Miracle-dz/UniFAR-FTUs huggingface dataset:
Enterprise Risk Management and Firm Performance Empirical evidence from Vietnam

Enterprise risk management (ERM) has emerged as a new model for managing a complex portfolio of risks. Firms are reluctant to adopt ERM because of the difficulty in quantifying the value side of ERM implementation. Our research draws attention to the performance and value effects of ERM implementation in emerging economies using the case of Vietnam. The paper contributes to the current literature on risk management which is intertwined with management accounting. Though Vietnam had experienced rapid economic growth through massive privatization and inflow of Foreign Direct Investments (FDI), this growth had slowed down in 2009. As with other emerging/transition economies, Vietnam is yet to strengthen its institutional capacity (e.g. legal & market infrastructure) to support its economic expansion. In this study, we test whether firms in Vietnam have proper ERM practices, and that the listed firms could implement at an enterprise level and whether this implementation provides an effective means of improving firm performance and firm value. Our results show strong empirical evidence for the benefits of effective ERM implementation in Vietnam. However, for some firms, ERM implementation has become a costly exercise and has a negative impact on performance.
Meteorological Drought Prediction in Karoon Watershed using Meteorological Variables

The drought prediction, its severity and occurrence time are among important issues of meteorology and hydrology researchers. In this respect, the importance of weather and meteorological variables for estimating the drought severity is important for researchers. In this research by using variables such as air temperature and geopotential height in various layers of atmosphere, the relation between these variables in 31 years was investigated by standardized precipitation index (SPI) as regional drought index in Karoon watershed. After estimating average precipitation by statistical index of mutual information of pointmeteorological variables that have a stronger relation with SPI profile in investigated area, meteorological variables were selected as suitable variables. Then along with prediction of regional drought class SPI, the support vector machine (SVM) was used as one of statistical learning methods. The results showed that this method is suitable for prediction of drought occurrence. Also by location searching for relation between meteorological variables and target values, the best combination of variables was selected and in most of cases this prediction with a suitable precision is applicable for real usages. The prediction precision in autumn and winter was higher than other seasons.
Research plan : Software Quality in Education Procedures , didactics , and tools

One of the aims of education in the field of software engineering is to teach students to value software quality. We would like students to be able to evaluate software with respect to quality, we would like them to be able to produce software with quality, and we would like them to know how to optimize software quality. Software quality is composed of characteristics of the software; those characteristics can be categorized according to the standard software quality framework [10]. We discern three ways to produce and guarantee software quality:
SUPPORT RENEWABLE ENERGY INTEGRATION

High integration of intermittent renewable energy sources (RES), in particular wind power, has created complexities in power system operations. On the other hand, large fleets of Electric Vehicles (EVs) are expected to have great impact on electricity consumption, and uncoordinated charging process will add load uncertainty and further complicate the grid scheduling. In this paper, we propose a smart charging approach that uses the flexibility of EV owners to absorb the fluctuations in the output of RES in a vehicle-to-grid (V2G) setup. We propose an optimal scheduling algorithm for charge/discharge of aggregated EV fleets to maximize the integration of wind generation as well as minimize the charging cost for EV owners. Challenges for people participation in V2G, such as battery degradation and feeling insecure for unexpected events, are also addressed. We first formulate a static model using mixed-integer quadratic programming (MIQP) with multi-objective optimization assuming that every parameter of the model is known a day ahead of scheduling. Subsequently, we formulate a dynamic (dis)charging schedule after EVs arrive into the system with updated information about EV availabilities, wind generation forecast, and energy price in real-time, using rolling-horizon optimization. Simulations using a group of 100 EVs in a micro-grid with wind as primary resource demonstrate significant increase in wind utilization and reduction in charging cost compared to uncontrolled charging scenario.
Design and Empirical Analysis Visualization Motion And Vector Analysis Program As Interactive Multimedia Physics Learning at Senior High School, Pekanbaru, Indonesia

This research aims to design and empirical analysis visualization and vector analyze program as Interactive Multimedia physics Learning topics Regular Circular Motion for senior high school (SMA). Multimedia have designed by implementing Research and Development (R & D) type. Use design instructional design ADDIE Model techniques (ADDIE Model ID), Development using Macromedia Flash with Regular Circular Motion matter physics include aspects of design, pedagogical aspects, aspects of content and programming aspects. Validation includes expert judgment and empirical validity and reliablity by expert users, namely teachers, senior high school physics and limited test against senior high school students. Description analysis results show that interactive media is valid with a score of 3.8 judgment expert Likert scale or r = 0.76. While the results of the empirical analysis shows interactive media is valid with r = 0.89 and reliable with Alpha Cronbach alpha (? = 0.87) From the analysis of the study, obtained visualization and vector analyze program as Interactive Multimedia physics Learning as a medium of learning physics on senior high school students are valid and reliable.
STUDENTS’ ORAL AND WRITTEN FEEDBACKSON STUDENTS’ WRITING QUALITYAT ONE OF PRE-INTERMEDIATE WRITING CLASS

