Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Classification Systems and Associated 3-Dimensional Model Libraries for Synthetic Environments of the Future

This paper describes a new hierarchical data structure used to store natural and man-made feature data for use in modern and future real-time simulation systems. This system is not based purely on a map oriented feature set as are the DFAD and FACC based feature classification structures. This scheme is based on visible man-made and natural features (tangible features) and a wide assortment of intangible objects that are encountered in geographic information system (GIS) databases. Also, a unique part of this classification scheme is the existence of an integrated feature-objects/3D-Model objects relationship. An integral part of the system is a set of 3D models, in standard OpenFlight format, each associated with a feature object. This classification system is an object oriented classification system. The feature and attribute objects included in this new system are based on earlier, more traditional feature classification systems such as DFAD/FID, DIGEST/FACC, SEDRIS/EDCS, USGS/Anderson, and USFWS/NWI. However, this classification scheme has been expanded with the express intent of opening up the real-time simulation field to a wide variety of scientific (and not so scientific), research, and production fields of study. This classification system is not limited to a specific discipline but allows internal cross-referencing between the various "standard" feature classification systems currently in use today. This not only makes the new classification system usable in the traditional Modeling and Simulation (M&S) environment. It also will allow the real-time simulation capability to migrate into many other disciplines – disciplines totally outside the M&S environment. Barry Bitters has worked as a Senior Software Engineer for the past 11 years within the Synthetic Environment Generation Group of Lockheed Martin Information Systems. In this capacity, he has developed and designed software and database products in direct support of the U.S. Air Force Special Operations Command’s real-time simulation effort. He also teaches Geographic Information Systems (GIS) and various other information technology subjects at the University of West Florida. He is a retired Army Warrant Officer with a mapping, computer science, and military intelligence background. He has a Masters degree in geography and is currently enrolled in a doctoral program at Florida State University where his primary research topic is Geographic Information Systems (GIS) and real-time simulation. Feature Classification Systems and Associated 3-Dimensional Model Libraries for Synthetic Environments of the Future Barry Bitters Lockheed Martin Information Systems P.O. Box 9340 Hurlburt Field, FL 32644 barry.bitters@lmco.com
Foot landmarking for footwear customization

As consumers are becoming increasingly selective of what they wear on their feet, manufacturers are experiencing problems developing and fitting the right footwear. Literature suggests that shoes with a shape similar to feet may be comfortable because they attempt to maintain the feet in a neutral posture. The objective of this paper is to develop a metric to quantify mismatches between feet and lasts and also to be able to generate the two-dimensional outline of the foot using the minimum number of landmarks. Fifty Hong Kong Chinese were participants in the experiment. In addition to subject weight, height, foot length and foot width, the left foot outlines were drawn and 18 landmarks were marked on each of the two-dimensional foot outlines. A step-wise procedure was used to reduce the chosen 18 landmarks to eight, such that the mean absolute negative error (an indicator of ‘tightness’) between the foot outline and the modelled curve was 1.3 mm. These eight landmarks seem to show an improvement over those proposed by other researchers, thus showing the importance of choosing the right landmarks for modelling the foot. The positive and negative absolute errors were on average 1.8 mm and 1.3 mm respectively. Moreover, the mean errors for the toe region and for the rest of the foot were 1.7 mm and 1.6 mm respectively. The results indicate that the foot outline, an important component for footwear functionality and fitting, may be modelled using eight critical landmarks.
SDN integration in LTE mobile backhaul networks

The major challenge in future mobile networks is how to improve throughput to support the increase demand in traffic. Software Defined Networks is the new technology proposed but so far it has been proposed to be integrated in the current 4G architecture without major changes. However, we present the mobile networks beyond 4G where Software Defined Network should be used in a more disruptive approach to redesign the current architecture. This proposal includes the proper migration path to ensure reasonable transition phase. The objective is not to meet short term needs but to fulfill the future throughput requirements by revamping the transport network in the mobile backhaul, and moving most of the current LTE network elements to the cloud. In this approach we remove completely the core mobile network as it is known today. Instead, the mobile architecture beyond 4G consists of a simplified access network formed by base stations i.e. eNodeBs, interconnected through a backhaul network composed by SDN switches managed from the cloud together with the rest of LTE network elements.
An infectious recombinant foot-and-mouth disease virus expressing a fluorescent marker protein

