Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for learning photographic composition preferences from gameplay data

The automatic evaluation of images in computational cinema and photography is a challenging problem. There are neither comprehensive rules nor adequate training data to develop an expert system. This thesis presents the design and implementation of a computer game for synthesizing image data, and an experimental framework for learning photographic composition preferences from online ratings. The first topic addressed is the development of Panorama, a computer game for photographic composition research. Panorama generates images through gameplay by simulating the task of photography in a virtual environment. The synthesized photographs are automatically annotated from their underlying representation, and contribute to a corpus of images with well-defined visual features. Both the game and data are publicly available to support research in image analysis. The second topic is a photograph learning experiment using data from the Panorama corpus. In this section, machine learning is used for predicting user preferences of images, based on computed visual features. Image preference ratings are acquired by crowdsourcing to consider subjectivity across many individuals. Using this unique data collection process, it is shown how the framework can be applied to reason about image quality with respect to photographic composition.
Generating Massive Unstructured Meshes for OpenFOAM

OpenFOAM is an open source computational fluid dynamics (CFD) package with a large user base from many areas of engineering and science. This whitepaper documents an enablement tool called PMSH that was developed to generate multi-billion element unstructured tetrahedral meshes for OpenFOAM. PMSH is developed as a wrapper code around the popular open source sequential Netgen mesh generator. Parallelization of the mesh generation process is carried out in five main stages: (i) generation of a coarse volume mesh (ii) partitioning of the coarse mesh to get sub-meshes, each of which is processed by a processor (iii) extraction and refinement of coarse surface sub-meshes to produce fine surface sub-meshes (iv) re-meshing of each fine surface sub-mesh to get the final fine volume mesh (v) matching of partition boundary vertices followed by global vertex numbering. An integer based barycentric coordinate method is developed for matching distributed partition boundary vertices. This method does not have precision related problems of floating point coordinate based vertex matching. Test results obtained on an SGI Altix ICE X system with 8192 cores and 14 TB of total memory confirm that our approach does indeed enable us to generate multi-billion element meshes in a scalable way. PMSH tool is available at https://code.google. com/p/pmsh/.
Robust feedback model predictive control of norm-bounded uncertain systems

This thesis is concerned with the Robust Model Predictive Control (RMPC) of linear discrete-time systems subject to norm-bounded model-uncertainty, additive disturbances and hard constraints on the input and state. The aim is to design tractable, feedback RMPC algorithms that are based on linear matrix inequality (LMI) optimizations. The notion of feedback is very important in the RMPC control parameterization since it enables effective disturbance/uncertainty rejection and robust constraint satisfaction. However, treating the state-feedback gain as an optimization variable leads to non-convexity and nonlinearity in the RMPC scheme for norm-bounded uncertain systems. To address this problem, we propose three distinct state-feedback RMPC algorithms which are all based on (convex) LMI optimizations. In the first scheme, the aforementioned non-convexity is avoided by adopting a sequential approach based on the principles of Dynamic Programming. In particular, the feedback RMPC controller minimizes an upper-bound on the cost-to-go at each prediction step and incorporates the state/input constraints in a non-conservative manner. In the second RMPC algorithm, new results, based on slack variables, are proposed which help to obtain convexity at the expense of only minor conservatism. In the third and final approach, convexity is achieved by re-parameterizing, online, the norm-bounded uncertainty as a polytopic (additive) disturbance. All three RMPC schemes drive the uncertain-system state to a terminal invariant set which helps to establish Lyapunov stability and recursive feasibility. Low-complexity robust control invariant (LC-RCI) sets, when used as target sets, yield computational advantages for the associated RMPC schemes. A convex algorithm for the simultaneous computation of LC-RCI sets and the corresponding controller for norm-bounded uncertain systems is also presented. In this regard, two novel results to separate bilinear terms without conservatism are proposed. The results being general in nature also have application in other control areas. The computed LC-RCI sets are shown to have substantially improved volume as compared to other schemes in the literature. Finally, an output-feedback RMPC algorithm is also derived for norm-bounded uncertain systems. The proposed formulation uses a moving window of the past input/output data to generate (tight) bounds on the current state. These bounds are then used to compute an output-feedback RMPC control law using LMI optimizations. An outputfeedback LC-RCI set is also designed, and serves as the terminal set in the algorithm.
3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training

