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Objective: To compare the safety and efficacy of anti-leukotrienes and inhaled glucocorticoids as monotherapy in people with asthma. Design: Systematic review of randomised controlled trials comparing anti-leukotrienes with inhaled glucocorticoids for 28 days or more in children and adults. Main outcome measure: Rate of exacerbations that required treatment with systemic glucocorticoids. Results: 13 trials (12 in adults, one in children) met the inclusion criteria; all were in people with mild and moderate asthma. Leukotriene receptor antagonists were compared with inhaled glucocorticoids at a daily dose equivalent to 400–450 μg beclometasone dipropionate. Patients treated with leukotriene receptor antagonists were 60% more likely to suffer an exacerbation requiring systemic glucocorticoids (relative risk 1.6, 95% confidence interval 1.2 to 2.2; number needed to treat 27, 13 to 81). A 130 ml greater improvement (80 ml to 170 ml) in forced expiratory volume in one second and a 19 l/min greater increase (14 l to 24 l) in morning peak expiratory flow rate were noted in favour of inhaled glucocorticoids. Differences in favour of inhaled glucocorticoids were also observed for nocturnal awakenings, use of rescue β2 agonists, and days without symptoms. Risk of side effects was no different between groups, but leukotriene receptor antagonists were associated a 2.5-fold increase risk of withdrawals due to poor asthma control (relative risk 2.5, 1.8 to 3.5). Conclusions: Inhaled glucocorticoids doses equivalent to 400 μg/day beclometasone are more effective than leukotriene receptor antagonists in the treatment of adults with mild or moderate asthma. There is insufficient evidence to conclude on the efficacy of anti-leukotrienes in children. What is already known on this topic In 2000 a Cochrane systematic review tentatively concluded that control of asthma was better in patients treated with inhaled glucocorticoids as single agents than with anti-leukotrienes The 2002 Global Initiative for Asthma guidelines still classify the role of anti-leukotrienes as “under investigation” What this study adds Anti-leukotrienes as single agent are less effective than low doses of inhaled glucocorticoids for patients with mild and moderate persistent asthma

The sufficient utilization of the mega data acquired from operative power units is a promising way leading to high efficient, clean and safe operation of power plant. Hereinto, data filtering is a critical link to the data-driven dynamic model identification aiming at optimizing the process control. The machine learning is an advantageous approach for filtering usable data from mega databases for identification due to its effective statistical learning strategy to the field data with noises, disturbances and coupling quantities. Therefore, a data filtering method of combining Gaussian Naive Bayesian classifier and prediction error method (Gaussian NB-PEM) is proposed in this paper. Firstly, variables associated with identification model are selected by analyzing the characteristics of the process. Secondly, the GaussianNB classifier is used for coarse data filtering by calculating the priori probability of each attribute from training sample set and the probability with all possible values of the known categories for testing sample set. Thirdly, the prediction error method is used for further data filtering based on model fitting. By using the filtered closed-loop data, the dynamic characteristics of the superheated steam temperature is modeled and verified by closed-loop control simulation, showing the validity of the Gaussian NB-PEM data filtering method.

Essentially, the difficulty in dehydration technology of lignite depends on the energy state of water in lignite. The fundamental understanding of the water occurrence and energy state in lignite as well as its physical-chemical interaction with coal structure is helpful to the upgrading of lignite. In this paper, the water occurrence in lignite and the changes of oxygen-containing functional groups, pore structure, and water holding capacities at different drying temperatures were researched by DSC, NMR, FTIR and BET, respectively. The binding energies (calculated by DFT using model compounds) of different forms of water in lignite were also summarized. The relationships between energy state and occurrence mode of water in lignite as well as dehydration difficulty and structural changes during dewatering were clarified. The Results show that the energy state of water in lignite divided into three levels. The water in free and pore is in the lowest energy level. Its binding force with coal is pretty weak. So this type of water is easily vaporized and re-adsorbed. It is the main in removed moisture. Generally, the temperature removed free water mainly focused on below 100 °C, and the dehydration temperature of pore water mainly focused on 100–200 °C. The water bonded in hydrogen-bond and capillary confinement is in the middle energy level. The dehydration temperature mainly focused on 200–400 °C. The oxygen-containing functional groups of samples change a little and the re-adsorbed property improves a little after dehydrated. The water mainly produced by chemical reaction above 400 °C is in the highest energy level. Though this type of water does not belong to the natural occurrence of water in lignite, the re-adsorbed property improves much, and it plays the key role in stabilizing the dehydrated lignite interface.

