Miracle-dz/UniFAR-FTUs huggingface dataset:
Employees’ Perception of a Community College Dimensions as Learning Organization and Readiness to Change

Learning organizations are found to be more resilient and adaptive to globalized pressure. For a Community College that vows to serve quality education, it also needs to pursue how it can cope with the rapidly changing environment demanded by globalization. This study aimed to assess the dimensions of learning organization at a Community College and its readiness to change. This study utilized the mixed method integrating quantitative and qualitative approach. The researcher used the survey method consisted of a demographic questionnaire, the DLOQ (Watkins & Marsick, 1993, 1996, 1999) instrument, and attitude toward change instrument by Dunham et al. (1989). The study revealed that demographics like age, educational attainment, employment status and years of experience are a significant source of differentiating opinions among the respondents considering the seven dimensions of the learning organization. Learning organization as a paradigm should be approached holistically. It is of paramount importance that the community college values its faculty and staff, regarding them as the most important resource to gain competitive advantage and to meet the demands of globalized pressure. Keywords: Learning organization, readiness to change, demographics
Not so naive Bayesian classification

Of numerous proposals to improve the accuracy of naive Bayes by weakening its attribute independence assumption, both LBR and TAN have demonstrated remarkable error performance. However, both techniques obtain this outcome at a considerable computational cost. We present a new approach to weakening the attribute independence assumption by averaging all of a constrained class of classifiers. In extensive experiments this technique delivers comparable prediction accuracy to LBR and TAN with substantially improved computational efficiency.
Detecting changes of transportation-mode by using classification data

Several techniques aim to classify human activity using data from sensors e.g., GPS, accelerometer, Wi-Fi and GSM. The sensor data allow inferring transportation modes as car, bus, walk, and bike. Despite some techniques show improvements in accuracy, researchers constantly deal with issues such as over-segmentation and low precision in trip reporting. Journeys are over-segmented due to the ambiguous situations, for instance: traffic lights, traffic jam, bus stops and weak signal reception. Thereby, current techniques report high misclassification errors. We present a method for detecting changes of transportation mode on a multimodal journey, where the input data regard to the classification of human activities. We use a space transformation for extracting features that identify a transition between two transportation modes. The data are collected from the Google API for Human Activity Classification through a crowdsourcing-based application for smartphones. Results show improvements on precision and accuracy in comparison to initial classification data outcomes. Therefore, our approach reduces the over-segmentation for multimodal journeys.
An Efficient Biometric Cryptosystem using Autocorrelators

Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person’s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes. Keywords—Autocorrelators, biometrics cryptography, iris patterns, wavelets.
Real-time detection of nodding and head-shaking by directly detecting and tracking the "between-eyes"

Among head gestures, nodding and head-shaking are very common and used often. Thus the detection of such gestures is basic to a visual understanding of human responses. However it is difficult to detect them in real-time, because nodding and head-shaking are fairly small and fast head movements. We propose an approach for detecting nodding and head-shaking in real time from a single color video stream by directly detecting and tracking a point between the eyes, or what we call the "between-eyes". Along a circle of a certain radius centered at the "between-eyes", the pixel value has two cycles of bright parts (forehead and nose bridge) and dark parts (eyes and brows). The output of the proposed circle-frequency filter has a local maximum at these characteristic points. To distinguish the true "between-eyes" from similar characteristic points in other face parts, we do a confirmation with eye detection. Once the "between-eyes" is detected, a small area around it is copied as a template and the system enters the tracking mode. Combining with the circle-frequency filtering and the template, the tracking is done not by searching around but by selecting candidates using the template; the template is then updated. Due to this special tracking algorithm, the system can track the "between-eyes" stably and accurately. It runs at 13 frames/s rate without special hardware. By analyzing the movement of the point, we can detect nodding and head-shaking. Some experimental results are shown.
Passive Coplanar Circulator with the Yig Thin Films

This paper presents the design and analysis of a new triangular structure of a coplanar circulator using a coplanar topology (CPWG) in the X band frequency. Design and simulation were performed by the ANSOFT HFSS simulator based on the finite element methods. The design is a topology with its planar conductors in the same plane. As a result, a miniature ciculator at 11 GHz with insertion loss of 0.85 dB and isolation of 20.06 dB has been designed.
Do students want to succeed ? Peer group choice , social influence , and undergraduate performance

