Miracle-dz/UniFAR-FTUs huggingface dataset:
Will Rogers Is Jenksing Police Response Times

Abstract:Puisque les services de police se fient généralement aux différents schémas de classification des appels et gèrent différents types d'appels, il est difficile de comparer, d'un service à l'autre, la distribution des temps de réponse de la police dans un contexte à plusieurs priorités. Ces raisons rendent aussi difficile la comparaison des tendances dans le temps, et ce, même au sein d'un service de police donné. Des exemples hypothétiques illustrent les défis d'analyse principaux. Puis, une simple approche de regroupement, la méthode des seuils naturels de Jenks, est démontrée. Cette approche peut être utilisée pour comparer la distribution des temps de réponse de la police de manière objective. Les comparaisons qui en résultent ne sont pas affectées par des différences ou des changements dans les règles de classification des appels et ne peuvent pas facilement être manipulées ou faussées, intentionnellement ou non. La discussion se fait dans un contexte policier, mais l'approche analytique proposée peut être utile à d'autres services d'urgence et peut établir des références. Abstract:Because police jurisdictions typically rely on different call classification schemes and handle a different mix of calls, it is difficult to compare multi-priority police response time distributions between two or more jurisdictions. For the same reasons, it can be challenging to compare response time trends over time, even within a given police jurisdiction. Hypothetical examples illustrate the main analytical challenges. Then, a simple clustering approach, the Jenks natural breaks method, is demonstrated. This approach can be used to objectively com-pare police response time distributions. The resulting comparisons remain unaffected by differences or changes in call classification rules and cannot be easily manipulated or skewed, either intentionally or inadvertently. Although the discussion is framed within a police context, the proposed analytical approach has the potential to be useful for other emergency services and benchmarking settings.
Cache-Oblivious Computation: Algorithms and Experimental Evaluation

We describe our recent research results on cache-oblivious algorithms for certain types of dynamic programs and triply-nested loop computations, and for priority queues and their application in shortest path problems in graphs. We present some preliminary results from our ongoing experimental work on comparing our cache-oblivious algorithms to currently available code for these problems. Our results demonstrate that cache-oblivious methods can give rise to efficient algorithms both in theory and in practice
ETSCH: Partition-Centric Graph Processing

This paper presents ETSCH, a novel paradigm for processing large graphs. ETSCH departs from the vertex-based approach of BSP frameworks like PREGEL in two ways: first, the units of computation are not the vertices, but rather a collection of subgraphs, obtained by partitioning the input graph, second, the subgraphs are obtained through an edge-partitioning algorithm, in which edges, rather than vertices, are subdivided into disjoint subsets Global computations over the graph are then easily expressed using classical centralized algorithms executed on each of the partitions, with the only additional burden of specifying simple reconciliation procedures when vertices are replicated in multiple computing nodes. The ETSCH paradigm has been implemented both on top of existing frameworks like HADOOP, SPARK,, as a stand-alone service based on AKKA, a toolkit for building distributed message-driven applications. When considering problems like single-source shortest path, PageRank, our experiments show that solutions based on ETSCH/HADOOP, ETSCH/SPARK already outperform the standard solutions to the same problems in HADOOP, SPARK, respectively. But it is our AKKA implementation that really shines: the execution time on graphs with millions of edges falls down from from thousands of seconds (ETSCH/HADOOP) to tens of seconds (ETSCH/SPARK) to seconds (ETSCH/AKKA), while easily scaling to graphs with billions of edges. ETSCH/AKKA is also faster than other partition-centric frameworks like BLOGEL, GPS.
Breast cancer risk in primary care: implications for chemoprevention.

BACKGROUND Some women may benefit from taking tamoxifen citrate for breast cancer prevention if the probability of benefit outweighs that of adverse events. We determined the proportion of women aged 40 to 69 years attending general internal medicine practices who were potentially eligible for tamoxifen chemoprevention and calculated the maximum proportion of breast cancers that could be prevented. METHODS Six hundred five women aged 40 to 69 completed self-administered questionnaires in the waiting rooms of 10 general internal medicine practices in North Carolina in 2001. RESULTS Among white women, 9.0% (95% confidence interval [CI], 5.1%-15.2%) in their 40s, 24.0% (95% CI, 18.2%-31.0%) in their 50s, and 53.4% (95% CI, 46.1%-61.3%) in their 60s had a 5-year Gail model estimated breast cancer risk of 1.66% or greater. Among black women, 2.9% (95% CI, 0%-15.0%) in their 40s, 7.1% (95% CI, 1.1%-24.4%) in their 50s, and 13.0% (95% CI, 3.1%-34.3%) in their 60s had a similar risk. When adverse events were considered in white women, 10% or fewer in all age groups were potentially eligible for chemoprevention. The maximum proportion of breast cancers prevented in eligible women was 6.0% to 8.3%. CONCLUSIONS Small numbers of women in primary care practices are eligible for discussions about chemoprevention; the maximum proportion of breast cancers prevented if eligible women take tamoxifen is also small. Challenges lie in targeting discussions to the most appropriate women and in finding new chemoprevention strategies that have less risk of harms.
Exploring domain-specific term weight in archived question search

