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Photoacoustic (PA) microscopy allows imaging of the soft biological tissue based on optical absorption contrast and spatial ultrasound resolution. One of the major applications of PA imaging is its characterization of microvasculature. However, the strong PA signal from skin layer overshadowed the subcutaneous blood vessels leading to indirectly reconstruct the PA images in human study. Addressing the present situation, we examined a deep learning (DL) automatic algorithm to achieve high-resolution and high-contrast segmentation for widening PA imaging applications. In this research, we propose a DL model based on modified U-Net for extracting the relationship features between amplitudes of the generated PA signal from skin and underlying vessels. This study illustrates the broader potential of hybrid complex network as an automatic segmentation tool for the in vivo PA imaging. With DL-infused solution, our result outperforms the previous studies with achieved real-time semantic segmentation on large-size high-resolution PA images.

Today, many complex multiobjective problems are dealt with using genetic algorithms (GAs). They apply the evolution mechanism of a natural population to a &ldquo, numerical&rdquo, population of solutions to optimize a fitness function. GA implementations must find a compromise between the breath of the search (to avoid being trapped into local minima) and its depth (to prevent a rough approximation of the optimal solution). Most algorithms use &ldquo, elitism&rdquo, which allows preserving some of the current best solutions in the successive generations. If the initial population is randomly selected, as in many GA packages, the elite may concentrate in a limited part of the Pareto frontier preventing its complete spanning. A full view of the frontier is possible if one, first, solves the single-objective problems that correspond to the extremes of the Pareto boundary, and then uses such solutions as elite members of the initial population. The paper compares this approach with more conventional initializations by using some classical tests with a variable number of objectives and known analytical solutions. Then we show the results of the proposed algorithm in the optimization of a real-world system, contrasting its performances with those of standard packages.

Feature-based attention allocates resources to particular stimulus features and reduces processing and retention of unattended features. We performed four experiments using self-paced video games to investigate whether sustained attentional selection of features could be created without a distractor task requiring continuous processing. Experiments 1 and 2 compared two versions of the game Two Dots, each containing a sequence of images. For the more immersive game post-game recognition of images was very low, but for the less immersive game it was significantly higher. Experiments 3 and 4 found that post-game image recognition was very low if the images were irrelevant to the game task but significantly higher if the images were relevant to the task. We conclude that games create sustained attentional selection away from task-irrelevant features, even if they are in full view, which leads to reduced retention. This reduced retention is due to differences in attentional set rather than a response to limited processing resources. The consistency of this attentional selection is moderated by the level of immersion in the game. We also discuss possible attentional mechanisms for the changes in recognition rates and the implications for applications such as serious games.

Although many studies of iterative based reconstruction algorithm have been performed on dose reduction in medical applications, there is little research on how to approach the systematical acquisition method to reduce the dose. In this study, we proposed a hybrid imaging technique using half ROI and full view scan as a new acquisition method. A prototype of the CT system (TVX-IL1500H, GERI, Korea) was used. The source-to-detector and the source-to-center of rotation distance were 1178 and 905 mm, respectively. A total of 720 projection data were obtained, from which full view CT reconstructed images were obtained as a reference image using a filtered back projection (FBP). Interior ROI CT images were reconstructed using the 720 truncated projection data. Proposed hybrid CT image was reconstructed using 360 truncated and variable number of nontruncated full-size projection data. We set a total of 6 acquisition parameters according to the number of full-size projection data and acquire hybrid images. Dose reduction can be achieved through half ROI and full view scan. As the number of nontruncated full-size projection data on the hybrid image increases, the CNR value increases. FOM values were also derived for each parameter. In conclusion, appropriate acquisition parameter for half ROI and full view scan was derived based on the FOM values.