The paper presents a project of a prototype solution of a device for making inseparable crimped joints consisting in forming the material of two elements to be joined to each other with the use of punches. The work contains the assessment and analysis of the joints made in the stand with the use of various forming tools. Furthermore, the paper presents the analysis of the characteristic features of the new joints, as well as dependences in strength tests. The elements joined on the machine had been made of 5754 aluminium. This material and the presented joint are used in the construction of heat exchangers, such as water, oil coolers or condensers in the automotive or aircraft branch.

In this paper we present a parametric method for the identification of a horizontal positioning system for a billets unloading machine. The input-output models are obtained on the experimental models and on the priori information of the process. The obtained models are represented as second-order underdamped systems. The assessment of the models is made via simulation and a best fit model follows. In order to improve the current process performances, new automatic control structures for the positioning process can be derived using the determined model

Machining of highly abrasive carbon fibre reinforced polymer (CFRP) in the aerospace industry requires processes with excellent machining quality, sufficient tool lifetime and short cycle times. To reach these goals a detailed understanding of the physics of cutting and chip formation based on the tool geometry is necessary. This paper presents a fundamental study in milling of unidirectional CFRP focussing on variable process parameters, tool geometries and fibre orientations. A single-edged tool with cemented carbide inserts of variable macro geometry is utilised. The experiments are evaluated by 3D microscopy of the milled edges, detailed tool wear analyses and interpretation of cutting forces. The key conclusions from the experimental results are drawn to reach a better machining quality and increased tool lifetime. The delamination of top layer fibres from the ply below up to a certain distance from the milled edge, which depends on the forces at fibre cutting angle ϕ = 90°, has been identified as main quality issue. Force and tool wear models based on the measurement data are presented.

The classification of color image that contain skin pixel is a challenging process. It is challenging due to certain factor such as brightness, background similar to human skin represent the obstacles thereof. The basic approach of skin detection is color based classification. The human skin image is the composition of RGB color. The data values of skin is calculated by randomly sampling RGB color values of different face images which have different age, race, genders sets. However, its performance has not really been high because of the high overlapped degree between “skin” and “non-skin” pixels. This paper describes the linear norm fuzzy based twin support vector machine (LN-FTSVM)) approach for discriminate skin and non-skin data values of skin dataset and to enhance the skin recognition performance. The concept of fuzzy is resolved the unclassified and overlapped data region problems. If no decision function is positive for a data set, this data set is classified into a class with the large membership value. By computational experiments shows that Experiments result shows that the accuracy is improved by linear norm fuzzy based TSVM (LN-FTSVM)) over the conventional methods.

A medical genetics clinic is a unique and complex environment in which care requires a combination of medical knowledge, social intelligence, and emotional sensitivity. We offer a few pearls from our medical genetics clinic that we hope will help the pediatric or general dermatologist when caring for patients with known or suspected genetic disorders. This paper addresses five main topics: When is it more than just atopic dermatitis? How should the clinician approach blistering in the newborn period? What is mosaicism? When is genetic testing useful? Where can clinician, patients, and families turn for available resources?

Software frameworks are difficult for plugin developers to use, even when they are well designed and documented. Some of these difficulties stem from the many constraints that frameworks impose on plugin code. These constraints might restrict operations from being called on certain objects, or they might restrict how long an object is available. Additionally, the constraints are relative to the current context of the plugin, and they can involve multiple, interacting framework objects. This paper proposes a lightweight specification system and analysis to check plugins from a semantic perspective, rather than a purely structural view.

Delivering reliable service requires satisfactory operation of numerous line components, spanning significant geographical areas and subject to environmental, electrical, and mechanical stresses, plus normal aging. Conventional reliability practices use periodic maintenance to minimize failures, coupled with rapid restoration procedures when outages occur. Reliability statistics have shown little change in decades. Newer technologies can shorten outages, by automatically rerouting service to customers on healthy feeder segments, but they: require redundant paths for power flow; react only after outages occur; and often require communications with pole-mounted switches. Over the past decade, Texas A&M University has demonstrated that electrical waveforms, available via conventional substation-based CTs and PTs, contain evidence of failures, incipient failures, and improper operation of feeder equipment, often well before these conditions escalate and cause outages. This provides the basis for conditioned-based maintenance and outage avoidance. This paper provides examples, from operating feeders, demonstrating some of these advances.

