Miracle-dz/UniFAR-FTUs huggingface dataset:
Festival attachment: antecedents and effects on place attachment and place loyalty

PurposeThe purpose of this paper is to propose the mechanism of festival attachment and examine how it serves as a significant predictor of place attachment and place loyalty.Design/methodology/approachThrough on-site survey with convenience sampling, 465 visitors were surveyed at the Pingxi Sky Lantern Festival, which is one of the most famous Taiwanese festivals. Structural equation modeling is used to examine the proposed research model.FindingsEmpirical results of this study reveal that “hedonism” is the most important antecedent for improving festival attachment, followed by novelty seeking, attractions and cultural exploration. Festival attachment exerts positive effects on place attachment, which then increases place loyalty. Moreover, place attachment partially mediates the relationship between festival attachment and place loyalty.Originality/valueBy hosting festivals, festival managers can induce festival attachment in visitors and then transfer the attachment with festivals into the host place. The findings of this study demonstrate the major role of festivals in promoting local tourism.
Adult Learners and Student Engagement: A Study of the Influence of Student Engagement on Community College Students and Their Intention to Transfer.

Community colleges serve as the postsecondary college of choice for many adult students. Community colleges are aware of their increased role in postsecondary education and understand that they must continue to analyze student populations and adapt to their needs as well as maintain their open access philosophy. This study was conducted at the 15 community college districts in the state with the intention to develop a deeper understanding of the influence of student engagement on adult community college students’ transfer intentions and STEM aspirations. The study utilized the new STEM Student Success Literacy survey instrument. The purpose of this study included: (a) to understand the demographics characteristics and engagement practices of adult students attending community colleges, (b) to understand the influence of engagement on students’ intentions to transfer to a 4-year institution and on students’ STEM degree aspirations, and (c) to add to the current body of literature on engagement. This research sought to understand how engagement factors impact adult learners at community colleges. The experiences, skills, and attitudes of adult students are different than that of the traditional-age student. Without effective practices to serve adult students, colleges will not adequately meet the needs of these students. Faculty and administrators need to take responsibility for this important student population.
Forced vibration method for identification of flutter derivatives of bridge section model

The method of extracting the flutter derivatives with the free vibration method of section model is simple in device and easy to implement, but in tests we found that the results are not perfect. One reason is that the model may be affected by the vortex and that at high wind speed, the signal is badly disrupted and SNR is low. Another reason is that the different forms of exciting vibration will bring the results with poor repeatability. Forced vibration method has been considered to be the most accurate method for the extraction of flutter derivatives, but because of its requirement for more complex devices, research and implementation of this method are less. In this paper, one experimental test with the forced vibration method for two kinds of bridge decks shows that the effect is good.
Latent and Abnormal Functional Connectivity Circuits in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is associated with disrupted brain networks. Neuroimaging techniques provide noninvasive methods of investigating abnormal connectivity patterns in ASD. In the present study, we compare functional connectivity networks in people with ASD with those in typical controls, using neuroimaging data from the Autism Brain Imaging Data Exchange (ABIDE) project. Specifically, we focus on the characteristics of intrinsic functional connectivity based on data collected by resting-state functional magnetic resonance imaging (rs-fMRI). Our aim was to identify disrupted brain connectivity patterns across all networks, instead of in individual edges, by using advanced statistical methods. Unlike many brain connectome studies, in which networks are prespecified before the edge connectivity in each network is compared between clinical groups, we detected the latent differentially expressed networks automatically. Our network-level analysis identified abnormal connectome networks that (i) included a high proportion of edges that were differentially expressed between people with ASD and typical controls; and (ii) showed highly-organized graph topology. These findings provide new insight into the study of the underlying neuropsychiatric mechanism of ASD.
Finite horizon optimal memoryless control of a delay in Gaussian noise: A simple counterexample

