Hewlett-Packard (Israel)

The three main tools in the single image restoration theory are the maximum likelihood (ML) estimator, the maximum a posteriori probability (MAP) estimator, and the set theoretic approach using projection onto convex sets (POCS). This paper utilizes the above known tools to propose a unified methodology toward the more complicated problem of superresolution restoration. In the superresolution restoration problem, an improved resolution image is restored from several geometrically warped, blurred, noisy and downsampled measured images. The superresolution restoration problem is modeled and analyzed from the ML, the MAP, and POCS points of view, yielding a generalization of the known superresolution restoration methods. The proposed restoration approach is general but assumes explicit knowledge of the linear space- and time-variant blur, the (additive Gaussian) noise, the different measured resolutions, and the (smooth) motion characteristics. A hybrid method combining the simplicity of the ML and the incorporation of nonellipsoid constraints is presented, giving improved restoration performance, compared with the ML and the POCS approaches. The hybrid method is shown to converge to the unique optimal solution of a new definition of the optimization problem. Superresolution restoration from motionless measurements is also discussed. Simulations demonstrate the power of the proposed methodology.

The increasing importance being placed on software measurement has led to an increased amount of research developing new software measures. Given the importance of object-oriented development techniques, one specific area where this has occurred is coupling measurement in object-oriented systems. However, despite a very interesting and rich body of work, there is little understanding of the motivation and empirical hypotheses behind many of these new measures. It is often difficult to determine how such measures relate to one another and for which application they can be used. As a consequence, it is very difficult for practitioners and researchers to obtain a clear picture of the state of the art in order to select or define measures for object-oriented systems. This situation is addressed and clarified through several different activities. First, a standardized terminology and formalism for expressing measures is provided which ensures that all measures using it are expressed in a fully consistent and operational manner. Second, to provide a structured synthesis, a review of the existing frameworks and measures for coupling measurement in object-oriented systems takes place. Third, a unified framework, based on the issues discovered in the review, is provided and all existing measures are then classified according to this framework. This paper contributes to an increased understanding of the state-of-the-art.

The emerging cloud-computing paradigm is rapidly gaining momentum as an alternative to traditional IT (information technology). However, contemporary cloud-computing offerings are primarily targeted for Web 2.0-style applications. Only recently have they begun to address the requirements of enterprise solutions, such as support for infrastructure service-level agreements. To address the challenges and deficiencies in the current state of the art, we propose a modular, extensible cloud architecture with intrinsic support for business service management and the federation of clouds. The goal is to facilitate an open, service-based online economy in which resources and services are transparently provisioned and managed across clouds on an on-demand basis at competitive costs with high-quality service. The Reservoir project is motivated by the vision of implementing an architecture that would enable providers of cloud infrastructure to dynamically partner with each other to create a seemingly infinite pool of IT resources while fully preserving their individual autonomy in making technological and business management decisions. To this end, Reservoir could leverage and extend the advantages of virtualization and embed autonomous management in the infrastructure. At the same time, the Reservoir approach aims to achieve a very ambitious goal: creating a foundation for next-generation enterprise-grade cloud computing.

The Karhunen-Loeve (KL) transform is an optimal method for approximating a set of vectors or images, which was used in image processing and computer vision for several tasks such as face and object recognition. Its computational demands and its batch calculation nature have limited its application. Here we present a new, sequential algorithm for calculating the KL basis, which is faster in typical applications and is especially advantageous for image sequences: the KL basis calculation is done with much lower delay and allows for dynamic updating of image databases. Systematic tests of the implemented algorithm show that these advantages are indeed obtained with the same accuracy available from batch KL algorithms.

In an earlier work (1999), we introduced the problem of reconstructing a super-resolution image sequence from a given low resolution sequence. We proposed two iterative algorithms, the R-SD and the R-LMS, to generate the desired image sequence. These algorithms assume the knowledge of the blur, the down-sampling, the sequences motion, and the measurements noise characteristics, and apply a sequential reconstruction process. It has been shown that the computational complexity of these two algorithms makes both of them practically applicable. In this paper, we rederive these algorithms as approximations of the Kalman filter and then carry out a thorough analysis of their performance. For each algorithm, we calculate a bound on its deviation from the Kalman filter performance. We also show that the propagated information matrix within the R-SD algorithm remains sparse in time, thus ensuring the applicability of this algorithm. To support these analytical results we present some computer simulations on synthetic sequences, which also show the computational feasibility of these algorithms.

