Reviewerly/exHarmony huggingface dataset:
Building High-Quality Datasets for Information Retrieval Evaluation at a Reduced Cost

Information Retrieval is not any more exclusively about document ranking. Continuously new tasks are proposed on this and sibling fields. With this proliferation of tasks, it becomes crucial to have a cheap way of constructing test collections to evaluate the new developments. Building test collections is time and resource consuming: it requires time to obtain the documents, to define the user needs and it requires the assessors to judge a lot of documents. To reduce the latest, pooling strategies aim to decrease the assessment effort by presenting to the assessors a sample of documents in the corpus with the maximum number of relevant documents in it. In this paper, we propose the preliminary design of different techniques to easily and cheapily build high-quality test collections without the need of having participants systems.
Extended reality in global software delivery: towards a common fabric of understanding and insights

Large IT organizations depend on a global software delivery model which involves large teams with various roles and stakeholders. As software delivery is inherently collaborative, it requires the different roles to share artifacts, knowledge and insights with each other throughout the delivery life-cycle. Typically, each role has different insight and understanding needs, based on her/his context and activities. An architect may need to understand the system from a modularity perspective, a developer from code quality purposes, whereas a tester would need to understand it from a user-triggered flow perspective. However, the way we represent, understand, and collaborate on software artefacts, is still limited by the confines of traditional 2D computer screens. In this paper, we present our early work of an Extended Reality (XR) based approach that leverages affordances of natural human perception to represent and visualize software applications in three dimensions. This immersive approach is aimed at becoming a common fabric across global delivery roles, making activities like application comprehension, architecture analysis, knowledge communication, and analysis of a software's dynamic aspects, more contextual, richer, and intuitive. We posit that the use of XR, specifically augmented/mixed reality-based multidimensional views of different software artefacts, can be adapted to be an intuitive bridge across different roles, and foster a novel way of collaboration (both locally and globally). Here, we present our immersive approach and its prototype implementation, along with examples of its usage by different project roles. We also discuss some early feedback and the way forward.
A FEW REMARKS ON THE METHODOLOGY OF THE HISTORY OF SAFETY RESEARCH

In this article, the author discusses the unanswered subject of the methodology of researching the history of safety. The starting point of his deliberations is the presen-tation of safety issues, the subject of safety history and discussion of the directions and methods of history research indicated in the literature. Next, the author justifies the necessity to start work on the methodology of safety history, then indicates the emer-gence of separate safety subdisciplines such as: safety philosophy, sociology of safety, safety psychology, safety culture. The natural consequence of this development of science, which is safety, should be the introduction of a safety history. An additional argument is the conduct of a subject in this field at Polish universities. In the further part of the article periodical patterns of history are presented. It is intended as a starting point for conducting safety history research. Finally, the author analyses the pos-sibilities of the research.
Discussions on the Strategies for Vitalizing Educational Ministries in Local Church

This paper discussed how to vitalize churches through educational ministries. For this, this paper attempted to show the present situations of Korean church. The statistical resources of Korean Statistical Information Service was cited for comparing the situation of major religion in Korea: Protestant Christianity, Buddhists, and Roman Catholics. From this statistics, it is known the fact that Protestant Christianity became the largest religion among the major religions but the absolute number of Christianity decreased. From this fact, the necessity of vitalizing church and church ministries is suggested. Then the core concepts such as educational ministries and vitalizing were discussed in order to clarify what this paper aims. The necessity of educational ministries provides the warranty of this paper. That is, through this paper it will be emphasized that the educational ministries is the most important factor for vitalizing local churches. And the basis of educational ministries was suggested as the Bible, theology, the principles of education, and the view of man. In the final chapter, Howard Snyder's theory for vitalizing local churches and educational ministries are introduced and discussed. He points out five theological principles such as worship, Church life, healthy balance between worship, fellowship, and evangelism, and building up leadership. With the theological principles, he suggests four practical principles. He points out five theological principles such as worship, Church life, healthy balance between worship, fellowship, and evangelism, and building up leadership. With the theological principles, he suggests four practical principles. Many scholars' views were presented and discussed. And the in this paper, the strategies for vitalizing local churches are suggested in three points such as spiritual worship service, leadership building, and clear vision.
Zero-shot Learning with Many Classes by High-rank Deep Embedding Networks