One of the main difficulties in intracranial aneurysms (IA) surgery refers to the choice of the appropriate clip(s) to be implanted. Although the imaging exams currently available ensure visualization of IA's morphology, they do not bring an accurate reference positioning for the surgeon in executing the surgery procedure nor efficiently contribute to planning the surgery. Unfortunately, for IA's largely inaccessible regions, there is not an efficient method of treatment planning. Therefore, we propose a novel method that allows the generation of a 3D biomodel of the IA region under investigation using additive manufacturing technology (AM). Thus, a physical copy of the IA is produced and offers the surgeon a full view of the anatomy of that region of the brain. The aim of this study is the creation of a flexible 3D physical model (elastomer) through the AM technique, in order to allow the clip selection prior to the surgery. DICOM angio-CT images from eight patients who underwent IA surgery were transformed into STL format and then built on a 3D printer. Preoperative surgical clip selection was performed and then compared with those used in surgery. At the end of the study, all 3D IA biomodels were reproduced for microsurgical clipping selection and it was possible to predict the metal clip to be used in the surgery. In addition, the proposed methodology helps to clarify the surgical anatomy and to avoid excessive manipulation of the intracranial arteries and prolonged surgical time. The major advantage of this technology is that the surgeon can closely study complex cerebrovascular anatomy from any perspective using realistic 3D biomodels, which can be handheld, allowing simulation of intraoperative situations and anticipation of surgical challenges.

CPI stacks are an intuitive way to visualize processor core performance bottlenecks. However, they often do not provide a full view on all bottlenecks, because stall events can occur concurrently. Typically one of the events is selected, which means information about the non-chosen stall events is lost. Furthermore, we show that there is no single correct CPI stack: stall penalties can be hidden, can overlap or can cause second-order effects, making total CPI more complex than just a sum of components. Instead of showing a single CPI stack, we propose to measure multiple CPI stacks during program execution: a CPI stack at each stage of the processor pipeline. This representation reveals all performance bottlenecks and provides a more complete view on the performance of an application. Multi-stage CPI stacks are easy to collect, which means that they can be included in a simulator with negligible slowdown, and that they can be included in the core hardware with limited overhead.

Labelling body parts in depth images is useful for a wide variety of tasks. Many approaches use skeleton-based labelling, which is not robust when there is a partial view of the figure. In this work we show that Minkowski networks, which have recently been developed for 3D point cloud labelling of scenes, can be used to label point clouds with body part categories, achieving 85.6% accuracy with a full view of the figure, and 82.1% with partial views. These results are limited by a small sample size of our training data, but there is evidence that some of these ‘misclassifications’ may be correcting mistakes in the reference labelling. Overall, we demonstrate that Minkowski networks are effective for body part labelling in point clouds, and are robust to occlusion.

In the coming era of connected autonomous vehicles, data-driven traffic optimization will reach its full potential. By collecting highly detailed real-time traffic data from sensors and vehicles, a traffic management system will have the full view of the entire road network, allowing it to plan traffic in a virtual world that replicates the real road network. This will bring significant innovations to transport-domain applications. We prototype a traffic management system that can perform traffic optimization with connected autonomous vehicles. We propose two route assignment algorithms that aim to reduce traffic delays by reducing intersecting routes. The proposed algorithms and two state-of-the-art route assignment algorithms are implemented in the prototype system. We evaluate the algorithms with both synthetic and real road networks. The experimental results show that the proposed algorithms outperform competitors in terms of the travel times of the routes.

Barrier coverage problems in wireless camera sensor networks (WCSNs) have drawn the attention by academic community because of their huge potential applications. Various versions of barrier coverage under WCSNs have been studied such as minimal exposure path, strong/weak barrier, 1/k barrier, full view barrier problems. In this paper, based on new (k−ω) coverage model, we study how to achieve (k −ω) barrier coverage problem under uniform random deployment scheme (hereinafter A(k − ω)BC problem). This problem aims to juggle whether any given camera sensor networks is (k − ω) barrier coverage. A camera sensor network is called (k − ω) barrier coverage if any crossing path is (k − ω) coverage. The A(k − ω)BC problem is useful because it can make balance of the number of camera sensors used and the information retrieved by the camera sensors. Furthermore, this problem is vital for design and applications for camera sensor networks when camera sensor nodes were deployed randomly. Thus, we formulate the A(k − ω)BC problem and then proposed an efficient method named Dynamic Partition for solving this problem . An extensive experiments were conducted on random instances, and the results indicated that the proposed algorithm can achieve high quality and stable solutions in real-time execution.

