Miracle-dz/UniFAR-FTUs huggingface dataset:
Is NGC 3108 transforming itself from an early‐ to late‐type galaxy – an astronomical hermaphrodite?

A common feature of hierarchical galaxy formation models is the process of ‘inverse’ morphological transformation: a bulge dominated galaxy accretes a gas disc, dramatically reducing the system's bulge-to-disc mass ratio. During their formation, present-day galaxies may execute many such cycles across the Hubble diagram. A good candidate for such a ‘hermaphrodite’ galaxy is NGC 3108: a dust-lane early-type galaxy which has a large amount of H i gas distributed in a large-scale disc. We present narrow-band Hα and R-band imaging, and compare the results with the H i distribution from the literature. The emission is in two components: a nuclear bar and an extended disc component which coincides with the H i distribution. This suggests that a stellar disc is currently being formed out of the H i gas. The spatial distributions of the Hα and H i emission and the H ii regions are consistent with a barred spiral structure, extending some 20 kpc in radius. We measure an extinction-corrected star formation rate (SFR) of 0.42 M⊙ yr−1. The luminosity function of the H ii regions is similar to other spiral galaxies, with a power-law index of −2.1, suggesting that the star formation mechanism is similar to other spiral galaxies. We measured the current disc mass and find that it is too massive to have been formed by the current SFR over the last few Gyr. It is likely that the SFR in NGC 3108 was higher in the past. With the current SFR, the disc in NGC 3108 will grow to be ∼6.2 × 109 M⊙ in stellar mass within the next 5.5 Gyr. While this is substantial, the disc will be insignificant compared with the large bulge mass: the final stellar mass disc-to-bulge ratio will be ∼0.02. NGC 3108 will fail to transform into anything resembling a spiral without a boost in the SFR and additional supply of gas.
La participación de la mujer en los Consejos de Administración y su influencia en los resultados empresariales

espanolLa participacion de la mujer en los consejos de administracion se ha convertido en un importante tema de debate dentro de la literatura de gobierno corporativo. Con la presente tesis doctoral se ha intentado poner luz a la disparidad de resultados existente en relacion a la influencia que tiene la participacion de la mujer en los consejos de administracion sobre los resultados empresariales . Para ello, en primer lugar se ha llevado a cabo una revision de la literatura para conocer el estado de la cuestion en este ambito de investigacion. En segundo lugar, analizamos la efectividad del consejo como variable intermedia entre su composicion y la performance de la empresa con el objetivo de intentar dar respuesta a la disparidad de resultados encontrada . Por ultimo , realizamos un analisis comparativo entre las empresas familiares y no familiares que nos ha permitido concluir la existencia de ciertas diferencias entre ambos tipo de empresas en relacion al tema en cuestion. EnglishWomen's participation on boards of directors has become an important topic in the corporate governance literature . The present doctoral thesis has attempted to shed light the disparity of results regarding the influence of the participation of women on boards of directors have on business results. In this way first, we have conducted a literature review to know the state in this area of research. Second, the effectiveness of the board was analyzed as intermediate variable between composition and performance of the company in order to respond to the disparity of results. Finally, we conducted a comparative analysis between family and non-family firms that have allowed us concluded the existence of certain differences between both types of companies in regard to the tapie of research.
Simultaneous transmission of MAP IE and data for minimizing MAC overhead in the IEEE 802.16e OFDMA systems

An advanced MAP transmission scheme for improving media access control (MAC) overhead in the IEEE 802.16e systems is proposed. In the IEEE 802.16e system, when a base station (BS) broadcasts a MAP message, which is a control message about scheduling information, it applies a robust modulation and coding scheme (MCS) level and allocates a large amount of radio resources, which induce a huge MAP overhead. Our proposed scheme utilizes piggybacked MAP IEs, in which control messages are concatenated with data packets and transmitted with the MCS level applied to data transmission. Due to the fact that the rate at which data is transmitted is generally higher than the rate at which broadcasting messages are transmitted, the proposed scheme can increase average data rate of a MAP transmission and consequently reduce the amount of resources allocated to the MAP transmission. Numerical analysis and simulations are presented to show that the MAP overhead is critical to system performance and can be improved by the proposed scheme.
Recommendation Networks and the Long Tail of Electronic Commerce

