Reviewerly/exHarmony huggingface dataset:
Perancangan Intelligent Tutoring System Sebagai Upaya Inovatif Pada Pembelajaran Pemrograman Terstruktur

The development of computers and information technology helps develop and provide solutions to problems in other fields, one of which is in the field of education. What must be considered in education is the learning method. Every student has different abilities in understanding the material, one of them is Structured Programming Material. This subject is one of the basic materials that must be understood by students of Engineering and Computers. Seeing the limited meeting some students felt that they did not understand the material. Therefore, learning is needed that is able to help independent learning effectively. The development of science and technology is one of the computer media used in learning today. Intelligent Tutoring System (ITS)  is an interactive application program that implements artificial intelligence methods that can be used as information media and as evaluation media in the learning process. Furthermore, ITS can be used as a tool in independent learning for students. Then the purpose of this study is as a learning solution for students who cannot understand the Structured Programming program. Keywords : Learning, ITS, Structured Programming
A Learning Resource Recommendation Model Based on Fusion of Sequential Information

The accuracy of learning resource recommendation is crucial to realize precise teaching and personalized learning. Recently, deep learning based models have been introduced in recommendations. Due to flexibilities of deep networks, several kinds of architectures have been proposed to tackle different problems recently. With the development of computing power, research on sequence data is increasing, which is one of the most important features for learning user’s interests. In order to improve accuracy of learning resource recommendation, we introduce deep learning and propose a deep sequence-fusion network (DSFN) based on fusion of multiple sequential data which is deemed to be more effective in learning resource recommendation than in other field. We take the self-attention mechanism as the core part to design the auxiliary subnet and the prediction subnet for fusing multiple sequential data. The proposed model works with joint training and detached predicting. When training, the two subnets both work by respectively compressing the sequential data into self-attention mechanism. Then the sequences output by self-attention layer flow through multiple feedforward neural networks to produce expected targets. When predicting, there is only prediction subnet working, it performs joint prediction of multiple sequential information by fusing the vector learned on training. The experimental results show that compared with the traditional user-based collaborative filtering algorithm, the proposed model improves the accuracy and recall rate by 20.5% and 13.6% respectively.
Image Super-Resolution Reconstruction Based on Deep Residual Network

In recent years, image super-resolution reconstruction methods based on convolution neural network have developed rapidly. In order to solve the problems of large amount of computation and long training time caused by increasing the depth and width of the network, this paper proposes an image super-resolution reconstruction model 1 based on deep residual network. The structure of the model is simple, it includes feature extraction block, stacked feature enhancement block and reconstruction block. The feature enhancement block is composed of an enhancement unit and a non-linear unit. The enhancement unit extract different kinds of features through convolution kernels in different paths, and the non-linear unit is responsible for extracting various non-linear features. On this basis, a model 2 is also proposed to add the connection between blocks. The experimental results of four data sets such as Set5 show that the proposed two model can speed up the convergence of the model, enhance the features better, thereby, improving the quality of image reconstruction.
PROBLEMS OF IMPLEMENTATION OF THE THIRD MISSION IN THE TRANSFORMING ROLE OF UNIVERSITIES

The study is devoted to the implementation of the «third mission» of universities, the relevance of which is due to the expansion of traditional functions, tasks and areas of responsibility of education. At the same time, the scientific community lacks a unified approach to understanding the nature, characteristics and forms of the «third mission» and the parameters of its Russian model have not yet been determined. The authors consider this problem through the prism of global challenges facing the system of higher education in Russia, which give universities new meanings and guidelines. The authors include mass characterization, globalization, utilitarianism and commercialization of higher education, innovation, the emergence of the social mission of universities associated with the reproduction of culture, Informatization, leading to the emergence of new forms of communication and organization of the educational process. Having analyzed the main scientific approaches to the definition of the essence, characteristics and directions of the «third mission» by the method of socio-philosophical analysis, the authors determine the positive effects of this activity for universities and regional society. They include the formation of a stable social environment in which it is possible to build long-term development strategies and the University and the region, increasing the attractiveness of the University for students, getting students competencies in demand in the economy and social sphere of the region. At the same time, the region has the opportunity to involve the University in the implementation of its development strategy. The main problems that prevent the introduction of the elements of the «third mission» in the practical work of educational institutions of higher education are identified, and ways to solve them are proposed. Conclusions are drawn about the need for universities to develop strategies for their development, taking into account the global transformation processes, changing needs of society, the peculiarities of interaction with the territorial authorities, the local community and other regional stakeholders.
EnMAP airborne soil Greece campaign 2019