Community Question Answering services, e.g., Yahoo! Answers, have accumulated large archives of question answer (QA) pairs for information and answer retrieval. An effective question retrieval model is essential to increase the accessibility of the QA archives. QA archives are usually organized into categories and question search can be performed within the whole collection or within a certain category. In this paper, we explore domain-specific term weight for archived question search. Specifically, we propose a novel light-weighted term weighting scheme that exploits multiple aspects of the domain information. We also introduce a framework to seamlessly integrate domain-specific term weight into the existing retrieval models. Extensive experiments conducted on real Archived QA data demonstrate the utility of the proposed techniques.
Tracking by Affine Kernel Transformations Using Color and Boundary Cues

Kernel-based trackers aggregate image features within the support of a kernel (a mask) regardless of their spatial structure. These trackers spatially fit the kernel (usually in location and in scale) such that a function of the aggregate is optimized. We propose a kernel-based visual tracker that exploits the constancy of color and the presence of color edges along the target boundary. The tracker estimates the best affinity of a spatially aligned pair of kernels, one of which is color-related and the other of which is object boundary-related. In a sense, this work extends previous kernel-based trackers by incorporating the object boundary cue into the tracking process and by allowing the kernels to be affinely transformed instead of only translated and isotropically scaled. These two extensions make for more precise target localization. A more accurately localized target also facilitates safer updating of its reference color model, further enhancing the tracker's robustness. The improved tracking is demonstrated for several challenging image sequences.
4P: Performant private peer-to-peer file sharing

In recent years fully decentralized file sharing systems were developed aimed at improving anonymity among their users. These systems provide typical file sharing features such as searching for and downloading files. However, elaborate schemes originally aimed at improving anonymity cause partial keyword matching to be virtually impossible, or introduce a substantial bandwidth overhead. In this paper we introduce 4P, a system that provides users with anonymous search on top of a semantic overlay. The semantic overlay allows users to efficiently locate files using partial keyword matching, without having to resort to an expensive flooding operation. Included into 4P are a number of privacy enhancing features such as probabilistic query forwarding, path uncertainty, caching, and encrypted links. Moreover, we integrate a content retrieval channel into our protocol allowing users to start downloading a file from multiple sources immediately without requiring all intermediate nodes to cache a complete copy. Using a trace-based dataset, we mimic a real-world query workload and show the cost and performance of search using six overlay configurations, comparing random, semantic, Gnutella, RetroShare, and OneSwarm to 4P. The state-of-the-art flooding based alternatives required approximately 10,000 messages to be sent per query, in contrast 4P only required 313. Showing that while flooding can achieve a high recall (more than 85% in our experiments) it is prohibitively expensive. With 4P we achieve a recall of 76% at a considerable reduction in messages sent.
Exchange Rate Regimes in the Americas: Is Dollarization the Solution?

The series of crises that have affected emerging markets in recent years have reopened the debate on the most appropriate exchange regime for an emergent economy. In particular, all countries that experienced severe crises in the 1990s had some sort of fixed exchange rate regime, the majority of them falling in the categories that Corden ( 2002) calls the fixed-but-adjustable exchange rate regime (FBAR) and in- between regimes of the pegged (including flexible and crawling pegs) and target zone types. As a result, in recent years countries have been emigrating to a corner solution: a credible fixed regime or a floating regime with a monetary anchor. Within the latter categories, the increasingly used monetary regime is the inflation targeting one. The paper discusses the advantages and disadvantages of alternative exchange rate regimes and ends with a discussion of the possibility of dollarization in the Americas.
Driver Vitalization : Investigating Sensory Stimulation to Achieve a Positive Driving Experience

