Miracle-dz/UniFAR-FTUs huggingface dataset:
The Mobile Data Challenge: Big Data for Mobile Computing Research

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of related mobile data analysis methodologies. First we review the Lausanne Data Collection Campaign (LDCC) an initiative to collect unique, longitudinal smartphone data set for the basis of the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC; describe the specific data sets used in each of them; and discuss some of the key aspects in order to generate privacy-respecting, challenging, and scientifically relevant mobile data resources for wider use of the research community. The concluding remarks will summarize the paper.
Face analysis using 3D morphable models

Face analysis aims to extract valuable information from facial images. One effective approach for face analysis is the analysis by synthesis. Accordingly, a new face image synthesised by inferring semantic knowledge from input images. To perform analysis by synthesis, a genera- tive model, which parameterises the sources of facial variations, is needed. A 3D Morphable Model (3DMM) is commonly used for this purpose. 3DMMs have been widely used for face analysis because the intrinsic properties of 3D faces provide an ideal representation that is immune to intra-personal variations such as pose and illumination. Given a single facial input image, a 3DMM can recover 3D face (shape and texture) and scene properties (pose and illumination) via a fitting process. However, fitting the model to the input image remains a challenging problem. One contribution of this thesis is a novel fitting method: Efficient Stepwise Optimisation (ESO). ESO optimises sequentially all the parameters (pose, shape, light direction, light strength and texture parameters) in separate steps. A perspective camera and Phong reflectance model are used to model the geometric projection and illumination respectively. Linear methods that are adapted to camera and illumination models are proposed. This generates closed-form solu- tions for these parameters, leading to an accurate and efficient fitting. Another contribution is an albedo based 3D morphable model (AB3DMM). One difficulty of 3DMM fitting is to recover the illumination of the 2D image because the proportion of the albedo and shading contributions in a pixel intensity is ambiguous. Unlike traditional methods, the AB3DMM removes the illumination component from the input image using illumination normalisation methods in a preprocessing step. This image can then be used as input to the AB3DMM fitting that does not need to handle the lighting parameters. Thus, the fitting of the AB3DMM becomes easier and more accurate. Based on AB3DMM and ESO, this study proposes a fully automatic face recognition (AFR) system. Unlike the existing 3DMM methods which assume the facial landmarks are known, our AFR automatically detects the landmarks that are used to initialise our fitting algorithms. Our AFR supports two types of feature extraction: holistic and local features. Experimental results show our AFR outperforms state-of-the-art face recognition methods.
The effects of stereotype activation on women's reactions to leadership situations, or, How reading Cosmo might prevent you from becoming CEO

The present experimental study investigated the effect of stereotype activation on women's responses to a leadership situation. Participants were exposed to either gender-stereotypic or gender -counterstereotypic magazine advertisements picturing women and then performed a leadership task involving two confederate s. Results supported the prediction that participants exposed to stereotypic advertisements would exhibit more negative reactions to the leadership . situ~tion than those exposed to counterstereotypic advertisements such that they reported lower perceived performance, self-esteem, and well-being. Sex-role orientation moderated this effect such that' advertisements had a stronger effect on feminine-oriented participants' domain identification, intent to lead in the future, and experienced cognitive load than on masculine oriented ·participants ' responses. In the opposite direction as pr edicted, participants in the gendercounterstereotypic condition indicated a higher relat ionship-oriented leadersh ip style than those in the gender-stereotypic condition. Sex-role orientation moderated this effect such that feminine-oriented participants in the gender-counterstereotypic condition indicated a higher relationship-oriented leadership style than participants i~ any other group.
On the Use of Dual-Polarized SAR Data for Oil Spill Observation

In this paper a novel approach for oil spill observation, based on partially polarimetric Synthetic Aperture Radar (SAR) data, is proposed. A model which relates the co-polarized phase difference (CPD) to the sea surface scattering mechanism with and without slicks is developed. Experiments accomplished over multi-look complex (MLC) C-Band SAR data, show that the CPD approach is useful both to observe oil spills and to distinguish between oil spills and biogenic slicks.
Sound static deadlock analysis for C/Pthreads

We present a static deadlock analysis for C/Pthreads. The design of our method has been guided by the requirement to analyse real-world code. Our approach is sound (i.e., misses no deadlocks) for programs that have defined behaviour according to the C standard and the Pthreads specification, and is precise enough to prove deadlock-freedom for a large number of such programs. The method consists of a pipeline of several analyses that build on a new context- and thread-sensitive abstract interpretation framework. We further present a lightweight dependency analysis to identify statements relevant to deadlock analysis and thus speed up the overall analysis. In our experimental evaluation, we succeeded to prove deadlock-freedom for 292 programs from the Debian GNU/Linux distribution with in total 2.3 MLOC in 4 hours.
Overapproximative arm occupancy prediction for human-robot co-existence built from archetypal movements