&amp;lt;p&amp;gt;In the frame of the science preparation activities for the upcoming German hyperspectral satellite mission EnMAP, an airborne survey took place in September 2019 with hyperspectral VNIR-SWIR-LWIR data using the HySpex sensor and the newly acquired Hyper-Cam LWIR camera from the GeoResearch Center Potsdam (GFZ) mounted on the airborne platform Cessna-T207A from the Free University Berlin (FUB). Although logistically complex conditions with several teams distributed in different locations, all the sites in central and northern Greece could be successfully acquired under clear sky conditions, and all data could be demilitarized providing 45 flight stripes covering a total area of 300 km&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This abstract is focusing on the Amyntaio soil site in northern Greece, an agricultural area of variable soil composition from carbonate rich to clay/silt content to organic carbon rich fields around the lignite mine south of the area, over which 11 flight stripes could be acquired. The science goals of the Amyntaio soil campaign were: (a) Simulation of hyperspectral satellite imagery and demonstration of the potential of upcoming spaceborne hyperspectral sensors (EnMAP, CHIME) for global soil mapping and monitoring; (b) Large test and validation for existing soil algorithms such as the HYSOMA / ENSOMAP software tools for the prediction of top-soil quantitative surface properties; (c) Data validation and comparison of soil products with recent relevant satellite sensors (e.g. S2, PRISMA, ECOSTRESS); (d) Enlargement of global soil spectral libraries with harmonised standards and testbed for their use as calibration-validation data for soil spectral models.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Simultaneous to the airborne survey, an intensive ground-based campaign took place in the area focusing on the acquisition of soil data, VNIR-SWIR and LWIR in-situ data with field spectroradiometers (PSR+, ASD FieldSpec3, MEMS, Handheld FTIR), fractional vegetation cover with RGB and UAV RGB data, soil moisture, infiltrometer and spectral data in undisturbed soil crust with the SoilPRO device, and Cal-Val data acquisition at the same time than the overflight (Temperature-loggers, ASD VNIR-SWIR, handheld FTIR) over bare soils and black/white thermal targets.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We present the project objectives, selected field, airborne, satellite data, with preliminary analyses that show the high data quality and the potential of multi hyperspectral airborne campaigns as a support for basic science developments and satellite mission preparations. The results represent how more sensor flexibility can bridge the gap from in-situ to satellite scale. Further airborne flights and carefully designed in situ campaigns will allow testing and iterative improvement of new observational modalities for soil monitoring based on the integrated information from satellite platforms with the one provided by in-situ systems on the ground and air.&amp;lt;/p&amp;gt;
An adaptive fractional calculus image denoising algorithm in digital reflection dispensation

Image de-noising has become an important step in digital image processing and removing unwanted noisy from the image is important area of the research. The project assign to generate the noise free images from the noisy images has consider the three objective which are (1) suppression of the noise effectively in uniform regions, (2) preserve edges and other similar image characteristics and (3) provide a visually natural appearance. In this project the hybrid nature of technique is used which include fractional order for determination diffusion coefficients and a residual error term and wavelet transform method for decomposition of images into low and high frequency. The diffusion coefficients can be used effectively for noise removal and the residual error term can help to prevent image distortion. In this project simulated performance of the image de-noising are done using MATLAB and peak signal-to-noise ratio (PSNR), Normalized Cross Correlation (NCC), Normalized Absolute Error (NAE) and Structural Content (SC) are used to evaluate the method.
Time-Aware Models for Software Effort Estimation.

It seems logical to assert that the dynamic nature of software engineering practice would mean that software effort estimation (SEE) modelling should take into account project start and completion dates. That is, we should build models for future projects based only on data from completed projects; and we should prefer data from recent similar projects over data from older similar projects. Research in SEE modelling generally ignores these recommendations. In this study two different model development approaches that take project timing into account are applied to two publicly available datasets and the outcomes are compared to those drawn from three baseline (non-time-aware) models. Our results indicate: that it is feasible to build accurate effort estimation models using project timing information; that the models differ from those built without considering time, in terms of the parameters included and their weightings; and that there is no statistical significance difference as to which of the two model building approaches is superior in terms of accuracy.
해외 인턴십의 현장지향성과 경력개발지원이 고용가능성에 미치는 영향: 글로벌 역량의 매개효과를 중심으로

