Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse Reconstruction for Temperature Distribution Using DTS Fiber Optic Sensors with Applications in Electrical Generator Stator Monitoring

This paper presents an image reconstruction method to monitor the temperature distribution of electric generator stators. The main objective is to identify insulation failures that may arise as hotspots in the structure. The method is based on temperature readings of fiber optic distributed sensors (DTS) and a sparse reconstruction algorithm. Thermal images of the structure are formed by appropriately combining atoms of a dictionary of hotspots, which was constructed by finite element simulation with a multi-physical model. Due to difficulties for reproducing insulation faults in real stator structure, experimental tests were performed using a prototype similar to the real structure. The results demonstrate the ability of the proposed method to reconstruct images of hotspots with dimensions down to 15 cm, representing a resolution gain of up to six times when compared to the DTS spatial resolution. In addition, satisfactory results were also obtained to detect hotspots with only 5 cm. The application of the proposed algorithm for thermal imaging of generator stators can contribute to the identification of insulation faults in early stages, thereby avoiding catastrophic damage to the structure.
Microsecond photocapacitance transients observed using a charged microcantilever as a gated mechanical integrator

A new way to measure the rate of light-induced charge generation in organic solar cell films with a nanometer-scale probe. How light is converted to electricity in blends of organic donor and acceptor molecules is an unsettled question, partly because the spatial heterogeneity present in these blends makes them challenging to characterize. Although scanned-probe measurements have provided crucially important microscopic insights into charge generation and transport in these blends, achieving the subnanosecond time resolution needed to directly observe the fate of photogenerated charges has proven difficult. We use a charged microcantilever as a gated mechanical integrator to record photocapacitance indirectly by measuring the accumulated change in cantilever phase as a function of the time delay between precisely synchronized voltage and light pulses. In contrast with previous time-resolved scanned-probe photocapacitance measurements, the time resolution of this method is set by the rise and fall time of the voltage and light pulses and not by the inverse detection bandwidth. We demonstrate in an organic donor-acceptor blend the ability of this indirect, “phase-kick” technique to record multiexponential photocapacitance transients on time scales ranging from 40 μs to 10 ms. The technique’s ability to measure subcycle, nanosecond charge dynamics is demonstrated by measuring the tens of nanosecond sample electrical charging time.
A Power Planning Algorithm Based on RPL for AMI Wireless Sensor Networks

The advanced metering infrastructure (AMI) is an architecture for two-way communication between electric, gas and water meters and city utilities. The AMI network is a wireless sensor network that provides communication for metering devices in the neighborhood area of the smart grid. Recently, the applicability of a routing protocol for low-power and lossy networks (RPL) has been considered in AMI networks. Some studies in the literature have pointed out problems with RPL, including sub-optimal path selection and instability. In this paper, we defend the viewpoint that careful planning of the transmission power in wireless RPL networks can significantly reduce the pointed problems. This paper presents a method for planning the transmission power in order to assure that, after convergence, the size of the parent set of the RPL nodes is as close as possible to a predefined size. Another important feature is that all nodes in the parent set offer connectivity through links of similar quality.
Intercepción de precipitación en dos especies de ambiente semidesértico: Acacia farnesiana y Prosopis laevigata

