Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Detection of Selfish Routing in Wireless Mesh Networks

Community wireless mesh networks are vulnerable to free riders who refuse to forward data for others. As the naive selfish strategy of dropping data is readily detected, free-riders are motivated to subtly manipulate the routing protocols to minimize their workload while still evading detection. This paper presents an adaptive on-line algorithm to detect such selfish behavior based solely on local observations of messages exchanged by AODV-like routing protocols. We use a finite state machine model of locally observable protocol actions to generate a statistical description of the behavior of each neighbor and apply statistical analysis to cluster neighboring nodes on the basis of behavioral similarities and identify the selfish ones. Through simulation, we evaluate the performance of our method with respect to the probability of detecting selfish nodes and the rate of false positives against two generic selfish strategies— dropping route requests and dropping route replies. We also evaluate the effect of detection on an adaptive adversary who attempts to operate as selfishly as possible while still evading detection. We find that our technique can detect dropped route requests as well or better than a variant of the widely-used Watchdog detection method, with a lower rate of false positives. In the case of dropped route replies, a fundamental scarcity of observable routing events prevents any algorithm from performing well, suggesting the need to revisit the design of routing protocols.
Robust outlier detection using SVM regression

The occurrence of outliers in industrial data is often the rule rather than the exception. Many standard outlier detection methods fail to detect outliers in industrial data because of the high dimensionality of the data. Outlier detection in the case of chemical plant data can be particularly difficult since these data sets are often rank deficient. These problems can be solved by using robust model-based methods that do not require the data to be of full rank. We explore the use of a robust model-based outlier detection approach that makes use of the characteristics of the support vectors obtained by the support vector machine method.
Resource Management for Public Sensing

Public sensing is a new research area in the fields of wireless sensor networks and mobile computing. It leverages the mobile sensors and system resources readily available in mobile phones to execute sensing tasks. In order to plan, execute and adapt large-scale sensing tasks, applications need to query for the available resources, e.g. the density of certain sensors. We investigate how such information can be provided, and we propose a resource manager for public sensing. Our primary goal is to minimize the energy consumed by the mobile devices to make public sensing feasible without disturbing users. We propose a cluster-based protocol for collecting local views of the resource state using local ad-hoc communication since this is much more energy-efficient than long-range (e.g. cellular) communication. We compare our solution to a standard approach where mobile devices communicate their resource states using the cellular phone network. We show that 65% of the energy is saved and the communication load on the infrastructure is reduced by 90% while an average delivery ratio of 93% is retained.
Learning Salient Samples and Distributed Representations for Topic-Based Chinese Message Polarity Classification

We describe our participation in the TopicBased Chinese Message Polarity Classification Task, based on the restricted and unrestricted resources respectively. In the restricted resource based classification, we focus on the selection of parameters in a multi-class classification model with highly-biased training data. In the unrestricted resource based classification, we explore the distributed representation of Chinese words through unsupervised feature learning and the annotation of salient samples through active learning, with a raw corpus of over 90 million messages extracted from Chinese Weibo Platform. For two classification subtasks, our submitted results ranked the 4th and the 2nd respectively.
On the linking of Knowledge Management to Knowledge-Based Business Strategy

To attract, retain and develop competence has become increasingly important for organizations, as well as the capability to evolve areas of core competence for long-term competitiveness. This paper aims to contribute to an understanding of knowledge and competence as organizational resources, and to propose ways of designing effective KM strategies. A main assumption is that knowledge is becoming the main source of competitive advantage. Popular KM project types are assessed in this regard, using a reference framework of organizations as knowledge systems (Holzner and Marx, 1979). The results indicate weak KM tool functionality pertaining to management of knowledge, and poor linking to knowledge as strategic resource. A set of knowledge-based theoretical contributions to an emerging strategic framework for KM is suggested; knowledge integration, modular design, and competence provision. In order to provide a means of testing the framework, a method for competence provision is sought. To this end, the CSF method is briefly presented as method prototype, together with an outline of how it may be adapted to accommodate the theoretical contributions.
Reimagining English language learners from a translingual perspective

This article explores the potential implications of theorizing in translingualism and translanguaging for foreign language teaching and learning. I discuss key terminology and introduce a translingual continuum as a potential way to understand language use practices both within and across communities. I report on an exploratory study into the self-identified future language use profiles of 116 adult EFL learners studying in the United Kingdom, the majority of whom perceive a need for translingual practices in their varied futures. I discuss the implications, both of these findings and other research for language teaching pedagogy, considering how translingual competence may differ from communicative competence, and providing practical suggestions for teachers working in different contexts. I also discuss how reimagining the language classroom as a translingual community potentially provides a way of redefining notions of authenticity and the role of the teacher as a translingual practitioner, thereby avoiding the divisive native-speaker–non-native-speaker dichotomy.
Local Line Derivative Pattern for face recognition

