Reviewerly/exHarmony huggingface dataset:
Research on the Development Needs of Young Postgraduate Tutors in Colleges and Universities in the New Era

Young postgraduate tutors of the colleges and universities is a potential for the future development of the school strength, at the same time they also shoulder the important task of leading generation of postgraduate innovation, therefore, to understand the needs of the development of young postgraduate tutors cultivate their positive work attitude and good work ability, improve their comfort level for the work, and strengthen the focus on their health of body and mind development, is the only way for school development and progress. In this paper, the development needs of young postgraduate tutors in universities and colleges are understood through questionnaires, and corresponding suggestions are put forward, in order to enhance their happiness in work, and contribute to the growth of faculty and the construction of "double first-class".
An Augmented Reality-based Application

Abstract: This paper is the art of applying 3D design and to implement the computer-generated 3D environment to our real- world environment using the latest augmented reality (AR) technology for entertainment or for educational or experimental purposes. Through this project we want to design and build an application and a game which helps to augment the computer-simulated environment into our real-world and which is a very latest and fastest growing technology nowadays where a user can experience the 3D computer-generated simulated world or a virtual world implemented on our real environment. It offers a wide range of proven and established 3D tools for application development and computer-generated from the concept of augmented reality to launch into our real environment. In this project we have used the Augmented Reality concept and uses Vuforia platform which is a very popular among the AR applications and also is very compatible to use and works on selected Samsung‘s smartphones as in Galaxy S6, S6 Edge, S7, S7 Edge and in few note series, Xiaomi Redmi 3S, Google Pixel, Motorola Moto G4, Xiaomi Redmi Note 3 (Snapdragon), etc. Also, Unity Game Engine has been used which is a very popular and have very effective rendering facilities and have detailed in its designing games and building an Augmented Reality application. To have a user a good experience of Augmented Reality we have used self-made our college 3D model which gives a full architectural view of the building in our real-life environment and a designed a game which help to understand AR more effectively. By using not only Unity 3D but Maya 3D has also used for designing 3D models. This project helps to show the knowledge behind Augmented Reality and real-life viewing experience by designing the AR compatible application and game. Keywords: Augmented reality (AR), three-dimension (3D), VR (virtual reality), game, image, computer-generated imagery (CGI) Cite this Article: Ankit Kumar. An Augmented Reality-based Application. Current Trends in Information Technology. 2019; 9(3): 14–39p.
Interactive Detection of Potential Occupational Hazard Signals

Disproportionality based methods are widely used in detecting occupational hazard signals. Yet, deciding on a proper background is hard because there are subgroups vulnerable to given exposures, and in many cases such subgroups can not be defined by job. This paper presents an interactive way to do disproportionality analysis on occupational health examination data. It firstly uses multi-dimensional scaling to project data from a subspace to a two-dimensional space, which is further divided into rectangle cells. Then each cell is served as a background to evaluate disproportionality for potential hazard record(PHR), which is jointly defined by a cell and a company. The PHRs with high disproportionalities are checked interactively to select interesting ones. The method has been used to analyse an occupational hearing loss data, and has found an interesting potential signal for further analysis.
Developing New and Innovative Apps that Will Lead to a Possibility of Significant Revenue

The increase in the mobile usage has increased in the past 5 years drastically. Therefore, there is a need to have a mobile application along with the website for proper growth of any company, institution, business and to reach their height of success. Mobile apps are essential as they provide functionalities that can serve useful purpose such as finding a location or booking movie tickets online. In this article, a case study of an Upload App has been discussed along with overall methods of developing the app. Also, the challenges are being compared that are faced while developing an app successfully. Here work has been done on android studio platform that's suits best for app development.
Impact of Corruption on Banking Sector Stability: Evidence from Middle East and North African Countries

This paper focuses on the effect of corruption on the stability of conventional interest and Islamic free interest banks in MENA states using post crisis age (2008-2016). Adopting system Generalized Method of Moments (GMM) condition to estimate the model. The analysis reveals that a higher control of corruption has a positive impact on the stability of the Islamic banking sector and is related to less bank credit loss. It further highlights that conventional banks benefited from corruption practices to attain their level of stability. Implementing rigorous.
Handwritten Odia Numerals Recognition: A Supervised Learning Perspective