Death domain (DD)-fold assemblies play a crucial role in regulating the signaling to cell survival or death. Here we report the crystal structure of the caspase recruitment domain (CARD)-CARD disk of the human apoptosome. The structure surprisingly reveals that three 1:1 Apaf-1:procaspase-9 CARD protomers form a novel helical DD-fold assembly on the heptameric wheel-like platform of the apoptosome. The small-angle X-ray scattering and multi-angle light scattering data also support that three protomers could form an oligomeric complex similar to the crystal structure. Interestingly, the quasi-equivalent environment of CARDs could generate different quaternary CARD assemblies. We also found that the type II interaction is conserved in all DD-fold complexes, whereas the type I interaction is found only in the helical DD-fold assemblies. This study provides crucial insights into the caspase activation mechanism, which is tightly controlled by a sophisticated and highly evolved CARD assembly on the apoptosome, and also enables better understanding of the intricate DD-fold assembly.

This research is based on the view that technology is the learner's way of life, and starts from the dilemma and problem of technology promoting learning. Using CTCL Research Paradigm that is based on Cognitive and Brain Science, Learning Psychology. and Constructivist Learning Theory, and using Learner-Centered Design based on the four variables of learning content, resource characterization, learning sequence and learning mode, this paper presents an empirical study on the three classes of G, M, and L. From the data analysis and discussion, three conclusions on technology for learning can be summarized. First is about whether the technology can promote learning. Second is about how technology could promote learning and should focus on learning content, learning resources, learning activities, etc. Third is about how the CTCL research paradigm provides an experimental way to focus on learning and provide a full view to technical effectiveness.

In order to obtain the full view image, proposing a fast method of generating full view images based on camera. the method based on multi-camera equipment and the spherical transform of the camera image acquisition using sphere transformation model. the improved SIFT algorithm is used to extract keypoints and match keypoints, and then calculating the transformation matrix based on the keypoints that filtered. finally, according to the projection matrix and transform matrix of each image, the images of subsequent cameras are spliced together. Using this method to generate full view images. the speed is fast and real-time.

Maritime oil exploration and transportation has increased more steeply due to the expansion of the world crude oil and natural gas production. The probability of oilrig pollution, burning, and explosion continues to rise. All these factors stimulate a greater danger for vessels, oil operation safety, and maritime environment. The continuous surveillance of the offshore oil fields and container vessels is essential to secure the production flow, avoid trespassing, and prevent vandalism from intruders and pirates. However, developing a large-scale camera sensor network (CSN) for a maritime surveillance is a challenging problem due to the environment complexity and network connectivity. Maritime wireless mesh networks (MWMNs) are envisaged to provide network connectivity in maritime environment and enable users to access the terrestrial communication networks. The high cost and low data-rate of satellite and other legacy maritime communication technologies and systems deployed in MWMNs pose a major limitation to establishing reliable and affordable maritime communications.

Traditional target coverage only ensures monitoring of targets. However, as people’s security awareness increases, the requirement for target coverage also increases from monitoring to identification. Thus full-view coverage model is proposed to guarantee that any facing direction of a target could be covered. Based on this coverage model, we study the maximum full-view target coverage problem in camera sensor networks, where each camera sensor has P working directions, aiming at maximizing the number of full-view covered targets by scheduling the working directions of camera sensors. To solve this problem, we design a ( 1 − 1 e ) -approximation algorithm based on pipage rounding and an efficient heuristic algorithm. Finally, simulation results are presented to demonstrate the performance of our algorithms.

As an information delivering platform, Twitter collects millions of tweets every day. However, some users, especially new users, often find it difficult to understand trending topics in Twitter when confronting the overwhelming and unorganized tweets. Existing work has attempted to provide a short snippet to explain a topic, but this only provides limited benefits and cannot satisfy the users' expectations. In this paper, we propose a new summarization task, namely sequential summarization, which aims to provide a serial of chronologically ordered short sub-summaries for a trending topic in order to provide a complete story about the development of the topic while retaining the order of information presentation. Different from the traditional summarization task, the numbers of sub-summaries for different topics are not fixed. Two approaches, i.e., stream-based and semantic-based approaches, are developed to detect the important subtopics within a trending topic. Then a short sub-summary is generated for each subtopic. In addition, we propose three new measures to evaluate the position-aware coverage, sequential novelty and sequence correlation of the system-generated summaries. The experimental results based on the proposed evaluation criteria have demonstrated the effectiveness of the proposed approaches.

