Reviewerly/exHarmony huggingface dataset:
Snap-shot fringe pattern enhancement using period-guided bidimensional empirical mode decomposition

We present an automatic, robust and effective algorithm, named period-guided bidimensional empirical mode decomposition, for fringe pattern enhancement. It solves the mode mixing problem and extracts complete fringe term in a single (first) decomposition component.
SQuARE: Semantics-based Question Answering and Reasoning Engine.

Understanding the meaning of a text is a fundamental challenge of natural language (NLU) and from its early days, it has received significant attention through question answering (QA) tasks. We introduce a general semantics-based framework for natural language QA and also describe the SQuARE system, an application of this framework. The framework is based on the denotational semantics approach widely used in programming language research. In our framework, valuation function maps syntax tree of the text to its commonsense meaning represented using basic knowledge primitives (the semantic algebra) coded using answer set programming (ASP). We illustrate an application of this framework by using VerbNet primitives as our semantic algebra and a novel algorithm based on partial tree matching that generates an answer set program that represents the knowledge in the text. A question posed against that text is converted into an ASP query using the same framework and executed using the s(CASP) goal-directed ASP system. Our approach is based purely on (commonsense) reasoning. SQuARE achieves 100% accuracy on all the five datasets of bAbI QA tasks that we have tested. The significance of our work is that, unlike other machine learning based approaches, ours is based on understanding the text and does not require any training. SQuARE can also generate an explanation for an answer while maintaining high accuracy.
Corruption and Debt Hangover: An Empirical Study of sub-Saharan Africa

This paper investigates the determinants of foreign debt for 25 countries in sub-Saharan Africa (SSA). Previous studies have emphasized factors such as oil price shocks, deteriorating terms of trade, rising public expenditures, and trade deficit as the main causes of debt hangover in SSA. This study uses a different approach, and measures the effects of corruption on debt through different regression models, and finds that the corruption index is significant in shaping debt hangover in sub-Saharan Africa. Also, the estimated results indicate that the corruption index plays a more important role compared to other macroeconomic fundamentals. The results also indicate that corruption has become a more significant post financial crisis of 2007 when several African countries faced with a new phase of debt forgiveness. Indeed, the results of this study suggest that debt forgiveness has entrapped SSA countries with more corruption, which has exacerbated the level of debt.
Parent-Child Interaction and Pre-Schooler’s Level of Writing Readiness

Parenting education programmes have been found to promote good parent-child interactions in their households.Consequently, benefits in academic success, proper development of a child, prevention of child maltreatment and child aggression, have been associated with these programs.This article reports findings of the study conducted in Siaya county, Kenya to establish whether parenting education programmes influence writing readiness skills of children.A sample comprising 196 caregivers and their preschool children participated in the study.Questionnaire and learners' writing tests were used to collect data from caregivers and preschool children respectively.To ensure validity of the instruments, content analysis was done.Descriptive statistics including means, standard deviation and percentages were used in summarizing data while Pearson Product Moment correlation coefficient was used to analyse the data with the help of Statistical Package for Social Sciences version 20.The study revealed an existence of a significant relationship between parent-child interactions and level of writing readiness of preschool children.
Crawler Type Autonomous Mobile Robot Platform Which Can Traverse Over Rough Terrain

The crawler type autonomous mobile robot platform that can traverse over rough terrain was developed successfully. The snow remover “Oh! Snow” on the market was utilized as a base vehicle. T-frog motor driver was applied to make easy a system development. Also, the mechanism around a rotary encoder, and the control circuit box were designed and implemented in the robot platform. In the driving experiment on rough terrain in the golf course, it showed that the crawler type mobile robot platform could traverse over rough terrain stably. The crawler type mobile robot platform is useful for the system development of an autonomous mobile robot which can traverse over rough terrain.
Implementasi Pengolahan Citra Digital Pada Penghitungan Anak Burung Puyuh Menerapkan Metode Blob

The process of counting quail chicks on farms using manual method is by moving 2 quail chicks on a cardboard that has been provided continuously until the amount specified. Calculations using this method can take a long time and it could be wrong in the calculation so the calculation must be repeated. Digital image is a picture of an object that is analog in the form of video signals on television monitors, mobile phones or is digital that can be directly stored on a storage medium. Digital imagery can also be used as segmentation, counting, detection, tracking and recognition. In this case the digital image will be able to detect the number of quail chicks through several processes before detecting. By using the morphology of dilation and erosion images, it can be done separating overlapping or close together quails. Detection of quail using the BLOB method, in this case a digital image will be able to detect an object that is either moving or not. Blob or blob detection method is detecting a collection of pixel dots that have different colors (lighter or darker).
Penggunaan Crazy Story Game untuk Meningkatkan Motivasi Mahasiswa Berbicara dalam Bahasa Inggris