This thesis aims to decrease the feeling of tiredness related to an on-going monotonous, undemanding driving task. It is not intended to enable people to drive longer, but rather for them to experience the time they spend driving as more pleasant. The perception of fatigue is considered as a type of discomfort. From this follows the hypothesis that this feeling of tiredness develops according to a similar system as the perception of discomfort or comfort. Following this premise, the approach in this thesis is to alter the interaction with the vehicle interior by developing features resulting in certain bodily sensations that contribute to feeling more fit.
Analysis and development of Java Grande benchmarks

Understanding the performance behaviour of Java Virtual Machines is important to Java systems developers and to applications developers. We review a range of Java benchmark programs, including those collected by the Java Grande Forum as useful performance indicators for large-scale scientific applications, or “Java Grande applications”. We systematically analyse these benchmarks on a collection of compute platforms including Pentium II, UltraSPARC II, Silicon Graphics, iMac and Alpha, and operating systems including Windows NT, Solaris, and Linux, and consider differences in performance between benchmarks running on the Java Development Kit (JDK) versions 1.1. 6 and 1.2. We also analyse some benchmark programs we have developed to augment existing collections. We observe some general trends in the performance of Java on various platforms and also conduct some comparisons between benchmarks written in Java and in traditional languages such as C and Fortran. We discuss performance variations across systems and the implications of Java systems performance for those developing scientific applications.
Predicting risky behavior in social communities

Predicting risk profiles of individuals in networks (e.g.~susceptibility to a particular disease, or likelihood of smoking) is challenging for a variety of reasons. For one, `local' features (such as an individual's demographic information) may lack sufficient information to make informative predictions; this is especially problematic when predicting `risk,' as the relevant features may be precisely those that an individual is disinclined to reveal in a survey. Secondly, even if such features are available, they still may miss crucial information, as `risk' may be a function not just of an individual's features but also those of their friends and social communities. Here, we predict individual's risk profiles as a function of both their local features and those of their friends. Instead of modeling influence from the social network directly (which proved difficult as friendship links may be sparse and partially observed), we instead model influence by discovering social communities in the network that may be related to risky behavior. The result is a model that predicts risk as a function of local features, while making up for their deficiencies and accounting for social influence by uncovering community structure in the network. We test our model by predicting risky behavior among adolescents from the Add health data set, and hometowns among users in a Facebook ego net. Compared to prediction by features alone, our model demonstrates better predictive accuracy when measured as a whole, and in particular when measured as a function of network "richness. "
The simulation and design for MPPT of PV system Based on Incremental Conductance Method

Completing the design for the model of photovoltaic array and achieving to track the array's maximum power point by the help of Incremental Conductance Method. This article firstly introduces a practical model of photovoltaic cells, by which the photovoltaic array`s model is obtained. To achieve the maximum power point tracking the Incremental Conductance method is used. Finally, with the help of embedded MATLAB function the article succeeds to achieve the algorithm. Simulation results show the accuracy of the PV model and the practical value in the algorithm which has better tracking performance and dynamic characteristics.
QSAR and its Role in Target-Ligand Interaction

Each molecule has its own specialty, structure and function and when these molecules are combined together they form a compound. Structure and function of a molecule are related to each other and QSARs (Quantitative Structure- Activity relationships) are based on the criteria that the structure of a molecule must contain the features responsible for its physical, chemical, and biological properties, and on the ability to represent the chemical by one, or more, numerical descriptor(s). By QSAR models, the biological activity of a new or untested chemical can be inferred from the molecular structure of similar compounds whose activities have already been assessed. QSARs attempt to relate physical and chemical properties of molecules to their biological activities. For this there are so many descriptors (for example, molecular weight, number of rotatable bonds, Log P) and simple statistical methods such as Multiple Linear Regression (MLR) are used to predict a model. These models describe the activity of the data set and can predict activities for further sets of (untested) compounds. These types of descriptors are simple to calculate and allow for a relatively fast analysis. 3D-QSAR uses probe-based sampling within a molecular lattice to determine three-dimensional properties of molecules (particularly steric and electrostatic values) and can then correlate these 3D descriptors with biological activity. Physicochemical descriptors, include hydrophobicity, topology, electronic properties, and steric effects etc. These descriptors can be calculated empirically, statistically or through more recent computational methods. QSARs are currently being applied in many disciplines, with many pertaining to drug design and environmental risk assessment. Key word: QSAR, Ligand Designing, LogP, Cheminformatics, Docking.
Closing the Gap between Global and Detailed Placement: Techniques for Improving Routability