Traditional data acquisition methods for wireless sensor networks (WSNs) require all sensor nodes to transmit at least once to the sink node to obtain a full view of the network. In this paper we present Disagree, a different data acquisition method to retrieve data in WSNs that works in the opposite way as compared with traditional methods. In Disagree, only nodes that do not satisfy an assertion are required to transmit data back to the sink node in order to obtain a complete view of the network. We show that this behavior is the base of an energy-efficient way to gather all data. An important feature of Disagree is that it saves energy at the sensor level by exploiting data correlation. Rather than requesting explicit data readings from all sensor nodes, Disagree estimates the readings from sensor nodes that did not respond to the assertion. As a result of this policy, Disagree can obtain a view of the sensing field with different levels of resolution involving the transmission of only a subset of the sensor nodes by exploiting spatial data redundancy. We implemented Disagree in NS-2 network simulator and results indicate Disagree can significantly reduce the percentage of nodes replying to queries compared with flat and a cluster head based approaches.

For viewing the complete image sent by the satellite to the earth image mosaicing is must. It integrates the different images sent, in a single frame for the full view of that big image. In this paper, we have mentioned two methods of satellite image mosaicing. These methods are EsiReg using SIFT algorithm and other method using SURF algorithm. There is also a brief comparison of these two methods. We have also proposed an automated method called SIGMA and its advantages over the other two.

The paper mainly focuses on the route design for community patrol by aircraft. On the basis of the surrounding condition, the aircraft will first build a model of the surrounding environment, grid the model next, and rectangle irregular barriers in the model. Based on Boustrophedon, the paper has raised a new strategy for gridding the surrounding environment. Under the new strategy, the overall environment will be divided into few patches. By covering all the patches, we will secure a full view of the surrounding environment. With the contribution of MATLAB, the aircraft has achieved experimental simulation over the whole area, as such, the whole environment has ensured a full coverage.

In this paper, we study full-view coverage in camera sensor networks, by exploiting their limited mobility of orientation rotation. We focus on the fairness based coverage maximization problem, i.e., how to schedule the orientations of the camera sensors to maximize the minimum accumulated full-view coverage time of target points. To solve this problem, we first try to reduce the space dimension of orientation search by dividing the orientation space into a set of discrete regions. We select the minimum number of sensing regions that camera sensors should rotate to in order to ensure the full-view coverage of all target points. Next, we attempt to understand the relationship of full-view coverage among the target points, which are spatially coupled. Based on results in these two steps, we devise an algorithm to solve the problem based on "largest demand first serve" principle. We provide extensive simulations to demonstrate the desired performance of the proposed algorithms.

At present, there is a common usage of adhering temperature recorder like black box to the surface of steel billet in the iron and steel Industry. After the heating process we can get the data and then analyze the heating process and establish a heating model of it. However, it's not easy to upmost the controlling in the practical application, this article use the full view real-time monitoring technology by applying a heat tracking precision instrument to monitor the temperature of the surface of inner steel billet, so we can get billet surface temperature distribution data through real-time online monitor and handle the image of the surface, then send the temperature distribution to the optimized control system and realize optimization control of the furnace temperature.

Barrier coverage is a critical issue in wireless sensor networks for many practical applications, e.g., national border monitoring, security surveillance and intruder detection, etc. Its aim is to detect intruders that attempt to cross the protected region. Available works mainly focused on the barrier coverage of static directional sensors (e.g., cameras), which leads to a waste of redundant camera sensors with limited coverage area and sensing angles. In this paper, we study how to achieve full-view barrier coverage with mobile camera sensors. We first deploy mobile camera sensors to form full-view barrier coverage in a random environment. Then we propose a novel full-view barrier covered model to select mobile camera sensors. Finally, we analyze and optimize the number of camera sensors required for this specific model. Extensive simulation results are provided to illustrate that our proposed solution outperforms others in terms of minimum number of camera sensors.

In order to support advanced remote collaborative works via WAN, sharing various visual contents between remote sites and displaying the existence of remote participants by transmission of high-quality video streaming in real scene is important. However, the display specification of large-scale screen system such as commercial projector and wide-area monitor to display these visual contents is low-resolution, and displaying of real video streaming with sufficient quality is difficult. In this paper, we have constructed tele-immersive environment with tiled display wall to realize dis- playing real video streaming and visual contents by high-resolution. In addition, we have tried the construction of the envi- ronment to display more high-quality video streaming on tiled display wall by transmitting multi-video streaming which captured by two cameras in remote site. By using the environment, we have conducted some experiments on tele-immersive communication on JGN2plus network which is a nationwide scale WAN. From experimental results, we have showed that these video streaming have been displayed wide area of remote site more high-quality than magnified view of video by a single small camera. Moreover, we have tried realistic display processing of ultra resolution astronomi- cal observation image and movie data to display in full view visualization contents with ultra resolution which is difficult to display on a usual PC. As these results, we have enabled to observe the entire image of observation data all over tiled dis- play wall.

