QoS-aware service composition for distributed video surveillance

Quality of Service (QoS) is essential for the ubiquitous access of media services in real-time distributed video surveillance applications. To have ubiquitous access of desired media with emergency officials’ handheld devices, appropriate media transcoding services are required. Currently, it is challenging to select and compose these services for each of the devices to satisfy the desired QoS demand. To compose these media services so that video stream is available for target pervasive and smart devices, a composition algorithm is required. Thus, this paper presents a QoS-aware service composition algorithm to select the best composition for the target ubiquitous client so that it can optimally provide QoS to heterogeneous users. We have implemented a video surveillance prototype to demonstrate the performance of the proposed QoS-aware composition algorithm. Results from this prototype reveal that the approach is suitable for real-time video surveillance.     

A multi-agent system model of a diesel engine using rule induction

The proliferation of a multi-agent system (MAS) and ideas from Artificial Intelligence (AI)/distributed AI have changed the way systems, in general are controlled, and operation of a system (diesel engine) in particular is automated. In this paper a distributed multi-agent architecture for a diesel engine and the knowledge sources that handle electricity generation is developed. Electronic devices and components used for data handling are described. The sensed data are presented in fuzzy logic and calculated in entropy values and depicted in a decision hierarchy. A comparative performance assessment of the proposed multi-agent based system with an existing system is presented and discussed.     

How to “alternatize” a clustering algorithm

Given a clustering algorithm, how can we adapt it to find multiple, nonredundant, high-quality clusterings? We focus on algorithms based on vector quantization and describe a framework for automatic ‘alternatization’ of such algorithms. Our framework works in both simultaneous and sequential learning formulations and can mine an arbitrary number of alternative clusterings. We demonstrate its applicability to various clustering algorithms—k-means, spectral clustering, constrained clustering, and co-clustering—and effectiveness in mining a variety of datasets.     

Intelligent facial emotion recognition and semantic-based topic detection for a humanoid robot

Automatic perception of human affective behaviour from facial expressions and recognition of intentions and social goals from dialogue contexts would greatly enhance natural human robot interaction. This research concentrates on intelligent neural network based facial emotion recognition and Latent Semantic Analysis based topic detection for a humanoid robot. The work has first of all incorporated Facial Action Coding System describing physical cues and anatomical knowledge of facial behaviour for the detection of neutral and six basic emotions from real-time posed facial expressions. Feedforward neural networks (NN) are used to respectively implement both upper and lower facial Action Units (AU) analysers to recognise six upper and 11 lower facial actions including Inner and Outer Brow Raiser, Lid Tightener, Lip Corner Puller, Upper Lip Raiser, Nose Wrinkler, Mouth Stretch etc. An artificial neural network based facial emotion recogniser is subsequently used to accept the derived 17 Action Units as inputs to decode neutral and six basic emotions from facial expressions. Moreover, in order to advise the robot to make appropriate responses based on the detected affective facial behaviours, Latent Semantic Analysis is used to focus on underlying semantic structures of the data and go beyond linguistic restrictions to identify topics embedded in the users’ conversations. The overall development is integrated with a modern humanoid robot platform under its Linux C++ SDKs. The work presented here shows great potential in developing personalised intelligent agents/robots with emotion and social intelligence.     

GaInAsP-InP distributed feedback waveguides for all-opticalswitching

All-optical switching characteristics of waveguide devices having a nonlinear distributed feedback structure are reported theoretically and experimentally. These devices were composed of a strip-loaded GaInAsP-InP waveguide and a Bragg reflector, which were suitable for optical integrated circuit. In the experiments, all-optical and gate operation and set-reset operation for two output ports were successfully demonstrated     

Validation of caregiver interviews to diagnose common causes of severe neonatal illness