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.

As processor performance increases and memory cost decreases, system intelligence continues to move away from the CPU and into peripherals. Storage system designers use this trend toward excess computing power to perform more complex processing and optimizations inside storage devices. To date, such optimizations take place at relatively low levels of the storage protocol. Trends in storage density, mechanics, and electronics eliminate the hardware bottleneck and put pressure on interconnects and hosts to move data more efficiently. We propose using an active disk storage device that combines on-drive processing and memory with software downloadability to allow disks to execute application-level functions directly at the device. Moving portions of an application's processing to a storage device significantly reduces data traffic and leverages the parallelism already present in large systems, dramatically reducing the execution time for many basic data mining tasks.

In children, a male predominance in the incidence of symptomatic disease has been reported for some infectious agents and not for others. Not only are the factors underlying these sex differences poorly understood, but it is also not clear why the differences are described only for selected infectious diseases. In this study of sex- and age-specific incidence of infectious diseases in children, a possible explanation for the inconsistencies in the literature was explored. The sex ratio in reported disease incidence in Israel during a period of about 20 years was examined for various viral and bacterial infections. In addition, an hypothetical mathematical model was developed which assumes increased susceptibility to infectious disease (such as in relative immune deficiency) in a proportion of males. In children aged under 4 years, a higher incidence among males was consistently observed for all diseases, and the sex ratio varied between 1.16 (95% confidence interval (CI): 1.13-1.18) for shigellosis to 1.98 (95% CI: 1.79-2.17) for viral meningitis. The highest ratios were associated with the diseases which tend to present asymptomatically most often, which is consistent with the predictions of the model. The male excess in symptomatic disease appears to be present for most infectious diseases and this should be taken into account in studies comparing observed disease incidence between groups with different sex ratios. The inconsistencies in reports on the excess male morbidity for infectious diseases may be due to variations in symptomatic to asymptomatic infection ratios.

Abstract We present a general approach to shape deformation based on energy minimization, and applications of this approach to the problems of image resizing and 2D shape deformation. Our deformation energy generalizes that found in the prior art, while still admitting an efficient algorithm for its optimization. The key advantage of our energy function is the flexibility with which the set of “legal transformations” may be expressed; these transformations are the ones which are not considered to be distorting. This flexibility allows us to pose the problems of image resizing and 2D shape deformation in a natural way and generate minimally distorted results. It also allows us to strongly reduce undesirable foldovers or self‐intersections. Results of both algorithms demonstrate the effectiveness of our approach.

T he magnitude of the risk of prostate cancer among Ashkenazi Jewish carriers of the common mutations in the BRCA1 and BRCA2 genes, the so-called Ashkenazi BRCA founder mutations (BRCA1 185delAG and 5382insC, and BRCA2 6174delT), remains uncertain. Two large epidemiological studies have suggested that the cumulative incidence of prostate cancer among male first degree relatives of individuals with a founder mutation may approach 30% by 80 years of age. 1 2 Smaller clinical studies have, in general, not demonstrated an increased frequency of founder mutations among Jewish men with prostate cancer. [3] 4][5][6] Only one study to date has examined clinical characteristics of prostate cancer patients with founder mutations. 3 In this study, the three BRCA associated tumours that were identified appeared to be associated with biologically more aggressive disease, presenting with higher PSA levels, higher Gleason scores and more advanced stage at diagnosis, than did prostate cancers diagnosed in men without mutations.

A complete characterization of optimal prefix codes for off-centered, two-sided geometric distributions of the integers is presented. These distributions are often encountered in lossless image compression applications, as probabilistic models for image prediction residuals. The family of optimal codes described is an extension of the Golomb codes, which are optimal for one-sided geometric distributions. The new family of codes allows for encoding of prediction residuals at a complexity similar to that of Golomb codes, without recourse to the heuristic approximations frequently used when modifying a code designed for nonnegative integers so as to apply to the encoding of any integer. Optimal decision rules for choosing among a lower complexity subset of the optimal codes, given the distribution parameters, are also investigated, and the relative redundancy of the subset with respect to the full family of optimal codes is bounded.

Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.

