Miracle-dz/UniFAR-FTUs huggingface dataset:
Trust as an organizational knowledge sharing enabler – validation of the impersonal trust scale

Purpose Contemporary organizations face challenges when they have an increasing need for trust, and yet there are decreasing opportunities for the development of interpersonal trust. Thus, the organizations cannot rely only on that and there is a need for complementary forms of organizational trust. Vanhala et al. (2011) developed the scale for measuring impersonal trust. The purpose of this study is to validate the scale in terms of discriminant and nomological validity as well as to test generalizability. Design/methodology/approach The validities and generalizability is tested on two samples from two industries in Finland: a forest company (411 respondents) and ICT company (304 respondents). Confirmatory factor analysis and structural equation modelling are used. Findings The scale represents both discriminant and nomological validity. Furthermore, the scale is generalizable in different industries. Research limitations/implications A more holistic approach to organizational trust is proposed, and the scale for the impersonal element of the organizational trust is validated. Practical implications This paper validates the scale for the less studied impersonal element of organizational trust. To manage and develop organizational trust, all of its dimensions should be measured. The scale validated allows the measurement of the impersonal dimension, and the more refined measure also makes it possible to focus development efforts on certain operational areas. Originality/value The scale validated represents a step forward toward the reliable measurement of organizational trust. To the best of the researcher’s knowledge, this is the first study to show that previously developed scale is valid and generalizable.
A Study of Tools Used in Implement AgentOriented Software Engineering

Agent oriented software engineering is a field which deals with agents and multi agents. There exist various tools to virtually implement the agents such as notation tools, formal tools and case tools. As there exist various methodologies to their corresponding implementing tools. The paper represents the different methodologies and the tools used to implement them. Although methodologies have their tools but still there exists various shortcomings to show the exact behavior of the agent. So this paper review on a tool named Petri net which is used to represent formal behavior of agents in more concise way so that their timing, their communication and working can been seen more clearly
Short-text Classification Method Based on Concept Network

Aiming at the short-text classification in archive domain,this paper designs an automatic classification method based on concept network.It constructs domain ontology by analyzing the short-text language characteristic in domain,and converts the short-text of title to structural concept network which expresses through Resource Description Framework(RDF) by means of natural language processing technology.On that basis,it defines a similarity measure for archives to classify the retention period of archives.Experimental results show that this method gets a relative 24.2% decrease in classification error rate,and it improves the system performance compared with traditional short-text classification method based on characteristic selection.
NAACL-HLT 2007/ AMTA Workshop on Syntax and Structure in Statistical Translation (SSST): Held in conjunction with NAACL-HLT 2007, Rochester, New York, USA, 26 April 2007

In this paper, we describe a sourceside reordering method based on syntactic chunks for phrase-based statistical machine translation. First, we shallow parse the source language sentences. Then, reordering rules are automatically learned from source-side chunks and word alignments. During translation, the rules are used to generate a reordering lattice for each sentence. Experimental results are reported for a Chinese-to-English task, showing an improvement of 0.5%–1.8% BLEU score absolute on various test sets and better computational efficiency than reordering during decoding. The experiments also show that the reordering at the chunk-level performs better than at the POS-level.
Otel Çalışanlarının Örgütsel Vatandaşlık Davranışlarının İş Performansı Üzerine Etkisi: Sivas İlinde Bir Uygulama (Effects of Organizational Citizenship Behaviors of Hotel Employees on Work Performance: A Case Study in Sivas Province)

İş performansı, işgörenin işle ilgili olarak amaçlanan hedefe ne derece ulaşabildiği ve neyi sağlayabildiğinin nicel ve nitel olarak ifade edilmesidir. Özellikle emek yoğun işletmeler olan turizm işletmelerinde iş performansı, işletmelerin sürdürülebilir rekabet avantajı sağlayıp varlıklarını devam ettirmede son derece önemlidir. İşgörenlerin kendi istekleri ile etkin ve verimli bir şekilde çalışmalarını ifade eden örgütsel vatandaşlık davranışı ise örgütsel açıdan olumlu çıktılar sağlamaktadır. Rekabetin oldukça şiddetli olduğu turizm sektöründe örgütleri diğerlerinden farklılaştıracak olan davranışların ve bunların çıktılarının belirlenmesi oldukça önemlidir. Bu nedenle bu çalışmada, otel işletmelerinde çalışan işgörenlerin sergilemiş oldukları örgütsel vatandaşlık davranışlarının iş performansı üzerine olan etkisi incelenmektedir. Bu sayede örgütsel vatandaşlık davranışı ve iş performansı değişkenleri kullanılarak ilgili alana katkı sağlanmaktadır. Çalışmada, Sivas ilinde dört yıldızlı otellerde istihdam edilen 237 işgörenden anket tekniği ile veri toplanmış ve analize tabi tutulmuştur. Analiz sonuçlarına göre örgütsel vatandaşlık davranışı ile iş performansı arasında ilişki olduğu ve örgütsel vatandaşlık davranışı boyutlarının iş performansını olumlu yönde etkilediği tespit edilmiştir.
Application of improved k-means algorithm based on clusering anlysis