In this work, we demonstrate that 3D poses in video can be effectively estimated with a fully convolutional model based on dilated temporal convolutions over 2D keypoints. We also introduce back-projection, a simple and effective semi-supervised training method that leverages unlabeled video data. We start with predicted 2D keypoints for unlabeled video, then estimate 3D poses and finally back-project to the input 2D keypoints. In the supervised setting, our fully-convolutional model outperforms the previous best result from the literature by 6 mm mean per-joint position error on Human3.6M, corresponding to an error reduction of 11%, and the model also shows significant improvements on HumanEva-I. Moreover, experiments with back-projection show that it comfortably outperforms previous state-of-the-art results in semi-supervised settings where labeled data is scarce. Code and models are available at https://github.com/facebookresearch/VideoPose3D
English for academic purposes

Introduction Over the past 25 years TESL/TEFL in universities/colleges and other academic settings – or in programmes designed to prepare non-native users of English for English-medium academic settings – has grown into a multi-million-dollar enterprise around the world. Teaching those who are using English for their studies differs from teaching English to those who are learning for general purposes only, and from teaching those who are learning for occupational purposes. English for academic purposes (EAP) is not only a teaching approach. It is also a branch of applied linguistics consisting of a significant body of research into effective teaching and assessment approaches, methods of analysis of the academic language needs of students, analysis of the linguistic and discoursal structures of academic texts, and analysis of the textual practices of academics. Background The practice of teaching EAP has been with us for a long time – wherever individual teachers of non-native students in academic contexts have taught with a view to the context rather than only to the language – but the term ‘EAP’ first came into general use through the British organisation SELMOUS (Special English Language Materials for Overseas University Students), which was formed in 1972. Although the organisation's first collection of papers from its annual meeting was titled English for academic purposes (Cowie and Heaton 1977), it didn't change its name to include the term until 1989, when it became BALEAP (British Association of Lecturers in English for Academic Purposes).
Disease activity during the first year predicts clinical long-term outcomes: impact of fingolimod in the TRANSFORMS phase III trial and its extension (P7.205)