PurposeThe purpose of this paper is to compare Google Books with WorldCat and to assess some other functionalities of Google Books.Design/methodology/approachOver 500 random samples generated from WorldCat were searched on Google Books. The search results were used to compare the coverage between Google Books and WorldCat, to estimate the successful link rate to a local library catalogue, the percentage available as full view, snippet, and preview on Google Books, and other services of Google Books.FindingsGoogle Books can retrieve almost all the books catalogued in WorldCat. Its “Find in a library” link to a local library catalogue works 75 percent of the time. Fewer than 10 percent of Google Books items have free full views, and about 15 percent have snippets and previews, respectively. Previews are much more useful than snippets. Google Books probably indexes books that it does not possess in digital form, in addition to indexing all the books that it has acquired in digital form.Originality/valueNo previous empirical studies of this kind have been found. This study assesses Google Books' coverage and services with quantitative measures.

SUMMARY Desert ants, Cataglyphis, use the sky's pattern of polarized light as a compass reference for navigation. However, they do not fully exploit the complexity of this pattern, rather – as proposed previously – they assess their walking direction by means of an approximate solution based on a simplified internal template. Approximate rules are error-prone. We therefore asked whether the ants use additional cues to improve the accuracy of directional decisions, and focused on ‘idiothetic’ cues, i.e. cues based on information from proprioceptors. We trained ants in a channel system that was covered with a polarization filter, providing only a single e-vector direction as a directional ‘celestial’ cue. Then we observed their homebound runs on a test field, allowing full view of the sky. In crucial experiments, the ants were exposed to a cue conflict, in which sky compass and idiothetic information disagreed, by training them in a straight channel that provided a change in e-vector direction. The results indicated that the polarization information completely dominates over idiothetic cues. Two path segments with different e-vector orientations are combined linearly to a summed home vector. Our data provide additional evidence that Cataglyphis uses a simplified internal template to derive directional information from the sky's polarization pattern.

Object permanence tests are a standard procedure to test the cognitive ability to mentally follow a hidden object. To test this capacity in mandrills, we used visible and color-tracking with invisible displacement tests. During visible displacement the object was hidden and moved within its container in full view of the tested individual. During color-tracking with invisible displacement the object was hidden in a colored container, also in full view, but then moved within its container out of view. The tested mandrills were successful in the visible but not in the color-tracking with invisible displacement tests. They did not use the color as a cue for the correct container. One of the animals memorized the position of the container, in which the reward was dropped before the invisible displacement. We assume that the capacity of solving invisible displacement tests has evolved after the evolutionary separation of mandrills and apes.

A panoptic camera allows to acquire a full 360 degree view of a scene by stitching images from a set of cameras [1, 3, 2, 5]. The images from the cameras are acquired at different positions and orientations to form a full view image. Stitching is performed by mixing and transforming the different images according to non-linear mapping equations. There are two kinds of stitching algorithms

Semiconductor devices are scale down to micro meter to Nano meter range; nonvolatile memory technologies are approaching their physical limits. One such device is Memristor. Memristors is having rapid growth during the past some years. Compared with transistor-related memory technology, memristors viewed as potential candidate for future memory devices due to their compact size and less power consumption. This survey will tell about the memristor's operation, functionality, characteristics, types of memristor, fabrication methods of memristor and etc. This will helps to know about the full view of the memristor.

In this paper, we describe the acquisition procedure and contents of a head orientation database, called as AISL head orientation database. The primary goals of creating the AISL head orientation database includes the following: (1) providing a new challenge of the head orientation database that is sufficient to simulate the impact of background changes in real applications; (2) helping the development of the state of the art techniques for estimating head orientation in real applications; and (3) covering multiple races which include Indonesian, Japanese, Latin of American and Netherland people. This database consists of 6,480 images of the full view the head of 20 persons. A turntable system equipped with two Kinect cameras is utilized to simultaneously capture 36 images with interval 10°. Each subject is asked to look straight ahead, up and down to obtain 324 images in three shots and three times of background change. We also discuss the preliminary evaluation based on the AISL database and present the performance of two state-of-the-art appearance-based head pose classification methods to do the following: (1) evaluate the difficulty of the database for classifying or estimating head orientation; (2) preference evaluation results for researchers using the database; and (3) identify the strengths and weaknesses of the commonly used methods.