Abstract The present paper proposes a conceptual ontology to evaluate human factors by modelling their key performance indicators and defining these indicators' explanatory factors, manifestations, and diverse corresponding digital footprints. Our methodology incorporates 6 main human resource constructs: performance, engagement, leadership, workplace dynamics, organizational developmental support, and learning and knowledge creation. Using sentiment analysis, we introduce a potential way to evaluate several components of the proposed human factors ontology. We use the Enron email corpus as a test case, to demonstrate how digital footprints can predict such phenomena. In so doing, we hope to encourage further research applying data mining techniques to allow real‐time, less costly, and more reliable assessments of human factor patterns and trends.

OBJECTIVES: Utilize a prospective in vivo clinical trial to evaluate the potential for mild neck compression applied during head impact exposure to reduce anatomical and physiological biomarkers of brain injury. METHODS: This project utilized a prospective randomized controlled trial to evaluate effects of mild jugular vein (neck) compression (collar) relative to controls (no collar) during a competitive hockey season (males; 16.3 ± 1.2 years). The collar was designed to mildly compress the jugular vein bilaterally with the goal to increase intracranial blood volume to reduce risk of brain slosh injury during head impact exposure. Helmet sensors were used to collect daily impact data in excess of 20 g (games and practices) and the primary outcome measures, which included changes in white matter (WM) microstructure, were assessed by diffusion tensor imaging (DTI). Specifically, four DTI measures: fractional anisotropy, mean diffusivity (MD), axial diffusivity, and radial diffusivity (RD) were used in the study. These metrics were analyzed using the tract-based Spatial Statistics (TBSS) approach - a voxel-based analysis. In addition, electroencephalography-derived event-related potentials were used to assess changes in brain network activation (BNA) between study groups. RESULTS: For athletes not wearing the collar, DTI measures corresponding to a disruption of WM microstructure, including MD and RD, increased significantly from pre-season to mid-season (p < 0.05). Athletes wearing the collar did not show a significant change in either MD or RD despite similar accumulated linear accelerations from head impacts (p > 0.05). In addition to these anatomical findings, electrophysiological network analysis of the degree of congruence in the network electrophysiological activation pattern demonstrated concomitant changes in brain network dynamics in the non-collar group only (p < 0.05). Similar to the DTI findings, the increased change in BNA score in the non-collar relative to the collar group was statistically significant (p < 0.01). Changes in DTI outcomes were also directly correlated with altered brain network dynamics (r = 0.76; p < 0.05) as measured by BNA. CONCLUSION: Group differences in the longitudinal changes in both neuroanatomical and electrophysiological measures, as well as the correlation between the measures, provide initial evidence indicating that mild jugular vein compression may have reduced alterations in the WM response to head impacts during a competitive hockey season. The data indicate sport-related alterations in WM microstructure were ameliorated by application of jugular compression during head impact exposure. These results may lead to a novel line of research inquiry to evaluate the effects of protecting the brain from sports-related head impacts via optimized intracranial fluid dynamics.

STUDY DESIGN: A cross-sectional survey was conducted. OBJECTIVES: To describe the occurrence of back pain and associated behaviors and disabilities in a semitraditional Australian aboriginal community. SUMMARY OF BACKGROUND DATA: There are few studies of back pain in isolated and nonindustrial societies. METHODS: The authors lived with, observed, and interviewed most adult members of a small aboriginal community and placed information about spinal pain in context of aboriginal beliefs and practices. RESULTS: Nearly half the adults in this community experienced long-term private spinal pain, but because of their cultural beliefs, did not commonly make this pain public. CONCLUSIONS: Cultural beliefs and practices influence how people respond to back pain in themselves and in others, including how and whether they present to health professionals or seek involvement of others.

Cadmium (Cd), a known human carcinogen, is one of the components of tobacco and also has many industrial uses. Smoking Cd-contaminated cigarettes at work may cause an increase in blood levels and toxicity of Cd. For a population of nonexposed workers, we compared blood Cd and urine cotinine (Cot) levels as biological markers of exposure to cigarette smoke of active smokers (AS) and passive smokers (PS) with those of unexposed nonsmokers (UNS) in 158 workers. The mean Cd in AS (0.097 microgram%; ie, 0.097 microgram/100 mL whole blood) was significantly higher than in UNS (0.085 microgram%), and was very close to the mean Cd levels in PS (0.093 microgram%). Mean Cd levels in exposed past smokers (0.105 microgram% was higher than in nonexposed past smokers (P < 0.05) and in AS. The mean Cot level was significantly higher in AS than in PS or in UNS. Increased smoking was associated directly with increased blood Cd and urine Cot. Our results supported and proved quantitatively that exposure to cigarette smoke is harmful to both AS and PS, as we show that in both cases there is an increase in blood Cd. According to our results, exposure to cigarette smoke via active and passive smoking increases blood Cd by an average of 0.01 micrograms% over the background (UNS). We conclude that exposure to cigarette smoke is a confounder to be taken into account when carrying out epidemiological studies and surveillance programs on workers exposed to Cd at work.