Semi-arid regions and environments are widely considered as marginal, although, in Mexico these areas represent over the 50% of the national territory they are scarcely studied. The composition and physiognomy of the areas covered with vegetation have a primary influence on the ecosystem? s hydrologic behaviour this means that the trees have the ability to establish a very efficient network between soil and atmosphere (Wattenbach et al., 2005). In Mexico, there are a few studies regarding the semi-arid vegetation role on the regulation of the hydrologic processes mainly those related with the portion of rainfall interception loss controlling the rainfall that moistens the surface elements, mainly vegetation (Brutsaert, 2005). This study was carried out on 2006 in three localities within the semiarid central region of Mexico: El Carmen in Guanajuato state, and Amazcala and Cadereyta in Queretaro State. In total six trees were selected, two per locality and one individual from each species (Prosopis laevigata and Acacia farnesiana). The methodology developed by Guevara-Escovar et al. (2006) was used to measure the rainfall interception loss. A climate station was placed on each site as well, in order to measure the climate variables, soil humidity and temperature profiles were taken every 20 minutes while the rainfall was recorded every 10 minutes and vegetation was typified using Gentry? s transects. The most vegetation-covered site was El Carmen (150.20 m2/100m2); Amazcala had a cover of 129.88 m2/100m2 while in Cadereyta the vegetation covered 90.4m2/100m2 Based on this data the sites were characterized as follows: El Carmen can be considered a closed site while Amazcala is described as semi-closed and Cadereyta as open environments. During 2006 the rainfall levels were 781mm in El Carmen, 746mm in Cadereyta and 457mm for Amazcala. Rainfall interception during the study period for Acacia farnesiana was 15.01%, 20.11% and 30.64 while Prosopis laevigata results were 27.04%, 21.51% and 14.42% for Cadereyta, El Carmen and Amazcala respectively. In summary, the interception loss values found in this study reinforce those for the Mexican semi-arid regions reported previously.
Recent Advances in Experimental Whole Genome Haplotyping Methods

Haplotype plays a vital role in diverse fields; however, the sequencing technologies cannot resolve haplotype directly. Pioneers demonstrated several approaches to resolve haplotype in the early years, which was extensively reviewed. Since then, numerous methods have been developed recently that have significantly improved phasing performance. Here, we review experimental methods that have emerged mainly over the past five years, and categorize them into five classes according to their maximum scale of contiguity: (i) encapsulation, (ii) 3D structure capture and construction, (iii) compartmentalization, (iv) fluorography, (v) long-read sequencing. Several subsections of certain methods are attached to each class as instances. We also discuss the relative advantages and disadvantages of different classes and make comparisons among representative methods of each class.
Expediting model selection for Support Vector Machines based on data reduction

In recent years, Support Vector Machines (SVM) have been extensively applied to deal with various data classification problems. However, in some cases, the application of SVM is limited due to the time taken to conduct model selection for SVM. This issue is of particular significant for some modern applications, such as web mining, in which the large-scale database is frequently updated. This paper proposes a data reduction based mechanism aimed at expediting the model selection process in SVM. Experimental results show that the proposed mechanism is able to greatly reduce the time taken to carry out model selection at minimum cost.
Measuring the Capacity of a Web Server

The widespread use of the World Wide Web and related applications places interesting performance demands on network servers. The ability to measure the effect of these demands is important for tuning and optimizing the various software components that make up a Web server. To measure these effects, it is necessary to generate realistic HTTP client requests. Unfortunately, accurate generation of such traffic in a testbed of limited scope is not trivial. In particular, the commonly used approach is unable to generate client request-rates that exceed the capacity of the server being tested even for short periods of time. This paper examines pitfalls that one encounters when measuring Web server capacity using a synthetic workload. We propose and evaluate a new method for Web traffic generation that can generate bursty traffic, with peak loads that exceed the capacity of the server. Finally, we use the proposed method to measure the performance of a Web server.
PRESERVED COMPRESSION BASED ON CONTOURLET TRANSFORM

It is well known that the commonly used separable extensions of one-dimensional transforms, such as the wavelet transform, have limitations in capturing the geometry of image edges. But natural scene images always have geographic lines, such as textures, edges which can not be well reconstructed when compressed by using one-dimensional transform. So in lossy compression of images, it is important to find a method which can best preserve the image by using a small description. To solve this problem, in this paper, we present a new compression method which can preserve one of the most important cues of image: the directional details. In order to show the ability of detail preserving lossy coder we present tests using typical images with much directional information, and a comparison between wavelets and the new wavelet based contourlet transform(WBCT) is made. Finally, we present the results obtained by using image quality assessment method. Our experiments demonstrate that the decompressed images based on WBCT can preserve more directional information than wavelet transform, which can be used efficiently in future image processing such as classification, edge detecting and so on. 1 This work was supported by China National “863” Foundation. No. 2006AA12Z136 and the National Natural Foundation of China under Grant 40601055.
An integrated 5‐Mb physical, genetic, and radiation hybrid map of a 1p36.1 region implicated in neuroblastoma pathogenesis

