Miracle-dz/UniFAR-FTUs huggingface dataset:
A Panel Cointegration Analysis: An Application to South East Asia Macroeconomic Recessions

This paper sought to find the long-run relationships among of macroeconomic variables such as GDP, interest rate, money supply, exchange rate and consumer price index for the period of 1996 to 2008. During recessions and a bear stock market the crisis fluctuate from America to Europe, and Asia. This paper used the standard panel unit root tests such as LLC (2002) panel unit root test, Breitung (2000) panel unit root test, IPS (2003) panel unit root test, Maddala and Wu (1999) and Choi (2001) panel unit root test and Handri (1999) panel unit root test. Moreover, the panel cointegration test based on Kao residual cointegration tests was used to test in panel among the variables. The Random-effects ML regression and The Random-effects GLS regression were also used to find better solutions in terms of the long-run relationship among of macroeconomic variables during economic recessions. This paper presents the empirical results regarding long-run results indicated that money supply in selected South East Asia countries (Malaysia, Philippines, Thailand, Vietnam, Cambodia and Lao) have a positive influence on GDP. In addition, the exchange rate of those countries has negative impact on GDP. The findings were consistent with its applications in these areas. Consequently, the theoretical framework of economic theory shows macroeconomic movement consistent with the hypothesis for a set of macroeconomic variables.
Energy band and spin-dependent many-body interactions in ferromagnetic Ni(110) : A high-resolution angle-resolved photoemission study

Mitsuharu Higashiguchi,1 Kenya Shimada,2,* Keisuke Nishiura,3 Xiaoyu Cui,1 Hirofumi Namatame,2 and Masaki Taniguchi1,2 1Graduate School of Science, Hiroshima University, Higashi-Hiroshima 739-8526, Japan 2Hiroshima Synchrotron Radiation Center, Hiroshima University, Higashi-Hiroshima 739-0046, Japan 3Faculty of Science, Hiroshima University, Higashi-Hiroshima 739-8526, Japan Received 16 August 2005; published 30 December 2005
Professional Development with Follow-up for an Effective Paradigm Shift

The importance of transferring learning from a professional development programme is widely acknowledged. The problem lies in overcoming the mitigating factors and promoting the enabling factors that ensure transfer of learning by the teachers and educational leaders in the classrooms and schools. When transfer is successful school students are motivated that culminates in quality education for students. In addition, the teachers and educational leaders review and re-evaluate their own understanding and experiences taking on the path of continuous professional development. The findings of this study are important for planners of professional development programmes say for enhancing skills of teachers in the 21 century. A case study approach was used with data collated from documents, in-depth interviews, observations, questionnaires and focus group. The findings through inductive analysis are that intensive followup, feedback and feed forward are required to support teachers to transfer their learning into the classrooms in both short term and long term professional development.
Incentives and Workers Motivation in the Public Sector

Civil servants have a bad reputation of being lazy. However, citizens' personal experiences with civil servants appear to be significantly better. We develop a model of an economy in which workers differ in laziness and in public service motivation, and characterise optimal incentive contracts for public sector workers under different informational assumptions. When civil servants' effort is unverifiable, lazy workers find working in the public sector highly attractive and may crowd out workers with a public service motivation. When effort is verifiable, the government optimally attracts motivated workers as well as the economy's laziest workers by offering separating contracts, which are both distorted. Even though contract distortions reduce aggregate welfare, a majority of society may be better off as public goods come at a lower cost.
Movie Review analysis using Rule-Based &Support Vector Machines methods

Sentiment analysis (SA) is broad forte of Natural language processing which deals with the computational treatment of opinion, sentiment and subjectivity in text. Due to increased availability of online reviews, there is a growing need to organize them. Sentiment analysis is one present day solution for this issue. An important part of our informationgathering behavior has always been to find out what other people think and whether they have favorable (positive) or unfavorable (negative) opinions about the subject. This survey studies the role of negation in an opinion-oriented information-seeking system. We investigate the problem of determining the polarity of sentiments in movie reviews when negation words, such as not and hardly occur in the sentences. This paper combines rule-based classification, supervised learning and machine learning into a new combined method. This method is tested on movie review.
Americas Conference on Information Systems ( AMCIS ) December 2001 Security in Today ' s EWorld

