New Jersey Institute of Technology

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual. This report by the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations. Integrative analyses reveal profiles of rare and common variants in different populations. The frequencies of rare variants vary across biological pathways, and hundreds of rare, non-coding variants at conserved sites — such as changes disrupting transcription-factor motifs — can be established for each individual.

Abstract Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy‐in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log‐normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait‐based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

A novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio (PSNR) of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm.

The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains, including real-time monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in the UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate more than $45 Billion market value of UAV usage. In this paper, we present UAV civil applications and their challenges. We also discuss the current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including charging challenges, collision avoidance and swarming challenges, and networking and security-related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

This paper introduces a novel Gabor-Fisher (1936) classifier (GFC) for face recognition. The GFC method, which is robust to changes in illumination and facial expression, applies the enhanced Fisher linear discriminant model (EFM) to an augmented Gabor feature vector derived from the Gabor wavelet representation of face images. The novelty of this paper comes from 1) the derivation of an augmented Gabor feature vector, whose dimensionality is further reduced using the EFM by considering both data compression and recognition (generalization) performance; 2) the development of a Gabor-Fisher classifier for multi-class problems; and 3) extensive performance evaluation studies. In particular, we performed comparative studies of different similarity measures applied to various classifiers. We also performed comparative experimental studies of various face recognition schemes, including our novel GFC method, the Gabor wavelet method, the eigenfaces method, the Fisherfaces method, the EFM method, the combination of Gabor and the eigenfaces method, and the combination of Gabor and the Fisherfaces method. The feasibility of the new GFC method has been successfully tested on face recognition using 600 FERET frontal face images corresponding to 200 subjects, which were acquired under variable illumination and facial expressions. The novel GFC method achieves 100% accuracy on face recognition using only 62 features.

This paper presents an overview of the theory and currently known techniques for multi-cell MIMO (multiple input multiple output) cooperation in wireless networks. In dense networks where interference emerges as the key capacity-limiting factor, multi-cell cooperation can dramatically improve the system performance. Remarkably, such techniques literally exploit inter-cell interference by allowing the user data to be jointly processed by several interfering base stations, thus mimicking the benefits of a large virtual MIMO array. Multi-cell MIMO cooperation concepts are examined from different perspectives, including an examination of the fundamental information-theoretic limits, a review of the coding and signal processing algorithmic developments, and, going beyond that, consideration of very practical issues related to scalability and system-level integration. A few promising and quite fundamental research avenues are also suggested.

Over the past 5 years, there has been a significant interest in employing terahertz (THz) technology, spectroscopy and imaging for security applications. There are three prime motivations for this interest: (a) THz radiation can detect concealed weapons since many non-metallic, non-polar materials are transparent to THz radiation; (b) target compounds such as explosives and illicit drugs have characteristic THz spectra that can be used to identify these compounds and (c) THz radiation poses no health risk for scanning of people. In this paper, stand-off interferometric imaging and sensing for the detection of explosives, weapons and drugs is emphasized. Future prospects of THz technology are discussed.

Inspired by recent advances in multiple-input multiple-output (MIMO) communications, this proposal introduces the statistical MIMO radar concept. To the authors' knowledge, this is the first time that the statistical MIMO is being proposed for radar. The fundamental difference between statistical MIMO and other radar array systems is that the latter seek to maximize the coherent processing gain, while statistical MIMO radar capitalizes on the diversity of target scattering to improve radar performance. Coherent processing is made possible by highly correlated signals at the receiver array, whereas in statistical MIMO radar, the signals received by the array elements are uncorrelated. Radar targets generally consist of many small elemental scatterers that are fused by the radar waveform and the processing at the receiver, to result in echoes with fluctuating amplitude and phase. It is well known that in conventional radar, slow fluctuations of the target radar cross section (RCS) result in target fades that degrade radar performance. By spacing the antenna elements at the transmitter and at the receiver such that the target angular spread is manifested, the MIMO radar can exploit the spatial diversity of target scatterers opening the way to a variety of new techniques that can improve radar performance. This paper focuses on the application of the target spatial diversity to improve detection performance. The optimal detector in the Neyman–Pearson sense is developed and analyzed for the statistical MIMO radar. It is shown that the optimal detector consists of noncoherent processing of the receiver sensors' outputs and that for cases of practical interest, detection performance is superior to that obtained through coherent processing. An optimal detector invariant to the signal and noise levels is also developed and analyzed. In this case as well, statistical MIMO radar provides great improvements over other types of array radars.