As a key stage in writing process, peer feedback plays a very important role in writing. It has been proven to be an effective way to improve students’ writing. This study examines the result of students’ essay before and after being given oral and written feedback in one of pre-intermediate writing class of Lampung University. The researcher discusses which type of feedback results in better writing quality. This study used descriptive qualitative. Firstly, in order to find out whether or not there is difference between before and after on students’ oral and written feedback in students’ writing quality. Secondly, to find out which type of feedback results in better writing quality improvement. In collecting data the researcher used document analysis (essay). The researcher analyzed the data by the other ways, namely, students’ essay before and after being given students’ oral and written feedback, transcription in students oral feedback,, and comment box in students written feedback. The result of this study found that there were students’ essays with correct changes and revision, essay with changes but incorrect revision, and essay with no changes and revision after being given feedback. Most of the students’ essays were correct changes and revision after being given oral and written feedback. The students’ written feedback gave more effective to improve the students’ writing quality. Therefore, this study might be the window for further studies to involve the teachers’ role in giving clarification of oral and written feedback if the students get difficulty. Keywords: oral feedback, written feedback, students’ essay
Cube Assessment Framework For B2C Websites Applied To The Fashion Industry

The paper proposes a framework for assessment and design of B2C websites focussing on Web 2.0 and social media as vehicles for involvement of current and potential customers. Three overall strategic dimensions are proposed for characterization of websites, whether the 1) purpose is branding or e-commerce, 2) communication is one-way or two-way, 3) focus is transaction or innovation. When these three strategic binary dimensions are combined, we get 2 x 2 x 2 or a total of 8 different triplet combinations. The framework is used for an assessment of 15 fashion websites in the years 2006, 2008 and 2010.
Low rank methods for optimizing clustering

Hou, Yangyang PhD, Purdue University, December 2016. Low Rank Methods for Optimizing Clustering. Major Professor: David F. Gleich. Complex optimization models and problems in machine learning often have the majority of information in a low rank subspace. By careful exploitation of these low rank structures in clustering problems, we find new optimization approaches that reduce the memory and computational cost. We discuss two cases where this arises. First, we consider the NEO-K-Means (Non-Exhaustive, Overlapping K-Means) objective as a way to address overlapping and outliers in an integrated fashion. Optimizing this discrete objective is NP-hard, and even though there is a convex relaxation of the objective, straightforward convex optimization approaches are too expensive for large datasets. We utilize low rank structures in the solution matrix of the convex formulation and use a low-rank factorization of the solution matrix directly as a practical alternative. The resulting optimization problem is non-convex, but has a smaller number of solution variables, and can be locally optimized using an augmented Lagrangian method. In addition, we consider two fast multiplier methods to accelerate the convergence of the augmented Lagrangian scheme: a proximal method of multipliers and an alternating direction method of multipliers. For the proximal augmented Lagrangian, we show a convergence result for the non-convex case with bound-constrained subproblems. When the clustering performance is evaluated on real-world datasets, we show this technique is effective in finding the ground-truth clusters and cohesive overlapping communities in real-world networks. The second case is where the low-rank structure appears in the objective function. Inspired by low rank matrix completion techniques, we propose a low rank symmetric
EXERGOECONOMIC MODELING OF GEOTHERMAL DISTRICT HEATING SYSTEMS FOR BUILDING APPLICATIONS

Leyla Ozgener, Arif Hepbasli, Ibrahim Dincer, and Marc A. Rosen 1 Graduate School of Natural and Applied Sciences, Mechanical Engineering Science Branch, Ege University, 35100 Bornova, Izmir, Turkey 2 Department of Mechanical Engineering, Faculty of Engineering, Ege University, 35100 Bornova, Izmir, Turkey 3 Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario, L1H 7K4, Canada
Admitting Students through an Open Online Course in Programming: A Multi-year Analysis of Study Success

Since 2012, part of computer science student body at the University of Helsinki has been selected by using a massively open online version of the same introductory programming course that our freshmen take. In this multi-year study, we compare study success between students accepted through the online course (MOOC intake) and students accepted through the traditional entrance exam and high school matriculation exam based intake (normal intake). Our findings indicate that the MOOC intake perform better in computer science studies when looking at completed credits and grade point average, but there is no difference when considering other courses. Retention among the MOOC intake is better than among the normal intake. Additionally, students in the MOOC intake are more likely to complete their capstone project and Bachelor's thesis in the studied time-frame. However, the MOOC intake makes the already skewed gender balance more pronounced.
The Effect of Various Calcium and Phosphorus Sources on Productive and Egg Quality Performances of Spent Layers