Food caching birds hide food and recover the caches when supplies are less abundant. There is, however, a risk to this strategy because the caches are susceptible to pilfering by others. Corvids use a number of different strategies to reduce possible cache theft. Scrub-jays with previous experience of pilfering other's caches cached worms in two visuospatially distinct caching trays either in private or in the presence of a conspecific. When these storers had cached in private, they subsequently observed both trays out of reach of a conspecific. When these storers had cached in the presence of a conspecific, they subsequently watched the observer pilfering from one of the trays while the other tray was placed in full view, but out of reach. The storers were then allowed to recover the remaining caches 3 h later. Jays cached more worms when they were observed during caching. At the time of recovery, they re-cached more than if they had cached in private, selectively re-caching outside of the trays in sites unbeknown to potential thieves. In addition, after a single pilfering trial, the jays switched their recovery strategy from predominantly checking their caches (i.e. returning to a cache site to see whether the food remained there) to predominantly eating them. Re-caching remained constant across the three trials. These results suggest that scrub-jays use flexible, cognitive caching and recovery strategies to aid in reducing potential future pilfering of caches by conspecifics.

In Chapter 5, we explained how to use Yammer Open Graph API to bring information stored in different business applications into Yammer and allow users to discover data from other applications and see the full view in a structured manner. This is all good, but it provides only one-way integration—from your business applications to Yammer. What if you want to integrate Yammer data into your business applications and make your applications more social and able to share content? The Yammer REST APIs provide this capability.

Recent advances in smart mobile devices (e.g., smartphones and tablets) encourage researchers to utilize them in collaborative environments as a medium of interaction with large shared interactive wall displays. Such collaborative setups have additional advantages over the previous ones, e.g., users' freedom to move around the environment, full view of the whole screen, etc. In this work, we focus on finding different possible collaborative position patterns for pairs of users working in a collaborative setup, equipped with a shared interactive tiled-wall display and multiple mobile devices. For this, we observed users in a controlled study with 36 participants, who performed the collaborative test in 18 pairs.

Camera sensors can collect visual information from regions of interest (RoI) and provide more information to classify the intruder. In practice, randomly deployed camera sensors can not guarantee that the barrier is full-view covered, and lead to a waste of sensing resources. Our work takes the first attempt to explore the deployment strategy to achieve full-view barrier coverage with rotatable camera sensors. We propose a method to select camera sensors from an existing and arbitrary deployment and determine their orientation to obtain a full-view barrier coverage. Our simulation results demonstrate that our algorithm outperforms existing algorithms for fixed directional camera sensors in saving the number of camera sensors.

The current operating displays of DCS (Distributed Control System) are designed for 2D environments. This limits the full awareness situation of the industrial process, since it is distributed across multiple operator displays and requires the operator to navigate among them. This inspired the idea of creating a single operation DCS display, in a 2.5D/3D environment that allows a full view of the entire manufacturing process. This increases the amount and quality of information that is given to the operator and prevents unnecessary operation navigation between displays.

The full-view coverage ensures that the positive images of targets are obtained. In existing works, the topics only focus on whether a region is full-view covered or not, which needs too many nodes, and is less flexible for the change of surveillance environment. Therefore, full-view coverage for the targets is highlighted in this paper. Firstly, we derive the optimal observation angle between the sensing direction of nodes and the vector of target surface. We also prove that the full-view coverage is a NPC problem. Then the centralized and the distributed algorithms are proposed to maximize the number of full-view covered targets by scheduling the sensing directions of some sensors in the network. Simulation results show that local adjusting of the directional nodes will increase the full-view coverage for the global monitored objects in the condition of random deployment.