Purpose – The purpose of this paper is to explore the issues arising for women and men in senior management in New Zealand and Australian universities where life course and career trajectories intersect, and analyses how the stereotypical masculinist culture of universities can create additional problems for women. Design/methodology/approach – The data presented here comes from 47 interviews undertaken with women (27) and men (20) senior managers – a total of 26 interviews from New Zealand universities and 21 from Australian universities. “Senior Management” was defined in this study as those academic managers with university wide responsibilities, who were currently in senior management positions. Findings – Life-course issues for women aspiring to senior management roles in universities are framed around hegemonic constructions of masculinity; notions of academic careers subsuming personal life in professional roles; and structural constraints making rational choice impossible for many women. Furthermore, the excessive hours worked in such roles equate with the definition of extreme jobs. The paper concludes that the way in which women and men in senior HE endeavour to balance work and family life differs but creates issues for them both. Research limitations/implications – The structure and operation of Australian and New Zealand universities make gender diversity and management difficult to operationalise, given the competing imperatives of work and other life course trajectories. It is crucial to reframe life course and career intersections are conceptualised to ensure that diversity can be maximised. Originality/value – This paper focuses on women and men in senior management positions in New Zealand and Australian universities, but the findings can be generalised to other countries with HE systems based on the British University model. In discussing how institutional culture affects the intersection of career and life course trajectories, this paper highlights the detrimental outcomes for individuals and the resultant lack of diversity in the sector.

The Cygnus Dual Beam Radiographic Facility consists of two identical radiographic sources each with a dose rating of ∼4-rad at 1 m, and a ∼1-mm diameter spot size. The development of the rod pinch diode (RPD) was responsible for the ability to meet these criteria. The RPD in each machine uses a 0.75-mm tungsten diameter tapered anode rod extended through a 9-mm diameter cathode aperture. When properly configured, the electron beam born off the aperture edge can self-insulate and pinch onto the tip of the rod creating an intense, small x-ray source. These sources are utilized in concert with an imaging system on complex experiments, which are single-shot, high-value events. In such an application there is an emphasis on machine performance (reliability and reproducibility). Vacuum quality is a significant determinator for source performance. In this paper we discuss the Cygnus Dual Beam Radiographic Facility, the associated vacuum systems, vacuum monitor calibration and a multi-purpose vacuum chamber. Vacuum system performance, using various enhancements, will be reported. Using the vacuum system enhancements, as well as other machine tweaks, recent source performance has improved. This new level of performance will be presented via dosimetry and electrical measurements.

Pressure regulators have a great impact on the runtime and energy savings of supersonic wind tunnels. In order to investigate this impact quantitatively the theoretical isentropic (ideal) equations for the supersonic wind tunnel flow were compared with viscous CFD computations. The theoretical model was extended include the flow from the outflow from the pressure vessel up to the wind tunnel. This theoretical model was solved with and without pressure regulation valve using a Runge-Kutta method. The differences in runtime and energy consumption for both configurations with and without pressure regulator as well as the derivation of the analytical model and the numerical solution are presented in detail in this paper.

This paper presents a method for characterizing chemical solutions using nanowire field effect transistors. A pulsed gate potential method is used to prevent instabilities related to the dynamics of ions and other charged species present in the solution. Applying this method realizes a significant increase of the stability of the drain current versus gate potential characteristics of the devices, enabling reproducible characterization of chemical solutions with nanowire field effect transistors in aqueous environments.

This paper examines 1,089 private equity (PE) backed and non-PE backed (pure) UK buy-outs, determinants of their survival, and their exit behaviour during the period of 1966-2004. Our results suggest that 56% of the pure sample buy-outs remained in a buy-out organisational form for at least seven years after the original buy-out transaction, thus lending support to views that buy-outs present long rather than short term form. PE backed buy-outs exhibit higher exit rates, fewer early (within 12 months) exits and fewer liquidations than their pure counterparts. Buy-outs sponsored by PE syndicates, those harvested during periods with strong market conditions and greater supply of PE funding, tend to have shorter longevity. The most notable difference between the survival experiences of PE backed and pure buy-outs is documented in IPO exits, where a significant number of pure buy-outs exit early to the Alternative Investment Market (AIM). © 2011 Blackwell Publishing Ltd.

From the point of view of a data warehouse system, collecting and receiving information from source systems is crucial for all subsequent business intelligence applications. Incoming information can generally be classified into two types: (1) the state-oriented data and (2) event-oriented data or transactional data, which contains information about the change performed by processes on the instances of information objects. On the way towards achieving the goal of a full-fledged active data warehouse it becomes more and more important to provide data with minimal latency. In this paper we focus on dimensional data which is provided by general data warehouse applications. The information transfer is performed via messages containing the change of information on the dimension instances. The proposed approach is able to validate the event-messages, reconstruct the complete history of the dimension and provide a well applicable ''comprehensive slowly changing dimension'' (cSCD) interface for queries on the historical and current state of the dimension. A description of the prototype implementation for this kind of an ''active integration'' in a data warehouse and a case study at T-Mobile conclude the paper.