Common genetic aberrations of neuroblastoma are deletions of the short arm of chromosome 1 (1p36) and MYCN amplification. Our deletion analysis of 25 tumor cell lines and 171 tumors strongly suggests that 1p harbors several tumor suppressor loci. Distinct loci are involved in MYCN single‐copy versus MYCN‐amplified neuroblastoma. Deletions in MYCN single‐copy tumors have a shortest region of overlap (SRO) of 20 cM at 1p36.3. MYCN‐amplified tumors have large deletions with an SRO of about 60 cM, from 1p36.1 to the telomere. This SRO is defined by D1S7 (1p36.1), which was the most distal locus retained. Therefore, a suppressor gene associated with MYCN‐amplified tumors probably maps within a few megabases distal of D1S7. In order to map this locus, we further refined this SRO. We mapped the breakpoint of the MYCN‐amplified neuroblastoma with the smallest 1p deletion between 56.6 and 57.2 cM from 1pter. Pulsed‐field gel electrophoresis and radiation hybrid mapping were used to construct a 5‐Mb physical map of this region. The map includes the region from 82.73 till 92.89 cR from 1pter. About half of it was isolated in P1 and PAC clones. The region harbors the genes FGR, SLC9A1, HMG17, EXTL1, AML2, RH, OP18, four ESTs, and a newly identified gene with a transcript size of approximately 7 Kb. Several of the mapped genes have a putative role in cell growth, differentiation, and morphogenesis. Genes Chromosomes Cancer 27:143–152, 2000. © 2000 Wiley‐Liss, Inc.
Lung Cancer Detection on CT Scan Images: A Review on the Analysis Techniques

Lung nodules are potential manifestations of lung cancer, and their early detection facilitates early treatment and improves patient’s chances for survival. For this reason, CAD systems for lung cancer have been proposed in several studies. All these works involved mainly three steps to detect the pulmonary nodule: preprocessing, segmentation of the lung and classification of the nodule candidates. This paper overviews the current state-of-the-art regarding all the approaches and techniques that have been investigated in the literature. It also provides a comparison of the performance of the existing approaches.
An intent-driven planner for multi-agent story generation

The ability to generate narrative is of importance to computer systems that wish to use story effectively for entertainment, training, or education. We identify two properties of story ¿ plot coherence and character believability ¿ which play a role in the success of a story. Plot coherence is the perception by audience members that character actions have relevance to the outcome of the story. Character believability is the perception that character actions are motivated by agents' internal beliefs and desires. Unlike conventional planning in which plan goals represent an agent's intended world state, multiagent story planning involves goals that represent the outcome of a story. In order for the plans' actions to appear believable, multi-agent story planners must determine not only how agents' actions achieve a story's goal state, but must also ensure that each agent appears to be acting intentionally. We present a narrative generation planning system for multi-agent stories that is capable of generating narratives with both strong plot coherence and strong character believability. The planning algorithm uses causal reasoning and a simulated intention recognition process to drive plan creation.
Illumination-robust face recognition with Block-based Local Contrast Patterns

This paper proposes a novel facial image representation Block-based Local Contrast Patterns (BLCP) for illumination-robust face recognition. This method is based on an effective texture descriptor local contrast patterns (LCP). We use the directed and undirected difference masks to calculate three types of local intensity contrasts: directed, undirected, and maximum difference responses. These response images are divided into several nonoverlapping blocks. In each block these responses are quantized and encoded into specific patterns. A joint histogram of these patterns is computed for each block and then we concatenate all the blocks' histograms into an enhanced feature vector to be used as a face descriptor. The experimental results on Extended Yale-B and FERET databases illustrate the effectiveness of our proposed method in illumination-robust face recognition.
Occurrence and morphometrics of the brachioradialis muscle in wild carnivorans (Carnivora: Caniformia, Feliformia)