The objective of this study was to validate retrospective caregiver interviews for diagnosing major causes of severe neonatal illness and death. A convenience sample of 149 infants aged < 28 days with one or more suspected diagnoses of interest (low birthweight/severe malnutrition, preterm birth, birth asphyxia, birth trauma, neonatal tetanus, pneumonia, meningitis, septicaemia, diarrhoea, congenital malformation or injury) was taken from patients admitted to two hospitals in Dhaka, Bangladesh. Study paediatricians performed a standardised history and physical examination and ordered laboratory and radiographic tests according to study criteria. With a median interval of 64.5 days after death or hospital discharge, caregivers of 118 (79%) infants were interviewed about their child's illness. Using reference diagnoses based on predefined clinical and laboratory criteria, the sensitivity and specificity of particular combinations of signs (algorithms) reported by the caregivers were ascertained. Sufficient numbers of children with five reference standard diagnoses were studied to validate caregiver reports. Algorithms with sensitivity and specificity > 80% were identified for neonatal tetanus, low birthweight/severe malnutrition and preterm delivery. Algorithms with specificities > 80% for birth asphyxia and pneumonia had sensitivities < 70%, or alternatively had high sensitivity with lower specificity. In settings with limited access to medical care, retrospective caregiver interviews provide a valid means of diagnosing several of the most common causes of severe neonatal illness and death.     

A LAN emulation model for wireless ATM

An architecture based on emulated LAN is proposed which can efficiently provide the required bandwidth of mobiles as they migrate between cells. The proposed solution (1) ensures the required bandwidth of a mobile when its path changes because of handoff, (2) efficiently reserves bandwidth resulting in higher bandwidth/network utilization, (3) has the flexibility of reserving bandwidth depending upon the mobility (rate of handoff). Copyright © 2001 John Wiley & Sons, Ltd.     

Contouring of Diffused Objects by Using Lensless Fourier Transform Digital Holography and Dual‐Index Immersion Method

Abstract: A simple method for contouring of diffused objects by using lensless Fourier transform digital holography and dual‐index immersion method is presented. It is noticed that to get more accurate results speckle noise should be eliminated/reduced from the reconstructed phase map from digital holograms. Speckle noise is handled by 5 × 5 median filtering. Depth contour interval up to a maximum of 0.12 mm could be achieved without making the interference phase fringes overcrowded.     

Probabilistic Models of Damaging Deflections for Floor Elements

In this paper a number of serviceability issues related mainly to excessive deflections of structural floor elements (beams and slabs) are discussed. Field data of serviceability damage caused by excessive deflections of structural floor elements have been collected from various sources and probabilistic models are developed. Current serviceability specifications for allowable deflection limits in Australian, U.S., and other concrete structure codes have been compared against these probabilistic distributions of damaging deflections. Preliminary results confirm that allowable deflection limits in these design codes represent realistic lower-bound values of damaging deflections.     

Chitosan and marine phospholipids reduce matrix metalloproteinase activity in myeloma SP2 tumor‐bearing mice

An animal experiment was conducted to assess the antitumor effects of chitosan‐coated liposomes on myeloma SP2. The animal experimental groups designed for myeloma SP2 tumor‐bearing BALB/c mice were provided with five different drinks: (I) control (double‐distilled water); (II) squid phospholipid liposomes alone 1.0 mg/mL; (III) chitosan alone 5.0 mg/mL; (IV) squid phospholipid liposomes 1.0 mg/mL with chitosan 5.0 mg/mL in the form of a simple mixture; and (V) squid phospholipid liposomes 1.0 mg/mL coated with chitosan 5.0 mg/mL. At 20 days after implantation of the myeloma SP2 cells into mice, oral administration of the experimental drinks was provided for 35 days. There was significant suppression of tumor growth when chitosan and squid phospholipids were administered simultaneously in a simple mixture or as chitosan‐coated liposomes. Matrix metalloproteinase (MMP)‐2 and MMP‐9 activity was significantly less in the serum of mice that consumed chitosan‐coated liposomes than in control mice. We found that decreased tumor burden was related to MMP secretion. Therefore, chitosan‐coated marine phospholipid liposomes might be useful as potential agents for the treatment of myeloma SP2.