This paper applies an existing security model from IS research to the current e-commerce environment (a) to assess whether the model represents the risk components and (b) to identify the threats in todays e-commerce arena. Using data from a web-survey, this paper compares the changes in threats in the networked environment before 1992, with the current environment. Our findings indicate that (a) no major changes are required to improve the existing model and (b) viruses and system penetration by hackers are perceived to be the two most severe threats to an organization.
BUCKLING UNDER NONCONSERVATIVE LOAD: CONSERVATIVE SPATIAL CHAOS

Buckling of an elastic linkage under nonconservative load is investigated. There is a related initial value problem, which is conservative and chaotic, and gives valuable aid in finding the buckled shapes of the linkage. To illustrate the equilibrium configurations, the bifurcation diagram is constructed, which turns out to be a distorted version of the bifurcation diagram of the linkage under a conservative load.
The Effect of Ramadan Fasting on Lipid Profile in Pregnant Women

Introduction: Abnormal lipid profile causes maternal mortality and impairs fetal development. This study investigated the effect of Ramadan fasting on plasma lipid profile in pregnant women. Material and Methods: This self-control, cohort study was performed in healthy volunteer fasted pregnant women. Serum cholesterol, triglyceride (TG), low density lipoprotein (LDL), high density lipoprotein (HDL), and body mass index (BMI) were measured on 0, 7th, 14th, and 28th days of Ramadan, and two weeks after Ramadan. Statistical analysis was performed by SPSS. Results: The mean age and BMI of participants was 26.9±6.4 year and 25±4.2 kg/m respectively. Weight and BMI of women did not change during the study. Cholesterol and LDL significantly increased during Ramadan and decreased after Ramadan (p<0.05). No significant change was seen in TG and HDL during the study (p<0.05). Conclusion: Cholesterol and LDL During Ramadan increases and then decreases. There was no change in the levels of TG and HDL in pregnant women. The present study findings may not be sufficient to definitely conclude that Ramadan fasting is safe during pregnancy.
DPPH radical scavenging capacity and the reducing power of free and bound phenolics from wheat and porcino (Boletus edulis) flours

In this paper the content, DPPH radical scavenging capacity and the chelating activity on Fe2+ of free and bound phenolics extract from wheat and porcino flours were determined. The content of phenolic compounds in the extracts of free and bound phenolics from the wheat flour was 4.49 and 196.79 μg/g, and in the porcino flour these contents were 860.02 and 30.38 μg/g, respectively. The content of total phenolics in the porcino flour was considerably higher than that in the wheat flour. For DPPH test, the IC50 the value of free and bound phenolics from the wheat flour was 2.48 and 0.23 mg/ml, respectively, and these values for phenolics from the porcino flour were 0.22 and 0.06 mg/ml, respectively. For reducing power, the IC50 value of free and bound phenolics from the wheat flour was 5.12 and 0.21 mg/ml, and from the porcino flour it was 0.87 and 0.28 mg/ml, respectively. Free and bound phenolics from the porcino flour have a better DPPH scavenging capacity, and free phenolics from the porcino flour have a better reducing power than phenolics from the wheat flour. The results show that the addition of porcino to wheat flour could improve the antioxidant potential of the wheat flour and of final food products which could be obtained from the wheat-porcino flour mixture.
A Simple Single Step diffusion and Emitter Etching Process for High Efficiency Gallium Antimonide Thermophotovoltaic Devices