OBJECTIVES : To assess whether year-1 in-study MRI and/or relapses predict relapses or 6-month confirmed disability progression (6M-CDP), measured by EDSS, over the following 36 months in the TRANSFORMS population. To explore outcomes in year-2 following switch from IFN-β to fingolimod at year-1. BACKGROUND : Different approaches have been applied to explore predictors of long-term clinical outcomes, including early on-treatment MRI activity and/or relapses. DESIGN/METHODS : This is a post-hoc analysis of the 36-month follow-up of the double-blind, randomized, phase-III TRANSFORMS study of fingolimod (0.5mg/1.25mg daily) versus IFN-β (30μg weekly). On entering the extension, patients randomized to IFN-β were re-randomized to either fingolimod 0.5mg or 1.25mg (switch group). Unadjusted logistic regression was used to assess whether MRI-activity, defined as per Prosperini 2014 1 (蠅1 T1 Gd-enhancing lesion or 蠅2 T2 lesions) and/or 蠅1 relapses during year-1 (M0-M12) of treatment, was predictive of relapses or 6M-CDP from M12-M24 and M12-M48. RESULTS : 1292 patients were randomized in the core phase of TRANSFORMS, with 1030 (79.7[percnt]) entering the extension phase. Predictors for either relapses or 6M-CDP were MRI-activity in year-1 (M12-24 OR:1.359; 95[percnt] CI:0.958-1.926; p=0.0851; M12-M48 OR:1.701; 95[percnt] CI:1.246-2.322; p=0.0008); relapses in year-1 (M12-24 OR:2.096; 95[percnt] CI:1.654-2.655; p<0.0001; M12-48 OR:2.008; 95[percnt] CI:1.541-2.616; p<0.0001); combined MRI-activity and relapses in year-1 (M12-M24 OR:2.695; 95[percnt] CI:1.643-4.420; p<0.0001; M12-M48 OR:3.030; 95[percnt] CI:1.761-5.212; p<0.0001). The proportion of patients with MRI-activity and relapses during M0-M12 was 12.9[percnt] and 4.9[percnt] for IFN-β and fingolimod 0.5 mg, respectively. At M12-24 the rate remained low (3.2[percnt]) for continuous fingolimod and switch from IFN-β to fingolimod decreased the rate to 3.9[percnt]. CONCLUSIONS : In TRANSFORMS, MRI-activity and/or relapses during year-1 were predictors of later clinical outcomes. Switching from IFN-β to fingolimod after year-1 reduced the proportion of patients experiencing MRI-activity and relapses. 1.Prosperini et al. 2014 Mult Scler 20:566. Study Supported by: Novartis Pharma AG Disclosure: Dr. Repovic has received personal compensation for activities with Biogen Idec, Teva Neuroscience, Questcor, Genzyme, Novartis, Pfizer Inc., and EMD Serono as a consultant and/or speaker. Dr. Burton has received personal compensation for activities with Novartis Pharmaceuticals Corporation as an employee. Dr. Meng has received personal compensation for activities with Novartis as an employee. Dr. Meier has received personal compensation for activities with Novartis as an employee. Dr. Barkhof has received personal compensation for activities with Bayer Schering Pharma, Sanofi, Genzyme, Biogen Idec, Teva, Merck Serono, Novartis, Roche, Synthon BV, and Janssen Research as a consultant.
AS IF THROUGH ANOTHER'S EYES: A STUDY OF PEER TUTORING AND FIRST-YEAR STUDENTS' REVISION BEHAVIORS

This dissertation explores how first-year students use the feedback they receive from others as they revise their writing. Of particular interest is the feedback that students receive from writing center peer tutors. Through analysis of the feedback students received from various individuals (classroom peers, peer tutors, and teachers) in two sites (first year composition classrooms and the writing center), I clarify the effects responses from these individuals have on students' revision. To determine the role tutorials, specifically, play in students' development as revisers, I conducted a semester-long study of writing at a liberal arts university. I used two major research strategies: (1) a questionnaire about students' practices of revision and (2) case studies of nine first-year composition students. Data has been collected from interviews, writing center tutorials, first-year composition class meetings, and drafts and revisions of students' papers. This dissertation challenges several established claims within composition studies: that first-year students revise in limited ways; that they usually focus on word-level issues when they do revise; and that the most effective revisions are more reader- than writer-based. In fact, students I studied report that they do have strategies for dealing with their whole texts. Moreover, though many have argued that "experienced writers" revise in a reader-based way, this data suggests that students revise most substantially when readers find a way to help the writers control their words and convey their intentions. Finally, this dissertation challenges the assumption that because writing centers help make "better writers, not better writing," writing center scholarship should exclude student writing as an object of study. Sustained study of the drafts students bring with them to the writing center and the revised versions they produce after a tutorial offer writing center and composition studies scholars alike a fuller understanding of the role that collaboration generally and peer tutoring specifically play in students' development as writers and revisers.
THE ROLE OF SELF-EFFICACY IN PATIENTS WITH COMORBID TYPE 2 DIABETES AND CORONARY ARTERY DISEASE IN THE BYPASS ANGIOPLASTY REVASCULARIZATION INVESTIGATION 2 DIABETES (BARI 2D) TRIAL