Recently the microstrip patch antennas (MPA) has evolved into a most dynamic and indigenous field in the arena of UWB demanding low profile and mini antennas with ample frequency choice for ultra wide (UWB) applications. Thus the paper focuses on thorough analysis of a novel rectangular microstrip patch with carpet shaped fractal antenna fed by microstrip line for applications in Ultra- Wideband. The basic antenna structure is rectangular microstrip patch which is modified by adding slotted rectangular shape with partial ground plane at the rear end is iterated using fractal geometry that exhibits more bandwidth and reduce return loss. The proposed antenna has a compact size 50×42mm2 with height 1.6mm and designed on low cost FR4 (er = 4.3) substrate. A wider bandwidth (-10 dB) of around 3.1 – 8.25 GHz with stable radiation pattern is achieved and E-field, H-field current distributions are also examined. When compared with the existing traditional UWB antennas, the recommended antenna exhibits good characteristics, low profile and more so cost-effective. By using CST MW studio software the Proposed UWB antenna is designed and simulated to verify antenna parameters for improvements.

Investment decisions in the development and production of new aircraft models is difficult because of the technical and market uncertainties associated with such a complex process. The accompanying risks can be mitigated through a flexible approach that incorporates several decision points at different stages of the process. Therefore, as the project evolves, management will be able to diagnose its progress, compare it to previous expectations, and decide to continue or not. In this paper, we present a methodology to evaluate flexible business strategies that is based on real options analysis (ROA) and Monte Carlo simulation. This methodology takes into account the flexibility that managers have to affect the success of any given project and, therefore, it provides a better estimate of project value. Numerical results are given for a representative process based on actual aircraft manufacturer's data.

Purpose: In Micro-CT systems based on optical coupling detectors, the defects of scintillator or CCD-camera would lead to heavy artifacts in reconstructed CT images. Meanwhile, different detector units usually suffer from inhomogeneous response, which also leads to artifacts in the CT images. Detector shifting is a simple and efficient method to remove the artifacts due to inhomogeneous responses of detector units. However, it does not work well for heavy artifacts due to defects in scintillator or CCD. The purpose of this paper is to develop a data preprocessing method to reduce both kinds of artifacts. Methods: A hybrid method which involves detector random shifting and data inpainting is proposed to correct the projection data, so as to suppress the artifacts in the reconstructed CT images. The defects in scintillator or CCD-camera lead to data lost in some areas of the projection data. The Criminisi algorithm is employed to recover the lost data. By detector random shifting, the location of the lost data in one view might be shifted away in adjacent views. This feature is utilized to design the search window, such that the best match patch shall be searched across adjacent views. By this way, the best match patches should really enjoy high similarity. As a result, the heavy artifacts due to defects of scintillator or CCD-camera should be suppressed. Furthermore, a multiscale tessellation method is proposed to locate the defects and similarity patches, which makes the Criminisi algorithm very fast. Results: The authors tested the proposed method on both simulated projection data and real projection data. Experiments show that the proposed method could correct the bad data in the projections quite well. Compared to other popular methods, such as linear interpolation, wavelet combining Fourier transform, and TV-inpainting, experimental results suggest that the CT images reconstructed from the preprocessed data sets by our method is significantly better in quality. Conclusions: They have proposed a hybrid method for projection data preprocessing which fits well to typical Micro-CT systems. The hybrid method could suppress the ring artifacts in the reconstructed CT images efficiently, while the spatial resolution is not reduced even with a critical eye.

Despite strong economic growth, investment in basic urban infrastructure -- water supply, wastewater removal and treatment, roads, and other capital-intensive systems -- has failed to keep pace with urban growth, leaving a critical urban infrastructure deficit. At the same time, urban lands in these many developing countries are among the most expensive in the world. Much of this land is owned by public authorities. Significant parts of it lie vacant, unused for public service provision or inappropriate for conversion to higher-valued economic activity. A composite public-sector balance sheet for India's urban areas would show an asset mix strong on public-sector landholdings but weak on infrastructure. This raises the following questions: Can some excess public-sector land be exchanged for infrastructure, in a manner that is politically acceptable and economically efficient? Can public land sales be a realistic source of finance for critically needed urban infrastructure investment? This paper considers the policy context that has shaped different land-disposal and earmarking initiatives, provides details about the actual workings of institutions, and examines international experience in infrastructure investment. This study contributes to the consultative process underway in India to consider strategies to unlock public land values to help finance urban infrastructure investment.