In this paper, we propose a novel face descriptor for face recognition, named Local Line Derivative Pattern (LLDP). High-order derivative images in two directions are obtained by convolving original images with Sobel Masks. A revised binary coding function is proposed and three standards on arranging the weights are also proposed. Based on the standards, the weights of a line neighborhood in two directions are arranged. The LLDP labels in two directions are calculated with the proposed binary coding function and weights. The labeled image is divided into blocks where spatial histograms are extracted separately and concatenated into an entire histogram as features for recognition. The experiments on the FERET and Extended Yale B show superior performances of the proposed LLDP compared to other existing methods based on the LBP. The results prove that the LLDP has good robustness against expression, illumination and aging variations.
Modeling UpLink Power Control with Outage Probabilities

We investigate models for uplink interference in wireless systems. Our models account for the effects of outage probabilities. Such an accounting requires a nonlinear, even nonconvex model, since increasing interference at the receiving base station increases both mobile transmit power and outage probability, and this results in a complex interaction. Our system model always has at least one solution, a fixed point, and it is provably unique under certain reasonable conditions. Our main purpose is to model real wireless systems as accurately as possible, and so we test our models on realistic scenarios using data from a sophisticated simulator. Our algorithm for finding a fixed point works very well on such scenarios, and is guaranteed to find the fixed point when we can prove it is unique. A slightly simplified model reduces the main data structure for a K-sector market to 16K 2 bytes of memory.
Polynomial splittings of metabelian von Neumann rho-invariants

We show that if the connected sum of two knots with coprime Alexander polynomials has vanishing von Neumann rho-invariants associated with certain metabelian representations then so do both knots. As an application, we give a new example of an infinite family of knots which are linearly independent in the knot concordance group.
Combining multiple microarray studies and modeling interstudy variation

We have established a method for systematic integration of multiple microarray datasets. The method was applied to two different sets of cancer profiling studies. The change of gene expression in cancer was expressed as 'effect size', a standardized index measuring the magnitude of a treatment or covariate effect. The effect sizes were combined to obtain the estimate of the overall mean. The statistical significance was determined by a permutation test extended to multiple datasets. It was shown that the data integration promotes the discovery of small but consistent expression changes with increased sensitivity and reliability. The effect size methods provided the efficient modeling framework for addressing interstudy variation as well. Based on the result of homogeneity tests, a fixed effects model was adopted for one set of datasets that had been created in controlled experimental conditions. By contrast, a random effects model was shown to be appropriate for the other set of datasets that had been published by independent groups. We also developed an alternative modeling procedure based on a Bayesian approach, which would offer flexibility and robustness compared to the classical procedure.
Stabilization of cascades using integral input-to-state stability

We analyze nonlinear cascades in which the driven subsystem is integral ISS, and characterize the admissible integral ISS gains for stability. This characterization makes use of the convergence speed of the driving subsystem, and allows a larger class of gain functions when the convergence is faster. We show that our integral ISS gain characterization unifies different approaches in the literature which restrict the nonlinear growth of the driven subsystem and the convergence speed of the driving subsystem.
Age-related performance issues for PIN and face-based authentication systems

Graphical authentication systems typically claim to be more usable than PIN or password-based systems, but these claims often follow limited, single-stage paradigm testing on a young, student population. We present a more demanding test paradigm in which multiple codes are learned and tested over a three-week period. We use this paradigm with two user populations, comparing the performance of younger and older adults. We first establish baseline performance in a study in which populations of younger and older adults learn PIN codes and we follow this with a second study in which younger and older adults use two face-based graphical authentication systems employing young faces vs. old faces as code components. As expected, older adults show relatively poor performance when compared to younger adults, irrespective of the authentication material, but this age-related deficit can be markedly reduced by the introduction of age-appropriate faces. We conclude firstly that this paradigm provides a good basis for the future evaluation of memory-based authentication systems and secondly that age-appropriate face-based authentication is viable in the security marketplace.
Lipocalin 2 Regulates Inflammation during Pulmonary Mycobacterial Infections