In this paper, we investigate control strategies for a scalar, one-step delay system in discrete time, i.e., the system? s state is the input delayed by one time unit. We allow control policies that are memoryless functions of noisy measurements of the state of the delay system. We adopt a first order state-space representation for the delay system, where the initial state of the system is a Gaussian and zero mean random variable. In addition, we assume that the measurement noise is drawn from a white and Gaussian process with zero mean and constant variance. Performance evaluation is carried out via a finite-time quadratic cost that combines the second moment of the control signal, and the second moment of the difference between the initial state and the state at the final time. We show that if the time-horizon is one or two then the optimal control is a linear function of the plant? s output, while for a sufficiently large horizon a control taking only two values will outperform the optimal linear solution. This paper complements the well known counterexample by Hans Witsenhausen, which showed that the solution to a linear, quadratic and Gaussian optimal control paradigm might be nonlinear. Witsenhausen? s counterexample considered an optimization horizon with two time-steps (two stage control). In contrast to Witsenhausen? s work, the solution to our counterexample is linear for one and two stages but it becomes nonlinear as the number of stages is increased. Existing tests for linearity of the optimal memoryless control consider only the two-stage problem. The fact that our paradigm leads to non-linear solutions, in the multi-stage case, could not be predicted from prior results. In particular, the fact that the optimal solution for the two stage problem is linear, but the multiple stage might not be, also shows that dynamic programming principles cannot be used for our paradigm. Our paper provides analytical proofs which hold for any number of stages.
FUZZY BASED AUTOMATIC DETECTION AND CLASSIFICATION APPROACH FOR MRI-BRAIN TUMOR

The main objective of this study is to detect and classify the brain tumor automatically in MRI images. Here the proposed approach consists of various stages namely Pre-Processing, Detection, Segmentation, Feature Extraction and Classification. The image processing methodologies such as Speckle Noise Removal, Adaptive Histogram Equalization, Fuzzy C-Means clustering and Gabor Feature extractor combined with Fuzzy-KNN methods. It has been developed for detecting and classifying the brain tumor from the MRI images. The classification categorizes and says that the input image is Tumor affected or Normal Image with the severity level. The proposed approach proves its efficiency in terms of detection and classification whereas the proposed approach shows its accuracy is 13.5% more than the existing approach.
A QoS guaranteed low energy packet transmission technique for the IEEE 802.11 WLAN

This work presents an energy efficient packet transmission algorithm that exploits the multi-rate transmission technique used by the link adaption algorithm of the IEEE 802.11 standard. The proposed algorithm adapts both the transmission data rate and the transmission power to optimize energy consumption of a WLAN transmitter under specific Quality of Service (QoS) constraints. The proposed algorithm introduces a new cost function for data rate mapping based on a dual parameter approach, where both transmission delay and queue length are used for data rate selection. Transmitters always choose the lowest possible data rate that satisfies the QoS objective in order to minimize energy consumption; as the system load and the congestion increases, the required data rate to satisfy the QoS objective is increased to adapt to the network load condition. The developed algorithm requires minimum signaling feedback and introduces low computational load. Simulation results show that the proposed protocol can introduce significant energy savings compared to well-known Rate First Channel Driven Rate/Power adaptation (CDRPA) and Miser approaches while still maintaining the QoS at the required level. An OPNET based simulation model is used for the performance analysis.
Heterogeneous Iris Segmentation Based on Active Contour Model and Prior Noise Characteristics

Recently, iris segmentation has attracted increasing attentions due to its importance for iris recognition systems. A lot of efforts have been made to design iris segmentation methods; however, heterogeneous iris segmentation remains challenged. Therefore, this paper presents a heterogeneous iris segmentation method based on active contour model and prior noise characteristics. By evaluating prior noise characteristics, the proposed method first classifies heterogeneous iris images into two types. Following this, it integrates merits of the localizing region-based active contours model and Hough transform to localize the interior and exterior boundaries of iris regions with a "divide-and-conquer" pattern. Extensive experiments demonstrate the proposed method overcomes the disturbances caused by occlusions, reflection, and texture, improving the accuracy and success rate of heterogeneous iris segmentation.
Methylenetetrahydrofolate Reductase C677T Polymorphism and Susceptibility to Cervical Cancer and Cervical Intraepithelial Neoplasia: A Meta-Analysis

Background A number of studies have explored the association between methyl enetetrahydrofolate reductase (MTHFR) C677T polymorphism and susceptibility to cervical cancer and cervical intraepithelial neoplasia (CIN). However, results remained controversial. To address this gap, we decided to conduct a meta-analysis of all available published studies. Methods Electronic literature searches of the PubMed, EmBase and Medline databases were performed up to April 30, 2012. Fixed-effects or random-effects model was used to calculate the pooled ORs for different genetic models. Results A total of 12 case-control studies were ultimately identified. No statistical correlation was found between C677T variants and cervical cancer for the overall population. However, subgroup analyses on the White women pointed to a significant protective effect for individuals heterozygous or homozygous for the T-allele (for CT vs. CC: OR = 0.72, 95% CI 0.59–0.88; for TT vs. CC: OR = 0.69, 95% CI = 0.49–0.97; for CT+TT vs. CC: OR = 0.71, 95% CI 0.59–0.86). C677T variants were associated with neither combined nor stratified CIN among the overall population. Conclusions This meta-analysis suggests that White women with mutant C677T genotypes might have a lower risk of cervical cancer, yet lacking enough statistical robustness. Further investigations are needed to get more insight into the role of this polymorphism in cervical carcinogenesis.
Full-chip verification methods for DSM power distribution systems