The purpose of this study is to investigate the relationship among field orientedness and career development support―the traits of overseas internship program, global competencies, and employability of overseas internship program participants. The data used for this study is collected from internees who have participated or are participating in the overseas internship program operated with government’s financial support. To enhance reliability of the results, “Internees” were restricted to those who participating in the internship or working at the same company after the internship as of the survey date.This study found firstly, field orientedness and career development support have positive effect both on internal flexibility and external mobility and therefore positively affect to employability. In addition, it was found that field orientedness was more influential to internal flexibility while career development support has a greater impact in external mobility. Secondly, cross-cultural adaptability and language skills―lower factor of global competency― has positive effect both on internal flexibility and external mobility. Third, among the sub-variables of global competency, language skills have positive effect only on external mobility among the sub-variables of employment possibility, and cross-cultural adaptability has a positive effect both on internal flexibility and external mobility. Forth, global competency has mediating effect on the relationship between career development support and employability but not on the relationship between field oritentedness of the overseas internship and employability.Therefore, it is verified that employability can be increased by the mediating effect of global competency while being positively affected by field orientedness and career development support of overseas internship.Several implications can be drawn from these research results. Firstly, overseas internship need to be expended and more structured as a part of workplace learning, universities also need a global approach to improve students’ employability. Secondly, it is necessary to induce multi-national corporations or companies of host country to participate in the program since internees are less exposed to cross-cultural. Lastly, global competency and employability can be used as important outcome indicator.
DeepSPIN: Deep Structured Prediction for Natural Language Processing

DeepSPIN is a research project funded by the European Research Council (ERC) whose goal is to develop new neural structured prediction methods, models, and algorithms for improving the quality, interpretability, and data-efficiency of natural language processing (NLP) systems, with special emphasis on machine translation and quality estimation applications.
Working with Azure Cognitive Search

I would like congratulate you for starting with the toughest part of learning: starting! The fact that you are reading this book means you have taken the very first step to begin learning. I will ensure that this learning journey of Microsoft Azure AI will be a beneficial one. In this first chapter, I will introduce the recent most powerful service offered by Microsoft Azure for AI with cloud search, Azure Cognitive Search.
Shales Geochemistry within Kolosh Formation (Paleocene – Early Eocene ) in Dokan Region – Northeastern Iraq; Implications for Provenance, Paleoweathering and Tectonic Setting

The study is carried out on twenty shale samples that were collected from the Kolosh Formation (Paleocene – Early Eocene) within the Dokan area at northeastern part of Iraq. The samples were subjected to laboratory studies including chemical analyses for origin rock characterizing source rock composition, paleo-weathering conditions and tectonic. The origin rock compositions were evaluated mainly based on Al2O3/TiO2, TiO2/Zr ratios and a TiO2 and Al2O3bivariate. The result suggest predominantly intermediate igneous source rock of the Kolosh Formation shale’s. The bivariate plot, of (K2O/Na2O) and (SiO2), (MgO+Fe2O3 %) and (TiO2%), as well as the refashion ships based on the elemental components (Co ,Th, Sc, Zr, La) were used to reveal tectonic setting of the depositional basin. All Kolosh Formation shale’s samples were in Oceanic Island Arc. CIA values, bivariate plot of (SiO2%) and (Al2O3+Na2O3+K2O)% and ) (Al2O3- CaO+Na2O- K2O) %compositional space of the shale samples were utilized to infer the chemical maturity and the pale weathering conditions of the Formation. The results shows that Kolosh shale samples represent lower degree of chemical weathering of origine rock which imply semi-arid climatic conditions. .
Research Paper on Chatbot for Student Admission Enquiry

In this research paper, for Student Admission Enquiry we describe about the software/tools used in it. We are using Rasa NLP, we have used dialogflow to make interaction with chatbot and also the NLP toolkit. This chatbot was developed using Machine Learning Algorithms. Chatbots are prepared to change UI design. Chatbots are programs that duplicate human conversation using Artificial Intelligence (AI). It is proposed to be an authoritative modest assistant, delight reason, helping one to complete tasks running from tending to questions, getting driving heading, turning up the indoor controller in sharp home, to playing one's favored tunes etc. Chatbots are exhibited on various techniques, for instance, data base, AI based. Artificial intelligence based chatbots yields progressively reasonable results. Chatbot which gives responses reliant on the setting of conversation will when all is said in done be all the more simple to utilize. One of the noteworthy goals in the field of Human Computer Interaction (HCI) is the diagram of common and instinctive affiliation modalities. In any case, chatbots are at present being grasped at a high rate on PC talk stages. The advancement at the focal point of the climb of the discussion bot is ordinary language processing. Most business chatbots are dependent on stages made by the development mammoths for their standard language dealing with. These fuse Amazon Lex, Microsoft Cognitive Services, Google Cloud Natural Language API, Facebook DeepText, and IBM Watson. Stages where chatbots are passed on join Facebook Messenger, Skype, and Slack, among various others.
Public Service Motivation and Job Performance: An Exploratory Study in Jordanian Municipalities