This paper presents an efficient and accurate method for creating full view panoramas. A new feature points detection algorithm called Enhanced- FAST is proposed to accurately align images and a graph cuts algorithm is used to merge two adjacent images seamlessly. Based on the FAST algorithm, the Enhanced-FAST algorithm smoothes and extends the sampling area making the feature points detection more insensitive to noise. Our graph cuts algorithm uses image Laplacian to compute the edge weights which can find an optimized seam even under different lighting. Experiments and comparisons show that our method is efficient and robust to image noise and lighting changing

Vision of the Crowds is a paraphrase of the well-known notion Wisdom of the Crowds. In the latter, instead of using an ontology-based, top-down approach, we create knowledge rather bottom-up, relying on the knowledge of the members of a certain community. Well-known applications of this approach are cooperative tagging of photos or filtering spams. In the case of Vision of the Crowds, we do not insist on creating new knowledge; a new, cooperative view may also suffice for many purposes. Take as an example an open-air sport event, which happens on different locations over several hours or days. Many thousands of visitors make audio-visual recordings. Nobody has a full view of the event, but we have a large amount of partial views. The challenge is to provide concepts and tools with the help of which such partial views can be shared and automatically summarized corresponding to different intentions of the viewers. The talk describes a set of ideas and presents some first results of realizing the idea of the Vision of the Crowds. Beside general considerations, two particular applications will be introduced, in the area of medicine (in particular endoscopic videos) and traffic

In the mine, open field or a severe surveillance environment, it is limited to take both full view images of circumstance. The use of computers and data collection card to achieve surveillance task is fairly dangerous and unreliable. To counter such special case, this paper analyzes the optical structure principles of panoramic mosaic. The advantages and disadvantages of phase correlation methodology are also discussed. It also proposes the concept of establishing the surveillance platform. Finally we present the evaluation results, showing that this panoramic mosaic surveillance platform can satisfy the rugged environment.

Adapting for the requirement of personnel cultivation in high vocational institute, so to Cultivate undergraduates' innovative and practical ability, and to train their practical application ability, this paper is annotated deep into three aspects, the necessity of the instructional process optimized, how to optimize the instructional process and the implementation terms for optimizing instructional process. Then it promulgates the nature of teaching reform in E-commerce English instruction and the full view of practical process. It can be provided as the study reference on instructional process for achieving educational objectives by the educators in high vocational institutes.

It is unreliable to take both full view images of a conference room and face images of speakers, in most conference room, lecture hall or auditorium of the teleconference systems. This paper, countered such special surroundings which maintained more audiences and scatted positions, analyzes the principles of mosaic camera and discusses the advantages of phase correlation methodology. Besides, the idea of mosaic teleconference camera is proposed and the implementation of the whole system is presented. Finally, we shows the evaluation results and it can substantiate the requirement.

In this paper, a system for video rendering on multiscopic 3D displays is considered where the data is represented as layered depth video (LDV). This representation consists of one full or central video with associated per-pixel depth and additional residual layers. Thus, only one full view with additional residual data needs to be transmitted. The LDV data is used at the receiver to generate all intermediate views for the display. The paper presents the LDV layer extraction as well as the view synthesis, using a scene reliability-driven approach. Here, unreliable image regions are detected and in contrast to previous approaches the residual data is enlarged to reduce artifacts in unreliable areas during rendering. To provide maximum data coverage, the residual data remains at its original positions and will not be projected towards the central view. The view synthesis process also uses this reliability analysis to provide higher quality intermediate views than previous approaches. As a final result, high quality intermediate views for an existing 9-view auto-stereoscopic display are presented, which prove the suitability of the LDV approach for advanced 3D video (3DV) systems.

Using a retrospective ECG-gating technique, an extremely high frame rate (up to 8 kHz) was previously shown achievable for full-view (12times12 mm2) myocardial elastography in murine left ventricles. The purpose in this paper was to isolate the left ventricle from other structures for better displacement and strain visualization. In-vivo experiments were performed in anesthetized normal and infarcted mice. After manual selection of 40-50 points in the first frame of the cine-loop (corresponding to the R-wave), the myocardial contour was automatically tracked across the entire LV and throughout the full cardiac cycle, which correctly segmented the myocardial region of interest (ROI) for better interpretation. High precision of the displacement estimation, due to high frequency (30 MHz) and high frame rate (up to 8 kHz) available with this system, allowed for automated tracking of a manually-initialized myocardial contour over an entire cardiac cycle. The method of manually- initialized, automated contour tracking can further enhance the capability of the elastographic technique with minimal user intervention.

7.1 Package Specifications and Declarations 7.2 Package Bodies 7.3 Private Types and Private Extensions 7.3.1 Private Operations 7.4 Deferred Constants 7.5 Limited Types 7.6 User-Defined Assignment and Finalization 7.6.1 Completion and Finalization