In this paper, the results of our studies on some aspects of the carbohydrate metabolism of normal infants are presented. The infants were as nearly normal as it was possible to obtain in an active pediatric service. AVERAGE CONCENTRATION OF THE FASTING BLOOD SUGAR Conflicting values have been reported for the average concentration of the blood sugar in fasting infants. A critical review of the literature shows that one reason for this at least, aside from inherent errors in the methods used or errors in the technic of the investigator, is that a number of the workers did not determine carefully the interval required after a meal for the blood sugar to return to the fasting level. It has been demonstrated by Niemann1and Rumpf2that, three hours after a feeding, the blood sugar concentration is frequently above the initial level, while from four

To improve the intelligent image recognition abilities of edge devices, a parallel-optimization-based framework called POWER is introduced in this paper. With FPGA (Field-Programmable Gate Array) as its hardware module, POWER provides well extensibility and flexible customization capability for developing intelligent firmware suitable for different types of edge devices in various scenarios. Through an actual case study, we design and implement a firmware prototype following the specification of POWER and explore its performance improvement using parallel optimization. Our experimental results show that the firmware prototype we implement exhibits good performance and is applicable to substation inspection robots, which also validate the effectiveness of our POWER framework in designing edge intelligent firmware modules indirectly.

The dynamic programming is an important procedure for speech understanding and image recognition. In this paper, the application of dynamic programming to recognize the image basing on its contour is recalled, then the parallelism of this process is analyzed and exploited. Some parallel dynamic programming algorithms for evaluating the smallest value of the minimum intersegment distance path in a data table are designed in detail on several kinds or the specialized parallel computer, such as 2D Systolic Array, ID Systolic Array and an associative computer of the SIMD type. Their computation complexities are respectively estimated as O(k), O(k) and O(kw), while the cost O(mn) is obtained on serial computer, where k=max(2n,m), m is the number of segments of a contour to be recognized, n gives the number of segments of the sample contour and w is the bit-width of the used associative fields.

Windows 95 may provide a major stimulus to Intelligent Network (IN) development, to real technological convergence between computing and telecommunication, and to a major reordering of research priorities in the field. The paper examines IN in the context of the evolution of convergence and the larger framework of information superhighway, infrastructure and society developments. It shows how the pace and direction of IN development will be driven by demand associated with organisational and institutional change, not the simple supply of greater capacity or the discovery of ‘killer applications’. This will be associated with a shift in priorities to distributed networking, information-based service development and a diversity of very specific new applications.

Network coding has been applied successfully in peer-to-peer systems to shorten the distribution time, particularly in extreme conditions where peers in the network are clustered and separated by physical links with limited bandwidth. In this paper, we focus more closely on the use of source coding, i.e. encoding is done only at the source, as an alternative to network coding to facilitate content distribution under such limited bandwidth configuration. We observe analytically and experimentally that, in this specific case, with appropriately chosen expansion factors, source coding can have comparable performance to network coding in terms of distribution time, yet consuming much less computational resources than the latter approach does.

Air quality and fuel efficiency has become important factors in decision-makings on urban traffic planning and management. To support the process, simulation models have potential to play essential roles in evaluation of planning alternatives and control strategies. However, traffic and its environmental impacts are different processes and often require various levels of models. With concerns on high computing performance and rich functionalities, it may be not appropriate to model emission inventory within traffic simulation. In this paper, we present a distributed simulation approach, and an independent emission/energy computing platform is built to simulate, visualize and analyze online emission outputs, given a microscopic traffic simulation tool, KTH-TPMA. Two distributed computing frameworks, common objects request broker architecture (CORBA) and service oriented architecture (SOA), are adopted in the distributed software design and implementation. Several emission models are implemented and generally evaluated in micro simulation runs of two road networks.

The chief aim of the paper is to study the major function of higher education in cultural innovation through an analysis of how China's higher education nationalizes and internationalizes and draws challenges for cultural innovation. The starting points are an original contribution to the understanding of the role of higher education in relation to innovation (UNESCO Forum on Higher Education, Research and Knowledge, 2009). On this basis we move ahead and the procedure we follow can be briefly described as follows: firstly, the paper makes a simple analysis about the characteristics of higher education localization and its influence on cultural innovation; meanwhile, the author puts forward several proposals for the reform of higher education in order to promote cultural innovation. Secondly, the author proceeds to emphasize the importance of higher education internationalization and its value in cultural innovation. Thirdly, the paper expounds internationalization communication and cooperation of Chinese higher education. At last, It is concluded that higher educational localization and internationalization are of great significance for realization of the function of cultural innovation keeping balance between Chinese native culture and international culture. Index Terms - Cultural innovation, localization, internationalization, Chinese higher education

