ability of G-CLNs by solving all 124 problems in the linear Code2Inv benchmark. We also perform a quantitative stability evaluation and show G-CLNs have a convergence rate of 97.5% on quadratic problems, a 39.2% improvement over CLN models.
Perancangan Sistem Informasi Pelayanan Klinik Citra Utama Berbasis Web Dengan Metode Extreme Programming

Information development is very fast due to technological advances is one of the most important factors in data processing. Citra Utama Clinic is one of the clinics in the 7 Ulu area of Palembang. Citra Clinic provides a variety of health services. To provide maximum service, a health service information system is needed. This research develops an information system for image clinical services using the Extreme Programming method. This research has produced an information system that can help the health service process and has been tested with black box testing techniques.
A Study on Effective Data Acquisition of Writer's Works Analysis Using Web Crawling: Focusing on Korean Novelists ‘Kim Young-ha and Park Min-kyu’

People generally utilize internet searching as a mean of the obtainment of information before using any other searching method. However, the amount of data on the Internet is ginormous so that it is almost impossible to check them all manually at the same time there is a wide gap between the level and the reliability of the data. This paper began to solve the above-mentioned issues and proposed the method to collect and refine reliable information from the Internet using web crawling technology literary research. This research conducted the web crawling using a specified keyword based on Korean writer and collect the concerned data from the internet newspapers that guarantee minimum reliability. Nouns extracted from the collected data through the process and sorted by frequency. Nouns with a high frequency mean that they are highly related to the author so that they can utilize as basic data to decide the direction for research concerned writers