Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain Engineering for Graph Libraries

Acknowledgements First I would like to thank my advisor, Jean-Pierre Corriveau. He gave me support throughout these years in many ways. I just cannot find a way to thank him. I am also thankful to my fellow graduate students. They gave suggestions to this dissertation and helped me to improve my presentation. I couldn't finish my research without the support from my wife. She is always behind me, silently and firmly. Finally I would like to dedicate this dissertation to my father. In his time, going to university was a dream. I hope he can share my happiness. Abstract In this thesis, the problem we tackle is how to facilitate the reuse of a set of independently developed C++ graph libraries. We are concerned more precisely with library users being offered an alternative to having to study in detail the code of a library before deciding whether or not and how to reuse its components. Our fundamental postulate is that domain engineering does facilitate reuse, as extensively argued in the corresponding literature. Thus, the question we ask is the following: can the notions of domain engineering, and more specifically the technique of feature modeling, be applied to a set of independently developed C++ graph libraries (in order to facilitate reusing these libraries)? Our thesis is that they can and we demonstrate this by building feature models addressing the representational aspects of a family of independently developed graph libraries. First, we develop a partial feature diagram for each graph library. Our intention here is to have these models provide a conceptual " road map " (like the blueprint of a house) for each graph library. No such information is currently available in the documentation associated with each library. From a practical viewpoint, we believe that each such feature model helps in understanding the design of its corresponding library because this model provides a conceptual overview of its library. Then, as a second contribution, in order to highlight the differences between these libraries, we present an integrated feature model of the graph domain and explain how each library 'fits' in it. Though comparing libraries (e.g., with respect to requirements, variability, etc.) lies beyond the scope of this thesis, we hint at the usefulness of our feature models by using them to sketch a comparison between the libraries.
FIX - The Fear Index: Measuring Market Fear

In this paper, we propose a new fear index based on (equity) option surfaces of an index and its components. The quantification of the fear level will be solely based on option price data. The index takes into account market risk via the VIX volatility barometer, liquidity risk via the concept of implied liquidity, and systemic risk and herd behavior via the concept of comonotonicity. It thus allows us to measure an overall level of fear (excluding credit risk) in the market as well as to identify precisely the individual importance of the distinct risk components (market, liquidity, or systemic risk). As a an additional result, we also derive an upperbound for the VIX.
A software vulnerability orientation method based on complex network

Software vulnerability orientation is of great significance to vulnerability exploiting and vulnerability repairing. This paper presents a new method of vulnerability orientation based on complex network theory. We describe the software structure by system-level characteristics of complex network and generate structural signatures of original and patched software. By comparing patches of the similar signatures and splitting the connected components recursively, the vulnerability location can be orientated. Results of the experiments demonstrate the effective orientation power of this method.
Performance evaluation of conventional and MMSE multiuser detection algorithms with different spreading signature codes

Multiuser detection technique implies joint demodulation of overlapping data streams of data sent by different users, improving their individual performances based on the knowledge of some key parameters of all users. Each user is identified by its own signature code, which should be, in the ideal case, orthogonal on all the others. Several multiuser detectors have been developed for synchronous CDMA systems. This paper analyzes the performances of MMSE and conventional multiuser detectors. The results are compared in terms of Bit Error Rate (BER) as function of Signal to Noise Ratio (SNR). Extensive Monte Carlo simulations have been performed and the results obtained lead to several interesting conclusions that are highlighted in the last section.
Efficient global optimization (EGO) for multi-objective problem and data mining

In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation with the surrogate model, objective functions are converted to the Expected Improvements (EI) and these values are directly used as fitness values in the multi-objective optimization. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method is applied to a transonic airfoil design. In order to obtain the information about design space, two data mining techniques are applied to design results. One is analysis of variance (ANOVA) and the other is self-organizing map (SOM).
Application Specific Processors for Multimedia Applications

A well-known challenge during processor design is to obtain best possible results for a typical target application domain by combining flexibility and computational performance. ASIPs (Application Specific Instruction Set Processors) provide a tradeoff between generality of processor (flexibility) and its physical characteristics (computational performance and silicon area). This paper evaluates an ASIP design methodology based on the extension of an existing instruction set and architecture described with LISA 2.0 language. The objective is to accelerate the ASIPs design process by using partially predefined, configurable RISC-like embedded processor cores that can be quickly tuned to given applications by means of ISE (Instruction Set Extension) techniques. A case study demonstrates the methodological approach for the JPEG algorithm and motion estimation encoding algorithm of H.264 encoding standard.
Real-time Bidding based Vehicle Sharing Paper