Foot-and-mouth disease virus (FMDV) is one of the most extensively studied animal pathogens because it remains a major threat to livestock economies worldwide. However, the dynamics of FMDV infection are still poorly understood. The application of reverse genetics provides the opportunity to generate molecular tools to further dissect the FMDV life cycle. Here, we have used reverse genetics to determine the capsid packaging limitations for a selected insertion site in the FMDV genome. We show that exogenous RNA up to a defined length can be stably introduced into the FMDV genome, whereas larger insertions are excised by recombination events. This led us to construct a recombinant FMDV expressing the fluorescent marker protein, termed iLOV. Characterization of infectious iLOV-FMDV showed the virus has a plaque morphology and rate of growth similar to the parental virus. In addition, we show that cells infected with iLOV-FMDV are easily differentiated by flow cytometry using the inherent fluorescence of iLOV and that cells infected with iLOV-FMDV can be monitored in real-time with fluorescence microscopy. iLOV-FMDV therefore offers a unique tool to characterize FMDV infection in vitro, and its applications for in vivo studies are discussed.
Nanoassembled Thin-Film Gas Sensor II . An Intrinsic Highly Sensitive Fibre Optic Sensor for Ammonia Detection

A layer-by-layer approach was used for the deposition of coatings with a nanometre thickness onto a multimode optical fi bre, from which the cladding had been removed, with the aim of realizing a fi bre optic ammonia sensor. The fi lm was self-assembled with alternate layers of tetrakis-(4-sulfophenyl) porphine (TSPP) and poly(diallyldimethyla mmonium chloride) (PDDA). The exposure of the assembled fi lm to ammonia induced optical changes in the transmission spectrum of the coated optical fi bre, refl ecting the characteristic absorption bands (Soret and Q bands) of the assembled TSPP compound. The fi bre optic sensor showed a linear sensitivity to ammonia in the concentration range of 0.1–20 ppm and the response and recovery times were less than 3 min with a limit of detection of 0.9 ppm at 706 nm.
A New Random Coding Technique that Generalizes Superposition Coding and Binning

Proving capacity for networks without feedback or cooperation usually involves two fundamental random coding techniques: superposition coding and binning. Although conceptually very different, these two techniques often achieve the same performance, suggesting an underlying similarity. In this correspondence we propose a new random coding technique that generalizes superposition coding and binning and provides new insight on relationship among the two With this new theoretical tool, we derive new achievable regions for three classical information theoretical models: multi-access channel, broadcast channel, the interference channel, and show that, unfortunately, it does not improve over the largest known achievable regions for these cases.
Implementation of multimedia touch system with colour detection based computer vision algorithm

Touch screen technology, as an user friendly interface for electronics device is going through a revolutionary improvement. Higher implementation cost makes this technology unsuitable for big display screen like multimedia display. The proposed technology in this paper provides touch screen facility to big multimedia display which is highly cost effective and easy to implement. An efficient colour detection based computer vision algorithm is used to recognize hand gesture pattern to execute different commands for interacting with multimedia system.
A Probabilistic Correspondence Algorithm Using Shape Cuesand Prior Information

Correspondence of features between two or more images obtained from different views of the same object is still a challenging problem in vision. In many applications, these two views are part of a larger video sequence. The aim of this paper is to show that the original video data contains enough information (referred to as prior information) to de sign a robust correspondence algorithm. A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellation of features in the two sets, thus taking i nto account the spatial structure of the object. The method is applied for creating holistic 3D models from partial ones and the results are presented.
A Comparative Analysis of Resource Management in Cloud and Grid Computing

Cloud computing and Grid computing are two intricately connected concepts which are very popular among researchers as well as users because of its efficient resource management capability. Numbers of definitions have been given till now for Cloud and Grid. Both of these computing paradigms are milestones for the revolutionary change that has come into the field of distributed computing but when we talk about resource management then how these two paradigms differ from each other? , which one is better and why? What are the considerations which one has to think upon while using any of these two? In this paper we have tried to answer all these questions by doing a 360 degree comparative analysis in context of resource management. In the first section we have given an introduction of Grid and Cloud Computing paradigm and have described the Grids and Clouds resource management. In the next section we have explained the concepts whose understanding is must in order to understand the challenges faced by these two computing paradigms. In the next section we have presented a table which gives a comparative overview of these two computing paradigms. We have tried to bring out the challenges being faced today by these two computing paradigms. Finally we have drawn some conclusions based on our analysis and have suggested some future work in this area.
Microbial Community Responses to Organophosphate Substrate Additions in Contaminated Subsurface Sediments