This study was conducted at the University of Maiduguri Poultry and Research farm, to investigate the effects of various calcium sources on the productive and egg quality performance of spent layers. A total of ninety (96) Black Harco layers at the age of 58 weeks were randomly assigned in to four different treatment and replicated two times with12 birds each in a completely randomized design (CRD). They were reared on varying calcium and phosphorus sources name bone meal, oyster shell, periwinkle shell and limestone for treatment T1,T2,T3 and T4. The study revealed that feed consumption and feed conversion Ratio did not differ (P<0.05) significantly among treatment groups. Egg weight, Albumen length and Haugh unit also did not differ significantly. However, albumen height, albumen width and albumen index and shell thickness differ significantly between treatment groups and was in favour of limestone. This indicates that the various Ca/P sources affect these parameters. The mortality record of 5.20% recorded was in treatment T3 and T4. The study concluded that the various Ca/P sources did not affect feed consumption and FCR but some egg quality factors. KEY: Spent layers, calcium and phosphorus sources, egg quality, productive performance -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 07-01-2019 Date of acceptance: 22-01-2019 -------------------------------------------------------------------------------------------------------------------------------------
Voting as Communicating

This paper develops a model where voters trade-off two different motives when deciding how to vote: they care about current decision-making (they are "strategic"), but they also care about communicating their views about their most-preferred candidate so as to influence future elections, by influencing other voters' opinion and/or party positioning. In effect, voters in this model are intermediate between "strategic" and "sincere" voters of conventional models in elections with more than 2 candidates. This allows us to better investigate the relative efficiency of various electoral systems: our main conclusion is that since voting is used as a communication device electoral systems should be designed to facilitate efficient communication, e.g. by opting for 2-round systems rather than 1-round systems.
Buybacks Around the World Market Timing , Governance and Regulation

We document the consequences of open market share repurchases in a global setting, using over 20,000 announcements from 32 countries. Non-U.S. buybacks are associated, on average, with smaller announcement returns, and larger long-term excess returns. Governance quality matters: both short term and long term excess returns are positively related to country governance quality. The hypothesis that managers buy back shares to take advantage of an undervalued stock price explains long run returns around the world: long term returns are positively related to an undervaluation index (Peyer and Vermaelen, RFS 2009). In contrast to U.S. buybacks, however, they are unrelated to subsequent takeover activity or takeover risk. We also find strong evidence that long run excess returns in the U.S. are partly driven by the benefits from a reduction in agency costs of free cash flow. Finally, shareholders are better off when the buyback only requires board approval, rather than shareholder authorization, suggesting that the insistence of e.g. European regulators on shareholder approval as a tool for shareholder protection from buybacks is misplaced. *: Alberto Manconi: Finance Department, Tilburg University, CentER, PO Box 90153, 5000LE Tilburg, Netherlands, email: a.manconi@tilburguniversity.edu. Urs Peyer: Finance Department, INSEAD, Bd de Constance, 77305 Fontainebleau Cedex, France, email: urs.peyer@insead.edu. Theo Vermaelen: Finance Department, INSEAD, Bd de Constance, 77305 Fontainebleau Cedex, France, email: theo.vermaelen@insead.edu. We thank Cornelia Schuette for excellent research assistance and Raquel F. Oliveira of the Central Bank of Brazil for help clarifying the Brazilian regulation. We also thank seminar participants at Tilburg University, Payout Policy: Foundations and Trends conference (2011, Wupperthal), Exeter University, Warwick University, the AFA 2013 Meetings, the 2013 FMA European Meetings, the 2013 EFMA Meetings, and Panayotis Andreou, Ken Bechman, Bill Megginson, Roni Michaely, and Laura Starks, for valuable discussions and comments.
Does Human Capital Cause Economic Growth? A Case Study of India

This study examines the time series behavior of investment in physical capital, human capital (comprising education and health) and output in a co-integration framework, taking growth of primary gross enrolment rate and a dummy for structural adjustment programme (openness which has been initiated in 1991) as exogenous variables in India from 1960 to 2006. The results suggest that physical capital investment has no long-run nor short-run effect but the human capital investment has significant long-run effect on per capita GNP; the stock of human capital measured by primary gross enrolment rate (lagged by three years) and openness is found to have a significant effect on growth of per capita GNP. The Generalized Impulse Response Function confirms that the innovation in per capita GNP growth can only explain the movements of the growth of per capita GNP (itself) and investment in education human capital positively and significantly only for a short period of time but does not explain the movements of the investment in physical capital and health human capital. Moreover, the innovation in change in education human capital investment significantly and positively explains the movement of the changes in education human capital investment (itself), health human capital investment and growth of GNP per capita; the innovation in health human capital investment significantly explains the changes of education and health human capital investment only. This study may help towards policy modeling of economic growth in India, taking into account the relevance of endogenous growth.
Examining Validity of Aha! Ratings as a Construct of Insight