We consider the one-way vehicle sharing systems where customers can pick a car at one station and drop it off at another (e.g., Zipcar, Car2Go). We aim to optimize the distribution of cars, and quality of service, by pricing rentals appropriately. However, with highly uncertain demands and other uncertain parameters (e.g., pick-up and drop-off location, time, duration), pricing each individual rental becomes prohibitively difficult. As a first step towards overcoming this difficulty, we propose a bidding approach inspired from auctions, and reminiscent of Priceline or Hotwire. In contrast to current car-sharing systems, the operator does not set prices. Instead, customers submit bids and the operator decides to rent or not. The operator can even accept negative bids to motivate drivers to rebalance available cars in unpopular routes. We model the operator’s sequential decision problem as a constrained Markov decision problem (CMDP), whose exact solution can be found by solving a sequence of stochastic shortest path problems in real-time. Furthermore, we propose an online approximate algorithm using the actor-critic method of reinforcement learning, for which this algorithm has a fast convergence rate and small variance in generalization error. We also show that its solution converges to the stationary (locally optimal) policy.
Exploring synergies between digital tv recommender systems and electronic health records

Recommender systems have been around for several years in Digital TV scenarios as tools intended to discover items that are likely to be of interest for the viewers, as inferred from profiles that gather information about TV programs they watch or commercial products they purchase. In this paper, we introduce electronic health records as a new dimension of the viewer profiles, enabling a number of features that may have a significant impact in the field of interactive services to the home. This proposal brings in contributions related to (i) designing architectures and procedures to prevent the disclosure or guessing of sensitive health-related data, (ii) enabling access to information stored in standards-compliant EHR repositories from DTV set-top boxes, and (iii) refining the recommendation logic to reckon the enabling/disabling nature of such data.
Computation and analysis of natural compliance in fixturing and grasping arrangements

This paper computes and analyzes the natural compliance of fixturing and grasping arrangements. Traditionally, linear-spring contact models have been used to determine the natural compliance of multiple contact arrangements. However, these models are not supported by experiments or elasticity theory. We derive a closed-form formula for the stiffness matrix of multiple contact arrangements that admits a variety of nonlinear contact models, including the well-justified Hertz model. The stiffness matrix formula depends on the geometrical and material properties of the contacting bodies and on the initial loading at the contacts. We use the formula to analyze the relative influence of first- and second-order geometrical effects on the stability of multiple contact arrangements. Second-order effects, i.e., curvature effects, are often practically beneficial and sometimes lead to significant grasp stabilization. However, in some contact arrangements, curvature has a dominant destabilizing influence. Such contact arrangements are deemed stable under an all-rigid body model but, in fact, are unstable when the natural compliance of the contacting bodies is taken into account. We also consider the combined influence of curvature and contact preloading on stability. Contrary to conventional wisdom, under certain curvature conditions, higher preloading can increase rather than decrease grasp stability. Finally, we use the stiffness matrix formula to investigate the impact of different choices of contact model on the assessment of the stability of multiple contact arrangements. While the linear-spring model and the more realistic Hertz model usually lead to the same stability conclusions, in some cases, the two models lead to different stability results.
Single-Microphone Speech Separation : The use of Speech Models

Separation of speech sources is fundamental for robust communication. In daily conversations, signals reaching our ears generally consist of target speech sources, interference signals from competing speakers and ambient noise. Take an example, talking with someone in a cocktail party and making a phone call in a train compartment. Fig. 1 shows a typical indoor environment having multiple sound sources, such as speech from different speakers, sounds from a television set and telephone ringing, etc. These sources are often overlapped in time and frequency. While human attends to individual sources without difficulty, most speech applications are vulnerable and resulted in degraded performance. This chapter focuses on speech separation for single microphone input, in particular, the use of prior knowledge in the form of speech models. Speech separation for single microphone input refers to the estimation of individual speech sources from the mixture observation. It remains important and beneficial to various applications, namely surveillance systems, auditory prostheses, speech and speaker recognition. Over the years, extensive effort has been devoted. Speech enhancement and separation are two popular approaches. Speech enhancement (Lim, 1983; Loizou, 2007) generally reduces the interference power, by assuming that certain characteristics of individual source signals are held. There is one speech source at most. In contrast, speech separation (Cichocki & Amari, 2002; van der Kouwe et al., 2001) extracts multiple target speech sources directly.
Account and Accountability: Patrol Constables' Perceptions of Wife Assault Sensitivity Training, A Qualitative Evaluation

This study is a qualitative evaluation of in-service wife assault sensitivity training provided to patrol constables. The stakeholder group from which the perspective is sought is patrol constables. In applying a contextual constructionist analysis to the study, I demonstrate that constables' rejection of the training largely stemmed from organizational factors (in particular, workplace accountability concerns) as well as constables' claims to define their own account of the violence. In addition, the feminist account of wife assault (which informs the training) is revealed to contain inconsistencies, contradictions, dramatizations, and oversimplifications. Overall, this study challenges the popular view of sensitivity training as a panacea for attitude change in the workplace.
Kinetic Interplay between Herpes Simplex Virus Type 1 Helicase-Primase and Polymerase