Power distribution verification is rapidly becoming a necessary step in deep submicron (DSM) design of high performance integrated circuits. With the increased load and reduced tolerances of DSM circuits, more failures are being seen due to poorly designed power distribution systems. This paper describes an efficient approach for the verification of power distribution at the full-chip transistor level based on a combination of hierarchical static and dynamic techniques. Application of the methodology on practical design examples is provided. We also demonstrate the necessity of analysis at the full-chip transistor level to verify the complex interactions between different design blocks based on static and dynamic effects.
Bumping Strategies for the Private Incremental Multiagent Agreement Problem

We introduce the Multiagent Agreement Problem (MAP) to represent a class of multiagent scheduling problems. MAP is based on the Distributed Constraint Reasoning (DCR) paradigm and requires agents to choose values for variables to satisfy not only their own constraints, but also equality constraints with other agents. The goal is to represent problems in which agents must agree on scheduling decisions, for example, to agree on the start time of a meeting. We investigate a challenging class of MAP – private, incremental MAP (piMAP) in which agents do incremental scheduling of activities and there exist privacy restrictions on information exchange. We investigate a range of strategies for piMAP, called bumping strategies. We empirically evaluate these strategies in the domain of calendar management where a personal assistant agent must schedule meetings on behalf of its human user. Our results show that bumping decisions based on scheduling difficulty models of other agents can significantly improve performance over simpler bumping strategies.
Hierarchical Information Clustering Using Ontology Languages

The tools to analyze and visualize information from multiple, inhomogeneous sources have traditionally relied on improvements in statistical methods. The results from statistical methods, however, overlook relevant semantic features present within natural language and text-based information. Emerging research in ontology languages (e.g. RDF, RDFS, SUOKIF, and OWL) offers promising avenues for overcoming these limitations by leveraging existing and future libraries of meta-data and semantic mark-up. Using semantic features (e.g. hypernyms, meronyms, synonyms, etc.) encoded in ontology languages, methods such as keyword search and clustering can be augmented to analyze and visualize documents at conceptually higher levels. We present findings from a hierarchical clustering system modified for ontological indexing and run on a topic-centric test collection of documents each with fewer than 200 words. Our findings show that ontologies can impose a complete interpretation or subjective clustering onto a document set that is at least as good as meta-word search.
Origins of scaling in FX markets

Typical data sets employed by economists and financial analysts do not exceed a few hundred or thousand observations per series. However, in the last decade data sets containing tick-by-tick observations have become available. The studies of these data have turned up new and interesting facts about the pricing of assets. In this article we show that foreign exchange (FX) rate returns satisfy scaling with an exponent significantly different from that of a random walk. But what is more important, we also show that the conditionally exponential decay (CED) model can be used to solve a long standing problem in the analysis of intra-daily data, i.e. it can be used to identify the mathematical structure of the distributions of FX returns corresponding to the empirical scaling laws.
The decline of the Deontic nci construction in Late Modern English

Starting from a traditional corpus-based investigation of an example of constructional attrition, i.e. of a sustained drop in the frequency of use of a construction in a language’s history, this paper argues that usage data which make abstraction from individual speakers can no more account for this kind of constructional change than they can for constructionalization, the creation of new constructions. A more ‘radically’ usage-based approach to diachronic construction grammar implements the cognitive commitment of this subdiscipline of cognitive linguistics and ultimately explains all constructional change with reference to individual speakers’ grammars. Since no two speakers’ experience-based constructicons are identical, it is hypothesized that, very similar to constructionalization, constructional attrition starts from interpersonal variation and the paper encourages the use of idiolectal historical corpora to find corroboration for this. The case of constructional attrition presented in descriptive detail is that of the English Deontic nci construction, which is instantiated by such forms as be compelled to, be forbidden to, be obliged to and be permitted to. Previous research established this schema to have grown in frequency and productivity from the 14th until the 18th century and the current paper documents the start of its subsequent decline with data from the Corpus of Late Modern English Texts. It goes on to ask whether a usage-based approach should stop at offering cultural explanations for such developments and proposes a more genuinely cognitive line of explanatory attack.
A bitmap scaling and rotation design for SH1 low power CPU