Zero-shot learning (ZSL) is a recently emerging research topic which aims to build classification models for unseen classes with knowledge from auxiliary seen classes. Though many ZSL works have shown promising results on small-scale datasets by utilizing a bilinear compatibility function, the ZSL performance on large-scale datasets with many classes (say, ImageNet) is still unsatisfactory. We argue that the bilinear compatibility function is a low-rank approximation of the true compatibility function such that it is not expressive enough especially when there are a large number of classes because of the rank limitation. To address this issue, we propose a novel approach, termed as High-rank Deep Embedding Networks (GREEN), for ZSL with many classes. In particular, we propose a feature-dependent mixture of softmaxes as the image-class compatibility function, which is a simple extension of the bilinear compatibility function, but yields much better results. It utilizes a mixture of non-linear transformations with feature-dependent latent variables to approximate the true function in a high-rank way, which makes GREEN more expressive. Experiments on several datasets including ImageNet demonstrate GREEN significantly outperforms the state-of-the-art approaches.
A Picture of Abanded Children in Padang, A Human Interest Radio Feature

Abandoned children is one of the problems faced by Padang city. Many reasons make the number of abanded children still high. Although, the news about abandoned children have been posted in newspaper, magazine even online and social media, but seen that they just inform in partially. Therefore the researchers conducted a project on presenting the data on the picture of abanded children in padang in form of radio feature. It is expected that this radio feature can give useful information about the reason why they “work on the street”, the life that they run everyday. Hence it is hope that it can touch the human care of people and government to find the best solution for them. The data was gotten from the result of interview by using recorder tools. Then Cool Edit Pro 2.1 application was used to edit and mix the voice . Moreover this project applied the stages of making radio feature likes pre-production, production and post-production. The result of thisl project were in form of audio, radio feature with 15 minutes duration, and the English script with 756 word.
PREDIKSI PENJUALAN KOSMETIK DENGAN SUPPORT VECTOR MACHINE

The development of the cosmetics industry experienced a very significant development. Along with the development of cosmetics, information technology has become one of the inputs for the company. Information about the sale of cosmetics and information on cosmetic supplies is an inseparable thing. Cosmetics are products made from plants, minerals and animals. Predictions about future sales can control the amount of available product stock, so that shortages and excess product stock can be minimized. Accurate Prediction results will facilitate the fulfillment of market demand and can provide timely predictions. This research was conducted to predict cosmetic sales. Knowing the supply of cosmetics is something that can be found in cosmetic stores, to facilitate the prediction of cosmetic inventories in the coming period can use sales data in the previous period. Date time series is one of the time series methods used for forecasting methods to find out the pattern of patterns in the past to find out patterns in the future. The Support Vector Machine algorithm will work accurately when the required features are relevant. But inreality the features needed are not relevant, feature selection can be done to select the features needed to obtain accurate information, so as to increase efficiency. In this study the Support Vector Machine algorithm produces the best method, which is 0.136 based on the smallest error value with period 4 variables, Validation Shuffled Sampling 10 and Polynomial kernel type. The best model is also obtained with the Support Vector Machine algorithm with forward selection resulting in the smallest error value of 0.144 with period 8 variables, as well as the Validation Shuffled Sampling 10 and the polynomial kernel type. Keywords : Kosmetik, Data Mining,  Support Vector Machine, feature selection, forward selection
Automatic determination of a speaker’s gender based on the Cauchy distribution in the octave frequency band

Algorithms for recognition of a speaker’s gender based on the use of the Cauchy distribution in the octave frequency band with a geometric mean frequency of 125 Hz are obtained. Classifiers based on the maximum logarithm of the likelihood function are constructed. The algorithm for determining the speaker’s gender is considered, where not only the logarithm of the Cauchy distribution in the octave frequency band is taken into account, but also estimates of the average value of the formant frequencies and the antiformant frequencies. Studies of the probability of correct recognition of the speaker's gender determination algorithms are carried out
Advanced Input and Output

A filehandle is a connection between your script and a “port.” There are four standard filehandles in Perl by default:
Design and Implementation of Real Time and History multi-view IoT trend Display and Control System

The Internet of Things technology has brought a lot of convenience to regional situation monitoring. Facing complex and interrelated monitoring methods, IoT systems need to access a variety of sensor devices. It is necessary to comprehensively display a large number of multi-source heterogeneous sensing data. The existing work can access multi-source heterogeneous sensor devices and display the sensing data of different devices on different visual interfaces. However, the information displayed by the system lacks relevance, and it is difficult to clarify the relationship between different sensor data, and it is impossible to display comprehensive information after merging multi-sensor data. Moreover, there is few work that meet the needs of query and playback of historical data. This paper designs and implements a real-time and historical multi-view IoT trend system to deal with the mentioned problems. Using the target information graph, it displays the relationship between different sensor data, and using the method combined real time and history, it proposes a buffered batch data loading algorithm to form a dual-display mode system. An IoT trend simulation platform based on B/S-MVC-MVVM architecture was built. Based on this platform, multi-source heterogeneous sensor data is accessed. The experimental results show that the system can display the relevance of the information and realize the historical data playback effect.
Investigations on mooring system design for a floating platform in shallow water