Handwritten recognition is a challenging task in the area of pattern recognition and machine learning. Challenges arise due to variability observed in style, shape, and structure associated with individual writings. In this paper, we have made an attempt to compare four different feature extractions cum classifier schemes for handwritten Odia numeral recognition on the basis of recognition accuracy and computational time. It is found that single decision tree is better in terms of computational time whereas Support Vector Machine (SVM) is better in terms of recognition accuracy.
Webcam Based Eye Gaze Prediction System with Automatic Calibration for Web Browser

Now a day, researches about Eye Gaze Prediction Systems with General Webcam was interested by many researchers and has been continuously developed because it is cheap and can be applied in many ways. Currently, a Browser based open source library for eye gaze prediction has been developed, which is easy to use and can be developed in a variety fields. However, this method is still limited because of low precision and inconveniences because users must perform calibration every time before use it. Therefore, we propose ways to develop and solve the above problems. This research has two objectives. The first is to improve the accuracy of an existing Eye Gaze Prediction System. The solution is using the Simple Moving Average to reduce the volatile of results and increase accuracy. From a results, this method gives a test scores higher than the existing method with statistically significant at 0.01, calculated as 14.96 percent increase from average score of the old method. The second objective is to propose a solution for making the system can recalibrate itself to improve accuracy in a long time without having to perform calibration by the users. We record the gaze data from system in the first 1 minute and then take the recorded data to calculate the boundary of the screen. And then, compare the calculated boundary with the real screen boundary to find error factors. This calculated error factor has been applied back to the next result to increase accuracy. From the test results, we found that over time the average test scores gradually increase. And at the last minute, the average score from this method is higher than the average score from traditional method up to 13.66 percent.
Forkmon: Monitoring the Networks Supporting Bitcoin Hard Forks

The following topics are dealt with: storage management; cloud computing; decision making; peer-to-peer computing; distributed databases; cryptocurrencies; distributed processing; cryptography; data privacy; data mining.
Seismology as an elective subject in elementary school

The purpose of the master's thesis is to find out whether the basic concepts related to earthquakes are appropriate to address in an elementary school setting, namely elective content covered in Physics. In the introductory part of the thesis, we explain the basic seismological concepts that we aim to familiarize the students with, then we present a two-hour workshop that we developed and tested for the purpose of this master's thesis. The first part of the workshop is designed to familiarize students with the effects of earthquakes and the EMS (European Macroseismic Scale). The students use authentic reports of real earthquakes. In the second part, calculations are made from real seismological data and the epicenter of the earthquake is determined. By comparing the exams completed by students before and after the workshop, we assess the students' acquired knowledge and understanding of the seismological concepts introduced.
On Solving Classes of Differential Equations with Applications

Given the difficultly of applying the methods of variation of parameters and undetermined coefficients for many classes of differential equations and inspiration of the role of the Linear Differential Operators to solve classes of Differential equations. In this paper, we introduce the nested factorization technique for solving classes of Differential equations using the basic differentiation and integration approach. Numerical examples with encouraging results have been presented to illustrate the efficiency of the method.
Using Feature Spatial Order in Progressive Image Feature Matching

Image feature matching is a very important and fundamental task in computer vision. In this paper, a spatial-order based progressive feature matching framework is proposed. With the model of spatial order, the searching space is partitioned into many intervals with each interval associated with a probability that a correct match is occurred in this interval. Using this information, many incorrect features could be filtered out and only the survived features are passed for subsequent matching. As the features are progressively matched, the model of spatial order is also progressively updated and the lengths of partitioned intervals are further shortened to filter out more features. To demonstrate the feasibility of proposed system, a series of experiments were conducted. A standard benchmark image data set was used to test the proposed system and the results showed that the proposed framework can indeed produce more efficient and accurate feature matching compared with traditional brute force technique.
Sulci characterization to predict progression from mild cognitive impairment to Alzheimer's disease

Patients who develop Alzheimer’s disease (AD) have passed through a prodromal stage called mild cognitive impairment (MCI) but, not every MCI patient will develop AD. Structural magnetic resonance imaging (MRI) has the potential to capture the differences between the groups of MCI: patients who converted to dementia due to AD (MCIc) and those who remained stable (MCInc). Sulci and folding structures are affected due to the neurodegenerarive nature of AD. A characterization method for these structures is proposed by performing a multi-spherical mapping and a curvelet decomposition at different levels of the brain. 829 MCI subjects from the ADNI initiative were studied at 24, 36 and 60 months of conversion. A random forest classification model was used to validate the methodology achieving an AUC = 0.77 with high-dimensional feature vectors and AUC = 0.70 when 5% of the features are selected. This suggests discriminating differences in sulci and gyri depth between non-converters and converters to AD.
Rassegna bibliografica: didattica innovativa per l'insegnamento delle letterature di lingua inglese nella scuola secondaria di secondo grado