Pulmonary tuberculosis (TB), caused by the intracellular bacteria Mycobacterium tuberculosis, is a worldwide disease that continues to kill more than 1.5 million people every year worldwide. The accumulation of lymphocytes mediates the formation of the tubercle granuloma in the lung and is crucial for host protection against M.tuberculosis infection. However, paradoxically the tubercle granuloma is also the basis for the immunopathology associated with the disease and very little is known about the regulatory mechanisms that constrain the inflammation associated with the granulomas. Lipocalin 2 (Lcn2) is a member of the lipocalin family of proteins and binds to bacterial siderophores thereby sequestering iron required for bacterial growth. Thus far, it is not known whether Lcn2 plays a role in the inflammatory response to mycobacterial pulmonary infections. In the present study, using models of acute and chronic mycobacterial pulmonary infections, we reveal a novel role for Lcn2 in constraining T cell lymphocytic accumulation and inflammation by inhibiting inflammatory chemokines, such as CXCL9. In contrast, Lcn2 promotes neutrophil recruitment during mycobacterial pulmonary infection, by inducing G-CSF and KC in alveolar macrophages. Importantly, despite a common role for Lcn2 in regulating chemokines during mycobacterial pulmonary infections, Lcn2 deficient mice are more susceptible to acute M.bovis BCG, but not low dose M.tuberculosis pulmonary infection.
Service-oriented middleware for smart grid: Principle, infrastructure, and application

The current smart grid is undergoing a drastic change in order to deal with increasingly diversified and various service requests from the huge number of users. The next-generation smart grid, characterized by service-oriented middleware, will be upgraded by jointly employing the technologies in the areas of communications, control, and computing. To design a general middleware, an efficient design principle plays a fundamental role, while reliable communication infrastructure and heterogeneous applications lead to sustainability and stability. In this article, we propose an integrated and efficient middleware for heterogeneous services in a smart grid. Specifically, we first develop a mutual application access control principle that keeps users obtaining a satisfying assignment. Next, a collaborative and dynamic information exchange infrastructure is proposed for different smart meters, and a local information collector is designed to implement the communication and computing through power management messages. Finally, we present four steps to design a flexible service-oriented middleware for heterogeneous applications. Numerical simulation results are provided to demonstrate the efficiency of the proposed middleware.
Enhancing effects of serum-rich and cytokine-supplemented culture conditions on developing blastocysts and deriving porcine parthenogenetic embryonic stem cells

The present study was conducted to develop an effective method for establishment of porcine parthenogenetic embryonic stem cells (ppESCs) from parthenogenetically activated oocyte-derived blastocysts. The addition of 10% fetal bovine serum (FBS) to the medium on the 3rd day of oocyte culturing improved the development of blastocysts, attachment of inner cell masses (ICMs) onto feeder cells, and formation of primitive ppESC colonies. ICM attachment was further enhanced by basic fibroblast growth factor, stem cell factor, and leukemia inhibitory factor. From these attached ICMs, seven ppESC lines were established. ppESC pluripotency was verified by strong enzymatic alkaline phosphatase activity and the expression of pluripotent markers OCT3/4, Nanog, and SSEA4. Moreover, the ppESCs were induced to form an embryoid body and teratoma. Differentiation into three germ layers (ectoderm, mesoderm, and endoderm) was confirmed by the expression of specific markers for the layers and histological analysis. In conclusion, data from the present study suggested that our modified culture conditions using FBS and cytokines are highly useful for improving the generation of pluripotent ppESCs.
Estimating Nonparametric Random Utility Models with an Application to the Value of Time in Heterogeneous Populations

The estimation of random parameters by means of mixed logit models is now current practice for the analysis of transportation behaviour. One of the most straightforward applications is the derivation of willingness-to-pay distribution over a heterogeneous population, an important element for dynamic tolling strategies on congested networks. In numerous practical cases, the underlying discrete choice models involve parametric distributions that are a priori specified and whose parameters are estimated. This approach can however lead to many problems for realistic interpretation, such as negative value of time, etc. In this paper, we propose to capture the randomness present in the model by using a new nonparametric estimation method, based on the approximation of inverse cumulative distribution functions. This technique is applied to simulated data, and the ability to recover both parametric and nonparametric random vectors is tested. The nonparametric mixed logit model is also used on real data derived from a stated preference survey conducted in the region of Brussels (Belgium). The model presents multiple choices and is estimated on repeated observations. The obtained results provide a more realistic interpretation of the observed behaviours.
Critical race life course perspective theory: a framework for understanding racism over the life course

Abstract In this article, Raygine DiAquoi examines the conversations Black families have with their sons to prepare them for racial bias and discrimination. Over the course of a year, DiAquoi conducted a qualitative exploration of the content of ‘the talk,’ as this conversation has come to be known, that 17 families have with their sons about racism. An analysis of photo elicitation and standard interview data reveals a new framework for understanding the way that racism manifests over the life course of an individual: Critical Race Life Course Perspective.
Hyperkähler prequantization of the Hitchin system and Chern-Simons theory with complex gauge group

