The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect a...
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ISBN:
(纸本)9781479900145
The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.
We identified and organized a number of statements about technical debt (TD Folklore list) expressed by practitioners in online websites, blogs and published papers. We chose 14 statements and we evaluated them throug...
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We identified and organized a number of statements about technical debt (TD Folklore list) expressed by practitioners in online websites, blogs and published papers. We chose 14 statements and we evaluated them through two surveys (37 practitioners answered the questionnaires), ranking them by agreement and consensus. The statements most agreed with show that TD is an important factor in software project management and not simply another term for “bad code”. This study will help the research community in identifying folklore that can be translated into research questions to be investigated, thus targeting attempts to provide a scientific basis for TD management.
In this study, we explored the students' computer-supported collaborative learning behavior based on the Facebook platform. Sixty two senior college students major in information Management took Decision Support S...
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ISBN:
(纸本)9789810746490
In this study, we explored the students' computer-supported collaborative learning behavior based on the Facebook platform. Sixty two senior college students major in information Management took Decision Support System (DSS) class. Besides the lectures and class discussion, the students participated in the DSS Facebook for collaborative learning. We found that students' characteristics (e.g., gender and mindset of learning) are important factors to affect their Facebook usage behavior and learning performance. The students using DSS Facebook more often get better performance in their final projects, learning satisfaction and the online communication behavior survey. We also found that gender affects the usage of social networks platform. For instance, male students use social networks platform several times per week and get better performance in online communication, learning satisfaction and creativity self-efficacy.
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 1...
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
As the rapid growth of smart phone technology, people have a lot of digital image information such as digital photos or videos. Both data hiding and data compression are very important technologies in image processing...
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As the rapid growth of smart phone technology, people have a lot of digital image information such as digital photos or videos. Both data hiding and data compression are very important technologies in image processing field. On the overview, it seems that there is no relationship between data hiding and data compression because data hiding mechanisms focus on information security and data compression mechanisms emphasize the compression ratio. However, the more secret data is embedded, the more capacity the stego image increases. Actually, they are closely related. Until now, there are many literatures to discuss the secret data how to be embedded into the media image and keeps the original capacity as soon as possible. In this paper, a reversible data hiding scheme based on EMD data hiding and JPEG (Joint Picture Experts Group) compression technology will be proposed. According to experimental results, the authors can prove that our proposed scheme maintains high embedding capacity, security and good compression ratio.
This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requ...
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ISBN:
(纸本)9781450311786
This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of candidate projects, which is unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure. Results show evidence that the project selection technique can be used in large-scale scenarios and that GA presents better results than simpler search strategy. Copyright is held by the author/owner(s).
Chromosomal aberrations and somatic mutations constitute key elements of the pathogenesis of myelodysplastic syndromes (MDS), a clonal hematologic malignancy characterized by cytopenias, a dysplastic bone marrow and p...
Chromosomal aberrations and somatic mutations constitute key elements of the pathogenesis of myelodysplastic syndromes (MDS), a clonal hematologic malignancy characterized by cytopenias, a dysplastic bone marrow and propensity to clonal evolution. Next generation sequencing (NGS) enables definition of somatic mutational patterns and clonal architecture as a discovery platform, and for clinical *** systematically applied NGS to 707 cases of MDS and MDS-related disorders. 205 cases (low-risk MDS: N=78, high-risk MDS: N=42, MDS/MPN: N=48 and sAML: N=37) were tested by whole exome sequencing (WES). For validation in an additional 502 patients (low-risk MDS: N=192, high-risk MDS: N=104, MDS/MPN: N=111 and sAML: N=95), targeted deep NGS was applied for 60 index genes which were most commonly affected in the cohort analyzed by WES. For NGS data analysis a statistical pipeline was developed to focus on: i) identification of the most relevant somatic mutations, and ii) minimization of false positive results. We studied serial samples from 21 exemplary informative patients. We also compared somatic mutational patterns to those seen in primary AML TCGA cohort (N=201). Given the size of the cohort, there was, for example, a 87% chance of seeing mutations at a frequency of 1% and a 98% of seeing those with a frequency of 2%. While focusing on the most common events, we observed 1117 somatic mutations in 199 genes. The 88 genes mutated mutated in >1% of cases with MDS carried 388 mutations in MDS+sAML (2.5/case), 128 in MDS/MPN (2.7/case) and 398 in pAML (2.0/case). The average number of mutations per case increased during progression (2.2 in lower-risk, 2.8 in higher-risk MDS, 3.4 in sAML). In MDS, the 30 most frequently affected genes were present at least once in 70% of patients. The 30 most frequently mutated genes in MDS/MPN were mutated in 82% of patients. Individual mutations were also sub-grouped according to their function. When we compared three MDS subcateg
The research proposes monitoring network traffic to preventing malicious attacks. It uses statistical theory and fuzzy control architecture to create a single transmission behavior. It will establish a normal transmis...
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The research proposes monitoring network traffic to preventing malicious attacks. It uses statistical theory and fuzzy control architecture to create a single transmission behavior. It will establish a normal transmission behavior module in order to achieve network monitoring and an alert mechanism. The mechanism tries to improve the abnormal behavior detection rate. The study is divided into three parts. The first part uses tools to simulate detection and aggressive behavior. According to many defensive measure reports, we will build a detection mechanism. The third part uses statistical theory and fuzzy control to monitor each network flow. The mechanism will preprocess denial of service attacks for an intrusion detection system.
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Steven...
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O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s
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