It has recently been shown that multiple-input multiple-output (MIMO) antenna systems have the potential to improve dramatically the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, target scintillations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it takes the opposite view; namely, it capitalizes on target scintillations to improve the radar's performance. We introduce the MIMO concept for radar. The MIMO radar system under consideration consists of a transmit array with widely-spaced elements such that each views a different aspect of the target. The array at the receiver is a conventional array used for direction finding (DF). The system performance analysis is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction. It is shown that MIMO radar leads to significant performance improvement in DF accuracy.

The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. Obviously, with no knowledge of the transmitted data and many unknown parameters at the receiver, such as the signal power, carrier frequency and phase offsets, timing information and so on, blind identification of the modulation is a difficult task. This becomes even more challenging in real-world scenarios with multipath fading, frequency-selective and time-varying channels. With this in mind, the authors provide a comprehensive survey of different modulation recognition techniques in a systematic way. A unified notation is used to bring in together, under the same umbrella, the vast amount of results and classifiers, developed for different modulations. The two general classes of automatic modulation identification algorithms are discussed in detail, which rely on the likelihood function and features of the received signal, respectively. The contributions of numerous articles are summarised in compact forms. This helps the reader to see the main characteristics of each technique. However, in many cases, the results reported in the literature have been obtained under different conditions. So, we have also simulated some major techniques under the same conditions, which allows a fair comparison among different methodologies. Furthermore, new problems that have appeared as a result of emerging wireless technologies are outlined. Finally, open problems and possible directions for future research are briefly discussed.

An important consideration in similarity-based retrieval of moving object trajectories is the definition of a distance function. The existing distance functions are usually sensitive to noise, shifts and scaling of data that commonly occur due to sensor failures, errors in detection techniques, disturbance signals, and different sampling rates. Cleaning data to eliminate these is not always possible. In this paper, we introduce a novel distance function, Edit Distance on Real sequence (EDR) which is robust against these data imperfections. Analysis and comparison of EDR with other popular distance functions, such as Euclidean distance, Dynamic Time Warping (DTW), Edit distance with Real Penalty (ERP), and Longest Common Subsequences (LCSS), indicate that EDR is more robust than Euclidean distance, DTW and ERP, and it is on average 50% more accurate than LCSS. We also develop three pruning techniques to improve the retrieval efficiency of EDR and show that these techniques can be combined effectively in a search, increasing the pruning power significantly. The experimental results confirm the superior efficiency of the combined methods.

Multidimensional empirical examinations of the adoption of innovations in organizations, and the influence of factors within each dimension on the phases of adoption, are scarce. This study examines the effects of environmental, organizational and top managers' characteristics on the initiation, adoption decision and implementation of innovation. Using a sample of approximately 1200 public organizations in the United States, we found that while each dimension accounts for unique variance in the adoption of innovation, organizational characteristics and top managers' attitudes toward innovation have a stronger influence than environmental and top managers' demographic characteristics. We also found no difference in the direction of effects of any antecedent, but did find differences in the significance of effects of several antecedents, on the phases of innovation adoption. We discuss the implications of these findings and suggest ideas for future research.