This paper contains a study of the motion of a rotor possessing unequal flexibilities in two mutually perpendicular directions and mounted in bearings which likewise possess different stiffnesses in two mutually perpendicular directions, say, the horizontal and vertical directions. A two-pole turbogenerator is an example of such a rotor. As known, the effect of ρ, the fractional inequality in rotor flexibilities, by itself, that is, without unequal bearing flexibilities, consists in giving rise to an unstable range of speed near the critical whose width depends upon ρ; the larger ρ is, the wider is the unstable range. If neither ρ nor σ vanishes (σ = fractional inequality of bearing flexibilities), the investigation becomes more difficult due to the fact that the principal flexibility directions are fixed for the bearings but rotate for the rotor. The differential equations of motion now acquire periodic coefficients whose period is half the rotation period. Their solution shows that near the main critical speed, for small ρ the unstable range splits up into three parts, which coalesce into one range for large ρ. The separation of three unstable ranges increases with σ. A further slight instability also occurs when the rotor speed is near half of the main critical speed. If one attempts to revolve such a rotor at a constant speed inside an unstable range, it may, even if in perfect balance, whirl with an exponentially increasing amplitude. With friction the amount of instability decreases and the size of the unstable regions decreases too, and with sufficient friction complete stability is restored. The friction necessary to restore stability is computed and the effect of unbalance on the steady-state amplitudes is studied. The solution of linear differential equations with periodic coefficients leads to an infinite number of algebraic linear equations in an infinite number of coefficients. Various ways of solving these equations and of speeding up the convergence of the solution are discussed in detail.

Focal boost to dominant intraprostatic lesions (DILs) has recently been proposed for prostate radiation therapy. Accurate and fast delineation of the prostate and DILs is thus required during treatment planning. In this paper, we develop a learning-based method using positron emission tomography (PET)/computed tomography (CT) images to automatically segment the prostate and its DILs. To enable end-to-end segmentation, a deep learning-based method, called cascaded regional-Net, is utilized. The first network, referred to as dual attention network, is used to segment the prostate via extracting comprehensive features from both PET and CT images. A second network, referred to as mask scoring regional convolutional neural network (MSR-CNN), is used to segment the DILs from the PET and CT within the prostate region. Scoring strategy is used to diminish the misclassification of the DILs. For DIL segmentation, the proposed cascaded regional-Net uses two steps to remove normal tissue regions, with the first step cropping images based on prostate segmentation and the second step using MSR-CNN to further locate the DILs. The binary masks of DILs and prostates of testing patients are generated on the PET/CT images by the trained model. For evaluation, we retrospectively investigated 49 prostate cancer patients with PET/CT images acquired. The prostate and DILs of each patient were contoured by radiation oncologists and set as the ground truths and targets. We used five-fold cross-validation and a hold-out test to train and evaluate our method. The mean surface distance and DSC values were 0.666 ± 0.696 mm and 0.932 ± 0.059 for the prostate and 0.814 ± 1.002 mm and 0.801 ± 0.178 for the DILs among all 49 patients. The proposed method has shown promise for facilitating prostate and DIL delineation for DIL focal boost prostate radiation therapy.

Water distribution network that includes supply reservoirs, overhead tanks, consumer demand nodes, interconnecting pipes, lifting pumps, and control valves is the main mode of water supply for majority of the communities especially in urban areas. Supply of required quantity of water and at right time is the primary objective of water distribution network analysis. The analysis of water distribution networks can be broadly classified into design and operation problems and both problems have been the focus of many researchers over the past three decades. In the water distribution network design problems, the target is attaining the cost effective configuration that satisfies the minimum hydraulic head requirement at the demand nodes. In this paper, a new algorithm for design of water distribution network namely "heuristics-based algorithm" which completely utilizes the implicit information associated with the water distribution network to be designed has been proposed and validated with two water distribution networks. It is found that the proposed algorithm performs well for the least-cost design of water distribution networks. � 2009 ASCE.