The brachioradialis is an important muscle that acts in the external rotation of the forearm (supination). However, its occurrence is controversial and little studied in the order Carnivora. Thus, this study investigates the occurrence and anatomo-functional arrangement of this muscle in wild carnivorans species. Fifty-eight thoracic limbs of specimens from species of Canidae, Procyonidae, Mustelidae and Felidae were dissected. Measurements of the length of the muscle (ML), the length of the forearm (FL), latero-medial width of the muscle (MW) and the lateral-medial diameter of the forearm (FD) were obtained to establish the ratios MW/FD and ML/FL in order to investigate the relative proportion of the muscle in relation to the forearm of each species. The brachioradialis muscle was identified in all species, although it was unilaterally or bilaterally absent in some canid individuals. The ratios demonstrated significant differences in the anatomical proportions among the families, with greater functional importance in the mustelids, procyonids, and felids because of a set of elaborate movements in the thoracic limb of representatives of these families when compared to canids.
C-Reactive Protein Levels and Arterial Abnormalities in the Offspring of Patients with Premature Myocardial Infarction

Aims: To determine whether high C-reactive protein (CRP) levels and increased intima-media thickness of the common carotid arteries are coexistent in adolescents and young adults with a family history (FH) of premature myocardial infarction (MI). Methods: 50 healthy young subjects whose parents had had premature MI and 50 control matched subjects were enrolled in the study. CRP levels and the intima-media thickness of the distal common carotid arteries were evaluated in all subjects. Results: As compared with the control subjects, the offspring of patients with premature MI had a higher CRP concentration (mean ± SD 8.8 ± 2.6 versus 3.9 ± 0.6 mg/l, p < 0.02) and greater intima-media thickness of the common carotid arteries (values for combined sides, mean ± SD 0.48 ± 0.02 versus 0.43 ± 0.02 mm, p < 0.03). Conclusion: High serum levels of CRP and arterial structural changes are coexistent at an early age in subjects with an FH of premature MI.
A Fast , Effective , Non-Projective , Semantically-Enriched Parser

Dependency parsers are critical components within many NLP systems. However, currently available dependency parsers each exhibit at least one of several weaknesses, including high running time, limited accuracy, vague dependency labels, and lack of nonprojectivity support. Furthermore, no commonly used parser provides additional shallow semantic interpretation, such as preposition sense disambiguation and noun compound interpretation. In this paper, we present a new dependency-tree conversion of the Penn Treebank along with its associated fine-grain dependency link types and a parser that is, to the best of our knowledge, the first dependency parser capable of parsing more than 75 sentences per second at over 93% accuracy. We explain how a non-projective extension to shift-reduce parsing can be incorporated into non-directional easy-first parsing. The parser performs well when evaluated on the standard test section of the Penn Treebank, outperforming several popular open source dependency parsers.
An adaptive algorithm for mel-cepstral analysis of speech

The authors describe a mel-cepstral analysis method and its adaptive algorithm. In the proposed method, the authors apply the criterion used in the unbiased estimation of log spectrum to the spectral model represented by the mel-cepstral coefficients. To solve the nonlinear minimization problem involved in the method, they give an iterative algorithm whose convergence is guaranteed. Furthermore, they derive an adaptive algorithm for the mel-cepstral analysis by introducing an instantaneous estimate for gradient of the criterion. The adaptive mel-cepstral analysis system is implemented with an IIR adaptive filter which has an exponential transfer function, and whose stability is guaranteed. The authors also present examples of speech analysis and results of an isolated word recognition experiment. <<ETX>>
MUDOS-NG: Multi-document Summaries Using N-gram Graphs (Tech Report)

