Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast demand response with datacenter loads: a green dimension of big data

Demand response is one of the critical technologies necessary for allowing largescale penetration of intermittent renewable energy sources in the electric grid. Data centers are especially attractive candidates for providing flexible, real-time demand response services to the grid because they are capable of fast power ramp-rates, large dynamic range, and finely-controllable power consumption. This thesis makes a contribution toward implementing load shaping with server clusters through a detailed experimental investigation of three broadly-applicable datacenter workload scenarios. We experimentally demonstrate the eminent feasibility of datacenter demand response with a distributed video transcoding application and a simple distributed power controller. We also show that while some software power capping interfaces performed better than others, all the interfaces we investigated had the high dynamic range and low power variance required to achieve high quality power tracking. Our next investigation presents an empirical performance evaluation of algorithms that replace arithmetic operations with low-level bit operations for power-aware Big Data processing. Specifically, we compare two different data structures in terms of execution time and power efficiency: (a) a baseline design using arrays, and (b) a design using bitslice indexing (BSI) and distributed BSI arithmetic. Across three different datasets and three popular queries, we show that the bit-slicing queries consistently outperform the array algorithm in both power efficiency and execution time. In the context of datacenter power shaping, this performance optimization enables additional power
Realtime Free Viewpoint Video System Based on a new Panorama Stitching Framework

Free Viewpoint Video and TV is regarded as the future of digital entertainment allowing users to navigate through multiple video streams of an event to select novel viewpoints. This new capability will be able to give to the users the illusion that they are present at the event. In this thesis, we propose a novel framework for realtime video panorama generation. We first present our work for acquiring multiple high-definition video streams using hardware synchronized cameras with GPU accelerated Bayer demosaicing. The multiple streams are then color corrected using camera gain adjustment and Macbeth color checker chart to remove color variations between cameras. Next, we propose an automatic real-time video stitching algorithm using feature matching based approach and automatic camera calibration that is capable of producing spherical panoramas. The algorithm works by splitting the automatic image stitching steps into one-time and recurring computations. We utilize GPUs for accelerating the recurring computations and achieve real-time performance. By effectively caching the repeated transform maps database, we improve the stitching performance by two orders of magnitude compare to CPU implementations. In order to remove seams between the stitching images, we use Vornoi diagram based optimal seam selection algorithm. The stitched video streams are blended together using the first real-time implementation of Laplacian pyramid blending algorithm using multi-GPUs. Finally, we analyze the problems associated with the scalable transmission and rendering of the virtual views using commodity computers and network resources. The multiple stitching steps are pipelined to distribute the panorama stitching computations between multiple processing nodes to produce visually appealing panoramas at 30Hz without any noticeable blurring or stitching artifacts.
Seeking optimal confusion: a review on epistemic emotion management in interactive digital learning environments

ABSTRACT Emotions play a significant part in students’ learning experiences within complex educational environments. However, the impact of emotional experiences on effective learning is not straightforward. For example, being confused during learning may be perceived as an adverse event. There is, however, considerable research evidence suggesting that confusion can also be a productive aspect of a student's learning processes. Despite this, research also suggests that when confusion is persistent it can become harmful, promoting learner frustration or boredom. Key challenges for the design of interactive digital learning environments (IDLEs) are to detect and assess students’ emotions and to tailor the environment accordingly. In this paper we examine, from a review of the literature, the implications of learners’ confusion that can occur in IDLEs. Strategies for managing students’ confusion will then be discussed and examples of features enhancing learning in IDLEs will be suggested.
Multi-band synthetic aperture sonar mosaicing

Some synthetic aperture imaging techniques have strict path requirements and need to be processed in overlapping chunks. Path adjustments applied for images can decorrelate and alter the appearance of overlapping regions, which can make mosaicing the images chunks for post mission analysis challenging. In this paper, we investigate the application of automatic change detection techniques to the problem of high accuracy, multi-band mosaicing. We will describe and demonstrate the aspects of synthetic aperture sonar (SAS) change detection, in particular automated change detection (ACD) co-registration processing that enables the production of good quality of seabed maps known as mosaicing where individual SAS runs from different traverses are pieced together in adjacent positions to form a complete image.
Innovation in teaching undergraduate Social Theory: Towards an applied perspective