A single step diffusion followed by precise etching of the diffused layer has been developed to obtain a diffusion profile appropriate for high efficiency GaSb thermophotovoltaic cells. The junction depth was controlled through monitoring of light current-voltage (I-V) curves (photovoltaic response) during the post diffusion emitter etching process. The measured photoresponses (prior to device fabrication) have been correlated with the quantum efficiencies and the open circuit voltages in the fabricated devices. An optimum junction depth for obtaining highest quantum efficiency and open circuit voltage is presented based on diffusion lengths (or monitoring carrier lifetimes), carrier mobility and typical diffused impurity profile in GaSb.
Evaluation of Black Economic Empowerment (BEE) Policy Implementation in the Ngaka Modiri Molema District, North West Province, South Africa

Abstract Black Economic Empowerment (BEE) is a precondition for a truthful and meaningful transformation of the socio-economic landscape in the country in general, and Ngaka Modiri Molema District in particular. This is so, because BEE has been identified by the present South African government as one of the key areas that need to be tackled in order to address and redress the past inequalities and inequities inherited from the apartheid regime. Four pertinent themes that are the prerequisite for sustainable BEE at local government level were adopted and used as a basis for this analysis. These themes are: (1) development and support of small, medium, and micro enterprises, (2) job-creation, (3) poverty alleviation, and (4) entrepreneurial skills development. Using qualitative paradigm and the corresponding research design, as well as employing qualitative data collection methods such as participant observation, in-depth interviewing; and case studies as well as data analysis techniques such as content analysis, document analysis and case analysis, the article focused on the management’s capacity to enhance the functionality and performance of BEE in the District. It also explored the adequacy and/or the inadequacy of the BEE policies, plans, strategies and procedures. The findings revealed that management’s capacity to enhance the functionality and performance of BEE could not be easily ascertained due to the fact that the responsibilities and accountability pertaining to the implementation of BEE were non-existent. With regard to the adequacy and/or inadequacy of the BEE policies, plans, strategies, and procedures, it was established that managers in the District failed to establish relevant and adequate BEE policies, plans, strategies, and procedures for the entire District and thus contributing negatively to the functionality and performance of BEE. Based on these findings the article suggested “the all-inclusive participatory BEE model” and recommended it for the transformation of t he functionality and performance of BEE in the District.
Intergroup conflict in Lebanon : social identification and involvement in collective action predict more hopelessness for Lebanese young adults

The studies examined social identity, collective action, and individual hopelessness in young adults who were university students living through the severe escalating intergroup conflict in Lebanon in 2007 and 2008. As expected, participants in Study 1 (N =162) viewed the conflict as escalating, potentially leading to a civil war, and as leading to hopelessness. Studies 2 and 3 applied social identity theory (SIT; Tajfel & Turner, 1986) to address the determinants and consequences of social identification and involvement in collective action. As well, a hypothesis was derived from Staw's (1997) escalation of commitment theory. Structural equation modeling was conducted. As expected, participants in Study 2 (N = 566) who perceived the intergroup hierarchy as unstable, illegitimate, and group boundaries as impermeable (i.e., migration between groups is not possible) identified more with their group and were more involved in collective action. As well, social identification and collective action increased individual hopelessness. Perceiving the hierarchy as unstable was also directly linked to less hopelessness. Study 3 (N =278) was a modified replication which focused on perceived instability and social identity as determinants of hopelessness and depressio! 1' Parallel effects emerged, and hopelessness was linked to depression. As well, not only did social identification in Study 3 increase depression via hopelessness, but identification unexpectedly also directly decreased depression. Across both studies, perceived instability both increased and decreased hopelessness, via different pathways. The findings reveal complex pathways by which social identity processes influence adjustment. Implications are discussed for SIT and the broader context of Lebanon.
Intelligent health risk prediction systems using machine learning: a review

Humans are considered to be the most intelligent species on the mother earth and are inherently more health conscious. Since Centuries mankind has discovered various proven healthcare systems. To automate the process and predict diseases more accurately machine learning methods are gaining popularity in research community. Machine Learning methods facilitate development of the intelligence into a machine, so that it can perform better in the future using the learned experience. Machine learning methods application on electronic health record dataset could provide valuable information and predication of health risks.The aim of this research review paper are four-fold: i) serve as a guideline for researchers who are new to machine learning area and want to contribute to it, ii) provide state-of-the-art survey of machine learning, iii) application of machine learning techniques in the health prediction, and iv) provides further research directions required into health prediction system using machine learning.
Analyzing Behavioral Big Data: Methodological, practical, ethical, and moral issues