This report describes the MUDOS-NG summarization system, which applies a set of language-independent and generic methods for generating extractive summaries. The proposed methods are mostly combinations of simple operators on a generic character n-gram graph representation of texts. This work defines the set of used operators upon n-gram graphs and proposes using these operators within the multi-document summarization process in such subtasks as document analysis, salient sentence selection, query expansion and redundancy control. Furthermore, a novel chunking methodology is used, together with a novel way to assign concepts to sentences for query expansion. The experimental results of the summarization system, performed upon widely used corpora from the Document Understanding and the Text Analysis Conferences, are promising and provide evidence for the potential of the generic methods introduced. This work aims to designate core methods exploiting the n-gram graph representation, providing the basis for more advanced summarization systems.
Maximum Likelihood Wireless Sensor Network Source Localization Using Acoustic Signal Energy Measurements

A maximum likelihood (ML) acoustic source location estimation method is presented. This method uses acoustic signal energy measurements taken at individual sensors of an ad hoc wireless sensor network to estimate the locations of multiple acoustic sources. Compared to existing acoustic energy based source localization methods, this proposed ML method delivers more accurate results and offers the enhanced capability of multiple source localization. A multi-resolution search algorithm and an expectationmaximization (EM) like iterative algorithm are proposed to expediate the computation of source locations. The Cramer-Rao Bound (CRB) of the ML source location estimate has been derived. When there is only a single source in the sensor field, the corresponding CRB formulation can be used to analyze the impacts of sensor placement to the accuracy of location estimates. Extensive simulations have been conducted. Empirically, it is observed that this proposed ML method consistently outperforms existing acoustic energy based source localization methods. An example applying this method to track military vehicles using real world experiment data also demonstrates the performance advantage of this proposed method over a previously proposed acoustic energy source localization method.
What we can learn from measurements of air electric conductivity in 222Rn‐rich atmosphere

Electric conductivity of air is an important characteristic of the electric properties of an atmosphere. Testing instruments to measure electric conductivity ranging from ~10−13 to 10−9 S m−1 in natural conditions found in the Earth atmosphere is not an easy task. One possibility is to use stratospheric balloon flights; another (and a simpler one) is to look for terrestrial environments with significant radioactive decay. In this paper we present measurements carried out with different types of conductivity sensors in two 222Rn‐rich environments, i.e., in the Roselend underground tunnel (French Alps) and in the Institute of Radioprotection and Nuclear Safety BACCARA (BAnC de CAllibrage du RAdon) chamber. The concept of the conductivity sensor is based on the classical time relaxation method. New elements in our design include isolation of the sensor sensitive part (electrode) from the external electric field and sensor miniaturization. This greatly extends the application domain of the sensor and permits to measure air electric conductivity when the external electric field is high and varies from few tens of V m−1 to up to few tens of kV m−1. This is suitable to propose the instrument for a planetary mission. Two‐fold objectives were attained as the outcome of these tests and their analysis. First was directly related to the performances of the conductivity sensors and the efficiency of the conductivity sensor design to shield the external electric field. Second objective aimed at understanding the decay mechanisms of 222Rn and its progeny in atmosphere and the impact of the enclosed space on the efficiency of gas ionization.
National Center for Geographic Information and Analysis The Integration of Spatial Analysis and GIS: The Development of the Statcas Module for ARC/INFO

It seems widely expected that future GISs will have increased analytical capabilities that will take them beyond being efficient display and database management devices. Several attempts have already been made to link existing analytical software to various GISs. However, a problem with all of these attempts is that the user is forced to switch back and forth between the GIS operating environment and the analytical software. In this paper we present a statistical analysis package, STACAS, that runs totally within the operating environment of a GIS and utilizes a command structure that makes running the package transparent to the user of the GIS. THE INTEGRATION OF SPATIAL ANALYSIS AND GIS: THE DEVELOPMENT OF THE STATCAS MODULE FOR ARC/INFO