EXAMINING VALIDITY OF AHA! RATINGS AS A CONSTRUCT OF INSIGHT Ekaterina Y. Shurkova Old Dominion University, 2019 Director: Dr. Ivan K. Ash Currently, there are two main views on insightful problem solving. Results of the studies supporting “business-as-usual” theory suggest that the processes involved in solving insight problems are the same as in analytical problem solving—slow, controlled, and effortful, while findings of the studies supporting the restructuring theory of insight suggest involvement of fast and automatic, one-trial-learning type of processes. The goal of the current study was to investigate the construct validity of the Aha! ratings, used in many studies as the measure of insight, by isolating its three components, effort, confidence, and suddenness, and examining their correlation with working memory span. Ninety-eight undergraduate students from a Southeastern university completed reading and operational span tasks, as well as the compound remote associates task. Self-reported ratings of Effort, Confidence, and Suddenness were collected individually for each compound remote associates set. Correlations between the three ratings were low to moderate; Cohen’s kappa used to measure pair-wise agreement between the ratings was below . 80 for each pair; Cronbach’s alpha demonstrated low internal consistency. Of the three components, only Suddenness correlated with working memory capacity. Suddenness also correlated with the difficulty of the problem.
Extended Information Filtering and nonlinear control for cooperating robot harvesters

A method for autonomous navigation of agricultural robots under a master-slave scheme is developed. The method uses: (i) a nonlinear controller that makes the robots track with precision the desirable trajectories, (ii) a distributed filtering scheme (Extended Information Filter) for estimating the motion characteristics of the vehicles through the fusion of measurements coming from on-board sensors, as well as measurements about the vehicles’ coordinates coming from multiple position sensors (e.g. multiple GPS devices). The autonomous navigation of the cooperating agricultural robots is finally implemented through state estimation-based control. The nonlinear controller uses the estimated state vector of the robots, as provided by an Extended Information Filter. In this manner, the control signal that defines the robots speed and heading angle is generated.
Accent reclassification and speech recognition of Afrikaans , Black and White South African English

We consider the unsupervised re-assignment of training set accent labels and the associated effect on recognition accuracy of multi-accent automatic speech recognition (ASR) systems. Since training set accent labels are assigned by human annotators or are based on a speaker’s mother-tongue or ethnicity, these may not be optimal for acoustic modelling purposes. We reclassify the accents of training set utterances for Afrikaans, Black and White accents of South African English using firstpass acoustic models trained using the original accent labels. We find that the proposed relabelling does not lead to improvements in speech recognition accuracy and that the best strategy remains the use of the originally labelled training data.
The effects of teaching multiple-meaning sight word vocabulary with pictures and visual prompts to Deaf children

This research study analyzed the effects of explicit instruction of multiplemeaning vocabulary words using visual representations of sign language and pictures to increase reading comprehension skills for Deaf children. The goal of this project was to increase students’ skills and strategies when decoding words with multiple meanings. The sample population consisted of three Deaf children, ages 10-11 years old, attending a Midwestern public school that has a Deaf Education program. This eight-week research study consisted of a four-week incidental instruction segment and second four-week segment when multiple-meaning sight words were taught with explicit instruction using visuals and picture prompts. The results of this study indicated that explicitly teaching multiple-meaning sight words with pictures and visual prompts positively impacted sight word recognition and reading comprehension skills for Deaf children. MULTIPLE-MEANING VOCABULARY INSTRUCTION 4
Algorithms , artificial intelligence and NLG in the production of Brazilian journalism

Technologies such as algorithms, artificial intelligence and Natural Language Generation (NLG) are present in several economic activities, essentially in the media field. However, the studies that discuss those facets are scarce in Brazil, notably the empirical studies that evaluate their applicability to the journalistic production. This work speaks about the scenario and possibilities of use for algorithms and NLG in the Brazilian media companies. An exploratory and descriptive research was performed, in which the administrators of the biggest communications companies in Brazil in national and local levels were interviewed. Amongst the achieved results, we can highlight the disbelief and skepticism regarding those technologies, with reduced prospects for their deployment in news production. Index Terms — Algorithms, Artificial Intelligence, NLG, Journalism, Media companies