Boulder, Colorado ii Acknowledgements Special thanks to my advisor, Dr. Rob Kuchta, for his guidance, mentorship, and support in my pursuit of honors in biochemistry and my future career. I also would like to extend thanks to the rest of the Kuchta lab, especially Dr. Andrew Olson for being a wonderful and patient mentor when I first started, and Sarah Dickerson for always being available to bounce ideas off of. Thanks who have been unwavering sources of strength for the last few years. Finally, I am deeply grateful to my family – my parents, Jing and Darrell, for supporting me and inspiring me to do my best in science and all aspects of my life; and my brothers, Conrad and Kendrick.
Effects and Safety of Calcimimetics in End Stage Renal Disease Patients with Secondary Hyperparathyroidism: A Meta-Analysis

Purpose Secondary hyperparathyroidism (SHPT) is one of the most common abnormalities of mineral metabolism in patients with chronic kidney disease. We performed a meta-analysis to determine the effect and safety of cinacalcet in SHPT patients receiving dialysis. Methods The meta-analysis was performed to determine the effect and safety of cinacalcet in SHPT patients receiving dialysis by using the search terms ‘cinacalcet’ or ‘mimpara’ or ‘sensipar’ or ‘calcimimetic’ or ‘R586’ on MEDLINE and EMBASE (January 1990 to February 2012). Results Fifteen trials were included, all of which were performed between 2000 and 2011 enrolling a total of 3387 dialysis patients. Our study showed that calcimimetic agents effectively ameliorated iPTH levels(WMD, −294.36 pg/mL; 95% CI, −322.76 to −265.95, P<0.001) in SHPT patients and reduced serum calcium (WMD, −0.81 mg/dL; 95% CI, −0.89 to −0.72, P<0.001) and phosphorus disturbances(WMD, −0.29 mg/dL; 95% CI, −0.41 to −0.17, P<0.001). The percentage of patients in whom there was a 30% decrease in serum iPTH levels by the end of the dosing was higher in cinacalcet group than that in control group(OR = 10.75, 95% CI: 6.65–17.37, P<0.001). However, no significant difference was found in all-cause mortality and all adverse events between calcimimetics and control groups(OR = 0.86, 95% CI: 0.46–1.60, P = 0.630; OR = 1.30, 95% CI: 0.78–2.18, P = 0.320, respectively). Compared with the control therapy, there was a significant increase in the episodes of hypocalcemia (OR = 2.46, 95% CI: 1.58–3.82, P<0.001), nausea (OR = 2.45, 95% CI: 1.29–4.66, P = 0.006), vomiting(OR = 2.78, 95% CI: 2.14–3.62, P<0.001), diarrhea(OR = 1.51, 95% CI: 1.04–2.20, P = 0.030) and upper respiratory tract infection (OR = 1.79, 95% CI: 1.20–2.66, P = 0.004)in calcimimetics group. Conclusions Calcimimetic treatment effectively improved biochemical parameters of SHPT patients receiving dialysis without increasing all-cause mortality and all adverse events.
Bounded Model Checking and Inductive Verification of Hybrid Discrete-continuous Systems

We present a concept to significantly advance the state of the art for bounded model checking (BMC) and inductive verification (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from different domains, like hybrid systems modeling and digital circuit verification, bounded planning and heuristic search, combinatorial optimization and integer programming. After sketching the overall verification flow we present first results indicating that the combination and tight integration of different verification engines is a first step to pave the way to fully automated BMC and IV of medium to large-scale networks of hybrid automata.
Neural Correlates of Object-Associated Choice Behavior in the Perirhinal Cortex of Rats

The perirhinal cortex (PRC) is reportedly important for object recognition memory, with supporting physiological evidence obtained largely from primate studies. Whether neurons in the rodent PRC also exhibit similar physiological correlates of object recognition, however, remains to be determined. We recorded single units from the PRC in a PRC-dependent, object-cued spatial choice task in which, when cued by an object image, the rat chose the associated spatial target from two identical discs appearing on a touchscreen monitor. The firing rates of PRC neurons were significantly modulated by critical events in the task, such as object sampling and choice response. Neuronal firing in the PRC was correlated primarily with the conjunctive relationships between an object and its associated choice response, although some neurons also responded to the choice response alone. However, we rarely observed a PRC neuron that represented a specific object exclusively regardless of spatial response in rats, although the neurons were influenced by the perceptual ambiguity of the object at the population level. Some PRC neurons fired maximally after a choice response, and this post-choice feedback signal significantly enhanced the neuronal specificity for the choice response in the subsequent trial. Our findings suggest that neurons in the rat PRC may not participate exclusively in object recognition memory but that their activity may be more dynamically modulated in conjunction with other variables, such as choice response and its outcomes.
Sensor Fusion for Predicting Vehicles' Path for Collision Avoidance Systems