We examine the equity premium puzzle with the perspective of the theory of Rational Beliefs Equilibrium (RBE) and show that from the perspective of this theory there is no puzzle. In an RBE agents need to be compensated for the endogenously propagated price uncertainty which is not permitted under rational expectations. It is then argued that endogenous uncertainty is the predominant uncertainty of asset returns and its presence provides a natural explanation of the observed premium. Utilizing data on the asset allocation of 63 U.S. mutual funds, we test some empirical implications of the theory of rational beliefs as well as estimate the parameters of risk aversion of mutual fund managers. Our tests show that the predictions of the theory are consistent with the empirical evidence. We then construct a simple two agent model of the U.S. economy in which the agents hold rational beliefs and calibrate it to the empirical experience in accord with the parameters of the Mehra and Prescott (1985) paper. The results of our calculations show that for a large set of parameter values the model predictions fit closely the historical record.

Gain-cell embedded DRAM (GC-eDRAM) is an attractive alternative to traditional SRAM, due to its high-density, low-leakage, and inherent 2-ported operation, yet, its dynamic nature leads to limited retention time that requires periodic, power-hungry refresh cycles. This drawback is further aggravated in scaled technologies, where increased leakage currents and decreased in-cell storage capacitances lead to accelerated data integrity deterioration. However, the emerging approximate computing paradigm utilizes the inherent error resilience of some applications to tolerate data errors. Such error tolerance can be exploited by reducing the refresh rate in GC-eDRAM to achieve a substantial decrease in power consumption, at the cost of an increase in cell failure probability. In this paper, we present the first fabricated and fully functional GC-eDRAM in a 28 nm bulk CMOS technology. The array, which is based on a novel mixed-V t 4T bitcell, can be used in both traditional and for approximate computing applications, featuring a small silicon footprint and supporting high-performance operation. Silicon measurements demonstrate successful operation at 800 Mhz under a 900 mV supply, while retaining almost 30% lower area than a single-ported 6T SRAM in the same technology.

In this paper, a new configuration for a multi-terminal offshore wind farms based VSC-HVDC and large scale photovoltaic system using modified unified adaptive linear neuron (Adaline) algorithm is presented. In the offshore station, the permanent magnet synchronous generator (PMSG)-based wind turbines are tied to the bus via back-to-back converters and a step-up transformer. The large scale photovoltaic power is connected to the dc bus between the offshore voltage source converters (VSC) and onshore VSC-HVDC stations via a modular multilevel converter (MMC). The Power management and the synchronization between two buses are achieved by controlling the two VSC converters. The performance of the topology proposed is tested using Matlab/Simulink during permanent operation mode and in the presence of DC fault.

The combination of Java applications as graphical user interfaces and the Matlab-Simulink environment as the simulation engine seems to be a good solution for taking a particular control lab to distant students. In this paper, it is presented a new kind of simulation environment for qualitative teaching on concepts of Control Engineering by means of a suitable configuration of experiments by the tutor or teacher.

The learning behavior of the agent is a challenging and interesting issue in an unknown environment. Reinforcement learning obtain the developed strategy through exploration and interaction with the environment, and the characteristic of online learning make it as an important branch of machine learning research. In this paper, we summarize the current research of the reinforcement learning applications and hotspots. Firstly, the principle, structure and the main classic algorithms of the reinforcement learning are introduced. Secondly, according to the recent research results, we introduce four main applications of reinforcement learning, namely robot, unmanned aerial vehicle, multi-agent and intelligent traffic. Finally, the research hotspots and the development direction of the reinforcement learning are introduced, which conclude the partial perception, hierarchical reinforcement learning, combination with other artificial intelligence technologies and game theory.

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

Texas Instruments has been developing a passive tag which removes some of the practical difficulties, meeting the optimum cost/performance trade off and performance requirements for two dedicated market sectors. In the form of a "smart label" the transponder electronics have been laminated into paper labels and plastic cards and this product is called Tag-it/sup TM/. This passive transponder has been developed for the target markets of express parcels and airline baggage though, over time, we expect that it will be adapted for use in other market sectors. In these two markets a flexible label is required where it can meet existing label specifications and form factors and be easily introduced into existing hardware.

Visual lifelogging is the process of automatically recording images and other sensor data for the purpose of aiding memory recall. Such lifelogs are usually created using wearable cameras. Given the vast amount of images that are maintained in a visual lifelog, it is a significant challenge for users to deconstruct a sizeable collection of images into meaningful events. In this paper, random matrix theory (RMT) is applied to a cross-correlation matrix C, constructed using SenseCam lifelog data streams to identify such events. The analysis reveals a number of eigenvalues that deviate from the spectrum suggested by RMT. The components of the deviating eigenvectors are found to correspond to "distinct significant events" in the visual lifelogs. Finally, the cross-correlation matrix C is cleaned by separating the noisy part from the non-noisy part. Overall, the RMT technique is shown to be useful to detect major events in SenseCam images.

