Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentence Alignment by Means of Cross-Language Information Retrieval

In this chapter, we focus on the specific problem of sentence alignment given two comparable corpora. This task is essential to some specific applications such as parallel corpora compilation Utiyama & Tanimura (2007) and cross-language plagiarism detection Potthast et al. (2009). We address this problem by means of a cross-language information retrieval (CLIR) system. CLIR deals with the problem of finding relevant documents in a language different from the one used in the query. Different strategies are used, from ontology based Soerfel (2002) to statistical tools. Latent Semantic Analysis can be used to get a list of parallel words Codina et al. (2008). Multidimensional Scaling projections Banchs & Costa-jussa (2009) can also be used in order to find similar documents in a cross-lingual environment. Other techniques are based on machine translation, where the search is performed over translated texts Kishida (2005). Within this framework, two basic components should be distinguished: a translation model, and a retrieval model that may work as in the monolingual case. The translation can be faced either in the query, or in the document. In the case of document translation, statistical machine translation systems can be used for translating document collections into the original query language. In the case of query translation, the challenges of deciding how a term might be written in another language, which of the possible translations should be retained, and how to weight the importance of translation alternatives when more than one translation is retained should be considered. Here, we use the query translation approach. Then, a segment of text in a given source language is used as query for recovering a similar or equivalent segment of text in a different target language. Given that we are using complete sentences which provide a certain context for the terms to be translated, we do not have the disadvantages mentioned in the above lines. Particularly, when using the query translation approach, we investigate if using either a rule-based or a statitical-based machine translation system influence the final quality of the sentence alignment. Additionally, we test if standard automatic MT metrics are correlated with the standards metrics of the sentence alignment. Rule-based machine translation (RBMT) systems were the first commercial machine translation systems. Much more complex than translating word to word, these systems develop linguistic rules that allow the words to be put in different places, to have different meaning depending on context, etc. RBMT technology applies a set of linguistic rules in three 2
Cost Effectiveness of Virtual Reality Graded Exposure Therapy with Physiological Monitoring for the Treatment of Combat Related Post Traumatic Stress Disorder

Virtual Reality Graded Exposure Therapy (VRGET) is an effective treatment for combat-related PTSD. We summarize the outcomes of a VRGET pilot study with 12 participants who completed one to multiple combat tours in support of the War on Terrorism and who were subsequently diagnosed with combat-related PTSD. Details of the collaborative program amongst the Virtual Reality Medical Center (VRMC), Office of Naval Research, the Naval Medical Center San Diego (NMCSD) and the Navy Hospital Camp Pendleton are discussed as is the VRGET outcomes of significant reductions in PTSD symptoms severity. We also described the estimated cost-effectiveness of VRGET for the treatment of combat-related PTSD, as contrasted to Treatment as Usual (TAU) for combat-related PTSD.
Endogenous Market Thickness, Prices and Honesty: Quality Demand Traps

We study the interaction between product quality, prices and demand in a dynamic model of asymmetric information. Sellers choose between producing high quality goods which gives low profits today but increases probability of future survival in the market and low quality ones which gives higher returns today but lowers future survival. However, demand depends on expected quality. Multiple steady states (high demand high quality, low demand low quality) exist if the present discounted value of lifetime profits from selling high quality goods exceeds a certain cutoff. We also characterise the equilibrium price which depends on the distribution of buyer valuations.
Efficient Wakeup Scheduling Considering Both Resource Usage and Timing Budget for Power Gating Designs

Power gating has been a very effective way to reduce power leakage. Normally, wakeup scheduling is required to control the turn-on times of sleep transistors to limit the surge current during the wakeup process. In this paper, a voltage sensor is adopted to compare the virtual ground voltage with the predesigned reference voltages, and use the result to determine the turn-on times of sleep transistors. We then propose a novel wakeup scheduling formulation that considers the tradeoff between wakeup times and hardware resources incurred by the voltage sensor. To address this problem, on the one hand, an efficient algorithm is proposed to find a wakeup scheduling with minimum wakeup time under the resource constraint. On the other hand, the algorithm to find a wakeup scheduling with minimum resource usage under the timing budget is presented. Experimental results show that with little increase in wakeup times, our algorithm can achieve significant hardware resource reduction for power gating designs.
An Algorithm for Generation of Attack Signatures Based on Sequences Alignment

This paper presents a new algorithm for generation of attack signatures based on sequence alignment. The algorithm is composed of two parts: a local alignment algorithm-GASBSLA (Generation of Attack Signatures Based on Sequence Local Alignment) and a multi-sequence alignment algorithm-TGMSA (Tri-stage Gradual Multi-Sequence Alignment). With the inspiration of sequence alignment used in Bioinformatics, GASBSLA replaces global alignment and constant weight penalty model by local alignment and affine penalty model to improve the generality of attack signatures. TGMSA presents a new pruning policy to make the algorithm more insensitive to noises in the generation of attack signatures. In this paper, GASBSLA and TGMSA are described in detail and validated by experiments.
Still Image Objective Segmentation Evaluation using Ground Truth