Multimedia processor media extensions to general purpose processors present new challenges to the compiler writer, language designer, and microarchitect. Multimedia workloads have always held an important role in embedded applications, such as video cards or set top boxes, but these workloads are becoming increasingly common in general purpose computing as well. Over the past three years the major vendors of general purpose processors (GPPs) have announced extensions to their instruction set architectures that supposedly enhance the performance of multimedia workloads. These include North Carolina MAX 2 extensions to Hewlett-Packard PA-RISC, MMX for Intel's x86, UltraSparc's VIS, and MDMX extensions to MIPS V. Merging these new multimedia instructions with existing GPPs poses several challenges. Also, some doubt remains as to whether multimedia extensions are a real development or just a competition induced fad in the GPP industry. If it is indeed a development, how must current processor microarchitectures change in reaction? And if they change, can GPPs and MMPs apply application specific integrated circuit (ASIC) solutions to the same problems?.

The purpose of this paper is to present radiological findings of a short-term (8 to 10 months) computerized tomography (CT) follow-up study on 1-stage maxillary sinus lift cases. Pre- and postoperative dental CT scans of 21 patients (24 sinuses) after sinus lift procedures were compared. CT scans were used to assess newly formed bone and its interface with the implants, condition of the sinus membrane, evidence of buccal window cortication, and presence of any sinus pathology. Of the 57 implants placed, 28 had bone fully covering the implant on all sides which did not extend above the apical portion; 20 had bone fully covering the implant which did extend above the apex; and 9 exhibited incomplete bone coverage. All implants supported a fixed ceramo-metal prosthesis, and no implant failures were recorded after 3 years of follow-up. There was evidence of cortication of the buccal window in 10 sinuses; in the 14 remaining sinuses, bone consolidation on the buccal aspect was evident, but no evidence of cortication was seen. All sinuses healed without complications or clinical signs of sinusitis. In 11 sinuses, no changes in membrane thickness were noted. Membrane thickness decreased postoperatively in 12 sinuses, and in one, there was evidence of membrane thickening. Bone cortication in the anterior wall window may serve as an indicator for the remodeling status of the entire graft. Postoperative findings showed a significant improvement in overall membrane thickness. No clinical symptoms of sinusitis were evident, indicating that sinus lift procedures can be considered safe and do not predispose the sinus to acute or chronic sinusitis.

Like other complex, multifaceted interventions in medicine, meditation represents a mixture of specific and not-so-specific elements of therapy. However, meditation is somewhat unique in that it is difficult to standardize, quantify, and authenticate for a given sample of research subjects. Thus, it is often challenging to discern its specific effects in order to satisfy the scientific method of causal inferences that underlies evidence-based medicine. Therefore, it is important to consider the key methodological challenges that affect both the design and analysis of meditation research. The goal of this paper is to review those challenges and to offer some practical solutions. Among the challenges discussed are the mismatches between questions and designs, the variability in meditation types, problems associated with meditation implementation, individual differences across meditators, and the impossibility of double-blind, placebo-controlled meditation studies. Among the design solutions offered are aptitude x treatment interaction (ATI) research, mixed quantitative-qualitative methods, and practical (pragmatic) clinical trials. Similar issues and solutions can be applied more generally to the entire domain of mind-body therapies.

This paper suggests a discriminative approach for wavelet denoising where a set of mapping functions (MFs) are applied to the transform coefficients in an attempt to produce a noise free image. As opposed to the descriptive approaches, modeling image or noise priors is not required here and the MFs are learned directly from an ensemble of example images using least-squares fitting. The suggested scheme generates a novel set of MFs that are essentially different from the traditional soft/hard thresholding in the over-complete case. These MFs are demonstrated to obtain comparable performance to the state-of-the-art denoising approaches. Additionally, this framework enables a seamless customization of the shrinkage operation to a new set of restoration problems that were not addressed previously with shrinkage techniques, such as deblurring, JPEG artifact removal, and various types of additive noise that are not necessarily Gaussian white noise.