Improving routability during both global and detailed routing stage has become a critical problem in modern VLSI design. In this work, we propose a placement framework that offers a complete coverage solution in considering both global and detailed routing congestion. A placement migration strategy is proposed, which improves detailed routing congestion while preserving the placement integrity that is optimized for global routability. Using the benchmarks released from ISPD2014 Contest, practical design rules in advanced node design are considered in our placement framework. Evaluation on routability of our placement framework is conducted using commercial router provided by the 2014 ISPD Contest organizers. Experimental results show that the proposed methodologies can effectively improve placement solutions for both global and detailed router.
Intertemporal Dynamics of Corporate Voluntary Disclosures

While empirical evidence alludes to the intertemporal nature of corporate voluntary disclosures, most of the existing theory analyzes firms' voluntary disclosure decisions within single‐period settings. Introducing a repeated, multiperiod, disclosure setting, we study the extent to which firms' strategic disclosure behavior in the past affects their prosperity to provide voluntary disclosures in the future. Our analysis demonstrates that by voluntarily disclosing private information firms make an implicit commitment to provide similar disclosures in the future, and therefore are less willing to voluntarily disclose information in the first place. This effect is expected to be of larger magnitude for firms (1) with a long history of absence of voluntary disclosures and an impressive past operating performance, or (2) that operate in a relatively stable and predictable business and information environment, or (3) whose managers have a long time horizon and a high degree of risk aversion.
A Context-based Approach to Discover Multitasking Behavior at Work

Despite the availability of several task and personal information management tools, an appropriate support to human multitasking at work is still lacking. Supporting multitasking behavior entails capturing and modeling this behavior. In this paper, we refine an approach to model multitasking behavior in organizations, through an ontology based on two interrelated primitives; action and interaction contexts. The main contributions of the proposed ontology are: (1) enable the discovery of scheduling heuristics combining personal and inter-personal elements, (2) enable bottom-up discovery of tasks and (3) suggest a flexible system architecture for multitasking support. The first two contributions are illustrated through a case study.
Current state of personal data protection in electronic voting: Demand on Legislature's Bill

The strongest benefit has been offered for the implementation of electronic voting related to cost and time reduction. Therefore, recent publicity concerning the reliability, security and privacy issue of various e-voting systems has increased public scrutiny of the machines themselves as well as the election process as a whole. In the greater scale, it could reduce public confidence to entrust the adoption of e-voting system to augment participation rate, to improve the quality of voting and to aid the political right effectively and efficiently. This paper aims to provide general analysis of typical legal issues and its demand for personal data protection based on demographic data such as gender, age, occupation, electoral participation, education, earnings and legal literacy. By understanding the perception of voters in viewing current electoral regulation are essential to provide some insights and suggestion for better improvement, either through drafting or enforcing legislation. This study investigates the tendency of people in demanding the legislative to cater electronic voting.
Trajectory generation of biped running robot with minimum energy consumption

The exact and general formulation of optimal control for biped robots based on a numerical representation of the motion equation is proposed. We can solve exactly the minimum energy consumption trajectories for a biped running motion. Through the numerical study of a five link planar biped robot, it is found that big peak power and torque is required for the knee joints but its consumption power is small and the main work is done by the hip joints.
Long range mutual information

Network traffic modeling generally views traffic as a superposition of flows that creates a timeseries of volume counts (e.g. of bytes or packets). What is omitted from this view of traffic is the contents of packets. Packet contents (e.g. header fields) contain considerable information that can be useful in many applications such as change and anomaly detection, and router performance evaluation. The goal of this paper is to draw attention to the problem of modeling traffic with respect to the contents of packets. In this regard, we identify a new phenomenon: long range mutual information (LRMI), which means that the dependence of the contents of a pair of packets decays as a power of the lag between them. We demonstrate that although LRMI is hard to measure, and hard to model using the mathematical tools at hand, its effects are easy to identify in real traffic, and it may have a considerable impact on a number of applications. We believe that work in modeling this phenomenon will open doors to new kinds of traffic models, and new advances in a number of applications.
Investigating the Use of Extractive Summarisation in Sentiment Classification

In online reviews, authors often use a short passage to describe the overall feeling about a product or a service. A review as a whole can mention many details not in line with the overall feeling, so capturing this key passage is important to understand the overall sentiment of the review. This paper investigates the use of extractive summarisation in the context of sentiment classification. The aim is to find the summary sentence, or the short passage, which gives the overall sentiment of the review, filtering out potential noisy information. Experiments are carried out on a movie review data-set. The main finding is that subjectivity detection plays a central role in building summaries for sentiment classification. Subjective extracts carry the same polarity of the full text reviews, while statistical and positional approaches are not able to capture this aspect.