This paper analyses the current offer of contemporary social theory in sociology programmes at the University of Southampton and proposes pathways for innovation. Drawing on module evaluation feedback (3 academic years), group interviews with students (n=12) and interviews with staff (n=3), this research sheds light onto the expectations of studying social theory, evaluations of teaching and learning activities, and avenues for higher alignment. The data analysed suggests that students experience a lack of connection between studying social theory and its applicability, and unawareness of the need for theoretically informed empirical skills. Interviewed members of staff highlight the need for a stronger alignment of assessment methods in the module. These complementing findings lead to proposed changes to the social theory offer by which we seek (i) higher complementarity between core social theory modules, (ii) stronger alignment of assessment methods, (iii) higher content of applied social theory in both teaching and assessment methods.
Self-Contained GPS Integrity Check Using Maximum SOLUTION SEPARATION AS THE TEST STATISTIC

Previous approaches to the self-contained GPS integrity problem have been in a hypothesis testing setting where the two hypotheses are: (1) a single satellite has failed, or (2) there is no failure. In this setting, selective availability is the major source of noise that impedes the detection scheme's ability to detect failures and, at the same time, have a low false alarm rate. This paper poses the problem in a different setting where the basic questions posed are: (1) is the radial position error less than some preset bound? or (2) is it greater than that bound? This is a more fundamental approach, because the pilot does not really care where the error comes from; rather, he is only concerned that the radial position error does not exceed a certain specified level. Results of simulations using a 24-satellite constellation and maximum separation of redundant solutions as the test statistic are presented. These results indicate that this scheme could provide radial error protection of about 250 m with acceptably low alarm and miss rates.
ВИКОРИСТАННЯ ЗАСОБІВ ІКТ У ПРОЦЕСІ ЕКСПЕРИМЕНТАЛЬНОГО ДОСЛІДЖЕННЯ ЕМОТИВНО-ОЦІННОГО СТАВЛЕННЯ УЧНІВ ДО РІЗНИХ ФОРМ ТЕСТОВИХ ЗАВДАНЬ З УКРАЇНСЬКОЇ МОВИ

The article reflects the results of one of the stages of the study, which is connected with determining the characteristics of the influence of various factors on the effective test scores. In particular, the connection between the respondents' emotionally-estimated attitude to various forms of responses to test tasks and the results of their implementation is examined. The proposed study was conducted with using of the authors' tests in the field of Ukrainian language. To determine the generalized students' assessment of the forms of answers, proposed in these tests, we used questionnaire, developed according to the method of semantic differential, which allowed to build a profile of the characteristics of the test in accordance with the semantic cognitive space of the sample. The results of respondents' assessment of response forms are generally correlated with test results and can be an additional explanatory element of their analysis and a prognostic element in the process of further designing and applying the tests. The use of factor analysis of the research results allowed: 1) to draw conclusions about the influence of the response forms offered in the test on the respondents' general perception of test tasks regardless of its content; 2) to justify the assumption that the form of test tasks and answers, as an externally organized test constructs, are a sensory afferent stimulus of the operational imagination of the activity, which, in particular, is expressed in the formation of interest and motivation to doing an assignment. An analysis of the respondents' generalized perception of the separate forms of answers showed the need for combining various forms of test tasks and the forms of answers they defined, both for the formation of positive attitudes and the motivational optimum in the process of their implementation, and for verification and refinement the test results.
Real-Time Spatial Object Tracking on iPhone

Real-Time Spatial Object Tracking on iPhone Amin Heidari Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2011 In this thesis, a novel Object Tracking Algorithm is proposed which tracks objects on Apple iPhone 4 platform in real-time. The system utilizes the colorspace of the frames provided by iPhone camera, in parallel with the motion data provided by iPhone motion sensors, to cancel the effect of iPhone rotations during tracking and matching different candidate tracks. The proposed system also adapts to changes in target appearance and size, thus leading to an object tracking robust to such changes. Several experiments conducted on actual video sequences are used to illustrate the functionality of the proposed approach.
Endogeneity in Okun’s law

ABSTRACT This article contributes to the literature of Okun’s law by addressing an under-noticed but important problem, i.e. endogeneity. By using annual variation in the international oil price weighted with countries’ average oil net-export GDP ratios as a plausibly exogenous instrumental variable for economic growth, the two-stage least squares estimates indicate that faster real GDP growth is associated with lower overall, male and female unemployment rates, confirming the validity of Okun’s law. According to our benchmark estimate, 1 percentage point increase in economic growth leads to a 0.252 percentage point decrease in civil unemployment rate.
Throughput and Handover Latency Evaluation for Multicast Proxy Mobile IPV6