Introduction Introduction and Notation, Joseph Y-T. Leung A Tutorial on Complexity, Joseph Y-T. Leung Some Basic Scheduling Algorithms, Joseph Y-T. Leung Classical Scheduling Problems Elimination Rules for Job-shop Scheduling Problem: Overview and Extensions, Jacques Carlier, Laurent Peridy, Eric Pinson, and David Rivreau Flexible Hybrid Flowshops, George Vairaktarakis Open Shop Scheduling, Teofilo F. Gonzalez Cycle Shop Scheduling, Vadim G. Timkovsky Reducibility among Scheduling Classes, Vadim G. Timkovsky Parallel Scheduling for Early Completion, Bo Chen Minimizing the Maximum Lateness, Hans Kellerer Approximation Algorithms for Minimizing Average Weighted Completion Time, Chandra Chekuri and Sanjeev Khanna Minimizing the Number of Tardy Jobs, Marjan van den Akker and Han Hoogeveen Branch-and-Bound Algorithms for Total Weighted Tardiness, Antoino Jouglet, Philippe Baptiste, and Jacques Carlier Scheduling Equal Processing Time Jobs, Philippe Baptiste and Peter Brucker Online Scheduling, Kirk Pruhs, Jiri Sgall, and Eric Torng Convex Quadratic Relaxations in Scheduling, Jay Sethuraman Other Scheduling Models The Master/Slave Scheduling Model, Sartaj Sahni and George Vairaktarakis Scheduling in Bluetooth Networks, Yong Man Kim and Ten H. Lai Fair Sequences, Wieslaw Kubiak Due-Date Quotation Models and Algorithms, Philip Kaminsky and Dorit Hochbaum Scheduling with Due-Date Assignment, Valery S. Gordon, Jean-Marie Proth, and Vitaly A. Strusevich Machine Scheduling with Availability Constraints, Chung-Yee Lee Scheduling with Discrete Resource Constraints, J. B_lazewicz, N. Brauner, and G. Finke Scheduling with Resource Constraints-Continuous Resources, Joanna J'ozefowska and Jan Weglarz Scheduling Parallel Tasks-Algorithms and Complexity, M. Drozdowski Scheduling Parallel Tasks Approximation Algorithms, Pierre-Franc' ois Dutot, Gr'egory Mouni'e, and Denis Trystram Real-Time Scheduling The Pinwheel: A Real-Time Scheduling Problem, Deji Chen and Aloysivs Mok Scheduling Real-Time Tasks: Algorithms and Complexity, Sanjay Baruah and Joael Goossens Real Time Synchronization Protocols, Lui Sha and Marco Caccamo Fair Scheduling of Real-Time Tasks on Multiprocessors, James Anderson, Philip Holman, and Anand Srinivasan A Categorization of Real-Time Multiprocessor Scheduling Problems and Algorithms, John Carpenter, Shelby Funk, Philip Holman, Anand Srinivasan, James Anderson, and Sanjoy Baruah Approximation Algorithms for Scheduling Time-Critical Jobs on Multiprocessor System, Sudarshan K. Dhall Scheduling Overloaded Real-Time Systems with Competitive/Worst Case Guarantees, Gilad Koren and Dennis Shasha Minimizing TotalWeighted Error for Imprecise Computation Tasks and Related Problems, Joseph Y-T. Leung Dual Criteria Optimization Problems for Imprecise Computation Tasks, Kevin I-J Ho Periodic Reward-Based Scheduling and Its Application to Power-Aware Real-Time Systems, Hakan Aydin, Rami Melhem, and Daniel Mosse Routing Real-Time Messages on Networks, G. Young Stochastic Scheduling and Queueing Networks Offline Deterministic Scheduling, Stochastic Scheduling, and Online Deterministic Scheduling: A Comparative Overview, Michael Pinedo Stochastic Scheduling with Earliness and Tardiness Penalties, Xiaoqiang Cai and Xian Zhou Developments in Queueing Networks with Tractable Solutions, Xiuli Chao Scheduling in Secondary Storage Systems, Alexander Thomasian Selfish Routing on the Internet, Artur Czumaj Applications Scheduling of Flexible Resources in Professional Service Firms, Yalcin Akcay, Anantaram Balakrishnan, and Susan H. Xu Novel Metaheuristic Approaches to Nurse Rostering Problems in Belgian Hospitals, Edmund Kieran Burke, Patrick De Causmaecker and Greet Vanden Berghe University Timetabling, Sanja Petrovic and Edmund Burke Adapting the GATES Architecture to Scheduling Faculty, R. P. Brazile and K. M. Swigger Constraint Programming for Scheduling, John J. Kanet, Sanjay L. Ahire, and Michael F. Gorman Batch Production Scheduling in the Process Industries, Karsten Gentner, Klaus Neumann, Christoph Schwindt, and Norbert Trautmann A Composite Very-Large-Scale Neighborhood Search Algorithm for the Vehicle Routing Problem, Richa Agarwal, Ravinder K. Ahuja, Gilbert Laporte, and Zuo-Jun Max Shen Scheduling Problems in the Airline Industry, Xiangtong Qi, Jian Yang and Gang Yu Bus and Train Driver Scheduling, Raymond S. K. Kwan Sports Scheduling, Kelly Easton, George Nemhauser, and Michael Trick Index

It is not well understood how privacy concern and trust influence social interactions within social networking sites. An online survey of two popular social networking sites, Facebook and MySpace, compared perceptions of trust and privacy concern, along with willingness to share information and develop new relationships. Members of both sites reported similar levels of privacy concern. Facebook members expressed significantly greater trust in both Facebook and its members, and were more willing to share identifying information. Even so, MySpace members reported significantly more experience using the site to meet new people. These results suggest that in online interaction, trust is not as necessary in the building of new relationships as it is in face to face encounters. They also show that in an online site, the existence of trust and the willingness to share information do not automatically translate into new social interaction. This study demonstrates online relationships can develop in sites where perceived trust and privacy safeguards are weak.