OBJECTIVES: Type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) are highly comorbid conditions that are affected by psychological factors, such as self-efficacy. Psychological factors can either hinder or promote medical interventions. Self-efficacy, the belief that one is able to make changes necessary for self-management, is associated with glycemic control and cardiac symptom burden, as well as behaviors that affect CAD prevention and outcomes.METHODS: Using data from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial, we assessed the relationship between self-efficacy and the treatment, risk factor control, and cardiac outcomes of patients with T2DM and CAD.RESULTS: The first paper (N=889) showed no significant relationships between self-efficacy and randomized treatment for CAD (revascularization vs. medical therapy β=0.06, p=0.66) and T2DM (insulin sensitizers vs. insulin providers β=0.06, p=0.65) in patients with baseline self-efficacy scores ≤8. The second paper (N=1,562) verified a negative association between baseline self-efficacy and follow-up HbA1c (β=-0.03, p<.001) and a positive association with self-efficacy and physical functioning in which time negatively modified the association(interaction p=0.02). A lagged association (feedback loop) was shown between self-efficacy and HbA1c, physical functioning, and BMI over time. The feedback loops were stronger in White non-Hispanic patients compared to minority patients. In the third paper (N=1,817), poor baseline self-efficacy was associated with an increased risk of a composite endpoint of death/myocardial infarction/stroke (hazard ratio [HR] =1.34, p=0.01), subsequent revascularizations (HR=1.30, p=0.004), subsequent PCIs (HR=1.43, p<.001), and angina (odds ratio [OR] =1.11, p<.001) compared to Fair-Excellent self-efficacy, but not after adjusting for baseline covariates. A decrease in self-efficacy from baseline to Year 1 was positively associated with all-cause mortality (adjusted HR=2.32, p<.001) and death/MI/stroke (adjusted HR=1.79, p<.001). CONCLUSIONS: In summary, self-efficacy was associated with clinical risk factors and cardiac outcomes in patients with CAD and T2DM. This is of public health significance because it stresses the importance of improving a patient's confidence in managing their conditions outside of the medical setting.
Residual Vibration Suppression Using Simple Motion Trajectory for Mechanical Systems

This paper proposes motion-trajectory generation for mechanical systems that can be widely used in industrial applications. Many industrial systems, such as feed drive tables, gantry cranes, and material handling systems, are operated using S-curve acceleration and deceleration trajectory, and simple controllers that allow only such a simple motion trajectory are employed from the viewpoints of controller hardware and implementation cost efficiency. This study deals with simple mechanical dynamics including vibration properties and derives a necessary and sufficient condition for the motion trajectory to suppress residual vibration. Simulation and experimental results demonstrate the validity of the proposed conditions.
Architecting Efficient Data Centers

Architecting Efficient Data Centers by David Max Meisner Chair: Thomas F. Wenisch Data center power consumption has become a key constraint in continuing to scale Internet services. As our society’s reliance on “the Cloud” continues to grow, companies require an ever-increasing amount of computational capacity to support their customers. Massive warehouse-scale data centers have emerged, requiring 30MW or more of total power capacity. Over the lifetime of a typical high-scale data center, power-related costs make up 50% of the total cost of ownership (TCO). Furthermore, the aggregate effect of data center power consumption across the country cannot be ignored. In total, data center energy usage has reached approximately 2% of aggregate consumption in the United States and continues to grow. This thesis addresses the need to increase computational efficiency to address this growing problem. It proposes a new classes of power management techniques: coordinated full-system idle low-power modes to increase the energy proportionality of modern servers. First, we introduce the PowerNap server architecture, a coordinated full-system idle lowpower mode which transitions in and out of an ultra-low power nap state to save power during brief idle periods. While effective for uniprocessor systems, PowerNap relies on full-system idleness and we show that such idleness disappears as the number of cores per processor continues to increase. We expose this problem in a case study of Google Web search in which we demonstrate that coordinated full-system active power modes are necessary to reach energy proportionality and that PowerNap is ineffective because of a lack of idleness. To recover full-system idleness, we introduce DreamWeaver, architectural support for deep sleep. DreamWeaver allows a server to exchange latency for full-system
Emergency management: penetrating eye injuries and intraocular foreign bodies

COMMUNITY EYE HEALTH JOURNAL | VOLUME 31 | NUMBER 103 | 2018 Up to 40% of penetrating eye injuries are complicated by the presence of an intraocular foreign body (IOFB). 1,2 It may be toxic (iron, copper, vegetable matter) or inert (glass or plastic). Vision loss may result from the mechanical injury or from post-traumatic complications such as endophthalmitis, retinal detachment, metal toxicity and sympathetic ophthalmia.2 Prompt diagnosis, referral, removal of the IOFB and surgical repair will help to preserve the visual acuity and the globe anatomy.
Partial Convolution based Padding