The objective of this paper is to present performance analysis of a new enhanced mobile multicast network mobility management scheme. The initial developed network mobility management called Proxy Mobile IPv6 (PMIPv6) is based on unicast network support. This paper enabled multicast support in network mobility management and named it as MPMIPv6. Additionally this enhancement also provides better network performance with the new context transfer operations and fast reroute operations. In brief, this paper also describes other current mobile multicast schemes. The new scheme is evaluated using mathematical analysis and NS3.19 simulator. Theoretically this scheme reduces service recovery time, total signalling cost, handover latency, and packet loss for multicast communication. However for this paper, the analysed parameters are throughput and handover latency. Both mathematical and simulation results exhibit better network performance for multicast environment compared to the standard benchmark scheme.
ConfBuster: Open-Source Tools for Macrocycle Conformational Search and Analysis

Macrocycles are cyclic macromolecules that have gained an increased interest in drug development. To our knowledge, the current bioinformatics tools that are available to investigate and predict macrocycles 3D conformations are limited in their availability. In this paper, we introduce ConfBuster, a suite of tools written in Python with the goal of sampling the lower energy conformations of macrocycles. The suite also includes tools for the analysis and visualisation of the conformational search results. Coordinate sets of single molecules in MOL2 or PDB format are required as input, and a set of lower energy conformation coordinates is returned as output, as well as PyMOL script and graphics for results analysis. In addition to Python and the optional R programming languages with freely available packages, the tools require Open Babel and PyMOL to work properly. For several examples, ConfBuster found macrocycle conformations that are within few tenths of A of the experimental structures in minutes. To our knowledge, this is the only open-source tools for macrocycle conformational search available to the scientific community
Exploration of Sustainable Urban Transportation Development in China through the Forecast of Private Vehicle Ownership

With the acceleration of China’s urbanization process, the urban transportation problem has become increasingly serious. The rapid expansion of private vehicle ownership, in particular, has become one of the barriers to the realization of sustainable urban transition. This paper applied the Gompertz model to analyze the non-linear relationship between private vehicle ownership and per capita GDP in China using provincial data. In addition, we forecasted private vehicle ownership for 31 Chinese provinces for the period of 2019–2030 and predicted the time to reach the upper limit of 1000 people vehicle ownership of each province according to different scenarios. The main findings revealed that the number of private vehicles owned in China’s provinces was in line with “S”-shaped development and was currently in the process of accelerated growth. Under the scenario of an annual per capita GDP growth rate of 6%, China’s private vehicle ownership will reach 246 million, 375 million, and 475 million in 2020, 2025, and 2030, respectively. This indicates that China’s expansion of private vehicle ownership will generate significant challenges, such as on-road vehicle-related fossil fuel consumption, pollutant emissions, traffic congestion, and scrapped vehicle recycling. These issues will become increasingly prominent. In provinces such as Hubei, Hebei, Hunan, and other central provinces that have a 50–60% urbanization rate, the large potential for income promotion will significantly stimulate the increase in private vehicle ownership, and the upper limit of 1000 people vehicle ownership in each province will be reached in 2032, 2037, and 2046 with annual per capita GDP growth rates of 8%, 6%, and 4%, respectively.
An Entrepreneurship Education Model for Promoting Students’ Entrepreneurial Intentions: The Case of Indonesian Higher Education

This study aimed to provide an understanding and evaluating the implementation of entrepreneurship education as a mandatory program in Indonesia. The study emphasizes the measurement of the effectiveness of different entrepreneurship education programs in higher education implementation, intracurricular and cocurricular programs. The study used the Theory of Planned Behavior (TPB) to measure students’ entrepreneurial intentions. The objects of the research were students who participated in the entrepreneurship programs. The study used quantitative approach and purposive sampling as the sampling technique. The survey resulted in 304 valid respondents from ten universities in Indonesia. The findings showed that intracurricular-based entrepreneurship education was unable to give a significant emphasis on students’ entrepreneurial intention. In contrast, cocurricular-based entrepreneurship education was able to give a significant emphasis on students’ entrepreneurial intention and emphasized on attitude as a single factor. Keywords: entrepreneurship education, theory of planned behavior, intracurricular, cocurricular, entrepreneurial intention
Semi-Supervised Named Entity Recognition of Medical Entities in Swedish