Students routinely choose others to partner with in studying or discussing course material. The influence of study groups on their members may differ depending upon the student-level preferences expressed in this choice. This study searches for evidence of such heterogeneity by exploiting a unique classroom experiment in study group assignment within a University of South Australia introductory economics course. Drawing a conceptual framework from the treatment effects literature, I decompose the peer effect and measure the strength and nature ∗I thank Paul Frijters, Andrew Leigh, Chikako Yamauchi, two anonymous referees, and seminar participants in the economics group of the Research School of Social Sciences of the Australian National University, and in the Department of Economics and Finance at the Queensland University of Technology, for helpful comments. I also acknowledge UniSA’s School of Commerce and Centre for Regulation and Market Analysis for support over the course of this project. All viewpoints expressed within the paper and errors that remain are solely my own.
Evolution of Binary Compact Objects That Merge

Beginning from massive binaries in the Galaxy, we evolve black hole-neutron star (BH-NS) binaries and binary neutron stars, such as the Hulse-Taylor system PSR 1913+16. The new point in our evolution is a quantitative calculation of the accretion of matter by a neutron star in a common-envelope evolution that sends it into a black hole. We calculate the mass of the latter to be ~2.4 M☉. The black hole fate of the first neutron star can only be avoided if the neutron star does not go through common-envelope evolution. This can be realized if the two massive binaries are sufficiently close in mass, not more than ~5% apart, so that they burn helium at the same time. Then their common hydrogen envelope is expelled by the tightening in the double He star system, with attendant hydrodynamical coupling to the envelope. In this way, we obtain a rate of ≲10-5 per yr per galaxy for production of the narrow neutron star binaries, such as Hulse-Taylor 1913+16 or Wolszczan 1934+12. This is in agreement with estimates based on the observed number of such systems extrapolated to the entire Galaxy, with beaming factors and corrections for the ~90% of binary pulsars estimated to be unobservable. Our chief conclusion is that the production rate for BH-NS binaries (in which the neutron star is unrecycled) is ~10-4 per yr per galaxy, an order of magnitude greater than that of neutron star binaries. Not only should this result in a factor of ~10 more mergings for gravitational wave detectors such as LIGO, but the signal should also be larger. We include some discussion of why BH-NS binaries have not been observed, but conclude that they should be actively searched for.
Predicting Faculty Integration of Faith and Learning

ABSTRACT Concern regarding the secularization of Christian higher education has prompted researchers to investigate the extent that faith and learning is integrated at a faculty level and what factors might predict faculty integration (Lyon, Beaty, Parker, & Mencken, 2005). This research attempted to replicate Lyon et al.’s (2005) logistic regression model predicting faculty integration of faith using survey responses gathered as part of Phase II of the Council for Christian Colleges & Universities (CCCU) Denominational Study (Rine, Glanzer, & Davignon, 2013). Respondents included 2,074 faculty from 55 institutions. The first model used in this study suggested that the most powerful predictors of faculty integration are full-time employment status, earning a degree from an institution that shares the same denominational affiliation, and a match between the faculty member's religious denominational affiliation and the institutional affiliation. A second logistic regression model added faculty academic specialization as a predictor of integration to investigate if that model was a better fit. Results suggested that religion and philosophy instructors are the most likely to integrate faith into their teaching, and professors specializing in computer science, math, and engineering were the least likely. As faculty are considered the primary influence on the integration of faith and learning, existing faculty and institutional administrators concerned with maintaining faith in the classroom may want to consider the contributing factors discussed.
European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study: rationale, design and population characteristics

Abstract The European Prospective Investigation into Cancer and Nutrition (EPIC), which covers a large cohort of half a million men and women from 23 European centres in 10 Western European countries, was designed to study the relationship between diet and the risk of chronic diseases, particularly cancer. Information on usual individual dietary intake was assessed using different validated dietary assessment methods across participating countries. In order to adjust for possible systematic over- or underestimation in dietary intake measurements and correct for attenuation bias in relative risk estimates, a calibration approach was developed. This approach involved an additional dietary assessment common across study populations to re-express individual dietary intakes according to the same reference scale. A single 24-hour diet recall was therefore collected, as the EPIC reference calibration method, from a stratified random sample of 36 900 subjects from the entire EPIC cohort, using a software program (EPIC-SOFT) specifically designed to standardise the dietary measurements across study populations. This paper describes the design and populations of the calibration sub-studies set up in the EPIC centres. In addition, to assess whether the calibration sub-samples were representative of the entire group of EPIC cohorts, a series of subjects’ characteristics known possibly to influence dietary intakes was compared in both population groups. This was the first time that calibration sub-studies had been set up in a large multi-centre European study. These studies showed that, despite certain inherent methodological and logistic constraints, a study design such as this one works relatively well in practice. The average response in the calibration study was 78.3% and ranged from 46.5% to 92.5%. The calibration population differed slightly from the overall cohort but the differences were small for most characteristics and centres. The overall results suggest that, after adjustment for age, dietary intakes estimated from calibration samples can reasonably be interpreted as representative of the main cohorts in most of the EPIC centres.
Are other customer perceptions important at casino table games? Their impact on emotional responses and word-of-mouth by gender