The classic algorithm of k-means is discussed,that is one of the most widespread methods in clustering,including both strongpoints and shortages.Not only it is sensitive to the original clustering center,but also it may be affectedby the outliers.Given these shortages,an improved algorithm is discussed,which makes improvements in outliers and selection of original clustering center.The outlier detection based on the distance method.To select original clustering center based on the nearest neighbour assimilated.Check experiment was done,which indicates the improved one is more stable,more accurate and the affection by the outliers is much low.
Sustainable Assets and Strategies Affecting the Forestry Household Income: Empirical Evidence from South Korea

This study aims to identify the factors determining the forestry household income in South Korea. An empirical analysis was conducted on the Korea Forest Service’s 3-year-panel data. Korea Forest Service is an institution responsible for the sustainable management of South Korea’s forest lands. In the study, the hypothesized factors determining the forestry household income are classified into four types of assets and three types of livelihood strategies. The forestry household income (FHI) is divided into three elements: forestry income (FI), non-forestry income (NFI), and transfer income (TI). The influence of household assets and livelihood strategies on each income were also assessed. A random effect model was used as a statistical analysis of the three-year data of 979 forestry households. Based on the analysis, we found that household head’s age, household head’s labor capacity, savings, business type, cultivated land size, and region are significantly associated with FHI. While FI was influenced by labor capacity, cultivated land size, business type, forestry business portfolio, and region, NFI was determined by household head’s age, household head’s gender, forestry business portfolio, and savings. TI was affected by household head’s age, household head’s education level, forestry business portfolio, savings, and region. The effect sizes and directions varied across different types of income (FHI, FI, NFI, and TI). The findings showed that South Korea forestry was highly dependent on sustainable assets and livelihood strategies. Based on our findings, we expect the effectiveness of forest policies in increasing the forestry household income would differ depending on the source of each income. The results of this study draw attention to the need for an income support policy which considers the characteristics of household assets and livelihood strategies in order to enhance FHI in South Korea.
Percepciones de afiliados a fondos de pensiones privados

El siguiente artículo estudia los determinantes de la elección de un fondo de pensiones privado, mediante el procesamiento de un cuestionario de 514 afiliados. El cuestionario intenta medir las percepciones del consumidor con respecto a sus AFPs. Usando un modelo de ecuación estructural, encontramos que las variables socioeconómicas son irrelevantes, pero algunas percepciones como el retorno de la cartera y el liderazgo del fondo de pensiones privado fueron relevantes en la elección de una institución de fondos de pensiones privada. Contrastamos el modelo en dos diferentes períodos de tiempo : 2009 y 2016. Estos son los períodos antes y después de la turbulencia internacional en el mercado de valores.
Software-defined measurement to support programmable networking for SoyKB

Campuses are increasingly adopting hybrid cloud architectures for supporting big data science applications that require "on-demand" resources, which are not always available locally on-site. Policies at the campus edge for handling multiple such applications competing for remote resources can cause bottlenecks across applications. To proactively avoid such bottlenecks, we investigate the benefits in the integration of two complementary technology paradigms of software-defined measurement and programmable networking. The integration inherently allows flexible end-to-end application performance monitoring and dynamic control of big data application flows using: (a) software-defined networking for transit selection to remote sites, and (b) pertinent selection of local or remote compute resources. Using the Soybean Knowledge Base (SoyKB) as an exemplar application, we demonstrate the benefits of software-defined measurement to support programmable networking. As part of our study methodology, we first profiled the original data flows within SoyKB’s use of iPlant public cloud resources, and identified bottleneck cases such as slow data transfer speeds, lack of performance information (e.g., such as cluster availability, job status and network health) and inflexible control of hybrid cloud resources to address application-specific needs. The profiling study motivated us to propose a new hybrid cloud architecture for SoyKB workflows that utilize end-to-end performance measurements to support a cost-optimized selection of sites for computation and effective traffic engineering at the campus-edge. We validate our approach for a SoyKB workflow use case that we setup on a wide-area overlay network testbed implementation across two geographically-distributed campuses. Our performance results show a notable performance improvement in SoyKB remote data transfer flows that utilize iRODS and TCP tuning mechanisms in the presence of cross-traffic big data flows. Additionally, we implement a SoyKB system that provides: (i) flexible workflow performance analytics at a glance to SoyKB researchers handling big data, and (ii) web service mechanisms for interfacing with popular dynamic resource management technologies such as OpenStack, HTCondor and Pegasus.
The Effects of Web-Assisted Problem Based Learning Model of Physics Learning on High School Students’ Critical Thinking Skills