In this paper, a bitmap scaling and rotation design with low computation requirements is proposed and implemented using a platform with a low power CPU, SHl, that has a limited amount of computation power. This design is composed of the incrementa algorithm, the fixed-point mathematics, and the prestored bitmap operation function table. First, by using the incremental algorithm, we can reduce the computations based on additive operations to locate the current parameters of the image pixels from the previous parameters. Second, by using fixed-point mathematics, we can reduce the computation of graphic images in comparison. with that for floating-point computation. Finally, by using the prestorcd bitmap operation function table, we can exchange the complex function computations for a simple table look-up. Based on these three arrangements for the SHl platform, the experimental results show a three to six times reduction of time for graphic image rotation.
Designing Flexible Resource Rental Models for Implementing HPC-as-a-Service in Cloud

Due to its ability of delivering virtually unlimited computing power as a metered service, the emerging cloud computing paradigm becomes an attractive option for scientific communities to experiment large-scale resource-demanding applications traditionally deployed in high performance computing (HPC) centers. Planning resource rental is difficult in cloud environment because various parties may have fundamentally different interests. To accommodate such diverse heterogeneity, designing flexible resource rental models for multiple parties in the cloud market becomes a challenging issue. In this study, we investigate the problem of designing flexible resource rental models for implementing HPC-as-a-Service in cloud market. First, from the perspective of resource customers, we present cost-effective resource rental planning models to better utilize on-demand and spot resources in cloud. Next, we approach the problem from the perspective of resource providers, and propose a novel service scheduling model for a multi-tenant cloud resource sharing platform. The remaining work to complete the PhD dissertation is then presented. The proposed research highlights flexibility for resource rental planning in the following two aspects. (1) Flexibility for resource customers ensures them to deploy elastic HPC applications taking most advantage of both fixed-price on-demand resources and dynamic spot resources. (2) Flexibility for resource providers accommodates differentiated service requirements from various customers and achieves efficient HPC service scheduling. We believe that the proposed work presented in this paper offers a novel means to address the need for flexible resource rental models in cloud, and sheds light on future research in the broad area of resource management in cloud computing.
Academic Stress, Resilience, Peer Relation, and Teacher Support as Predictors of Undergraduates’ Academic Confidence

Globally, finding the predictors for undergraduates' mental health through academic success is critical for fostering youth to become productive citizens as adults. The study therefore addresses the predictive power of academic stress, resilience, peer relation, teacher support, and parental involvement on academic confidence among undergraduates in at Babcock University Ilishan, Ogun State, Nigeria. The study adopted a descriptive survey research design of an ex-post facto type. Two research hypotheses were formulated and tested at 0.05 level of significance. Data were collected using five standardized instruments. Research questionnaires were administered to three hundred (300) undergraduates at Babcock University. Data was analysed using Multiple Regression statistical methods. The findings of this study indicated that academic stress, resilience, peer relation, and teacher support are significant predictors of undergraduates’ academic confidence (R = .545; R 2 = .297; Adj. R 2 = .291; F (1, 296) = 33.459; p <. 05). Also, resilience (β= .110; t-value = 2.170), academic stress (β= .107; t-value = 1.817), peer relation (β= .083; t-value = 1.737), and teacher support (β= .100; t-value = 1.808) are potent factor to the prediction of undergraduates’ academic confidence. However, the most potent predictor is resilience. It was therefore concluded that concluded that an increase in undergraduates' wellbeing through adequate teacher support, positive peer relation and academic stress may lead to enhanced academic resilience, which may also promote a meaningful and fulfilled life academically. It was recommended that since an increase in undergraduates' wellbeing through adequate teacher support, positive peer relation and academic stress may lead to enhanced academic resilience, which may also promote a meaningful and fulfilled life academically. Keywords: Academic stress, resilience, peer relation, teacher support, parental involvement, academic confidence, undergraduates
Evaluating sectoral training : a utility tool for SETAs

The South African skills development framework has mandated Sectoral Education and Training Authorities (SETAs) to initiate sector-specific training programmes. If SETA planning is to be proactive, the evaluation and forecasting of improvements in industry outcomes from these training programmes (such as productivity or profitability metrics) should be of concern. This article pursues this end through the well-established area of decision theoretic utility analysis. It suggests a method whereby SETAs may forecast or estimate the industry gains from a given training programme. It is suggested that percentage increases in output may be the utility output of greatest interest and use to SETAs. The national accounts of South Africa are used to estimate the appropriate input data for each industry in these techniques. Other issues in application and research are also suggested.