ABSTRACT The term “big data” evokes emotions ranging from excitement to exasperation in the statistics community. Looking beyond these emotions reveals several important changes that affect us as statisticians and as humans. I focus on Behavioral Big Data (BBD), or very large and rich multidimensional datasets on human behaviors, actions, and interactions, which have become available to companies, governments, and researchers. This article describes the BBD landscape and examines opportunities and critical issues that arise when applying statistical and data mining approaches to Behavioral Big Data, including the move from macro- to micro-decisioning and its implications.
Fermi surface with Dirac fermions in CaFeAsF determined via quantum oscillation measurements.

Despite the fact that 1111-type iron arsenides hold the record transition temperature of iron-based superconductors, their electronic structures have not been studied much because of the lack of high-quality single crystals. In this study, we completely determine the Fermi surface in the antiferromagnetic state of CaFeAsF, a 1111 iron-arsenide parent compound, by performing quantum oscillation measurements and band-structure calculations. The determined Fermi surface consists of a symmetry-related pair of Dirac electron cylinders and a normal hole cylinder. From analyses of quantum-oscillation phases, we demonstrate that the electron cylinders carry a nontrivial Berry phase $\pi$. The carrier density is of the order of 10$^{-3}$ per Fe. This unusual metallic state with the extremely small carrier density is a consequence of the previously discussed topological feature of the band structure which prevents the antiferromagnetic gap from being a full gap. We also report a nearly linear-in-$B$ magnetoresistance and an anomalous resistivity increase above about 30 T for $B \parallel c$, the latter of which is likely related to the quantum limit of the electron orbit. Intriguingly, the electrical resistivity exhibits a nonmetallic temperature dependence in the paramagnetic tetragonal phase ($T >$ 118 K), which may suggest an incoherent state. Our study provides a detailed knowledge of the Fermi surface in the antiferromagnetic state of 1111 parent compounds and moreover opens up a new possibility to explore Dirac-fermion physics in those compounds.
Prediction of Added Resistance by Means of Unsteady Wave-Pattern Analysis

for the 25th Intl Workshop on Water Waves and Floating Bodies, Harbin (China), May 9-12, 2010 Prediction of Added Resistance by Means of Unsteady Wave-Pattern Analysis Masashi Kashiwagi Department of Naval Architecture & Ocean Engineering, Osaka University 2-1 Yamada-oka, Suita, Osaka 565-0871, Japan, E-mail: kashi@naoe.eng.osaka-u.ac. jp
A complete motor protection algorithm based on PCA and ann: A real time study

Protection of an induction motor (IM) against possible faults, such as a stator winding fault, due to thermal deterioration, rotor bar and bearing failures, is very important in environments in which it is used intensively, as in industry as an actuator. In this work, a real time digital protection algorithm based on principal component analysis (PCA) and neural network method is presented for induction motors. The proposed protection algorithm covers internal winding faults (also known as stator faults), broken rotor bar faults, and bearing faults. Many laboratory experiments have been performed on a specially designed induction motor to evaluate the performance of the suggested protection algorithm. The hybrid protection algorithm described in this paper uses is based on a three phase rms supply. These currents are first preprocessed by PCA to extract distinctive features called residuals. The calculated residuals are applied to a feed-forward back-propagation neural network as input vectors for decision making. Outputs of the network are signals denoting winding fault, rotor bar fault, bearing fault, and normal operation. The proposed algorithm is implemented by using MatlabTM and C++ with a NI-DAQ data acquisition board.
A Novel Hybrid Duplex Scheme for Two-hop Relaying System