Various ways and efforts have provided by Speaking lecturers to increase students’ motivation, especially in Speaking. However, based on a preliminary study, researchers found that students' speaking motivation was still considered insufficient. For that, the researcher applied a game, namely Crazy Story. The purpose of this study was to see how students’ motivation who were taught and not taught using Crazy Story Game and to find out whether there was a significant difference between students’ motivation who were taught and not taught using Crazy Story Game. This research was an experimental research. This type of research was a quasi-experimental study using an unequal group design. This study consisted of two groups, namely experimental and control group. The population of this study were students of the third semester of the English Education Study Program. Two groups (classes) of students consisted of 60 people were taken as samples using cluster random sampling. The two groups of students were both given a questionnaire to see their motivation in speaking before and after implementing Crazy Story Game. The data collection techniques were questionnaire and observation. Questionnaire was used to determine students’ motivation in speaking English. Meanwhile, observation was used to see the learning process of Speaking by using Crazy Story Game. From the research findings, it was obtained that the Speaking Motivation data of students who joined the experimental class increased by 4.75%. Meanwhile, students’ speaking motivation who joined the control class only increased by 0.98%. The result of data analysis from T-test was 2.028. This result was compared with the t table with a df (Degree of Freedom) level of 78, namely 1.99. Because t count t table (2.028 ≥ 1.99) and the significance was (0.046 0.05), H0 was rejected and Ha was accepted. The researcher concluded that there was a significant difference between students’ motivation those who were taught and not taught using Crazy Story Game.
Marketing Indicators and Effective Patronage of the University of Uyo Library

The study investigated marketing indicator and effective patronage of University of Uyo Library in the University of Uyo library.To carry out the study, two objectives, research questions, and hypotheses were formulated.The survey research design was adopted for the study.The population and sample of the study was 62 library staff in the University of Uyo Library using census sampling technique.A researcher developed questionnaire titled Marketing Indicators and Effective Patronage Questionnaire (MIEPQ) was developed to obtain data for the study.Mean and standard deviation was used to answer research questions while independent t-Test was used to test the hypotheses at .05 level of significant.The findings from the study showed that marketing indicator such as resources promotion, public relations and library publicity have significant influence on effective patronage of University of Uyo library resources.The study recommended among other things that the library management should utilize social media in marketing their University of Uyo Library and service to increase user patronage.
Simultaneously determining the frequency sum and time difference of two photons through sum frequency generation

We propose, analyze, and evaluate a technique for the joint measurement of time-frequency entanglement between two photons. In particular, we show that the frequency sum and time difference of two photons could be simultaneously measured through the sum-frequency generation process, without measuring the time or frequency of each individual photon. We demonstrate the usefulness of this technique by using it to design a time-frequency entanglement based continuous variable superdense coding and a quantum illumination protocol. Performance analysis of these two protocols suggests that the joint measurement of strong time-frequency entanglement of non-classical photon pairs can significantly enhance the performance of joint-measurement based quantum communication and metrology protocols.
Klasifikasi profil lulusan berdasarkan tracer study lulusan menggunakan algoritma Naive Bayes Classifier

The graduate profile is the role of the graduate of the study program or field of expertise / field of work planned after completing education from the study program. The determination of the profile of study program graduates is generally carried out based on the results of the assessment of stakeholder needs. Based on data from the Ministry of Research, Technology and Higher Education, the IT study program is one of the most majors or study programs in Indonesian universities and the highest number of enthusiasts choose this study program each year. Each year, graduates of IT study programs have a large number of graduates, both vocational and non-vocational colleges. The number of IT graduates is large but they have low graduate competencies, even they do not have competencies in the IT field so that their work is not in accordance with the graduate profile that has been designed. Therefore, it is necessary to conduct research to classify the profile of graduates who have worked based on tracer study data using the Naive Bayes Classifier method. This study uses attributes, namely study program, value criteria, gender and field of work and the labels used are status (Linear and Non-Linear). The results of the study on the classification of the profile of graduates using the Naive Bayes Classifier method show that alumni work not according to the profile of graduated by 73% and according to the profile of graduates by 23%, with a data accuracy rate of 87% and are included in the good classification category.
Automatic Generation of Training Data for Deep Learning in AR-based Transportation Support System