DOI: 10.17456/SIMPLE-145 Bibliografia De Luca, Barbara et al. 1982. Language in Literature . Torino: Loescher. De Luca, Barbara et al . 1993. Views of Literature. Text, Context and Film . Torino: Loescher. De Luca, Barbara et al . 1997. Literature and Beyond. Film Music and Art . Torino: Loescher. De Luca, Barbara et al. 1999. Fast Lane . Torino: Loescher. De Luca, Barbara et al. 2000. Literature and Beyond. American Writers and Themes . Torino: Loescher. De Luca, Barbara et al. 2001. Books and Bookmarks . A Modular Approach to Literature . Torino: Loescher. De Luca, Barbara et al. 2003. Barbara De Luca & P. Pace eds. Books and Bookmarks. The Context. A Historical and Literary Companion . Torino: Loescher. De Luca, Barbara et al. 2005. Literature in Time . Torino: Loescher. De Luca, Barbara et al. 2006. Words that Speak . Torino: Loescher. Ellis, Deborah J. & Barbara De Luca. 2017. White Spaces. Culture, literature and languages . To- rino: Loescher Ellis, Deborah J. & Barbara De Luca. 2018. Making Space for Culture. White Spaces Compact Edition. Torino: Loescher. Ellis, Deborah J. 2010. Literature for Life . Torino: Loescher. Ellis, Deborah J. 2012. Literature for Life. Light . Torino: Loescher.
Define the Scope and Identify Learner Characteristics Computer Based Test (CBT) for Junior High School Students in Makassar

AbstractThis research aims to develop computer based test (CBT) application for junior high school students in the city of Makassar in effort to resolve various obstacles in the implementation of Computer-based National Test (UNBK)and as a simulation media of the test implementation for junior high school students. The model of development used was interactive multimedia model and design developed by Stephen M. Alessi and Stanley R. Trollip through steps of planning, design, and development. At the stage planning, there were some steps to conduct, including define the scope and identify learner characteristics. The research subject was junior high school students in Makassar city. Technique of data collection was by using questionnaire, interviews guidelines, and documentation, and then the data was analyzed with qualitative descriptive design. Results of the scope of the Computer Based Test (CBT) application development research was limited to the level of junior high school (SMP) in Makassar, while the identification of user characteristics includes mental characteristics and readiness for using the CBT application. Students at this stage enjoyed experimenting and exploring, andworking tendencies in groups, while the readiness is that one hundred percent students were able to use computers and even had internet devices they use every day. In addition, on average students use computers more than thirty minutes a day using mobile devices.Keywords: Computer-based test (CBT), Computer-based National Test (UNBK), Junior High School
Displaying Labeled Quantitative Data

Abstract The information world is full of labeled quantitative data, in which a number of qualitative categories are to be compared based on a quantitative variable. Their graphical representations are various and serve different audiences and purposes. Based on a simple data set and its different visualizations, we will play with the data and their visual representation. We will use well-known charts, such as a regular table, a bar plot, and a word cloud; less-know, such as Cleveland’s dot plot, a fan plot, and a text-table; and new ones, constructed for the very aim of this essay, such as a labeled rectangle plot and a ruler-like graph. Our discussion will not aim to choose the best graph but rather to show the different faces of visualizing labeled quantitative data. I hope to convince the readers that it is always worth spending a minute on pondering how to present their data.
Online feature selection for multi-label classification in multi-objective optimization framework

The current paper addresses the online feature selection problem in multi-label classification framework where multi-labelled data with features arriving in an online fashion is considered as input. The proposed approach works in two phases, in the first phase, the best subset of features is selected from the initial available set of features using a multi-objective optimization (MOO) based feature selection technique. In the second phase of the proposed feature selection technique, a newly arrived feature is accepted or rejected based on redundancy with respect to the already selected set of features and relevancy of the arrived feature with respect to the class labels. In order to show the efficacy of the proposed algorithm, it is tested on 7 various types of multi-label datasets of different domains such as text, biology, and audio. The obtained results outperform the results obtained by state-of-the-art approaches in majority of the cases.
IMPLEMENTASI DATA MINING DALAM MEMPREDIKSI TRANSAKSI PENJUALAN MENGGUNAKAN ALGORITMA APRIORI (STUDI KASUS : PT.ARMA ANUGERAH ABADI CABANG SEI RAMPAH)