In this paper, an objective segmentation evaluation metric suitable for the evaluation of still image segmentation results is proposed. The proposed metric is based on the spatial accuracy approach, originally proposed for the evaluation of foreground/backgroung segmentation masks generated from video sequences. This approach is extended to still image segmentation evaluation, where both the estimated segmentation masks and the ground truth mask typically contain multiple regions. The proposed method takes into account, using a single metric, not only the accuracy of the boundary localization of the created segments but also the under-segmentation and over-segmentation effects, which can hinder the performance of any segmentation algorithm and decrease the usability of the segmentation results in content-based applications. Several experiments have shown the potential of this approach.
Instruction replication: reducing delays due to inter-PE communication latency

As feature sizes are becoming smaller, wire delays are becoming very critical. Clustering is a popular decentralization approach to reduce the impact of shrinking technologies on clock speed. In this approach, the centralized instruction window is replaced with multiple smaller windows, called clusters (PEs). The performance of these clustered processors depends on the amount of inter-PE communication and load imbalance incurred by the distribution algorithm used to distribute instructions among the PEs. We investigate a novel approach of reducing the impact of inter-PE communication latency, while preserving good load balance. The basic idea is to selectively replicate instructions in those PEs where their results are required. The replication is done based on heuristics that weigh the potential benefits of replication. We found that with instruction replication, the IPC of a clustered processor is significantly higher than that obtained without instruction replication and is within just 8% of that of a superscalar configuration with a centralized instruction window.
Texting laws and cell phone users: motivations for texting while driving

ii ACKNOWLEDGMENTS First, I would like to express my deep gratitude for the committee that helped make this possible. Your careful instruction and willingness to help me through this arduous task is greatly appreciated and will never be forgotten. Dr. Reynolds, thank you for chairing my thesis. You made the process much easier and were always there when I lost my way on the thesis road. Professor Freeman, thank you for your careful advice with the legal component of my thesis. Your positive reinforcement always kept me upbeat about my topic. Dr. Porter, thank you for helping me with the technology component of my thesis. Your deep interest in my topic and your advice regarding technology was always greatly appreciated. I could not have done this without all of you. Next, I would like to give a special thanks to Dr. Danny Shipka. You are truly one of the few great educators of mass communication. I am honored to call you a friend and I would not be here today if it was not for your belief in me throughout the graduate school process. Thank you for all your help and support. Next, I would like to thank all the graduate instructors in the Manship School of Mass Communication, you made this truly a life changing experience. Thank you for the instruction and help in all of your classes. Last, but not least, thank you Melanie Kalmin. I could not have done this process without your love and support. I am truly grateful to have someone like you in my life.
Genetic Algorithm for the Construction of Small and Highly

A Genetic Algorithm (GA) is applied to derive circuits that combine area eeciency and testability. These circuits are obtained from Ordered Kronecker Functional Decision Diagrams (OKFDDs). In \Becker and Drechsler (1995)" a heuristic approach has been presented. In this paper we show how these results can further be improved by GAs. Finally , we apply our minimization algorithm to technology mapping for FPGAs. We present experimental results to show the eeciency of our approach.
Statistical classification for E-glass fiber fabric defects based on sparse coding

In this research, a statistical classification algorithm based on sparse coding is presented to classify the defects on E-glass fiber fabrics adaptively. First, all images are preprocessed by being convolved with the MR8 filter banks to obtain the filter responses. For the filter response space of each type of image, we will learn a Class-specific dictionary, and all the Class-specific dictionaries are concatenated to form a complete dictionary. Then, the reconstructed contribution rate of each atom of the complete dictionary to the image filter response is counted to obtain two types of histogram features of each image. Finally, the improved sparse representation classification is used to classify test defect images based on the histogram features. The proposed adaptive classification method has achieved an average classification accuracy of 96.67% on the dataset collected onsite. The results validate the superiority of the proposed method to E-glass fiber fabrics.
Adaptive fuzzy control of operation space constrained exoskeletons under unmodelled dynamics

In this paper, we present adaptive fuzzy tracking an exoskeletons that operates in a constrained region of the task space. The exoskeleton enables a human forearm to track any continuous desired trajectory within the constrained range, in the presence of parametric/functional uncertainties, unmodelled dynamics including actuator dynamics, and/or disturbances from the environment. Barrier Composite Energy Function (BCEF) scheme with a novel Barrier Lyapunov Function is proposed to facilitate the analysis of state tracking error convergence without the end-effector ever transgressing the constrained region. Adaptive scheme of fuzzy approximation controller to compensate for functional uncertainties in the dynamic model of human and exoskeleton, and unknown disturbances from the environment. The proposed adaptive control performance is validated through actual experiments.
A Differential Geometric Approach to Equidistributed Knots on Riemannian Manifolds

