Multimodal fusion for multimedia analysis: a survey

This survey aims at providing multimedia researchers with a state-of-the-art overview of fusion strategies, which are used for combining multiple modalities in order to accomplish various multimedia analysis tasks. The existing literature on multimodal fusion research is presented through several classifications based on the fusion methodology and the level of fusion (feature, decision, and hybrid). The fusion methods are described from the perspective of the basic concept, advantages, weaknesses, and their usage in various analysis tasks as reported in the literature. Moreover, several distinctive issues that influence a multimodal fusion process such as, the use of correlation and independence, confidence level, contextual information, synchronization between different modalities, and the optimal modality selection are also highlighted. Finally, we present the open issues for further research in the area of multimodal fusion.     

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.     

AR-based serious game framework for post-stroke rehabilitation

Stroke is considered one of the main causes of death around the world. Survivors often suffer different kinds of disabilities in terms of their cognitive and motor capabilities, and are therefore unable to perform their day-to-day activities. To regain some of their cognitive as well as motor abilities, they require rehabilitation. To this end, we present a serious game framework based on augmented reality technology that may motivate the patients’ involvement in the rehabilitation exercise. Additionally, we analyze the requirements for such a framework and describe the concept and implementation of the proposed approach. Furthermore, we designed a wireless vibrotactile output device that is attached to a tangible object. The tangible object that is connected to the framework can give haptic as well as audio-visual feedback to the patient in a more motivating and entertaining environment for rehabilitation exercises. The suitability and utility of the proposed framework was evaluated with real stroke patients and compared against the performance of a healthy control group, thus facilitating occupational therapists in assessing a patient’s progress. Our evaluations show that the serious games with vibrotactile feedback are well accepted by patients.     

A flexible edge matching technique for object detection in dynamic environment

Considering the robustness, stability and reduced volume of data, researchers have focused on using edge information in various video processing applications including moving object detection, tracking and target recognition. Though the edge information is more robust compared to intensity, it also exhibits variations in different frames due to illumination change and noise. In addition to this, the amount of variation varies from edge to edge. Thus, without making use of this variability information, it is difficult to obtain an optimal performance during edge matching. However, traditional edge pixel-based methods do not keep structural information of edges and thus they are not suitable to extract and hold this variability information. To achieve this, we represent edges as segments that make use of the structural and relational information of edges to allow extraction of this variability information. During edge matching, existing algorithms do not handle the size, positional and rotational variations to deal with edges of arbitrary shapes. In this paper, we propose a knowledge-based flexible edge matching algorithm where knowledge is obtained from the statistics on the environmental dynamics, and flexibility is to deal with the arbitrary shape and the geometric variations of edges by making use of this knowledge. In this paper, we detailed the effectiveness of the proposed matching algorithm in moving object detection and also indicated its suitability in other applications like target detection and tracking.     

Effect of multipath fading and multiple access interference on broadband code division multiple access systems

In this paper, the performance of uncoded uplink transmissions in a broadband code division multiple access (CDMA) system using tapped delay line (TDL) antenna array under multipath conditions is investigated. An expression for broadband CDMA system is derived to calculate the optimal weights of TDL antenna array. Using the derived broadband expression, the performance of TDL antenna array is investigated and compared with that of the already existing narrowband systems. Simulation results show that TDL antenna array can reduce multipath fading and multiple access interference (MAI). It is shown that if the signal‐to‐noise ratio (SNR) level is maintained at 20 dB and two‐ray channel model is used, two antennas with four taps each can support 30 users with a BER of 10^?3. If three‐ray channel model is used, the same antenna arrangement is not enough to support 30 users. To support these 30 users with BER of 10^?3, the number of taps needs to be increased to eight. Finally, the number of taps needs to be further increased to 16 if four‐ray channel model is used. Not only that, the SNR should also be increased to 25 dB to achieve the same BER. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of gamma irradiation on structural,morphological and optical properties of thermal spray pyrolysis deposited CuO thin film

This study reports the influences of gamma irradiation (GI) in the range of 20–100 kGy on CuO thin films via thermal spray pyrolysis technique on the glass substrates. The results demonstrate significant influences of GI on the crystallographic, microstructural and optical characteristics of CuO thin films. The obtained XRD results showed that the crystallinity of the films deteriorates by gradually decreasing crystallite size (from 59.13 to 46 nm) as applied gamma doses increases. However, the basic monoclinic crystal structure remains same. The dislocation density and lattice strain increased with the rise of GI absorbed dose due to the creation of defects. The values of number of crystallites per unit surface area increased as dose increased indicating the abundance of crystallization of nano CuO thin films. A UV–Vis–NIR spectrophotometer was utilized to determine the optical properties and obtained results indicated that the optical energy band gap (OBG) energies reduced from 2.00 to 1.72 eV as the doses increased from 0 to 100 kGy. No distinctions of the monoclinic phase of virgin CuO thin film have been perceived under applied absorbed doses, notwithstanding the slight deterioration of the crystallinity and narrowing the OBG.     

Radiation crosslinked polyvinyl alcohol/polyvinyl pyrrolidone/acrylic acid hydrogels: swelling,crosslinking and dye adsorption study

Iranian Polymer Journal - Hydrogels were produced from mixtures of polyvinyl alcohol (PVA), polyvinyl pyrrolidone (PVP), and acrylic acid (AAc) using γ-radiation at doses of 3, 7, and...     

System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm

In reservoir system operation, optimization is very much essential and the compatibility of different optimization techniques is essential to be checked by some performance checking indices. In this study, various types of performance-measuring index are used and compared to provide a complete knowledge on adopting different approaches. Here, the considered performance-measuring indicators will check the operation policy in terms of three different scenarios—how the method is efficient in achieving best results (reliability); how vulnerable the method is for different critical situation (vulnerability); and how capable it is to handle a failure of the model (resiliency). Therefore, the study proposed the artificial bee colony (ABC) optimization technique to develop an optimal water release policy for the well-known Aswan High Dam, Egypt. Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. A release curve is developed for every month as a guidance to the decision maker. Simulation has been done for each method using historical actual inflow data, and reliability, resiliency and vulnerability are measured. All model indicators proved that the release policy provided by ABC optimization outperforms in terms of achieving minimum water deficit, less waste of water and handling critical situations.