Hitchin has shown that the moduli space ${\mathcal M}$ of the dimensionally reduced self-dual Yang-Mills equations has a hyperK\"{a}hler structure. In this paper we first explicitly show the hyperK\"{a}hler structure, the details of which is missing in Hitchin's paper. We show here that ${\mathcal M}$ admits three pre-quantum line bundles, corresponding to the three symplectic forms. We use Quillen's determinant line bundle construction and show that the Quillen curvatures of these prequantum line bundles are proportional to each of the symplectic forms mentioned above. The prequantum line bundles are holomorphic with respect to their respective complex structures. We show how these prequantum line bundles can be derived from cocycle line bundles of Chern-Simons gauge theory with complex gauge group in the case when the moduli space is smooth.
Cooperative control of a multi-arm system using semi-autonomous telemanipulation and adaptive impedance

This paper addresses problems to achieve transparency and contact stability for Single Master Multi-Slave telemanipulation that consists of unconstrained and constrained motions. The adaptive bilateral control with a local force compensator is developed based on adaptive impedance control and contact force driven compensation with auto-switching functions. With a limited amount of knowledge about robotic and environment dynamics and a time-varying communication delay, the developed method guarantees good adaptive tracking performance in unconstrained motion and reduction of oscillating contacts to keep a balance of the system in constrained motion. Based on an actual haptic device and virtual robots, haptic simulations are presented to demonstrate adaptive transparency and contact stability in the presence of communication delays.
On French prosody

This report describes the organization of the fundamental frequency (F 0) variations in French sentences. It is based on the analysis of the Fo patterns of declarative sentences read by six native speakers of French. The prosodic-syntactic structure has several levels: the prosodic sentence, the prosodic sense-group and the prosodic word. It describes the different strategies used by the speakers, and the effect of the rate of speech. The paper mentions a feature unnoticed in the previous studies in French: the initial rise at the beginning of the lexical words in sentences read in a neutral manner. It describes the effect of the nature of the underlying phonemes on the exact location of the Fo rises and valleys, and the differences between speakers.
Musical data mining for electronic music distribution

Music classification is a key ingredient for electronic music distribution. Because of the lack of standards in music classification (or the lack of enforcement of existing standards), there is a huge amount of unclassified music titles in the world. The authors propose a classification method based on a musical data mining technique based on co-occurrence and correlation analysis that can be used for classification. It gives a new approach to similarity between several titles of music or several artists. We study large corpora of textual information referring titles of music or artists whose names are decided by humans without particular constraints other than readability, and draw various hypotheses concerning the natural similarities that emerge from these corpora. Based on a clustering technique, we show that interesting groups can reveal specific music genres and allow classification of music titles in an objective manner.
The Relationship Between Hope, Core Self-Evaluations, Emotional Well-Being, Sexual Risk Taking, Substance Use, and Academic Performance in Freshman University Students

3 PROPOSAL . 4-42 SURVEY . 43-51 EXECUTIVE SUMMARY . 52 SLIDE PRESENTATION . 53-82 DISSEMINATION PLAN . 83
Contribution of stroke volume to the change in pulse pressure pattern with age.

This study investigated the effect of age on pulse pressure and its underlying mechanisms in unmedicated hypertensive men with the same level of mean arterial pressure. We included 77 men 17 to 76 years old with daytime mean arterial pressure between 95 and 114 mm Hg. In the supine position, pulse pressure showed a significant widening in young (<30 years) and older (>/=60 years) patients. Pulse pressure decreased in parallel with stroke index from age >30 to 40 to 49 years. Upright posture, however, eliminated this difference through a larger orthostatic fall in stroke index and pulse pressure in the youngest patients. After age 50 years, pulse pressure exhibited a progressive widening despite the further age-related decrease in stroke index. Supine, upright, and 24-hour pulse pressure fitted a curvilinear correlation with age (r=0.55, 0.56, and 0.68, respectively, P<0.001), with a transition at age 50 years. Before age 50 years, 24-hour pulse pressure correlated positively with stroke volume (r=0.5, P<0.001) and negatively with arterial compliance (SV/PP ratio, r=-0.37, P<0.01). In contrast, in men >/=50 years old, 24-hour pulse pressure correlated negatively with the SV/PP ratio (r=-0.5; P<0.01), without significant influence of stroke volume. Thus, in hypertensive men, the age-related change in stroke volume significantly accounted for the change in clinic and ambulatory pulse pressure during young adulthood, but its contribution decreased after the fifth decade.