Based on the finite water depth Green function, Morison equation and coupled dynamic analysis method, dynamic response analysis was performed for a platform in shallow water with different types of mooring systems.The results show that traditional catenary or taut mooring systems, usually adopted for medium or deep water depth, will encounter a range of problems in very shallow water near islands and reefs, and the room for further optimization is very limited.However, the pile anchor chain hybrid mooring system proposed in this paper can overcome these problems, and at the same time, makes ship docking much more convenient.The analysis results in this paper have certain guiding significance for model tests and further design of mooring systems in very shallow water.
AWARENESS AND USE OF N-LIST E-RESOURCES OF THE SELECT DEGREE COLLEGES AFFILIATED TO PANJAB UNIVERSITY, CHANDIGARH; A COMPARATIVE ANALYSIS

This research paper explains the usage of the N-LIST E-resources among the student and faculty members of the various select Degree Colleges affiliated to Panjab University, Chandigarh. A questionnaire method was used as a tool for collection of data from the 32 select degree colleges in Punjab and Chandigarh. The total data was collected from the 466 out of 513 respondents. The total response rate is 90.84%. Out of 466 respondents, total 286 are users (faculty and student) respondents and 180 are non-users (faculty and student) respondents. The statistical test have been applied and the inferences have been drawn thereof.
EFFECT OF BANK-CHARACTERISTIC AND MACRO-ECONOMIC FACTORS ON LISTED COMMERCIAL BANKS’ PROFITABILITY IN SUB-SAHARAN AFRICA

This study investigated Bank-characteristic and Macro-Economic factors affecting commercial banks’ profitability in Sub Saharan Africa for the period of 2008-2017 using panel data of 56 listed banks drawn from the Sub-Region. Secondary data ex-tracted from the listed Commercial Banks' financial statements were analyzed. The explanatory variables were represented by Credit Risk, Liquidity Risk, Leverage Ratio and Exchange Rate while profitability was represented by Return on Assets (ROA). The study explored a correlational research design to examine the effect of Bank-characteristic and Macro-Economic factors on commercial banks’ profitability. VCE Robust Regressions were employed for the combined banks and country-specific banks’ analysis based on the Hausman Test Specification (fixed and random effects model). Although the Hausman specification test suggested that a fixed effect model is appropriate for the integrated banks’ data analysis, the study used VCE Robust Re-gression to underpin the outcome of the Hausman specification. The study found that Bank-characteristic and macro-economic factors had significantly affected the com-mercial banks' profitability over the study period for the aggregate model of all the banks while only internal factors mainly influenced banks’ profitability for the coun-try-specific banks’ profitability. The Credit Risk had a positive and significant rela-tionship with banks’ profitability while Exchange Rate had a negative and significant relationship with bank profitability during the study period. In controlling foreign exchange rate volatility, Sub-Sahara Africa Clearing Union (SACU) is recommended for Central Banks of member countries to enable them to settle payments for transac-tions within the Sub-region on the basis of multilateral pacts. This will, in turn, reduce the negative effect of an exchange rate increase in the sub-region and subsequently enhance banks’ profitability.
3-5세 누리과정에 기초한 어린이집 프로그램의 안전교육 내용 분석: 아동복지법을 기준으로

Objective: The purpose of this study was to analyze the Nuri-curriculum daycare programs for 3, 4, and 5-year-olds based on the Child Welfare Act.Methods: Data were analyzed according to the analysis criteria for 195 children s safety education programs in the Nuri-Program. The analyzed data used frequency and percentages.Results: First, life safety education was the most important element. And after looking at the contents category of the Child Welfare Act, the results in order are as follows: “raffic safety”; “Health and hygiene management, including the prevention of contagious diseases and drug abuse”; “Safety measures against disasters”; “Precaution and prevention of disappearance and abduction”; and “Prevention of sexual violence and child abuse.” Second, there were many safety education activities in accordance to chronological age (3-to 5-years old). Health and safety by subject, season, and life tools were more frequent. By type of activity, conversation and language activity, fairy tales, and plays were the most common activities.Conclusion/Implications: This suggests the need to systematically plan safety education content through a program that links safety-related laws and elements related to the Nuri curriculum in child care centers.
THE CORRELATION BETWEEN FREQUENCY OF WATCHING ENGLISH MOVIES AND VOCABULARY MASTERY

This study aims to determine whether there is a correlation between frequency of watching English movies and vocabulary mastery of SMAN 1 Bontonompo Selatan Gowa Regency. This study uses the descriptive method. The population of this research was the second grade of SMAN 1 Bontonompo Selatan Gowa Regency. The sample is 20 students by using purposive sampling in one class. In collecting the data, researchers used a questionnaire instrument to look at the frequency of students’ watching movie and vocabulary tests. The results of this study indicated that there is a significant relationship between the level of frequency of watching movies in English and the students' vocabulary mastery. It can be proved through the data and test the value of r-table where the value of r-test (0.358) is lower than r-table (0.444). The researchers concluded that there is a low correlation to the frequency of watching movies in English and the students' vocabulary mastery.
Group binary weight networks