Human motion is fast and hard to predict. To implement a provably safe collision-avoidance strategy for robots in collaborative spaces with humans, an overapproximative prediction of the occupancy of the human is required, which needs to be calculated faster than real time. We present a method for computing volumes containing the entire possible future occupancy of the human, given its state, faster than real time. The dynamic model of the human is built from analysing a set of archetypal movements performed by test subjects. The occupancy prediction is tested on a publicly available database of motion capture data, and shown to be overapproximative for all movements relating to everyday activities, sport and dance. Our novel algorithm is useful to guarantee safety in human-robot collaboration scenarios.
Imagable 4 T 1 model for the study of late stage breast cancer

Background: The 4T1 mouse mammary tumor cell line is one of only a few breast cancer models with the capacity to metastasize efficiently to sites affected in human breast cancer. Here we describe two 4T1 cell lines modified to facilitate analysis of tumor growth and metastasis and evaluation of gene function in vivo. New information regarding the involvement of innate and acquired immunity in metastasis and other characteristics of the model relevant to its use in the study of late stage breast cancer are reported. Methods: The lines were engineered for stable expression of firefly luciferase to allow tracking and quantitation of the cells in vivo. Biophotonic imaging was used to characterize growth and metastasis of the lines in vivo and an improved gene expression approach was used to characterize the basis for the metastatic phenotype that was observed. Results: Growth of cells at the primary site was biphasic with metastasis detected during the second growth phase 5–6 weeks after introduction of the cells. Regression of growth, which occurred in weeks 3–4, was associated with extensive necrosis and infiltration of leukocytes. Biphasic tumor growth did not occur in BALB/c SCID mice indicating involvement of an acquired immune response in the effect. Hematopoiesis in spleen and liver and elevated levels of circulating leukocytes were observed at week 2 and increased progressively until death at week 6–8. Gene expression analysis revealed an association of several secreted factors including colony stimulatory factors, cytokines and chemokines, acute phase proteins, angiogenesis factors and ECM modifying proteins with the 4T1 metastatic phenotype. Signaling pathways likely to be responsible for production of these factors were also identified. Conclusion: The production of factors that stimulate angiogenesis and ECM modification and induce hematopoiesis, recruitment and activation of leukocytes suggest that 4T1 tumor cells play a more direct role than previously appreciated in orchestrating changes in the tumor environment conducive to tumor cell dissemination and metastasis. The new cell lines will greatly facilitate the study of late stage breast and preclinical assessment of cancer drugs and other therapeutics particularly those targeting immune system effects on tumor metastasis. Published: 9 August 2008 BMC Cancer 2008, 8:228 doi:10.1186/1471-2407-8-228 Received: 24 April 2008 Accepted: 9 August 2008 This article is available from: http://www.biomedcentral. com/1471-2407/8/228 © 2008 Tao et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Subsidizing Entertainment Projects As A Strategy For Urban Economic Development: A Cost-Benefit Analysis Of Miami’s American Airlines Arena

OF THE THESIS SUBSIDIZING ENTERTAINMENT PROJECTS AS A STRATEGY FOR URBAN ECONOMIC DEVELOPMENT: A COST-BENEFIT ANALYSIS OF MIAMI’S AMERICAN AIRLINES ARENA by Marcos Feldman Florida International University, 2005 Miami, Florida Professor Guillermo Grenier, Major Professor This thesis evaluates the practice of subsidizing entertainment projects as economic development strategy through a case study of the American Airlines Arena (AAA). Subsidy proponents argued that it would generate new tax revenue and jobs, and enhance the city’s image and pride. This rationale neglects factors that mitigate the economic impact of arenas and fails to consider the social costs. The AAA subsidy is evaluated using a cost-benefit method that has been underutilized in academic research. The economic impact is analyzed by estimating the fiscal return on the public’s investment and the number and quality of new jobs created. The social costs are considered in light of Miami’s economic development history and the policy implications are discussed. The AAA subsidy results in hundreds of millions of dollars in losses over the term of the public-private partnership and created a negligible number of low quality jobs. Furthermore, the AAA subsidy may have exacerbated relations between residents
The early response in fMRI: A modeling approach