Background Radionuclide- and heavy metal-contaminated subsurface sediments remain a legacy of Cold War nuclear weapons research and recent nuclear power plant failures. Within such contaminated sediments, remediation activities are necessary to mitigate groundwater contamination. A promising approach makes use of extant microbial communities capable of hydrolyzing organophosphate substrates to promote mineralization of soluble contaminants within deep subsurface environments. Methodology/Principal Findings Uranium-contaminated sediments from the U.S. Department of Energy Oak Ridge Field Research Center (ORFRC) Area 2 site were used in slurry experiments to identify microbial communities involved in hydrolysis of 10 mM organophosphate amendments [i.e., glycerol-2-phosphate (G2P) or glycerol-3-phosphate (G3P)] in synthetic groundwater at pH 5.5 and pH 6.8. Following 36 day (G2P) and 20 day (G3P) amended treatments, maximum phosphate (PO4 3−) concentrations of 4.8 mM and 8.9 mM were measured, respectively. Use of the PhyloChip 16S rRNA microarray identified 2,120 archaeal and bacterial taxa representing 46 phyla, 66 classes, 110 orders, and 186 families among all treatments. Measures of archaeal and bacterial richness were lowest under G2P (pH 5.5) treatments and greatest with G3P (pH 6.8) treatments. Members of the phyla Crenarchaeota, Euryarchaeota, Bacteroidetes, and Proteobacteria demonstrated the greatest enrichment in response to organophosphate amendments and the OTUs that increased in relative abundance by 2-fold or greater accounted for 9%–50% and 3%–17% of total detected Archaea and Bacteria, respectively. Conclusions/Significance This work provided a characterization of the distinct ORFRC subsurface microbial communities that contributed to increased concentrations of extracellular phosphate via hydrolysis of organophosphate substrate amendments. Within subsurface environments that are not ideal for reductive precipitation of uranium, strategies that harness microbial phosphate metabolism to promote uranium phosphate precipitation could offer an alternative approach for in situ sequestration.
Minced Umbilical Cord Fragments as a Source of Cells for Orthopaedic Tissue Engineering: An In Vitro Study

A promising approach for musculoskeletal repair and regeneration is mesenchymal-stem-cell- (MSC-)based tissue engineering. The aim of the study was to apply a simple protocol based on mincing the umbilical cord (UC), without removing any blood vessels or using any enzymatic digestion, to rapidly obtain an adequate number of multipotent UC-MSCs. We obtained, at passage 1 (P1), a mean value of 4, 2 × 106 cells (SD 0,4) from each UC. At immunophenotypic characterization, cells were positive for CD73, CD90, CD105, CD44, CD29, and HLA-I and negative for CD34 and HLA-class II, with a subpopulation negative for both HLA-I and HLA-II. Newborn origin and multilineage potential toward bone, fat, cartilage, and muscle was demonstrated. Telomere length was similar to that of bone-marrow (BM) MSCs from young donors. The results suggest that simply collecting UC-MSCs at P1 from minced umbilical cord fragments allows to achieve a valuable population of cells suitable for orthopaedic tissue engineering.
Time Efficient Tag Searching in Multiple Reader RFID Systems

RFID technologies have been applied in various applications such as inventory control and supply chain management. In this paper, we investigate the tag searching problem in large RFID systems containing multiple readers. Given a particular set of wanted tags, tag searching refers to finding which of them present in the system. Tag searching is important to many practical applications and it should be done quickly. Prior researches on tag searching did not consider interference among nearby readers, which will greatly affect the time efficiency of tag searching solutions. In this paper, we propose a tag searching protocol that achieves high time efficiency by jointly optimizing the searching precision and reader scheduling. We propose a novel technique to quickly test whether a wanted tag exists in the system or not. The execution time of the protocol is greatly affected by the scheduling of readers. We formulate the minimum time reader scheduling problem and prove its NP-hardness. We then design a heuristic algorithm to find a feasible reader scheduling. Simulation results show the superior performance of the proposed searching protocol: Compared with the best existing solutions, the proposed protocol reduces execution time by more than 40 percent.
Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition

ure vector generation is an important step in biometric authentication. Biometric traits such as fingerprint, palmprint, iris, & finger-knuckle prints are rich in texture. This texture is unique and the feature vector extraction algorithm should correctly represent the texture pattern. In this paper a texture feature extraction methodology is proposed for iris and pamlprints. This method is based on one step transform of the two dimensional images and then using the intermediate transformation data to generate complex planes for feature vector generation. This method is implemented using Walsh, DCT, Hartley, Kekre Transform &Kekre Wavelets. Results indicate the effectiveness of the feature vector for biometric authentication.
Parameters estimation of target with precession based on combined feature

It is beneficial for the recognition and classification of targets to obtain geometrical and motional parameters simultaneously. This paper proposes a new method to estimate parameters of target with precession based on combined feature, which is generated by Doppler feature and high range resolution feature of target from a new radar-OFDM radar. Expanded Hough transform (EHT) is employed to establish the combined feature with range and motion information of scatterers. The paper mainly presents the principle to establish the combined feature and the estimation of precession angle, target posture and target length. Finally, the results from simulations and anechoic chamber data prove the validity of the method.
Visualizing structural “inverted pyramids” in English news discourse across levels