We introduce a diierential geometric approach to the numerical generation of equidistributed knots on closed compact Rieman-nian manifolds. The algorithms are based on minimization of a potential function by intrinsic versions of gradient or BFGS methods. Our approach nds also applications to equidistribution on spheres and is able to reproduce already known results. Numerical examples are given at the end of the paper. x1. Introduction The problem of nding equidistributed knot sets on a sphere has a long history. Applications of such knots can be found, e.g., in interpolation or numerical quadrature on spheres, in geophysics, meteorology, astrophysics, and elsewhere. A common way to generate equidistributed points on spheres is the minimization of a given potential function E where the points can be interpreted as electrons innuenced by repulsing forces. For optimal points an equilibrium position is reached (in physics, this problem is known as Thomson's problem 10]). Here, x i 2 IR 3 are the coordinates of the electrons and k k 2 is the usual Euclidean norm in IR 3. Because all electrons should stay on the sphere, we have the additional constraints kx i k 2 = 1 with i = 1; : : : ; N, and minimization of E is a constrained optimization problem. All rights of reproduction in any form reserved.
Dynamic cooperative spectrum sensing in cognitive radio networks

The prime objective of spectrum sensing in Cognitive Radio (CR) networks is to increase the efficiency of spectrum utilization and improve the network performance. Both of false probability and misdetection probability can reduce the network performance. We use the mean error detection probabilities to denote the network performance. As the value of the mean detection probabilities decreases, the network performance will be improved. In order to achieve this aim, we use the Markov model of the channel occupancy to estimate the prior probabilities for the hypothesis test in dynamic traffic environment. Because of the uncertainty under local detection, the spectrum detection scheme is extended to cooperative sensing among multiple second users. Moreover, we also propose a dynamic decision threshold to optimize the cooperative spectrum detection. The numerical results show that our proposed scheme can further reduce the mean error detection probabilities.
A Design Space for Exploring Rich and Complex Information Environments

In this paper we discuss the visualization and interaction paradigms based on overview+detail and focus+context models, proposing a design methodology suitable for rich information environments, made of multivariate data and multi-device deployment. We propose to identify a set of meaningful categories of information visualization and interaction corresponding to different user goals and exploration spaces, starting from a global universe of discourse and going down into the ultimate data items, through discrete intermediate steps corresponding to structured context and overview levels. Each category defines an association with a specific knowledge goal, the deployment on a suitable class of devices and the access through adequate interaction techniques. Such design methodology is applied to two case studies, one in the domain of energy consumption management, the other in cultural heritage fruition.
A Distributed Algorithm to Construct Multicast Trees in WSNs: An Approximate Steiner Tree Approach

Multicast tree is a key structure for data dissemination from one source to multiple receivers in wireless networks. Minimum length multicast tree can be modeled as the Steiner Tree Problem, and is proven to be NP-hard. In this paper, we explore how to efficiently generate minimum length multicast trees in wireless sensor networks (WSNs), where only limited knowledge of network topology is available at each node. We design and analyze a simple and distributed algorithm, which we call Toward Source Tree (TST), to build multicast trees in WSNs. We show three metrics of TST algorithm, i.e., running time, tree length and energy efficiency. We prove that its running time is O(√nlog n), the best among all existing solutions to our best knowledge. We prove that TST tree length is in the same order as Steiner tree, give a theoretical upper bound and use simulations to show the ratio between them is only 1.114 when nodes are uniformly distributed. We evaluate energy efficiency in terms of the number of forwarding nodes in multicast trees, and prove that it is order-optimal. We give an efficient way to construct multicast tree in support of transmission of voluminous data.
PECAM-1 Interacts With Nitric Oxide Synthase in Human Endothelial Cells: Implication for Flow-Induced Nitric Oxide Synthase Activation