The proliferation of antipersonnel landmine use has created problems world-wide. This study identifies and clarifies the complex issues that have created the current landmine dilemma. In addition, this research discusses international and Congressional attempts to regulate antipersonnel landmine use and critically analyzes these efforts. This paper also proposes recommendations as to what the role of the United States should be in resolving the land mine dilemma.

Ensuring long processor lifetimes by limiting failuresdue to wear-out related hard errors is a critical requirementfor all microprocessor manufacturers. We observethat continuous device scaling and increasing temperaturesare making lifetime reliability targets even harder to meet.However, current methodologies for qualifying lifetime reliabilityare overly conservative since they assume worst-caseoperating conditions. This paper makes the case thatthe continued use of such methodologies will significantlyand unnecessarily constrain performance. Instead, lifetimereliability awareness at the microarchitectural design stagecan mitigate this problem, by designing processors that dynamicallyadapt in response to the observed usage to meeta reliability target.We make two specific contributions. First, we describean architecture-level model and its implementation, calledRAMP, that can dynamically track lifetime reliability, respondingto changes in application behavior. RAMP isbased on state-of-the-art device models for different wear-outmechanisms. Second, we propose dynamic reliabilitymanagement (DRM) - a technique where the processorcan respond to changing application behavior to maintainits lifetime reliability target. In contrast to currentworst-case behavior based reliability qualification methodologies,DRM allows processors to be qualified for reliabilityat lower (but more likely) operating points than theworst case. Using RAMP, we show that this can save costand/or improve performance, that dynamic voltage scalingis an effective response technique for DRM, and that dynamicthermal management neither subsumes nor is sub-sumedby DRM.

There are a number of methods for classification of mobile apps, but most of them rely on a fixed set of app categories and text descriptions associated with the apps. Often, one may need to classify apps into a different taxonomy and might have limited app usage data for the purpose. In this paper, we present an app classification system that uses object detection and recognition in images associated with apps, along with text based metadata of the apps, to generate a more accurate classification for a given app according to a given taxonomy. Our image based approach can, in principle, complement any existing text based approach for app classification. We train a fast RCNN to learn the coordinates of bounding boxes in an app image for effective object detection, as well as labels for the objects. We then use the detected objects in the app images in an ensemble with a text based system that uses a hierarchical supervised active learning pipeline based on uncertainty sampling for generating the training samples for a classifier. Using the ensemble, we are able to obtain better classification accuracy than if either of the text or image systems are used on their own.

Optical Burst-switched (OBS) is a promising switching technology and expected to support the future Internet backbone with dramatically increasing bandwidth demand. In an OBS network, burst contention causes burst loss due to bufferless nature of OBS core network. This kind of burst loss will interact with the above TCP layer. In this paper, we study the impact of this interaction on TCP fairness. We find significant unfairness among TCP flows that share the OBS core network, i.e. one flow obtains higher throughput while any others with much lower throughputs. The cause is the phenomenon called "the bigger eats the smaller (BES)", in which a TCP flow with higher rate occasionally will "see" less burst contentions and increase its rate further, while a TCP with lower rate will see more burst contentions and decrease its rate continually. Discuss a simple model to explain BES and verify that a continuous sequence of bursts will enhance BES. Then observe that offset time will be a good choice to control TCP fairness by a curve of unfairness control with offset time adjustment. Finally an adaptive offset time scheduling (AOS) algorithm is proposed. AOS assigns burst offset time value adaptive to the rate of TCP flow. The simulation results show that the fairness can be significantly improved by our AOS scheme.

In nature, many species became extinct as they could not adapt quickly enough to their environment. They were simply not fit enough to adapt to more and more challenging circumstances. Similar things happen when algorithms are too static to cope with particular challenges of their "environment", be it the workload, the machine, or the user requirements. In this regard, in this paper we explore the well-researched and fascinating family of adaptive indexing algorithms. Classical adaptive indexes solely adapt the indexedness of the data to the workload. However, we will learn that so far we have overlooked a second higher level of adaptivity, namely the one of the indexing algorithm itself. We will coin this second level of adaptivity meta-adaptivity. Based on a careful experimental analysis, we will develop an adaptive index, which realizes meta-adaptivity by (1) generalizing the way reorganization is performed, (2) reacting to the evolving indexedness and varying reorganization effort, and (3) defusing skewed distributions in the input data. As we will demonstrate, this allows us to emulate the characteristics of a large set of specialized adaptive indexing algorithms. In an extensive experimental study we will show that our meta-adaptive index is extremely fit in a variety of environments and outperforms a large amount of specialized adaptive indexes under various query access patterns and key distributions.