A big opportunity within today’s society is the vast amounts of data generated each day. Especially within the health-care sector where a lot of journals are written daily and needs to be processed in some way to properly identify the content within. Enter the field of Named Entity Recognition (NER), where text is analyzed to locate and classify entities into predefined classes; in our case Disorder & Finding, Pharmaceutical Drug and Body Structure. With a model that can do this with a great accuracy, analyzing medical texts could be automated and strain could be removed from people having to read through them manually. Since journals and other medical text often are very sensitive and should be handled with care due to privacy, a method for constructing these models without the need for real annotated journals would be a big step in the right direction. During this thesis we have implemented two models for solving the problem of NER for medical texts in Swedish. Both models were created from lists of seedterms, which consist of words and phrases found in medical taxonomies which we assume belong to one of the three categories. Training data were extracted from the health-care magazine Lakartidningen as well as a subset of Swedish Wikipedia. The first model implemented is based on the work of Zhang and Elhadad [23] where a vector representation is calculated for the possible words and compared against vectors calculated the same way for the different categories. The results of our implementation is on par with the results given by Zhang and Elhadad which suggests that this method works as well for Swedish as it does for English. The second model implemented is based on recurrent neural networks and is built from the same seed-terms as the first model but instead of using only vectorcalculations for classification the network is trained to automatically classify words on character-basis, reading the text both forwards and backwards at the same time. Solving the problem of NER using only unsupervised methods is inherently hard and techniques for solving the problem are not quite there yet. However, by just improving them bit by bit will in the end lead to great results.
Gay Men’s Identity Negotiation Strategies within the Methodist Church of Southern Africa in Grahamstown, South Africa

ABSTRACT This paper explores the experiences of gay men within the Methodist Church of Southern Africa in Grahamstown in the Eastern Cape, South Africa. Their experiences of the church are explored in relation to gay identity creation and negotiation in a religious environment. Six participants spoke about how they negotiate their intersecting sexual and religious identities. While adopting a qualitative approach utilising in-depth open narrative interviews to explore the stories of the research participants, this study applied Brekhus’s theoretical model, which was later employed by Schnoor to classify and categorise gay men into ideal types of gay methodist lifestylers, gay methodist commuters and gay methodist integrators in order to analyse the participants’ gay identity negotiation strategies within the MCSA church in Grahamstown.
Relationship Between Child Perfectionism and Psychological Disorders

Objective: Perfectionism is one of the variables related to the correct emotional development or with the appearance of clinical symptomatology in childhood. A study has been designed to evaluate the differential effect that each dimension of perfectionism (external pressure, self-exigency, and negative self-evaluation) has in a Spanish children sample of general population for each of the following clinical aspects: irritability, worthlessness feelings, thinking problems, and psychophysiological symptoms. Method: By a random cluster sampling, a total of 2,636 children from 8 to 12 years (M = 9.9, SD = 1.2; 51.3% boys) took part in this research. A serial multiple mediators model was used to check the relation between external pressure over the clinical symptoms through self-exigency and negative-self-evaluation. Results: The results have shown a predictive effect of external pressure over a great variety of clinical symptomatology (irritability, worthlessness, thinking problems, and psychophysiological symptoms), a relation mediated by self-exigency and negative self-evaluation. These relations suggest that external pressure and negative self-evaluation are maladaptive dimensions as they predict the appearance of symptomatology, being the level of self-exigency a protective dimension and favoring the child’s positive development. Conclusions: In consequence, these results point to the importance of the study of these variables that can generate difficulties in childhood in order to improve children’s quality of life and their correct development.
Faktor-Faktor yang Mempengaruhi Kriminalitas di Indonesia Tahun 2011-2016 dengan Regresi Data Panel

<p>Criminality in Indonesia is increasing every year, therefore an effort is needed to reduce criminality in Indonesia, one of which can be used by knowing which factors influence the increase of criminality. This paper discusses the factors that influence criminality by using panel data regression analysis. Unemployment, domestic violence cases, narcotics cases, embezzlement cases, and fraud cases have positive effect on the amount of criminality with <em>R</em><em><sup>2</sup></em> of 0,85823 or 85,823%. </p><p><strong>Keywords</strong><strong> : </strong>panel regression analysis, crime, Indonesia</p>
Determinants of Companies' Propensity to Patent

What determines companies to file patents? To answer this question we present a systematic review, in which 22 empirical studies published in scientific periodicals were selected. Based on the descriptive analysis of these studies, a framework is proposed that brings together a set of explanatory variables that influence the propensity to patent in internal and external factors. The cumulative results of the reviewed articles suggest a positive correlation of firm size and R & D with the propensity to patent. A unanimous result among the articles is that the Industrial Sector in which the company is inserted has a significant influence on the propensity to patent. Regarding the variables Age, Collaboration Network and Competition, the results of the research were divergent, indicating a positive, negative or non-significant relationship. However, these determinants are still poorly understood due to the divergence of the research results.