Objective—We have previously shown that fluid shear stress (FSS) triggers endothelial nitric oxide synthase (eNOS) activity in endothelial cells and that the mechanotransduction mechanisms responsible for activation discriminate between rapid changes in FSS and FSS per se. We hypothesized that the particular sublocalization of eNOS at the cell–cell junction would render it responsive to activation by FSS temporal gradients. Methods and Results—In human umbilical vein endothelial cells (HUVECs), immunofluorescence revealed strong eNOS membrane staining at the cell–cell junction colocalizing with platelet/endothelial cell adhesion molecule-1 (PECAM-1). In PECAM-1 −/− mouse aorta, eNOS junctional localization seen in the wild type was absent. Similarly, junctional staining was lost in wild-type aorta near intercostal artery branches. eNOS/PECAM-1 association in HUVECs was confirmed by coimmunoprecipitation. When HUVECs were subjected to a 0.5s impulse of 12 dynes/cm2, a transient disruption of the eNOS/PECAM-1 complex was observed, accompanied by an increase in eNOS activity (cGMP production). Ramped flow did not trigger complex dissociation or an increase in cGMP production. In a cell-free system, a direct inhibition of eNOS activity by PECAM-1 is shown. Conclusions—These results suggest that eNOS is complexed with PECAM-1 at the cell–cell junction and is likely involved in the modulation of eNOS activity by FSS temporal gradients but not by FSS itself.
Is faecal calprotectin equally useful in all Crohn's disease locations? A prospective, comparative study

Introduction There are data suggesting that the diagnostic usefulness of faecal calprotectin (FC) may vary depending on the Crohn's disease (CD) location. The aim of the study was to compare the diagnostic usefulness of FC in CD patients with different disease locations. Material and methods We prospectively enrolled 120 CD patients in the study. Disease activity was assessed by using Crohn's Disease Activity Index (CDAI), biochemical markers, and endoscopic and radiographic methods. Faecal calprotectin concentration was assessed in single stool samples by using the ELISA method. Results Among all patients, 54 (45%) had ileocolonic CD location, 44 (36.5%) had isolated small bowel location, and 22 (18.5%) had colonic CD location. FC correlated significantly with C-reactive protein concentration and endoscopic and radiographic activity among patients with isolated small bowel CD (p = 0.03, r = 0.32; p < 0.0001, r = 0.78; p = 0.03, r = 0.35; respectively) and with C-reactive protein and endoscopic activity in isolated colonic CD (p = 0.0009, r = 0.7; p = 0.0002, r = 0.78; respectively). CDAI and inflammatory biochemical markers did not correlate with endoscopic and radiographic assessment in small bowel CD. In patients with ileocolonic CD, FC correlated significantly with endoscopy (p = 0.006, r = 0.5), radiographic assessment (p = 0.04, r = 0.3), CDAI (p = 0.0006, r = 0.5) and the majority of biochemical markers. Conclusions Faecal calprotectin is a useful diagnostic marker in all CD patients. Although its usefulness in small bowel CD seems to be the lowest, it should be utilized particularly in this disease location because of the lack of other reliable, non-invasive diagnostic methods.
Scatter-partitioning Rbf Network for Function Regression and Image Segmentation: Preliminary Results

Scatter-partitioning Radial Basis Function (RBF) networks increase their number of degrees of freedom with the complexity of an input-output mapping to be estimated on the basis of a supervised training data set. Due to its superior expressive power a scatter-partitioning Gaussian RBF (GRBF) model, termed Supervised Growing Neural Gas (SGNG), is selected from the literature. SGNG employs a one-stage error-driven learning strategy and is capable of generating and removing both hidden units and synaptic connections. A slightly modiied SGNG version is tested as a function estimator when the training surface to be tted is an image, i.e., a 2-D signal whose size is nite. The relationship between the generation, by the learning system, of disjointed maps of hidden units and the presence, in the image, of pictorially homogeneous subsets (segments) is investigated. Unfortunately, the examined SGNG version performs poorly both as function estimator and image segmenter. This may be due to an intrinsic inadequacy of the one-stage error-driven learning strategy to adjust structural parameters and output weights simultaneously but consistently. In the framework of RBF networks, further studies should investigate the combination of two-stage error-driven learning strategies with synapse generation and removal criteria. y Internal report of the paper entitled \Image segmentation with scatter-partitioning RBF networks: A feasibility study," to be presented at the conference
A New Energy-Efficient, Scalable and Robust Architecture for Wireless Sensor Networks

The major problem for most of wireless sensor networks applications is the energy consumption. In this paper we propose a new architecture called EDETA (Energy-efficient aDaptive hiErarchical and robusT Architecture) optimized to save node's power. This architecture is scalable and suitable for heterogeneous and homogeneous wireless sensor networks, supports single or multiple sinks, and also provides features increasely-demanded in the current applications such as fault tolerance and bounded-time response communications. The proposed protocol is able to autoconfigure, and it is based on two-levels hierarchical architecture. The lower level is based on cluster organization, while the upper one is formed as a dynamic tree of clusters heads to send the data to the sink. Our experiments, based on real energy measures, show that EDETA can reduce the energy consumption in typical applications in a factor of 8x compared with most popular power-aware protocols. Furthermore, EDETA multiplies the lifetime of the sensor network while providing, in addition, extra-features such as fault-tolerant mechanisms and bounded time.