A mathematical model is presented to study the generation of the early response phenomenon in fMRI. Initially, we demonstrate that a simple combination of the changes taking place in cerebral blood volume and flow could create the transient early signal decrease, by analyzing their effects on total per voxel deoxyhemoglobin content. Also, we examine the traditional paradigm for the early response: that it may be caused by an early burst of oxidative metabolism and conclude that such changes also explain the early transient response. We suggest that the volume effect may play a role in the generation of the early response phenomenon along with an early upregulation of oxidative metabolism, and that this role may be important if the early response phenomenon is shown to occur at the level of the venous blood pool, and not just at the level of the capillary bed. Magn Reson Med 1999:41:550–554, 1999. © 1999 Wiley‐Liss, Inc.
Fracturing material models based on micromechanical concepts: recent advances

The paper summarizes three recent advances in the modeling of inelastic behavior and fracturing of concrete, achieved at Northwestern University and Politecnico di Milano. First, improvements of microplane model M4 which allow a more realistic simulation of frictional shear and of lateral strains in tensile fracturing are presented. Second, development of microplane model M5 which can capture the transition from distributed cracking damage to complete cohesive fracture is described and its novel concept—a combination of kinematic and static constraints— is discussed. Third, a new lattice type model for concrete, which can simulate (with the same material parameters) tensile fracturing, complete cohesive fracture, compression-shear behavior with softening at zero or mild confinement, and response at confined compression at which there is only hardening (i.e., no peal and no postpeak softening), is outlined.
A Second Order Virtual Node Method for Poisson Interface Problems on Irregular Domains

We present a second order accurate, geometrically flexible and easy to implement method for solving the variable coe cient Poisson equation with interfacial discontinuities on an irregular domain. We discretize the equations using an embedded approach on a uniform Cartesian grid employing virtual nodes at interfaces and boundaries. A variational method is used to define numerical stencils near these special virtual nodes and a Lagrange multiplier approach is used to enforce jump conditions and Dirichlet boundary conditions. Our combination of these two aspects yields a symmetric positive definite discretization. In the general case, we obtain the standard 5-point stencil away from the interface. For the specific case of interface problems with continuous coe cients, we present a discontinuity removal technique that admits use of the standard 5-point finite di erence stencil everywhere in the domain. Numerical experiments indicate second order accuracy in L 1 .
Developing a Chunk-based Grammar Checker for Translated English Sentences

Machine Translation systems expect target language output to be grammatically correct. In Myanmar-English statistical machine translation system, target language output (English) can often be ungrammatical. To address this issue, we propose an ongoing chunk-based grammar checker by using trigram language model and rule based model. It is able to solve distortion, deficiency and make smooth the translated English sentences. We identify the sentences with chunk levels and generate context free grammar (CFG) rules for recognizing grammatical relations of chunks. There are three main processes to build a grammar checker: checking the sentence patterns in chunk level, analyzing the chunk errors and correcting the errors. According to experimental results, this checker can detect simple, compound and complex sentence types for declarative and interrogative sentences. This system is useful for reducing grammar errors of target language in Myanmar-English machine translation system.
Fostering Hope and Closing the Academic Gap: An Examination of College Retention for African-American and Latino Students who Participate in the Louis Stokes Alliance Minority Participation Program (Learning Community) While Enrolled in a Predominately White Institution

i Dedication . iii Acknowledgments.iv List of Tables . viii CHAPTER I: THE ISSUE Introduction and Background . 1 Purpose Statement . 3 Significance . 4 Personal Journey . 7 Key terms & Concepts . 11 CHAPTER II: LITERATURE REVIEW Organization of the Literature . 12 Defining Retention and Persistence . 13 STEM Education Reform . 15 Diversity and Learning Communities . 18 Retention of Students and Faculty of Color in Higher Education . 19 Framework: Tinto‘ Student Integration Theory . 22 General Issues with Retention Models . 25 Cultural Issues with Tinto Student Integration Theory . 26 Students of Color Engagement, Persistence & College Climate . 29 Literature on Learning Communities . 34 Theoretical Foundations of Learning Communities . 35 Types of Learning Communities . 39 Challenges for Learning Communities . 42 Benefits and Strengths of Learning Communities . 43 Collaboration, Partnerships and Shared community . 45 Stages of Community Development . 47 Summary of Literature Review . 48 CHAPTER III: METHODOLOGY Introduction . 49 The Research Approach . 50 Research Setting . 54 vii Research Participants . 55 Data Collection & Techniques . 61 Data Analysis, Management & Interpretation . 66 Accuracy, Trustworthiness & Soundness of the Design . 70 Limitations of the Study . 71 Chapter Summary . 72 Moving Forward . 73 CHAPTER IV: RESULTS & FINDINGS Introduction and Overview of the Results and Findings . 74 Theme #1 From a High school diploma to a College degree . 76 Personal influences and Self-motivation Theme #2 Navigating the College Terrain . 80 First Generation students and the LSAMP Program Theme #3 Surprise, Surprise . 86 College Persistence & Discrimination Theme #4 A Sense of Belonging . 89 College Persistence & Retention Chapter Summary . 93 CHAPTER V: DISCUSSION & IMPLICATIONS Linking Findings . 94 Summary of data highlights . 97 Study Summary . 99 Theme #1 From a high school diploma to a college degree . 100 Theme #2 Navigating the college terrain . 101 Theme #3 Surprise, Surprise . 103 Theme #4 A Sense of Belonging . 106 Implications for Policy and for Practice . 107 Recommendations for Future Research . 109 Conclusion . 110 REFERENCES . 112 Appendix A: Informed Consent Form . 128 Appendix B: Participant Demographic Questionnaire . 130 Appendix C: Focus Group Guide, Structure, Questions . 132 Appendix D: Face to Face Interview Questions . 135
Deterministic solutions of the Boltzmann equation for charge transport in graphene on substrates