To take advantages of the high spectral efficiency of full-duplex (FD) mode and control rate reduction caused by the self-interference introduced to the relay receiver, a novel hybrid duplex scheme is proposed where the relay works in FD mode following a duty cycle, and receives-only for the rest of time. After characterizing the achievable rate, a joint FD duty cycle and source power allocation problem is formulated to maximize the achievable rate. It is proved that the optimal source power allocation follows a water-filling algorithm over time. Moreover, the optimal FD duty cycle is obtained by considering low-, medium-, and high-source power cases. Specially, closed-form approximation of the optimal FD duty cycle for medium-source power case is presented. Besides, it is shown that the proposed hybrid duplex scheme degenerates to half-duplex and FD modes for low-and high-source power cases, respectively. Numerical results demonstrate that the proposed scheme can effectively improve the achievable rate for a wide range of parameters.
Iterative Calibration of VISSIM Simulator Based on Genetic Algorithm

In the recent decade, computer simulation has been developed enormously in all engineering fields and has become a basic step of design. Accordingly, simulation plays a fundamental role in road traffic engineering offering a basis for the effective analysis of intelligent traffic control systems. A reliable simulator is able to provide effective analysis of a given traffic network if the applied simulation scenarios properly converge to the real-word situation. This requirement can be achieved based on the mixed use of prior real-world traffic measurements and proper simulation settings. The latter one, however, is not straightforward. Accordingly, the paper proposes a potential calibration method to create true-to-life VISSIM simulations. VISSIM is one of the most popular microscopic traffic simulator, a well-known software applied in engineering and scientific practice as well. Basically, a calibration technique with genetic algorithm optimization is proposed to reproduce realistic traffic on a network based on floating car speed data.
Application of Public Domain Satellite-Based DEMs in Natural Hazard Modeling

This paper describe the specification and applications of public domain satellite-based DEMs including SRTM and ASTER-GDEM which, are globally available free. From the result, it was found that several advantages were recognized for public domain satellite–based DEMs including ease of accessibility, elimination of institutional bureaucracy, unlimited coverage and adequate spatial resolution.
Predicting the mutual intelligibility of Germanic languages from linguistic and extra-linguistic factors

In dit proefschrift is de onderlinge verstaanbaarheid van het Deens, Duits, Engels, Nederlands een Zweeds onderzocht en de factoren die deze onderlinge verstaanbaarheid beinvloeden. Wat verstaanbaarheid betreft, was van het Deens en het Zweeds al bekend dat ze in hoge mate onderling verstaanbaar zijn. Dit onderzoek bevestigt dat opnieuw. Daarnaast blijken het Nederlands en het Duits ook in relatief hoge mate onderling verstaanbaar te zijn. Dat Nederlanders het Duits goed verstaan, kan verklaard worden door het feit dat Duits als vreemde taal onderwezen wordt op Nederlandse scholen. Duitsers leren echter geen Nederlands op school. Het feit dat zij het Nederlands relatief goed verstaan, ligt aan de nauwe linguistische verwantschap tussen beide talen. Engels wordt het beste verstaan door sprekers van de andere talen. Dit is logisch, gezien Engels de eerste vreemde taal is op het schoolcurriculum in alle betrokken landen. Sprekers van het Engels verstaan de andere talen het minst goed. Dit kan uitgelegd worden door het feit dat de overige Germaanse talen (behalve Duits) niet onderwezen worden in het middelbaar onderwijs in Groot-Brittannie en het feit dat Engels door invloeden van o.a. het Frans verschilt van de overige Germaanse talen. Tot slot zijn Deens en Zweeds aan de ene kant en Duits en Nederlands aan de andere kant slechts in geringe mate onderling verstaanbaar in gesproken taal en in hogere mate in geschreven taal. Wat voorspellende factoren voor de onderlinge verstaanbaarheid van Germaanse talen betreft, is blootstelling aan een taal de belangrijkste extra-linguistische factor. Lexicale afstand is de belangrijkste linguistische factor. Daarnaast spelen orthografische, fonologische en syntactische afstanden een rol.