ABSTRACT This study examined (1) the effects of three types of other customer perceptions on emotional responses, (2) the causal relationships between emotional responses and word-of-mouth, and (3) the moderating role of gender. The data were collected from 216 table game players in the United States. The results indicated that similarity and physical appearance had significant effects on positive emotion, while physical appearance and suitable behavior had significant influences on negative emotion. In addition, positive and negative emotions help to form word-of-mouth. Lastly, this study found that gender has a key moderating function in the relationship between negative emotion and word-of-mouth.
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect

Twenty healthy young women participated in thislaboratory resea rch. They completed the Exercise Induced Inventory (EFI - Gauvin & Rejesk i, 1993) before, immediately after, and 15-mins after a 20-minute progressive treadmill exercise during which they ran for 5-mins at 50%, 60%, 70% and 80% of th eir maximal heart rate reserve (MHRR). Before, during every stage of exerci se, and twice after exercise, the participants were asked to continuously identify a letter in a specific position in unexpected words – presented in 8 second intervals over a period of three minutes – while their information processing speed (IPS) was gauged. Results showed that IPS was shortest when participants ran at 8 0% of MHRR, suggesting that quick mental choices are made easier under heig htened levels of arousal. No changes in affect (transient mood states) from pre- to post-exercise were seen. These findings appear to support the circumplex model of affect claiming that affective valence is invariant (unchanged) when distracting men tal tasks are undertaken during exercise.key words: Affect, Circumplex model, Cognitive processing, Exercise intensity, Information processing
Predictors of Student

With the help of an ALISE Research Grant, a study was conducted of the 1,042 students who attended UCLA's GSLIS for more than a single quarter between 1972 and 1987. Twenty-eight variables were coded for 120 nongraduates and a matched sample of 240 graduates from this period. Among the student characteristics examined were gender, ethnicity, age, undergraduate institution, undergraduate major, undergraduate grade point average (UGPA), GRE and TOEFL scores, library-related work experience, recommendation letters, and stated reason for withdrawal from the program. UCLA's GSLIS was found to be similar to other schools of library and information science in terms of makeup of the student population and the predictability of students' performance. Ethnic minorities, foreign students, and males dropped out in larger proportions than other types of students. A multiple regression model found the optimal predictors of GSLIS GPA to be UGPA, GRE quantitative score, ethnicity, and gender. These same variables, along with the GRE verbal score and the amount of library experience, tended to predict completion of the program as well. These results are discussed in terms of the roles of competing career opportunities and commitment to the profession.
Gender Differences in Commuter Travel in Tucson : Implications for Travel Demand Management Programs

