Percutaneous transjejunal biliary intervention: 10-year experience with access via Roux-en-Y loops

Ancylostoma duodenale is still the dominant hookworm species in the Mediterranean area, India, China and Japan. In the present study, biopsied materials were taken from the small intestine of 30 patients infected only with A. duodenale and 12 cross matched controls. The results showed some pathological changes in severely infected cases. However, normal or insignificant changes were seen in the enzymatic activity of the intestinal mucosa.     

An interactive lung field segmentation scheme with automated capability

Feasible clinical application of any automated segmenting methodology demands more than just accuracy. Amendment to the automated delineation is necessary when the algorithm fails, however, integrated solution to such a scenario is largely absent in literature. Hence in this survey we devised an architecture that does both the automated and interactive lung field localizations using a single segmenting engine—random walker algorithm—so that intuitive amendment is only necessary when the automated generated delineation is unsatisfactory. The algorithm proceeds by first extracting 18 intensity profiles running horizontally, each of them equally spacing apart, and in each intensity profile three extreme points denoting the two lungs and the esophagus are determined through profile matching. This done, the algorithm removes profiles that do not intersect with the lung, and the rest of the extreme points are plugged into random walker algorithm to perform segmentation. The achieved accuracy in localization by the above was 0.8875 in terms of overlap measure (the maximum value for this parameter is 1) over 341 images. In the case where unsatisfactory delineation prompts amendment necessary, the user can interactively segment the lung by just a shift on some of the previous-determined points to the desired locations, and random walker algorithm is run again with the amended input. By such a fusion, the benefits of both the automated and interactive segmentation are shared in a single architecture.     

MARVLE: a VLSI chip for data compression using tree-based codes

Describes the architecture and design of a CMOS VLSI chip for data compression and decompression using tree-based codes. The chip, called MARVLE, implements a memory-based architecture for variable length encoding and decoding based on tree-based codes. The architecture is based on an efficient scheme of mapping the tree representing any binary code onto a memory device. A prototype 2-mm CMOS VLSI chip has been designed, verified, and fabricated by the MOSIS facility. The chip has a 512×12 static RAM with an access time of 4 ns and logic circuitry for compression as well as decompression. The chip occupies a silicon area of 6.8 mm×6.9 mm and consists of 49695 transistors. The prototype chip yields a compression rate of 95.2 Mb/s and a decompression rate of 60.6 Mb/s with a clock rate of 83.3 MHz. The VLSI hardware can be used to implement the JPEG baseline compression scheme     

Mobility support for IP over wireless ATM

A wireless ATM system consists of a core network infrastructure that provides mobility support to end terminals and a wireless access link. This article outlines two schemes for supporting mobility of IP terminals in this network. In the first scheme, location management and handoff support is integrated within the ATM signaling and control framework (“mobile ATM”), and mobility is transparently supported at the IP layer by mobile ATM underneath. In the second approach, the IP protocol stack is directly executed on ATM switches (without an intermediate ATM signaling stack) using an IP switching technique called IPSOFACTO (IP Switching Over Fast ATM Cell Transport), and terminal mobility is supported via mobile IP     

Master–Slave Current-Sharing Control of a Parallel DC–DC Converter System Over an RF Communication Interface

Using analog wireless communication, we demonstrate a master-slave load-sharing control of a parallel dc-dc buck converter system, thereby eliminating the need for physical connection to distribute the control signal among the converter modules. The current reference for the slave modules is provided by the master module using radio-frequency (RF) transmission, thereby ensuring even sharing of the load current. The effect of delay due to RF transmission on system stability and performance is analyzed, and regions of operation for a stable as well as satisfactory performance are determined. We experimentally demonstrate a satisfactory performance of the master-slave converter at 20-kHz switching frequency under steady state as well as transient conditions in the presence of a transmission delay. The proposed control concept, which can potentially attain redundancy that is achievable using a droop method, may lead to more robust and reconfigurable control implementation of distributed converters and power systems. It may also be used as a (fault-tolerant) backup for wire-based control of parallel/distributed converters.     