The purpose of this research is to determine differences in critical thinking skills outcomes between groups with students who take physics learning with web-assisted problem based learning model with students who take physics learning using learning commonly used by teachers to student of XI class. This research was a quasi-experimental (quasi experiment) with the draft “post-test only control group design”. The population in this study is a XI class of even semester in SMA Negeri 2 Yogyakarta, Indonesia. The sample selection is based on the adjustment of the material that is used. The data were taken using the test methods and instruments used for assessment is 8 essay questions with 8 indicators of critical thinking skills tests. Based on the results of hypothesis testing that has been done by t-test sample independent found that there are differences in critical thinking skills outcomes significantly among students who take physics learning with web-assisted problem based learning model. Furthermore, there are effects web-assisted problem based learning model in students’ critical thinking skills. This is evident from the high effect size of Cohen’s test is included in the high category. Based on this it can be concluded that physics learning with web-assisted problem based learning model influence on high school students critical thinking skills outcomes.
A Case Study of PERPADUAN Pre-School settings Inculcates Multi-Ethnic Awareness among Preschoolers’

This paper presents an overview of how children from the three different ethnic groups inculcate multi-ethnic awareness in ethnically diverse pre-school settings and how pre-school nurtured children’s unity. The study involved 25 children and their teachers from one PERPADUAN Pre-school. A qualitative methodology was applied. Direct observation and in-depth interviews were conducted with the children and teachers within 16 weeks. The primary findings of this research found that the PERPADUAN Pre-school can be considered a “Mini Malaysia” because the ethnic situation in the school reflects the diversity of Malaysian society. Activities such as celebrating festivals in Malaysia based on ethnic backgrounds are held in pre-school. Finally, the PERPADUAN Pre-school ethos toward children’s social development is to promote a feeling of unity and acceptance among the ethnically diverse society of Malaysia. The pre-school teacher sees that it is the responsibility of PERPADUAN Pre-school to instil the knowledge that the children need to integrate and participate in a common shared national culture, values and identity of Malaysian. International Journal of Academic Research in Business and Social Sciences Vol. 8 , No. 10, Oct. 2018, E-ISSN: 2 22 2 -6990 © 2018 HRMARS 1183
10-K Filing length and M&A returns

ABSTRACT This study examines the association between 10-K filing length and M&A returns. We posit that 10-K filing length influences shareholder information acquisition and processing costs. Longer 10-K filings reduce information acquisition costs by making more information about the target available to the shareholder, but may increase information processing costs by increasing the difficulty of extracting that information. Which effect dominates ultimately determines the association between 10-K filing length and M&A returns. We find that 10-K filing length is positively related to M&A returns, suggesting that the reduction in information acquisition costs dominates the increase in information processing costs. This relation is stronger when the acquirer has limited access to private information about the target, and when 10-K filings contain text denoting risk. The relation is weaker when 10-K filings contain complex text and financial statements exhibiting high accounting quality.
SPEAKER CLASSIFICATION OPTIMIZATION DESIGN BY VECTOR QUANTIZATION DECISION RULE

The rapid development of the forensic science technologies has been evolved speaker recognition to becoming one of the research topic. However, pattern classification from speech signal remains as challenging problem encountered in general speaker recognition system, including speaker verification and speaker identification. The use of Gaussian Mixture Models (GMM) are most common pattern classification technique in speaker identification due to it can be performed in a completely text independent situation. However, it sounds efficient to speaker identification application, but it results long time processing in practice. In this paper, we propose a decision rules by using vector quantization (VQ) techniques to decrease the training model for GMM in order to reduce the processing time. In our proposed modeling, we take the superiority of VQ, which is simplicity computation to distinguish between male and female speaker. Then, in phase 2 classification, we utilize dominance of GMM model to get the accuracy rates. Experimental result shows that our hybrid VQ/GMM method always yielded better improvements in accuracy and bring almost 30% reduce in time processing.
Caracterização do carvão vegetal produzido em fornos retangulares industriais

The objective of this study was to characterize the properties of charcoal produced in industrial rectangular furnaces, using principal components analysis. For this, three industrial stocks of charcoal were sampled from Furnace I and II, with volumetric capacity of 500m 3 and 180m 3 of wood, respectively. The average particle size, fines content, bulk density and proximate composition were determined. Descriptive analysis and principal component analysis were carried out to evaluate the relationships between charcoal properties. In general, for both furnaces, it was found that the average particle size showed a negative relationship with fines content as the bulk density had a positive relationship with the content of fines. However, the relationship between the fixed carbon and ash content for Furnace I was direct, and for Furnace II was inverse. The charcoal properties of the rectangular furnaces, in general, present a medium asymmetry. The charcoal has a high variability in its properties, however, it is possible, by operating adjustments to improve the quality of coal to the consumer.
Improving Metacognitive Abilities As An Important Prerequisite for Self-Regulated Learning in Preschool Children