is one of ten regional units mandated by Congress and established in Fall 1988 to support research, education, and training in surface transportation. The UC Center serves federal Region IX and is supported by matching grants from the U.S. Department of Transportation, the California Department of Transportation (Caltrans), and the University. Based on the Berkeley Campus, UCTC draws upon existing capabilities and resources of the Institutes of Transportation Studies at Berkeley, Davis, Irvine, and Los Angeles; the Institute of Urban and Regional Development at Berkeley; and several academic departments at the Berkeley, Davis, Irvine, and Los Angeles campuses. Faculty and students on other University of California campuses may participate in Center activities. Researchers at other universities within the region also have opportunities to collaborate with UC faculty on selected studies. UCTC's educational and research programs are focused on strategic planning for improving metropolitan accessibility, with emphasis on the special conditions in Region IX. Particular attention is directed to strategies for using transportation as an instrument of economic development, while also accommodating to the region's persistent expansion and while maintaining and enhancing the quality of life there. The Center distributes reports on its research in working papers, monographs, and in reprints of published articles. It also publishes Access, a magazine presenting sumg maries of selected studies. For a list of publications in print, write to the address below. The contents of this report reflect the views of the author who is responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California or the U.S. Departraent of Transportation. This report does not constitute a standard, spccification, or regulation. BURNS This paper reports on part of a study funded by the U.S. Department of Labor to evaluate whether individual transportation demand management (TDM) measures differentially affect salaried men and women in various household situations. Working women with children are the least able to make drastic changes in their daily activities but may be the most affected by employer sanctions and financial penalties. The study found that in Tucson. Arizona, women are (a) substantially more dependent on the private car driven alone than are comparable men, (b) far less likely to have switched to alternative modes, and (c) more likely to have chosen different alternative modes when they did switch. Moreover, there were differences between the sexes …
Altered pharmacokinetics of daunorubicin in rats with CCl4-induced hepatic injury.

PURPOSE The effect of CCl4-induced experimental hepatic injury (CCl4-EHI) on the pharmacokinetics of daunorubicin was investigated systemically in rats, in an attempt to elucidate the major determinants of the effect of CCl4-EHI on the pharmacokinetics of the drug. METHODS CCl4-EHI was induced in rats by a single intraperitoneal injection of CCl4 (1 mL/kg rat), and a 24 h fasting period. Daunorubicin was administered intravenously to control and EHI rats at a dose of 11.3 mg/mL/kg and the in vivo pharmacokinetics was studied. The in vitro uptake of the drug into isolated hepatocytes and canalicular liver plasma membrane (cLPM) vesicles, as well as the liver microsomal degradation of the drug, were also determined. RESULTS The area under the plasma concentration-time curve (AUC) of daunorubicin was increased by 1.6 times, resulting in a 34% decrease in the systemic clearance (CL) in rats with CCl4-EHI. The apparent biliary (CLbile) and urinary (CLurine) clearance of the drug were unchanged, whereas the AUC of daunorubicinol, the major metabolite of daunorubicin, was decreased by 66% in rats with CCl4-EHI. EHI seemed to affect the hepatobiliary elimination of the drug in several ways: the in vitro intrinsic sinusoidal uptake clearance was decreased by 20%; the in vitro intrinsic canalicular excretion clearance of the drug was increased by 1.7 times; and the in vitro liver microsomal degradation of daunorubicin was significantly retarded. CONCLUSIONS CCl4-EHI appears to impair the hepatic metabolism of daunorubicin, thereby decreasing the CL and increasing the AUC of daunorubicin.
The effect of disfluencies and learner errors on the parsing of spoken learner language

NLP tools are typically trained on written data from native speakers. However, research into language acquisition and tools for language teaching & proficiency assessment would benefit from accurate processing of spoken data from second language learners. In this paper we discuss manual annotation schemes for various features of spoken language; we also evaluate the automatic tagging of one particular feature (filled pauses) ‐ finding a success rate of 81%; and we evaluate the effect of using our manual annotations to ‘clean up’ the transcriptions for sentence parsing, resulting in a 25% improvement in parse success rate by completely cleaning the texts of disfluencies and errors. We discuss the need to adapt existing NLP technology to non-canonical domains such as spoken learner language, while emphasising the worth of continued integration of manual and automatic annotation.
Sparse multi-class prediction based on the Group Lasso in multinomial logistic regression

Summary: Continuous variable selection using shrinkage procedures have recently been considered as favorable models in a wide range of scientific research; in particular biomedical research. In some cases, it is desirable to select as few predictors as possible, to increase the interpretability of the attained prediction rule. One frequently used shrinkage procedure; the Lasso, imposes a L 1 regularization on the regression coefficients of general linear models, inherently leading to sparse prediction rules. When dealing with multi-class prediction in generalized linear models each predictor has a regression coefficient for each class. A major disadvantage is that the Lasso selects individual regression coefficients instead of the more logical selection of predictors. In this paper, we demonstrate a new regularization procedure, based on the Group Lasso in multinomial logistic regression. This results in a lower number of retained predictors, but with similar prediction accuracy when compared to the regular Lasso regularization. To illustrate the new regularization applicability we have employed it on a large cohort of acute myeloid leukemia patients (AML, n=531) who are characterized on a gene expression microarray.