In this paper, we present a simple yet effective padding scheme that can be used as a drop-in module for existing convolutional neural networks. We call it partial convolution based padding, with the intuition that the padded region can be treated as holes and the original input as non-holes. Specifically, during the convolution operation, the convolution results are re-weighted near image borders based on the ratios between the padded area and the convolution sliding window area. Extensive experiments with various deep network models on ImageNet classification and semantic segmentation demonstrate that the proposed padding scheme consistently outperforms standard zero padding with better accuracy.
Factors Causing Students' Drop out from Education Programmes at the Open University of Tanzania: a Case of Tanga Region Centre

The study on factors causing students' dropout from the Open University of Tanzania (OUT) focused on selected districts of Tanga Region. The selected districts are Korogwe, Handeni, Lushoto, Muheza and Tanga Urban. The main instruments for data collection were interview guides and focused group discussion (FGD). The result of the study showed that, students of the OUT in Tanga region dropped out from education programmes due to students' personal factors. Under this category, students dropped out due to failure to pay tuition fees, the need for realizing personal objectives e.g. promotion while studying at OUT, students' lack of seriousness in OUT studies, family barriers, students failing to write assignments and difficulty incomprehending some of the OUT courses such as Philosophy of Education (OED102) and Calculus 1 (OMTI0l). The second category of factors which caused OUT students' dropout in Tanga Region were those related to work environments. Under this category, students were found to dropout of the education programmes of education due to excessive teaching load at work places, collision of students' duties and OUT schedule and discouraging work places culture. The OUT administration was not found to cause students' dropout in Tanga region. This study recommends that, the Open University of Tanzania needs to increase face-to-face sessions at least once every month. Another recommendation was the government through its ministry of Education and Vocational Training (MoEVT) to offer to OUT students, the necessary study requirements such as money for buying books. Lastly, the organization managers must take into consideration the Government Circular no.1 of 2003, which directs them to give OUT students enough time for study
Pengaruh Pemungutan Pajak Hotel dan Pajak Hiburan Terhadap Peningkatan Pendapatan Asli Daerah Kota Medan

Penelitian ini bertujuan untuk mengetahui hasil pemungutan, dan ada atau tidaknya pengaruh pemungutan pajak hotel dan pajak hiburan terhadap peningkatan pendapatan asli daerah Kota Medan. Pendekatan penelitian yang digunakan dalam penelitian ini adalah pendekatan asosiatif. Penyusunan skripsi ini menggunakan teknik pengumpulan data dengan teknik dokumentai dan kepustakaan. Hipotesis diuji dengan menggunakan uji t. Hasil penelitian yang di lakukan di BPPRD Kota Medan menunjukkan bahwa pemungutan pajak hotel dan hiburan mengalami peningkatan tetapi masi ada yang tidak mencapai target. Variabel yang digunakan adalah pajak hotel dan pajak hiburan sebagai variabel bebas dan pendapatan asli daerah sebagai variabel terikat. Untuk mengetahui pengaruh pemungutan pajak hotel terhadap peningkatan pendapatan asli daerah Kota Medan, dilakukan pengujian hipotesis statistik t -. 433 dengan probabilitas sig 0,666>0,05 dengan demikian maka disimpulkan bahwa tidak menemukan adanya pengaruh positif signifikan pemungutan pajak hotel terhadap peningkatan pendapatan asli daerah Kota Medan dan nilai thitung berbentuk negatif. Dan untuk mengetahui pengaruh pemungutan pajak hiburan terhadap peningkatan pendapatan asli daerah Kota Medan, dilakukan pengujian hipotesis statistik t 2.129 dengan probabilitas sig 0,038<0,05 dengan demikian H2 diterima maka disimpulkan bahwa pemungutan pajak hotel berpengaruh signifikan terhadap peningkatan pendapatan asli daerah Kota Medan.