Abstract Drawing on an analogy between discourse and syntactic trees, this paper chooses 359 Wall Street Journal articles with multiple paragraphs from the Rhetorical Structure Theory (RST) Discourse Treebank, and converts each discourse tree into three additional dependency ones, at discourse, paragraph and sentence levels, with exclusively elementary discourse units of clauses, sentences and paragraphs, respectively. It empirically tests and visually presents the genre-specific “summary+details” or “inverted pyramid” structuring of news discourse. It further extends the idea of inverted pyramid structuring to the paragraph and sentence levels. It proves that the body of the report also has a similar schematic top-down installment organization with macro-propositions on top. It also visually and statistically presents the rhetorical structures at sentence level, which differ to some extent from grammatical structures. Operated in line with the compositionality criterion and hierarchy principle of RST, the converted trees provide unique analytical advantages and constitute new research prospects.
Researching children and childhood in the digital age

The entirely revised third edition of Research with Children forms a unique resource book on the methodology of childhood research with a core emphasis on theory driven practices. As in the previous two editions, this edition presents particular standpoints in the field, whilst also reflecting the latest developments in the now well-established interdisciplinary field of childhood studies.
The Consequences of Identity Theft Victimization: An Examination of Emotional and Physical Health Outcomes

ABSTRACT Identity theft—one of the fastest growing crimes—results in considerable financial losses as well as time spent to restore credit and prevent future attacks. While scholars have begun to devote more attention to identifying the factors that increase risk of identity theft, little is known about the aftermath for victims. Using data from the Identity Theft Supplement to the National Crime Victimization Survey, we address this gap in the literature. Results indicate that, in addition to financial losses and loss of time, victims also experience emotional (e.g., depression) and physical (e.g., poor health) symptoms. The implications of these findings for theory, research, and policy are discussed.
Carboplatin and teniposide as third-line chemotherapy in patients with recurrent oligodendroglioma or oligoastrocytoma: a phase II study.

BACKGROUND This study was a phase II study of third-line chemotherapy with carboplatin plus teniposide in patients with recurrent oligodendroglioma. PATIENTS AND METHODS Patients with oligodendroglioma progressive or recurrent after surgery, radiotherapy and chemotherapy with PCV (lomustine/procarbazine/vincristine) and temozolomide were treated with 350 mg/m(2) carboplatin on day 1, and 50 mg/m(2) teniposide on days 1-3, every 4 weeks. RESULTS Response and toxicity were evaluated in all 23 patients enrolled in the study. Two had partial response [8.6%; 95% confidence interval (CI) 1.8% to 28.6%] and 12 stable disease (52.17%; 95% CI 30% to 73%). Median time to progression was 19 weeks (95% CI 11.4-35.0), and 34.8% of the patients (95% CI 20.0% to 61.0%) had progression-free survival at 6 months. Median survival time was 60.7 weeks (95% CI 39.8 to not achieved) and 51% of the patients (95% CI 33.5% to 79.7%) were alive at 12 months. A total of 103 cycles were administered (on average 4.4 per patient; range 1-9). Toxicity was mild and mainly hematological, with grade 4 neutropenia and grade 4 thrombocytopenia in two (8.6%) and three patients (13%), respectively. CONCLUSIONS Although the response rate of combined carboplatin and teniposide chemotherapy in heavily pretreated oligodendroglial tumors is moderate, the toxicity is manageable, and delay of progression in responders or stable patients may still confer a relevant clinical benefit.
Speech-Assisted Mobile Text Entry

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Information Retrieval Using PU Learning Based Re-ranking

In this paper, we describe our approach for information retrieval for question answering (IR4QA) on simple Chinese language of NTCIR-7 tasks. Firstly, we use both bi-grams and single Chinese characters as index units and use OKAPI BM25 as retrieval model. Secondly, we re-rank all documents’ orders for the first retrieval documents. We focus mostly on the document re-ranking technique. We address probabilistically labeling relevant degree between the first retrieval documents and query topics. In other words, we want to know the probability of a document belongs to relevance/irrelevance class. We employ PU9‘ positive and unlabeled9’ learning to solve this problem, and use Bayesian classifier and EM algorithm in process of computing the probability. Consequently, those relevant documents with high probability are updated rank. Lastly, we use re-ranked retrieved documents to do query expansion. Evaluation at NTCIR-7 shows that our group achieves 0.3862 and 0.3806 MAP based on