According to Edholm’s law, the demand for point-to-point bandwidth in wireless short-range communications has doubled every 18 months over the last 25 years. It can be predicted that data rates of around 5–10 Gb/s will be required in ten years. In order to achieve 10 Gb/s data rates, the carrier frequencies need to be increased beyond 100 GHz. Over the past ten years, several groups have considered the prospects of using sub-terahertz (THz) and THz waves (100–2000 GHz) as a means to transmit data wirelessly. Some of the reported advantages of THz communications links are inherently higher bandwidth compared to millimeter wave links, less susceptibility to scintillation effects than infrared wireless links, and the ability to use THz links for secure communications. Our goal of this paper is to provide a comprehensive review of wireless sub-THz and THz communications.

A trade-off between growth and mortality rates characterizes tree species in closed canopy forests. This trade-off is maintained by inherent differences among species and spatial variation in light availability caused by canopy-opening disturbances. We evaluated conditions under which the trade-off is expressed and relationships with four key functional traits for 103 tree species from Barro Colorado Island, Panama. The trade-off is strongest for saplings for growth rates of the fastest growing individuals and mortality rates of the slowest growing individuals (r2 = 0.69), intermediate for saplings for average growth rates and overall mortality rates (r2 = 0.46), and much weaker for large trees (r2 < or = 0.10). This parallels likely levels of spatial variation in light availability, which is greatest for fast- vs. slow-growing saplings and least for large trees with foliage in the forest canopy. Inherent attributes of species contributing to the trade-off include abilities to disperse, acquire resources, grow rapidly, and tolerate shade and other stresses. There is growing interest in the possibility that functional traits might provide insight into such ecological differences and a growing consensus that seed mass (SM), leaf mass per area (LMA), wood density (WD), and maximum height (H(max)) are key traits among forest trees. Seed mass, LMA, WD, and H(max) are predicted to be small for light-demanding species with rapid growth and mortality and large for shade-tolerant species with slow growth and mortality. Six of these trait-demographic rate predictions were realized for saplings; however, with the exception of WD, the relationships were weak (r2 < 0.1 for three and r2 < 0.2 for five of the six remaining relationships). The four traits together explained 43-44% of interspecific variation in species positions on the growth-mortality trade-off; however, WD alone accounted for > 80% of the explained variation and, after WD was included, LMA and H(max) made insignificant contributions. Virtually the full range of values of SM, LMA, and H(max) occurred at all positions on the growth-mortality trade-off. Although WD provides a promising start, a successful trait-based ecology of tropical forest trees will require consideration of additional traits.

We propose a new shadowed Rice (1948) model for land mobile satellite channels. In this model, the amplitude of the line-of-sight is characterized by the Nakagami distribution. The major advantage of the model is that it leads to closed-form and mathematically-tractable expressions for the fundamental channel statistics such as the envelope probability density function, moment generating function of the instantaneous power, and the level crossing rate. The model is very convenient for analytical and numerical performance prediction of complicated narrowband and wideband land mobile satellite systems, with different types of uncoded/coded modulations, with or without diversity. Comparison of the first- and the second-order statistics of the proposed model with different sets of published channel data demonstrates the flexibility of the new model in characterizing a variety of channel conditions and propagation mechanisms over satellite links. Interestingly, the proposed model provides a similar fit to the experimental data as the well-accepted Loo's (1985) model but with significantly less computational burden.

Staphylococcal cassette chromosome mec (SCCmec) typing, in combination with genotyping of the Staphylococcus aureus chromosome, has become essential for defining methicillin-resistant S. aureus (MRSA) clones in epidemiological studies. We have developed a convenient system for SCCmec type assignment. The system consists of six multiplex PCRs (M-PCRs) for identifying the ccr gene complex (ccr), the mec gene complex (mec), and specific structures in the junkyard (J) regions: M-PCR with primer set 1 (M-PCR 1) identified five types of ccr genes; M-PCR 2 identified class A to class C mec; M-PCRs 3 and 4 identified specific open reading frames in the J1 regions of type I and IV and of type II, III, and V SCCmec elements, respectively; M-PCR 5 identified the transposons Tn554 and PsiTn554 integrated into the J2 regions of type II and III SCCmec elements; and M-PCR 6 identified plasmids pT181 and pUB110 integrated into J3 regions. The system was validated with 99 MRSA strains carrying SCCmec elements of different types. The SCCmec types of 93 out of the 99 MRSA strains could be assigned. The SCCmec type assignments were identical to those made with a PCR system that uses numerous primer pairs to identify genes or gene alleles. Our system of six M-PCRs is thus a convenient and reliable method for typing SCCmec elements.