Metacognition is a crucial prerequisite for self-regulated learning and refers to the knowledge and the regulation of cognitive processes. Several authors argue that children at preschool age can use initial metacognitive control strategies and monitor their learning activities. This fact will create the conditions for promoting metacognitive activities at an early stage. The development of these activities at this age is influenced by several contextual factors, such as home or school environments. Essential caregivers exert a strong influence in terms of the development of metacognitive abilities. In view of this above 137 children participated in an intervention study aiming to improve metacognitive skills, along with their important caregivers such as parents and kindergarten teachers. Training concepts were designed that combined different kinds of interventions: a direct age-appropriate training of the preschoolers and two indirect interventions catered to parents and kindergarten teachers. The aim of this study was to analyze which training condition is more effective in improving metacognitive skills. We assumed that preschoolers who are consistently supported in their self-regulated learning in kindergarten and at home would benefit the most. Based on our data, we could partly confirm this hypothesis.
Density-Sensitive Semi-Supervised Spectral Clustering

Clustering has been traditionally viewed as an unsupervised method for data analysis. In real world application,however,some background prior knowledge can be easily obtained,such as pairwise constraints. It has been demonstrated that constraints can improve clustering performance. In this paper,the drawback of only incorporating pairwise constraints in clustering is firstly analyzed,and then an inherent prior knowledge in data sets,namely space consistency prior knowledge is exploited. The method of utilizing space consistency prior knowledge is also given. Incorporating the two types of prior knowledge into original spectral clustering,a density-sensitive semi-supervised spectral clustering algorithm (DS-SSC) is proposed. Experimental results on UCI (University of California Irvine) benchmark data,USPS (United States Postal Service) handwritten digits and text data from TREC (Text REtrieval Conference) show that the two types of prior knowledge can supplement each other in clustering process,leading to substantial performance enhancement of DS-SSC over other semi-supervised clustering methods which only incorporate pairwise constraints.
Influence of GNSS Integrity Monitoring on Single and Multiple Fault Event Probabilities

Cases of multiple simultaneous faults are generally considered low probability in integrity analysis of GNSS augmentation systems. This assumption is not necessarily valid given the sensitivity limitations of practical integrity monitors. This paper introduces a method to account for monitor sensitivity in quantifying the probability that undetected faults occur. Analysis of the two-fault case suggests that the conventional method of designating a small integrity risk allocation to cover all multiple fault events does not necessarily ensure integrity for difficultto-detect, small and moderate-sized faults.
Mutual Information Medical Image Registration Based on Firefly Algorithm

To solve the problem that the object function is easy to get into local optimalization because of much local extremes in the mutual information registration method,a mutual information medical image registration algorithm based on firefly algorithm was put forward.The normalized mutual information is used as the similarity measure and registration parameters are expressed by the locations of fireflies in the algorithm,and mutual information function values are calculated according to the locations of fireflies and are set as brightness values of fireflies,and the best registration parameters are retrieved by updating the brightness and attractiveness iteratively while the mutual information function reaches the maximum value.The experimental results indicate that this algorithm can effectively overcome the problem that the mutual information function is easy to fall into local optimalization,and the precision of registration result is improved obviously.
Capital Flows, Financial Integration, and International Reserve Holdings; The Recent Experience of Emerging Markets and Advanced Economies

This paper examines the interaction between capital flows and international reserve holdings in the context of increasing financial integration. For emerging markets the sensitivity of reserves to net capital flows was negative in the 1980s, but became positive after the Asian crisis when these countries used net capital flows to build up reserves. For advanced countries, net capital flows had a negative effect on reserves, especially in recent years. Using measures of financial globalization, we also provide evidence that the sensitivity of reserves to net capital flows increased with globalization for emerging markets while it decreased for advanced countries.
Technology of image interpretation in flight test for examining accuracy of HMS

The research on examining accuracy of HMS(Helmet Mounted Sight) described in this article is a crucial subject in the flight test for evaluating and validating the design of a new fighter.According to requirements on validating the accu-racy of the HMS designed for the new helicopter,a non-contact measurement based on airborne digital imaging is developed.Algorithms based on Kalman filter tracking,cross-correlation matching and Harris corner detector are combined to accom-plish extractions of coordinates of feature points in a subpixel-precise manner.