This paper studies how public service motivation (PSM) among employees influences their job performance (JP) in the context of Jordanian municipalities. The quantitative descriptive cross-sectional approach was adopted with a structured questionnaire. Employees operating in the municipalities of Amman and Irbid-Jordan were targeted as a population and the sample included (382) respondents. SPSS and structural equation modelling (SEM) through AMOS was applied, the results reported that PSM dimensions achieved R2 = 45% of the variance in job performance. Two dimensions of PSM were not significant in influencing job performance, namely, attraction to policy making and self-sacrifice. Following the results, implications were provided, moreover, limitations and directions for future researches were also provided.
Target Project 1

In the previous chapter, you have learned about the Twitter Bootstrap grid system. In this chapter, you will develop a web page that has a navigation bar fixed at the top as seen in Figure 3-1.
Sparse Representation for Face Recognition Based on Projective Dictionary Pair Learning

In order to improve the recognition rate and speed of face recognition, the paper proposes a sparse representation for face recognition algorithm based on Gabor feature and projective dictionary pair learning. Firstly, we extract the local feature of the face image at multiple scales and orientations by using Gabor transform, in that Gabor feature shows significant robustness to the variations in expression, illumination and angle. And the augmented Gabor feature reduced dimension by principle component analysis can be obtained to form a new training data instead of original training sample. Secondly, a synthesis dictionary with reconstructing capability and an analysis dictionary with the capability of quickly obtaining representation coefficients are learned jointly during the training phase. Finally, the face is identified by the reconstructed error. The experimental results on ORL, extended YaleB, AR and CMU-PIE face database show that our proposed algorithm not only get a high recognition rate but also improve recognition speed efficiently.
The Hunters of New Sounds

DIY musical instrument building culture in Finland has its predecessors in folk culture, classical music, experimental music, underground culture, engineering, sculpture art, and workshop and leisure activities. In the past, people often built their own instruments if music instruments were not available for sale, if these were too expensive, or if they wanted to experiment and invent a new instrument. The chapter focuses on the early history of self-built electronic musical instruments and how DIY activity developed from the early years until the 1960s when radical change occurred in music, both technically and aesthetically.
INTEGRATED ENGLISH PHONOLOGY CONTEXTUAL-BASED IN TEACHING SPEAKING FOR GENERAL PURPOSES AT ENGLISH PROGRAM OF JAMBI UNIVERSITY: Integrated English phonology

This action research was aimed to describe on how was teaching speaking for general purpose by integrating English phonology contextual-based. This action research carried out by the lecturers through cyclical action in order to overcome teaching cases occurred in the classroom. This research was divided into two cycles. Each cycle consisted of four meetings. Each cycle used four phases. They were planning, action, observation and reflection. At the planning phase, the researchers made the research plan. At action phase, the researchers did teaching based on lesson plan that has been formulated. Furthermore, the work reflected to see the strengths and weaknesses as a reference for the next plan. The subject of the research was students of English program. The numbers of the subject of this research were twenty five students of English program. The data were obtained by doing observation and test. In observation, researchers looked at students’ attitude in speaking. Tests were conducted to determine the student's skill in speaking. Based on the data analysis, it’s found that the percentage level of students’ speaking performance increased from the first cycle to the second cycle, and students were motivated to be more active in speaking activity. In the first cycle, seven students were in the category of a very high level of understanding and very active, on the second cycle increased to 14 students are at a very high level of understanding and very high activity. This percentage of improvement increased 28% from the first cycle to the second cycle. Activeness of students in the learning process will lead to high interaction between students and lecturers or between students and colleagues. It could be concluded that the integrated English phonology contextual-based in speaking for general purpose can enhance student performance in speaking and the activeness in learning.
Deduplication Adapted CaseDB for Edge Computing

Log-structured merge-tree (LSM-tree) family key-value stores are becoming the databases most in demand for big data systems. They provide an easy-to-implement interface, and they automatically perform garbage collection by applying a compaction procedure over the multilevel structure. CaseDB offers various advantages by reducing write amplification considerably, using a metadata compaction technique. However, it suffers from a space amplification problem in update-intensive workloads. As an implementation of the LSM-tree structure, CaseDB refuses to instantly perform deletes, but delays them for the compaction process, resulting in an increasing amount of deprecated data. This paper proposes a deduplication extended compaction method for CaseDB. It scans for duplicated keys within the compaction method and removes the old values. Experiment results show that the proposed technique offers various threshold values of deduplication for different balances between space amplification and write amplification.