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.     

Petrophysical data prediction from seismic attributes using committee fuzzy inference system

This study presents an intelligent model based on fuzzy systems for making a quantitative formulation between seismic attributes and petrophysical data. The proposed methodology comprises two major steps. Firstly, the petrophysical data, including water saturation (S_w) and porosity, are predicted from seismic attributes using various fuzzy inference systems (FISs), including Sugeno (SFIS), Mamdani (MFIS) and Larsen (LFIS). Secondly, a committee fuzzy inference system (CFIS) is constructed using a hybrid genetic algorithms-pattern search (GA-PS) technique. The inputs of the CFIS model are the outputs and averages of the FIS petrophysical data. The methodology is illustrated using 3D seismic and petrophysical data of 11 wells of an Iranian offshore oil field in the Persian Gulf. The performance of the CFIS model is compared with a probabilistic neural network (PNN). The results show that the CFIS method performed better than neural network, the best individual fuzzy model and a simple averaging method.     

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.     

Isolation, purification and ultrastructure of bacteriophages from natural mosquito breeding places in Egypt

Two bacteriophages were isolated from field collected samples representing two different mosquito breeding places. The phage AB-1 (isolated from Abheit village, Faiyoum Governorate "seepage water") and the phage GA-2 (isolated from El-Gabal El-Asfer Qualyobia Governorate "sewage drain water") were purified. Both bacteriophages were ultrastructurally described with respect to their morphology, dimensions, phases of bacterial attack and lysogeny. No major differences were observed between both isolated phages in relation to specificity, however; they were isolated from two different types of breeding places and two different geographic areas as well. This study may assume a wide host range of the isolated phages and reflect how bacterial insecticides used for mosquito larval control could be inhibited by such bacteriophage.     

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.     

Biochemical Conversion of Microalgae Biomass into Biofuel

Biofuel production via microalgae is a promising and sustainable alternative to replace the typical fossil fuel that is the main contributor to the global warming. However, for a cost‐effective biofuel production, further advanced research is still needed for large‐scale operation. This article is a tutorial review on conversion processes of microalgae into biofuel, with emphasis on biochemical conversion. The following topics are discussed: (i) microalgae biomass and its composition, (ii) thermochemical conversion, (iii) chemical conversion, and (iv) biochemical conversion. In addition, various aspects of anaerobic digestion, digester designs, and effects of operating conditions on the production of methane, bioethanol, and biohydrogen are discussed. The general kinetics of biomass conversion into biofuel is presented. This study suggests, if that biomass contains less than 50 % moisture, then it is recommended to use the direct combustion method; otherwise, biochemical conversion is the most suitable process to biofuel production.     

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.