Data mining is a operation that involves collecting and using data to find patterns or relationships from large data sets. Data mining has been implemented in various fields, one of which is in the sale of bakery products. The company can find out the buyer's interest by using data mining to process data on sales of bakery products. This study discusses information retrieval from bread sales transaction data using data mining with a priori algorithms. Apriori algorithm is a type of association rule (Association rules) in determining the combination pattern of item set and association rules at PT. Arma Anugerah Abadi Sei Rampah Branch, namely with the highest value of support and confidence are the Chocolate Cheese Wrap Bread and the Pres coconut Wrap Bread with a support value of 17% and a confidence value of 77%.
Data Mining Techniques for the Analysis and Prediction in Bioenergy Yield

Unconstructed data mining is challenging task in current data mining research domain. Important information than text since it widely used and content very rich information, such as experiment results and parameters setting. This paper examines the large number of tables that existed in the bioenergy field and propose a framework for automatically acquiring data from papers in PDF format and outputs the table information. To evaluate the performance of our automatic data acquiring method, we compare four existing software. 110 tables have been used for evaluation and the final overall score of our method is 90.54 which shows our method has the best performance in terms of position accuracy. This result demonstrates that our approach is promising and scalable. This work also provides a foundation of data processing for bioenergy.
Mesure du degré d’intégration financière internationale des pays de la CEDEAO : Une analyse du paradoxe de Feldstein et Horioka (1980)

This paper investigates the Feldstein–Horioka coefficients for 13 ECOWAS countries using the recently developed Augmented Mean Group (AMG) estimator over the period of 1975 to 2014. AMG methodology incorporates the issues of endogeneity, heterogeneity and cross-sectional dependence. Furthermore, we also investigate the role of several other macroeconomic factors, Balance trade, inflation, credit and population growth, to improve the international capital mobility. The results show high value of saving retention coefficient (0,76), signifying high association between domestic savings and domestic investment and hence a slow capital mobility or financial integration in ECOWAS countries.
Damaged video reconstruction using inpainting

The process of repairing the damaged areas or removing any desired part of a video is called Video Inpainting. A powerful image inpainting algorithm along with a regeneration technique used to deal with those types of problems for reconstructing missing parts of a video sequence. Many techniques were available for video inpainting, but most of them are computationally intensive and fail to repair the damaged areas. To overcome this, we proposed the background registration method which is exemplar-based image inpainting method. This method uses frames to be replaced with the damaged frame. Here, we proposed a new fuzzy set of the exemplar-based method and use the fuzzy window to improve the replacing of most similar frame.
Research on Measures to Improve the Effect of Teacher Training

Teachers' comprehensive quality is the core factor to determine the quality of teaching. Training is one of the important ways to improve teachers' comprehensive quality. To ensure the effect of teacher training is the key to improve teachers' comprehensive quality. Through the analysis of the problems existing in the current teacher training process, this paper puts forward three measures to ensure the effectiveness of teacher training: teachers who have not completed the corresponding training tasks, teachers who have not participated in the training have not shared the training results with other teachers, and teachers who have not participated in the training have not been inspired. It provides effective measures to improve the effect of teacher training
The problem of effective deployment architecture in SOA

Service Oriented Architecture is popular in many organizations. In particular, it has already deeply rooted in large corporations that need to automate entire business processes and implement them in many systems. It has a unique feature that allows unambiguously indicate service that is to realise business process step. That indication is possible to show directly in BPMN diagram. Thus, it is possible to trace which server has used resources to implement the service and how much of those resources were needed. Therefore, it is possible to build an optimization task that, with limited and unreliable resources, will determine such allocation of components to servers and such an algorithm for assigning tasks to them, so that the processes will work as well as possible. The article presents a model of such an optimization task. This model consists of four layers. The Organization Layer describes the system environment – the types and frequency of initiating business process instances. The Integration Layer describes the business processes and indicates the services that should be performed at every step. The Component Layer describes component characteristics and what services they provide. In Server Layer both: server characteristics and runtime environments necessary for the component to run are described. Finally, the optimization task and evaluation criteria are formulated.
Research on Financial Fraud Forecasting Recognition Based on Machine Learning

This paper collects and pre-processes the financial statements of listed companies from the official website of the China Securities Regulatory Commission, Shanghai Stock Exchange and Shenzhen Stock Exchange, and then uses Logistic Regression, SVM, Decision Tree, Random Forest, Adaboost and XGBoost to built predictive models of 150 fraud companies and 523 non fraud companies of similar asset sizes.