It has been conjectured that the peer-based recommendations associated with electronic commerce lead to a redistribution of demand from popular products or "blockbusters" to less popular or "niche" products, and that electronic markets will therefore be characterized by a "long tail" of demand and revenue. We test this conjecture using the revenue distributions of books in over 200 distinct categories on Amazon.com and detailed daily snapshots of co-purchase recommendation networks that products of these categories are situated in. We measure how much a product is influenced by its position in this hyperlinked network of recommendations using a variant of Google's PageRank measure of centrality. We then associate the average influence of the network on each category with the inequality in the distribution of its demand and revenue, quantifying this inequality using the Gini coefficient derived from the category's Lorenz curve. We establish that categories whose products are influenced more by the recommendation network have significantly flatter demand and revenue distributions, even after controlling for variation in average category demand, category's size and price differentials. Our empirical findings indicate that doubling the average network influence on a category is associated with an average increase of about 50% in the relative revenue for the least popular 20% of products, and with an average reduction of about 15% in the relative revenue for the most popular 20% of products. We also show that this effect is enhanced by higher assortative mixing and lower clustering in the network, and is greater in categories whose products are more evenly influenced by recommendations. The direction of these results persists over time, across both demand and revenue distributions, and across both daily and weekly demand aggregations. Our work illustrates how the microscopic economic data revealed by online networks can be used to define and answer new kinds of research questions, offers a fresh perspective on the influence of networked IT artifacts on business outcomes, and provides novel empirical evidence about the impact of visible recommendations on the long tail of electronic commerce.
Solar PV-Powered SRM Drive for EVs With Flexible Energy Control Functions

Electric vehicles (EVs) provide a feasible solution to reduce greenhouse gas emissions and thus become a hot topic for research and development. Switched reluctance motors (SRMs) are one of the promised motors for EV applications. In order to extend the EVs' driving miles, the use of photovoltaic (PV) panels on the vehicle helps to decrease the reliance on vehicle batteries. Based on the phase winding characteristics of SRMs, a tri-port converter is proposed in this paper to control the energy flow among the PV panel, battery, and SRM. Six operating modes are presented, four of which are developed for driving and two for standstill onboard charging. In the driving modes, the energy decoupling control for maximum power point tracking (MPPT) of the PV panel and speed control of the SRM are realized. In the standstill charging modes, a grid-connected charging topology is developed without a need for external hardware. When the PV panel directly charges the battery, a multisection charging control strategy is used to optimize energy utilization. Simulation results based on MATLAB/Simulink and experiments prove the effectiveness of the proposed tri-port converter, which have potential economic implications to improve the market acceptance of EVs.
A Modified Algorithm for Removal of Salt and Pepper Noise in Color Images

In this paper a modified simple edge preserved denoising algorithm to remove salt and pepper noise in digital color images is presented. The algorithm has three steps: noisy pixel detection, replacement of noisy pixels, confirmation by comparing with a threshold. In addition a median filtering is added to improve the quality of the image. The proposed algorithm prevents the smoothing of edges in the noise removal process, by predicting the possible edges and taking the mean value from the predicted edge. In the proposed algorithm the computational complexity is less with maximum edge preservation. The color images are denoised by extracting the R, G and B planes from the noisy image, denoised separately and are merged together to form the color image, rather than converting to gray for denoising and then reconstructing from the denoised gray image. The algorithm is implemented partially in MATLAB and MODELSIM. Experimental results show that the proposed algorithm yields visually pleasing images in terms of qualitative and quantitative evaluation compared to other standard algorithms.
Examining the academic performance and retention of first-year students in living-learning communities, freshmen interest groups and first year experience courses

Based on Tinto's (1993) theory of student departure and Astin's (1993) Inputs- Environments-Outputs model, this dissertation presents the findings of a single-institution study into the effect participating in a living-learning community (LLC), FreshmenInterest Group (FIG) and First Year Experience course (FYE course) had on the academic performance and retention of first-year students. Multiple regression was conducted on institutional data covering a three-year period. After controlling for entering characteristic (i.e., high school GPA, ACT score, sex, race, and family income level) and environmental characteristics (i.e., initial major, residence hall living, and Greek membership) the researcher found that students who participate in FIGs did earn higher grades (standardized [beta] = .02, p [lesser tha] .01). Students in LLCs and FYE courses did not. This same dataset was analyzed using logistic regression to determine if, after controlling for these same variables plus the co-variable of first-semester GPA, participating in LLCs, FIGs and FYEs increased the odds of being retained. Participating in a FIG increased students' odds of being retained by 18% (Exp[(beta)] 1.18, p. [lesser than] . 05), but no change in odds was found for students in LLCs or FYE courses. The results of this study reinforce current research regarding the efficacy of FIG programs, but draw into question the benefits students gain from participating in an LLC or FYE course offered on this campus.
Formal verification of Sequential Systems with Infinitely Many States