In recent years, quantizing the weights of a deep neural network draws increasing attention in the area of network compression. An efficient and popular way to quantize the weight parameters is to replace a filter with the product of binary values and a real-valued scaling factor. However, the quantization error of such binarization method raises as the number of a filter's parameter increases. To reduce quantization error in existing network binarization methods, we propose group binary weight networks (GBWN), which divides the channels of each filter into groups and every channel in the same group shares the same scaling factor. We binarize the popular network architectures VGG, ResNet and DesneNet, and verify the performance on CIFAR10, CIFAR100, Fashion-MNIST, SVHN and ImageNet datasets. Experiment results show that GBWN achieves considerable accuracy increment compared to recent network binarization methods, including BinaryConnect, Binary Weight Networks and Stochastic Quantization Binary Weight Networks.
LibGuides: Summer Reading Assignment: Freshman

Uponyour returntoschoolinSeptember,yourteacherwillrequireyoutocompleteanassignment based on yourreading,whichwill countforpartofyourfirstmarkingperiodgrade.
Study on evaluation method for 3D perspective image

We described the evaluation method of stereoscopic images by using perspective images with continuity that is easy to feel a depth in 2D images. In this paper, we propose a new 3D evaluation method, using reversed images and an evaluation item of an incongruity. As a result, in terms of the perspective image, we got the effectiveness of the evaluation item “incongruity” in three evaluation items of depth feeling, stereoscopic feeling, incongruity.
The Effect of Using Rountable Technique on Student’S Writing Skill in Arranging Sentences

This research is concerned with applying roundtable technique writing skill in arranging&#x0D; sentences to form simple present tense. The aim of the research is to find out if&#x0D; applying roundtable technique effects on students’ writing skill in arranging sentences.&#x0D; The research is conducted by experimental method. The population of the research&#x0D; is XI students of SMA Swasta Dwi Tunggal Tanjung Morawa in 2018-2019 academic&#x0D; year. The sample consists of 60 students then divided into two groups, 30 students&#x0D; as experimental group and 30 students as control group. The experimental group&#x0D; is taught by applying roundtable technique and the control group without applying&#x0D; roundtable technique. The researcher uses writing test as instrument of the research.&#x0D; The test is answered by multiple choices and arranging sentences about simple present&#x0D; tense.The researcher analyzes the data by using the formula of t-test commonly used.&#x0D; After calculating and analyzing the data, it is concluded that tcalculate is higher than&#x0D; ttable (5,54 &gt; 2,02). It showed that there is a significant difference. The pre test mean&#x0D; score of experimental is 57,16 and post test is 84,5, the difference is 27,34. The value&#x0D; ot tcalculate is bigger than ttable (5,54 &gt; 2,02) degree of freedom is 58, and the level&#x0D; significance is 0,05. The result is that applying roundtable technique gives significant&#x0D; effect on students’ writing skill in arranging sentences simple presentt tense. So, It can&#x0D; concluded from t-test above that the hypothesis of this study is accepted.
Will the Visualization of Internet Affect Languages of Education?

The impact of digitalization on daily activities has become pervasive, even in the Global South. The dominance of colonial languages in education is both strengthened and weakened by latest technologies. The paper asks whether new technologies could bring native language education available to a larger number of children in the world. The great affordances of new technological innovations could be utilized by school systems, and give students tools to enhance their learning. Mobile and visual technologies such as videos and emoji can empower people and give opportunities for wider communication if policies are enacted to support underprivileged people and grassroots activity. However, intensification of research is needed to outline promising futures for education of minorities, disabled and indigenous peoples.
ANALISIS KINERJA ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK MEMPREDIKSI PRESTASI SISWA SEKOLAH MENENGAH KEJURUAN

This research informs students and teachers to anticipate early in following the learning period in order to get maximum learning outcomes. The method used is C4.5 decision tree algorithm and Naïve Bayes algorithm. The purpose of this study was to compare and evaluate the decision tree model C4.5 as the selected algorithm and Naïve Bayes to find out algorithms that have higher accuracy in predicting student achievement. Learning achievement can be measured by the value of report cards. After comparison of the two algorithms, the results of the learning achievement prediction are obtained. The results showed that the Naïve Bayes algorithm had an accuracy value of 95.67% and the AUC value of 0.999 was included in Excellent Clasification, for the C4.5 algorithm the accuracy value was 90.91% and the AUC value of 0.639 was included in the state of Poor Clasification. Thus the Naïve Bayes algorithm can better predict student achievement.