Social‐based reputation‐aware data forwarding for improved multicast delivery in the presence of selfish nodes in DTNs

Delay/disruption tolerant networks (DTNs) are potentially applicable in the challenged scenarios like post‐disaster environments. In such networks, data forwarding generally relies on the mutual cooperation of the nodes. However, in reality, despite the availability of necessary resources for data forwarding, a node could misbehave by dropping messages received from other nodes with whom it has no strong social ties. Such a node is called a socially selfish node, which would cause a poor delivery ratio in the network. In this paper, we aim to address the problem of multicast data forwarding in the presence of such selfish nodes, by means of efficient relay selection in DTNs. First, we define a realistic reputation model, in contrast to existing models, to define the socially selfish/misbehaving nodes in the network. Further, a game‐theoretic analysis is carried out that implies data forwarding cost is also an influential parameter in handling selfishness/misbehavior. Subsequently, the problem is formulated as a constrained optimization problem, which is NP hard. Therefore, a heuristic is proposed by combining the reputation of a node and the cost of message forwarding to appropriately identify relay nodes, thus improve the performance of the multicast message delivery in the network. We utilize a social metric, centrality to minimize the message forwarding cost in terms of the number of relay nodes. Finally, the comparative performance evaluation in ONE simulator with practical scenarios shows the superiority of the proposed scheme over the other prominent schemes.     

Completely automated multiresolution edge snapper--a new technique for an accurate carotid ultrasound IMT measurement: clinical validation and benchmarking on a multi-institutional database

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima-media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale-space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen-intima (LI) and media-adventitia (MA) interfaces for the far (distal) wall and IMT measurement. Our database of 365 B-mode longitudinal carotid images is taken from four different institutions covering different ethnic backgrounds. The ground-truth (GT) database was the average manual segmentation from three clinical experts. The mean distance ± standard deviation of CAMES with respect to GT profiles for LI and MA interfaces were 0.081 ± 0.099 and 0.082 ± 0.197 mm, respectively. The IMT measurement error between CAMES and GT was 0.078 ± 0.112 mm. CAMES was benchmarked against a previously developed automated technique based on an integrated approach using feature-based extraction and classifier (CALEX). Although CAMES underestimated the IMT value, it had shown a strong improvement in segmentation errors against CALEX for LI and MA interfaces by 8% and 42%, respectively. The overall IMT measurement bias for CAMES improved by 36% against CALEX. Finally, this paper demonstrated that the figure-of-merit of CAMES was 95.8% compared with 87.4% for CALEX. The combination of multiresolution CA recognition and far-wall segmentation led to an automated, low-complexity, real-time, and accurate technique for carotid IMT measurement. Validation on a multiethnic/multi-institutional data set demonstrated the robustness of the technique, which can constitute a clinically valid IMT measurement for assistance in atherosclerosis disease management.     

A Mobility-Prediction-Based Relay Deployment Framework for Conserving Power in MANETs

There has been a growing interest in designing mobile systems consisting of special relay nodes whose mobility can be controlled by the underlying network. In this paper, we consider the design of a heterogeneous mobile ad hoc network (MANET) consisting of two kinds of mobile nodes-traditional nodes with limited energy and a few controllable mobile relay nodes with relatively abundant energy resources. We propose a novel relay deployment framework that utilizes mobility prediction and works in tandem with the underlying MANET routing protocol to optimally define the movement of the relay nodes. We present two instances of the relay deployment problem, together with the solutions, to achieve different goals. Instance 1, termed Min-Total, aims to minimize the total energy consumed across all the traditional nodes during data transmission, while instance 2, termed Min-Max, aims to minimize the maximum energy consumed by a traditional node during data transmission. Our solutions also enable the prioritization of individual nodes in the network based on residual energy profiles and contextual significance. We perform an extensive simulation study to understand the trade-offs involved in deploying an increasing fraction of such relay nodes in the network. We also investigate the performance of the proposed framework under different mobility prediction schemes. Results indicate that even when the relay nodes constitute a small fraction of the total nodes in the network, the proposed framework results in significant energy savings. Further, we observed that while both the schemes have their potential advantages, the differences between the two optimization schemes are clearly highlighted in a sparse network.     

Gesture Recognition: A Survey

Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human-computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. Applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail. Existing challenges and future research possibilities are also highlighted