2001 Declaration I hereby declare that this thesis was composed by myself, and the work contained in it is my own, unless otherwise stated. I cite all the sources and literature used together with a reference to the corresponding source. Acknowledgment First of all, I would like to thank Antonín Kučera for his guidance and encouragement, and to Stefan Schwoon for providing me his LTL model checker. Special thanks go to my parents for their patience and constant support during my studies. I also want to thank all members of the ParaDiSe laboratory and, last but not least, to Ate, a Greek goddess who makes men blind so that they will blunder into guilty acts. Abstract In recent years, model checking algorithms for verification of infinite-state systems were deeply studied and applied to practical problems. We show, how to use the algorithms for pushdown systems and various modal logics of [4] for verification of Java programs. The process of mechanical abstract model generation is described, and a prototype tool called JAVACHECK is implemented to verify our concept. We also present some examples of properties which can be verified using our approach.
Study of Active Queue Management Algorithms---- Towards stabilize and high link utilization

The focus of this work is to study the behaviors of varies queue managements, including RED (Random Early Detection), SRED (Stabilized-RED), and BLUE. The performance metrics of the comparison are queue size, the drop probability, and link utilization. The simulation is done using NS-2. The results of this work shows that different from the RED, SRED and BLUE, which use the available queue length as the indicator of the severity of congestion, they use packet loss and link idle events to manage the congestion. Thus SRED and BLUE achieve significant better performance in terms of packet loss rates and buffer size requirement in the Network. Finally we report a new queue management, SBQ (Stochastic Blue Queue management), which enforce fairness among a large number of flows.
Knowledge engineering in the communication of Information for safety critical systems

The design and assessment of safety critical systems often involves broad and distributed teams of designers, suppliers and analysts who represent diverse areas of expertise and motivations. Accurate and effective communication between these groups is therefore an issue of primary importance. The formalisation of specifications and arguments of safety can be of significant benefit in ensuring the consistency of evidence in such cases, when it must be presented across many domains. However, a formal description of a safety critical system may be unconvincing unless it is presented in a form which is (or forms which are) accessible to the broad range of users and assessors of safety cases. This raises issues of human communication which include the tailoring of information to particular communicative tasks; the efficacy of differing media for communication and the cognitive impact that such differing media have. This paper draws together work in fields of knowledge engineering, knowledge based systems and human communication in an effort to address, from a sound theoretical basis, these and other communication issues raised by the use of formal descriptions in safety critical systems. Further, this paper argues that a primary role for knowledge based systems techniques in safety critical systems is in supporting the communication of information.
Latency-tolerant software pipelining in a production compiler

In this paper we investigate the benefit of scheduling non-critical loads for a higher latency during software pipelining. "Non-critical" denotes those loads that have sufficient slack in the cyclic data dependence graph so that increasing the scheduling distance to their first use can only increase the number of stages of the software pipeline, but should not increase the lengths of the individual stages, the initiation interval (II). The associated cost is in many cases negligible, but the memory stall reduction due to improved latency coverage and load clustering in the schedule can be considerable. We first analyze benefit and cost in theory and then present how we have implemented latency-tolerant pipelining experimentally in the Intel Itanium® product compiler. A key component of the technique is the preselection of likely long-latency loads that is integrated into prefetching heuristics in the high-level optimizer. Only when applied selectively based on these prefetcher hints, the optimization gives the full benefit also without trip-count information from dynamic profiles. Experimental results show gains of up to 14%, with an average of 2.2%, in a wide range of SPEC® CPU2000 and CPU2006 benchmarks. These gains were realized on top of best-performing compiler options typically used for SPEC submissions.
An analysis of regional product by Three Strata of Industry based on K-means method

This study applies cluster analysis K-means method to analyze the data of regional product by Three Strata of Industry in China. Firstly, we give a review of K-means method, according to self-organizing feature maps we determine the number of clusters, and then employ the K-means method to find the clusters. From the cluster analysis we get four clusters and conclude that the membership in Cluster 1 are all municipalities with the highest value of Per Capita GRP and the highest percentage composition of Tertiary Industry. It shows that the economy of this cluster is developed. Cluster 2 with the lowest composition of Tertiary Industry should enhance the development of Tertiary Industry. The Secondary Industry of Cluster 3 is the most developed. The most provinces in China concentrate in Cluster 4 with the lowest Per Capita GRP need to enhance both Secondary Industry and Tertiary Industry.
The Interface between Motivational and Emotional Facets of Organizational Commitment among Instructors at Higher Education