In this paper, we propose a method that automatically generates training data necessary for construction of deep learning-based model which supports indication of traffic data on augmented reality (AR). In the case of the data indication to road user by AR, there is a risk that important objects are hidden by the data. Thus, locations of the data indication should be adaptively determined. Therefore, accurate determination of the locations which recognizes the important objects via deep learning is expected. However, for deep learning, a large amounts of training data need to be prepared. In our method, the large amount of training data is automatically generated. Therefore, supporting location determination of the data indication via deep learning is realized. Experimental results show the effectiveness of our method.
IS Project Management Success in Developing Countries

The management of Information Systems (IS) projects occupies a prominent place in research given the need for continuously improve projects efficiency and efficacy. In the case of developing countries, this is even more important because projects success rates are typically lower than those of the so-called developed countries. Projects success is vital to development, because the countries not only need to use the scarce resources available in the best possible way, but also must gain trust from populations and investors to continue ensuring financing for future projects. Note that developing countries’ governments many times depend on foreign investment to undertake large projects, for instance in the construction or IS infrastructure sectors. However, there are few known studies about the success of IS projects in developing countries. To help fill this gap, we carried out a questionnaire-based survey in four countries. The focus of our survey was on IS projects from the public sector. This enabled to identify quite low levels of success, as well as an urgent need for training and education programmes on project management.
Big data Classification based on Distributed Fuzzy Decision Trees

Combining decision tree algorithms with fuzzy techniques provide a solution for classifying large amount of uncertain data. However, the time and space complexity remain as an issue. The proposed system is a distributed imple-mentation of fuzzy decision trees based on MapReduce paradigm that classifies large amount of data. This generates fuzzy partitions on each continuous attribute in a distributive manner and these partitions are given as input to the distributed FDT learning step that generates the final fuzzy decision tree model. Gini Index is used as the criteria for selecting attributes on each decision tree node leading to less computation thereby reducing time. The distributed implementation of Fuzzy decision tree is compared with normal fuzzy decision trees and classical decision trees based on accuracy and time complexity. The result of comparison shows that the distributed fuzzy decision trees outperform both classical and fuzzy decision trees by showing greater accuracy and less time.
Just in time delivery: Leveraging operating systems knowledge for better datacenter congestion control

Network links and server CPUs are heavily contended resources in modern datacenters. To keep tail latencies low, datacenter operators drastically overprovision both types of resources today, and there has been significant research into effectively managing network traffic and CPU load. However, all of this work looks at the two resources in isolation. In this paper, we make the observation that, in the datacenter, the allocation of network and CPU resources should be co-designed for the most efficiency and the best response times. For example, while congestion control protocols can prioritize traffic from certain flows, it is wasted work if the traffic arrives at an overloaded server that will only enqueue the request. Likewise, allocating more CPU resources to an application will not improve its performance if network congestion is causing a bottleneck in its requests. This paper explores the potential benefits of such a co-designed resource allocator and considers the recent work in both CPU scheduling and congestion control that is best suited to such a system. We propose a Chimera, a new datacenter OS that integrates a receiver-based congestion control protocol with OS insight into application queues, using the recent Shenango operating system.
THE ORGANIZATIONAL CULTURE OF THE UNIVERSITY AS A FACTOR IN THE FORMATION OF A NEW "INNOVATIVE" PERSONALITY TYPE AMONG RUSSIAN STUDENTS

The article analyzes the content of the concept "innovative personality" of the student from the perspective of its essential characteristics, as well as the impact of the organizational culture of Russian universities on the development of the concept mentioned above. The authors distinguish such basic personality traits of students of this type as: - need for change, skill to get away from the power of traditions, defining development points and social mechanisms appropriate to them; - presence of creativity as a personal quality and creative way of thinking; - ability to find ideas and opportunities for their optimal implementation; - a systematic and prognostic approach to the selection and organization of innovations; - ability to concentrate in a state of uncertainty and define the acceptable degree of risk; - readiness to overcome constantly appearing obstacles; - developed ability to reflection and introspection. The basis for determining the organizational culture of universities was the organizational culture diagnostics method - the OCAI by C. Cameron and R. Quinn. The typology underlying the method identifies four types of culture (or directions of its development) - clan, hierarchical (bureaucratic), market and adhocratic: as a rule, all four types are represented in an organization to varying degrees, but there is always a dominant type. In the most general form, the common profile of the organizational culture of the university, which contributes to the formation of the innovative personality of students, can be represented in the form of a pyramid based on a clan type culture that is consistently supplemented by an adhocratic, market, and then hierarchical culture. Nevertheless, the results of a secondary analysis of self-diagnosis studies of Russian universities, as a rule, show the dominance of the hierarchical (bureaucratic) culture type and the preference for the clan culture type, which does not contribute to the formation of an innovative personality among students. However, the universities` leadership aims at the development of elements of adhocratic and market types.
A Comparative Review of Emerging Wireless Technology