Path prediction is the only way that an active safety system can predict a driver's intention. In this paper, a model-based description of the traffic environment is presented - both vehicles and infrastructure - in order to provide, in real time, sufficient information for an accurate prediction of the ego-vehicle's path. The proposed approach is a hierarchical-structured algorithm that fuses traffic environment data with car dynamics in order to accurately predict the trajectory of the ego-vehicle, allowing the active safety system to inform, warn the driver, or intervene when critical situations occur. The algorithms are tested with real data, under normal conditions, for collision warning (CW) and vision-enhancement applications. The results clearly show that this approach allows a dynamic situation and threat assessment and can enhance the capabilities of adaptive cruise control and CW functions by reducing the false alarm rate.
Fetal, Neonatal, Infant, and Child International Growth Standards: An Unprecedented Opportunity for an Integrated Approach to Assess Growth and Development

The recent publication of fetal growth and gestational age–specific growth standards by the International Fetal and Newborn Growth Consortium for the 21st Century Project and the previous publication by the WHO of infant and young child growth standards based on the WHO Multicentre Growth Reference Study enable evaluations of growth from ∼9 wk gestation to 5 y. The most important features of these projects are the prescriptive approach used for subject selection and the rigorous testing of the assertion that growth is very similar among geographically and ethnically diverse nonisolated populations when health, nutrition, and other care needs are met and the environment imposes minimal constraints on growth. Both studies documented that with adequate controls, the principal source of variability in growth during gestation and early childhood resides among individuals. Study sites contributed much less to observed variability. The agreement between anthropometric measurements common to both studies also is noteworthy. Jointly, these studies provide for the first time, to my knowledge, a conceptually consistent basis for worldwide and localized assessments and comparisons of growth performance in early life. This is an important contribution to improving the health care of children across key periods of growth and development, especially given the appropriate interest in pursuing “optimal” health in the “first 1000 d,” i.e., the period covering fertilization/implantation, gestation, and postnatal life to 2 y of age.
Projective clustering of high dimensional data

Clustering of high-dimensional data can be problematic, because the usual notions of distance or similarity break down for data in high dimensions. More specifically, it can be shown that, as the number of dimensions increases, the distance to the nearest point approaches the distance to the farthest one. Two approaches are common for dealing with this problem. The idea behind the first approach is to project all the points to a lower dimensional subspace and then use a standard clustering algorithm on the low-dimensional representation. However, if different subsets of the points cluster well on different subspaces of the original feature space, then a global dimensionality reduction will fail. In the second approach, projection and clustering are performed simultaneously, allowing each cluster to have a different subspace associated with it. These projective clustering algorithms compute pairs (Ci,Di), consisting of the points Ci belonging in cluster i and the subspace Di in which these points have low variance. Three algorithms are presented that follow different approaches to projective clustering. One is a partitional method that iteratively assigns and reestimates the cluster centroids, similar to k-means but with projection steps included in the iteration. The second is density based; it works by extending the clusters to nearby points, where proximity in high dimensions is defined based on the variance of the clusters along different axes. The last algorithm is an ensemble method. It repeatedly performs random projections, which are then clustered using the EM algorithm and combined. The partitional method optimizes a well-defined objective function, but scales poorly to large dimensions. The density-based method scales linearly in the number of dimensions, but it only finds projections to axes-parallel subspaces and not to ones that are arbitrarily rotated. The ensemble method can exploit the diversity of the individual solutions and produces high quality clusters in practice, but lacks theoretical guarantees.
Beyond Weblog : Transform Blog into Personal Expertise and Social Network via myFOAF Support

To utilize the dramatically increasing Blog contents and widely accepted web 2.0 services, this research proposes myFOAF which extends FOAF to model dynamic social contexts over the web. Based on the richer social semantic, we can generate the blogger’s myFOAF profile, via the corresponding contents such as RSS, Blog content, tagging data, mashup service that retrieve from blogger’s daily web behavior. Two main application models are addressed in the system. Firstly, the Personal Expertise Explorer can accumulate blogger’s tagging ontology (myTag) to analyze the blogger’s domain related expertise. The evaluation result shows that the average precision reaches around 77.6%. Secondly, the Personal Social Explorer gathers the blogger’s friend information to form a personalized social network diagram which presents blogger’s social activities in certain tag domain. With the extra semantic supported by myFOAF, blogger can easily explore his own implicit expertise and web social relationship with minimal efforts.