In this paper, the low and high field mobilities of graphene on substrates are studied, by means of deterministic solutions, obtained using a Discontinuous Galerkin (DG) numerical scheme, of the semiclassical Boltzmann equation for charge transport in graphene. It is shown that there is a strong dependence on the distance between the impurities and the graphene layer with significant changes both in the low and high field mobility curves. We remark that the use of a DG scheme avoids the intrinsic noise typical of the Direct Monte Carlo Simulation (DSMC) results and allows to evaluate the low field mobility with considerable accuracy, making less ambiguous the comparison with experimental measurements.
Examination of Attitude Levels of Academic Personnel Towards Political Participation and Determination of Its Relationships with Organizational Commitment

The aim of this study was to determine the attitudes of academic personnel working in faculties of sports sciences in universities towards political participation; to examine whether there was a significant difference between the attitudes of academicians towards political participation according to demographic characteristics; to determine the relationships between academic personnel’s attitudes towards political participation and their organizational commitment. The study, which was designed in the correlational survey model of the general survey models, was carried out together with 204 academicians working in universities in Central Anatolia Region. The data of the study were collected by means of using the Political Participation Scale and Organizational Commitment Scale. Descriptive statistics, difference tests and Pearson correlation coefficient were used in the process of data analysis. At the result of the research, it was determined that the feelings of political activity and the feelings of alienation of academic personnel as well as their political perceptions arising from the institution were generally at a medium level. It was determined that there was a positive relationship between the feelings of political activity and the dimensions of organizational commitment of academicians.
Research on Local Motion-Blurred Image Restoration Algorithm Based on Physical Methods

A new restoration algorithm aimed at local motion-blur in a complex background is proposed in this paper. First, the local blur part of the image is extracted from the complex background and it is pasted on a bottom of monochromatic background. Then image restoration is done on the blur part in the monochromatic background which is easy to be restored. Finally, the restored local image is pasted back to the original complex background. The algorithm simplifies the restoration problem of local blur image with complex background. And all operations can be completed by physical methods. The algorithm is simple, fast and effectual. It is an effective method of image restoration.
Improving customer's profile in recommender systems using time context and group preferences

By the expanse of internet stores and products, recommender systems have emerged to increase store attractiveness and develop online customers. Recommender systems are systems which help customers to find product that they want. These systems recommend product to individual customer according to their preferences and interests. Recommender systems use several ways such as collaborative filtering and content-based filtering to create recommendation. In this study we proposed a recommender system based on collaborative filtering. In proposed model we endeavored to improve the customer profile in collaborative systems to enhance the recommender system efficiency. We do this improvement using time context and group preferences.
CLUSTER VALIDITY MEASURES DYNAMIC CLUSTERING ALGORITHMS

Cluster analysis finds its place in many applications especially in data analysis, image processing, pattern recognition, market research by grouping customers based on purchasing pattern, classifying documents on web for information discovery, outlier detection applications and act as a tool to gain insight into the distribution of data to observe characteristics of each cluster. This ensures that cluster places its identity in all domains. This paper presents the clustering validity measures which evaluates the results of clustering algorithms on data sets with the three main approaches of cluster validation techniques namely internal, external and relative criteria. Also it validates the cluster using the cluster indices namely Dunn’s index, DaviesBoludin index and Generalized Dunn Index using K-mean and Chameleon algorithm.