Communication Systems can be Wired or Wireless and the medium used for communication can be Guided or Unguided. In wired technology, communication or transmission of information is done via a medium (also called guided medium) such as co-axial cables, twisted pair cables and optical fiber links; which guides the propagation from one point to another. In wireless technology, communication or transmission of information is done via free space (air) using electromagnetic waves such as radio frequencies, infrared, satellite, and so on, which guides the propagation from one point to another. Data transmission is an unavoidable part of every application or system. This is necessary for additional data processing and evaluation, and different wireless technologies fulfill this purpose. This paper is focused on elements of wireless technology, types, advantage and disadvantage, as well as literature review on various applications and improvements of wireless technology and systems. Additionally, a comparative analysis between the various types of wireless technology based on different aspects and their characteristics was discussed. This paper will serve as a benchmark in wireless technology and use of a particular wireless technology based on the requirement of the application. Word Count: 189
THE EFFECT OF GALLERY WALK STRATEGY ON STUDENTS’ READING COMPREHENSION

The purpose of this research is to determine whether the application of the Gallery Walk Strategy can affect students’ reading abilities. This research was conducted by using Experimental method with quantitative form. The population of this study was students of MADRASAH TSANAWIYAH YASPI LABUHAN class VIII. researcher used Purposive Sampling to the Fifth Class which can be seen from the midterm grades of students in each class. From their results, the researcher decided that students of class VIII-A consisted of 30 students as the Experimental class and Class VIII-B consisted of 30 students as Control Class. This research was conducted in 8 meetings. Experimental class was  taught by using the Gallery Walk Strategy and control class was taught by not using conventional way. The researcher analyzed the data using the t-test, from the results of statistical calculations through SPSS, it was obtained the value of t count (2.990) and the t table value of df (58) at the 0.05 significance level was (2.002).  It means that t count was higher than the value of t table . Based on the results, the alternative hypothesis (H a ) was accepted and the null hypothesis (H o ) was rejected. Therefore, it can  concluded that the Gallery Walk Strategy significantly affects students’ abilities in Reading Comprehension.
Mapping Top Soil Water Content Using Ground Penetrating Radar Imaging

Measurement of water content in materials is needed in various fields, one of which is agriculture. Water content in top soil layer plays an essential role for success rate of agricultural. A method is needed to localization the water content in the top soil for a large area, Gravimetry is one of the method that require a lot of time and expensive to find information of water content in large area. Detection of top soil water content by remote sensing is the method of choice for mapping soil conditions over a large area. Ground Penetrating Radar (GPR) is a method that can be used in the process of Soil water Content. GPR works by transmitting electromagnetic waves into the ground and receiving reflected signals by an objects under the ground level. This thesis proposes to imaging top soil water content information using B-Scan methods. Information the top soil water get form post-processing method proposed the Least Square extraction model, then to imaging in B-scan method for two-dimensional data processing will developed using MATLAB. The GPR system consists of a transmit antenna connected to a signal generator and receive antenna connected to the Low Noise Amplifier that connected to the signal processing unit. In this experiment, GPR system is modelled using Vector Network Analyzer. Through processing B-Scan images will imaging of the area soil water content So that post processing using B-scan imaging on Ground Penetrating Radar will obtain information and mapping soil water content in a more efficient time.The 80 percent experiment was carried out by proving the success of previous studies in detecting top soil water content of 97 percent for scenarios with the distance between the ground and antenna R 35 mc, while for R 30 cm the accuracy in detecting top soil water content was 19.5 percent.The experimental results are not clear for the reconstruction of the B-scan signal because the device used during the experiment is unstable and soil type, setup settings in data collection due to signal transmission and the coupling between the two antennas must be prepared. Keywords: Ground Penetrating Radar, Soil of Water Content, Post-Processing, B-Scan, MATLAB.
On normalized generating sets for generalized quasi-twisted codes over finite fields

Abstract In this short correspondence, we firstly determine the normalized generating set for generalized quasi-twisted codes over finite fields. Then we present an algorithm to construct it. As an application, some optimal or the best-known linear codes are derived from generalized quasi-twisted codes by applying our method.