Teachers in higher education domain play a decisive role in advancing economic developments as well as nurturing the well-being of the societies. Thus, the issue of university instructors’ commitment and the factors influencing its development should be a compelling priority for higher education administrations. The present study aims to extend the research on teacher organizational commitment by investigating the contribution of job motivation and emotion regulation to teacher commitment at higher education. To this purpose, 135 English as a foreign language (EFL) instructors from different higher education institutes and universities took part in this study. They were requested to complete a battery of three questionnaires: Organizational Commitment Questionnaire (OCQ), Work Tasks Motivation Scale for Teachers (WTMST), and Emotional Regulation Questionnaire (ERQ). Findings demonstrated that both emotion regulation and motivation had a positive significant correlation with teacher organizational commitment. Moreover, findings obtained via regression analysis showed that among job motivation components, identified regulation was the best contributor of teacher organizational commitment. Also, among the subscales of emotion regulation, reappraisal strategy was a better predictor of teacher organizational commitment. Findings are discussed in details with respect to the implications for both theory and practice in higher education.
Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching

An efficient algorithm for isometry-invariant matching of surfaces is presented. The key idea is computing the minimum-distortion mapping between two surfaces. For this purpose, we introduce the generalized multidimensional scaling, a computationally efficient continuous optimization algorithm for finding the least distortion embedding of one surface into another. The generalized multidimensional scaling algorithm allows for both full and partial surface matching. As an example, it is applied to the problem of expression-invariant three-dimensional face recognition.
Assessing Success: The Impacts of a Fundamentals of Speech Course on Decreasing Public Speaking Anxiety

Despite assessment's prominence in higher education, many communication departments still find its implementation problematic. In this case study, we answer a call for heightened research pertaining to the best practices for assessment of large, multisection, standardized public speaking courses. We demonstrate the ease with which the basic course can be justified to administrators by citing the course's significant reduction of students' Public Speaking Anxiety (PSA) as assessed by one of the discipline's standard measures of PSA, the Personal Report of Public Speaking Anxiety. Implications include validation of a course design and assessment that provide administration with measures of significant and salient success, and an especially profound positive impact of the course for women.
IP over SONET

IP over SONET technology is being deployed today in IP backbone networks to provide efficient, cost-effective, high-speed transport between fast routers. The authors present an overview of the architectural considerations in the deployment of IP over SONET technology. In addition, an overview of the developments in IP over SONET interface design and specification is provided. Finally, the authors conclude with an examination of the future of high-speed Internet transport.
An Effective Hybrid Algorithm in Recommender Systems Based on Fast Genetic k-means and Information Gain

Personalization in a recommender system is to customize contents for users based on their preferences and interests. For a new user such systems face cold start problem. This is because system knows nothing about this user and is unable to present recommendations. For the above said problem an existing technique, Information Gain through Clustered Neighbors (IGCN), has proved to be productive but this technique uses k-means algorithm for making user clusters. The problem with k-means algorithm is it might get stuck at local optima and has initial value dependency. Genetic k-means Algorithm (GKA), a hybrid clustering technique, converges to global optima faster than traditional Genetic Algorithms (GAs). The performance of this technique was improved by Fast Genetic K-means algorithm (FGKA). As the above mentioned GAs has proved to overcome disadvantages of k-means, the paper intends to use a GA viz. FGKA for clustering instead of k-means due to its better performance. This is why the proposed algorithm is named Information Gain Clustering through Fast Genetic k-means Algorithm (IGCFGKA). We show through our results that IGCFGKA not only overcomes k-means disadvantages but it also provides high quality recommendations and an optimal or near optimal solution. Our paper is first to compare IGCFGKA with various strategies of Information gain in recommender systems.
Understanding risk factors in cardiac rehabilitation patients with random forests and decision trees

Cardiac rehabilitation is a well-recognised non-pharmacological intervention recommended for the prevention of cardiovascular disease. Numerous studies have produced large amounts of data to examine the above aspects in patient groups. In this paper, datasets collected for over a 10 year period by one Australian hospital are analysed using decision trees to derive prediction rules for the outcome of phase II cardiac rehabilitation. Analysis includes prediction of the outcome of the cardiac rehabilitation program in terms of three groups of cardiovascular risk factors: physiological, psychosocial and performance risk factors. Random forests are used for feature selection to make the models compact and interpretable. Balanced sampling is used to deal with heavily imbalanced class distribution. Experimental results show that the outcome of phase II cardiac rehabilitation in terms of physiological, psychosocial and performance risk factor can be predicted based on initial readings of cholesterol level and hypertension, level achieved in six minute walk test, and Hospital Anxiety and Depression Score (HADS) anxiety score and HADS depression score respectively. This will allow for identifying high risk patient groups and developing personalised cardiac rehabilitation programs for those patients to increase their chances of success and minimize their risk of failure.