Optimize adaptive media playout using dynamic fuzzy logic control for video streaming

Multimedia Tools and Applications - Adaptive Media Playout (AMP) controls adapt playout rate to prevent buffer outage and to reduce delay in playout. Most AMP techniques use buffer fullness or its...     

Exercise classification and event segmentation in Hammersmith Infant Neurological Examination videos

Image and video processing techniques are being frequently used in medical science applications. Computer vision-based systems have successfully replaced various manual medical processes such as analyzing physical and biomechanical parameters, physical examination of patients. These systems are gaining popularity because of their robustness and the objectivity they bring to various medical procedures. Hammersmith Infant Neurological Examinations (HINE) is a set of physical tests that are carried out on infants in the age group of 3–24 months with neurological disorders. However, these tests are graded through visual observations, which can be highly subjective. Therefore, computer vision-aided approach can be used to assist the experts in the grading process. In this paper, we present a method of automatic exercise classification through visual analysis of the HINE videos recorded at hospitals. We have used scale-invariant-feature-transform features to generate a bag-of-words from the image frames of the video sequences. Frequency of these visual words is then used to classify the video sequences using HMM. We also present a method of event segmentation in long videos containing more than two exercises. Event segmentation coupled with a classifier can help in automatic indexing of long and continuous video sequences of the HINE set. Our proposed framework is a step forward in the process of automation of HINE tests through computer vision-based methods. We conducted tests on a dataset comprising of 70 HINE video sequences. It has been found that the proposed method can successfully classify exercises with accuracy as high as 84%. The proposed work has direct applications in automatic or semiautomatic analysis of “vertical suspension” and “ventral suspension” tests of HINE. Though some of the critical tests such as “pulled-to-sit,” “lateral tilting,” or “adductor’s angle measurement” have already been addressed using image- and video-guided techniques, scopes are there for further improvement.     

Ag–Sr doped mesoporous bioactive glass nanoparticles loaded chitosan/gelatin coating for orthopedic implants

In this study, we investigated surface and biological properties of Ag–Sr-doped mesoporous bioactive glass nanoparticle (Ag–Sr MBGN) loaded chitosan/gelatin coatings deposited by electrophoretic deposition (EPD) on 316L stainless steel. The EPD parameters, that is, deposition time, applied voltage, and distance between the electrodes was optimized by the Taguchi design of experiment (DoE) approach. Scanning electron microscopy (SEM) images illustrated the spherical morphology of the synthesized Ag–Sr MBGNs with the mean particle size of 160 ± 20 nm. Energy-dispersive X-ray (EDX) spectroscopy results confirmed the presence of Ag and Sr in the synthesized MBGNs. Optimum EPD parameters determined by DoE approach were 5 g/L of Ag–Sr MBGNs, deposition time of 5 min, and applied voltage of 30 V. SEM images confirmed that the coatings were fairly homogenous. Fourier-transform infrared spectroscopy and EDX results confirmed the presence of chitosan, gelatin, and Ag–Sr MBGNs in the coatings. Chitosan/gelatin/Ag–Sr MBGN composite coatings exhibited suitable wettability for the protein attachment and proliferation of osteoblast cells. The composite coatings exhibited suitable adhesion strength with the substrate. The coatings developed HA crystals upon immersion in simulated body fluid. The results of the turbidity test confirmed that the coatings are antibacterial to the Escherichia coli cells.     

SQC and the fluency hypothesis

Students’ Quality Circles (SQCs) are considered in the context of English Language Teaching in Pakistan, with a focus on oral expression. SQCs offer many educational benefits.     

Interaction Between Two Mutually Orthogonal Heat-Generating Baffles in a Square Cavity

Laminar free convection induced by two mutually orthogonal discrete heat-generating baffles in a two-dimensional square cavity is analyzed numerically. The computations were carried out for different locations and combinations of heat source strengths of the baffles for a fixed Grashof number of 10⁶and Prandtl number of 0.71. The coupled governing equations were solved bya finite-difference method using alternating direction implicit technique and successive overrelaxation methods. The obtained results clearly show that the hydrodynamic and thermal fields in the cavity depend on both the location and strength of the heat-generating baffles. Though the flow inhibition is caused by both the baffles, the baffle with higher source strength plays a decisive role in inducing the flow. The locations of baffles with unequal source strengths produce significant changes in the net heat transfer rate. This is further magnified for higher contrast in source strengths. This study provides qualitative suggestions that may improve the thermal design of sealed enclosures, which are encountered frequently in the electronics industry.     

Estimation of Desired Motion Intention and compliance control for upper limb assist exoskeleton

International Journal of Control, Automation and Systems - In this paper, we have addressed two issues for upper limb assist exoskeleton. 1) Estimation of Desired Motion Intention (DMI); 2) Robust...     

Oil palm bunch ripeness classification using fluorescence technique

Oil palm is Malaysia’s major agriculture product and it covers approximately 5 million hectares of Malaysia’s land. Limited land resources have been an important factor that motivated the need to increase oil extraction rate (OER). OER of oil palm fresh fruit bunches (FFB) depends highly on their maturity stage. The ripe oil palm FFB will produce high OER while the under ripe and over ripe oil palm FFB will produce less oil. Thus, this paper presents a method of classification between oil palm FFB into ripe, under-ripe and over-ripe categories. This research was done at an oil palm plantation in peninsular Malaysia. A total of two-hundred and ten oil palm FFB that consist of seventy bunches for each category of under-ripe, ripe and over-ripe had been used. Each bunch was scanned ten times randomly with a hand-held multi-parameter fluorescence sensor called Multiplex®3. The parameter measured was the Blue-to-Red Fluorescence Ratio (BRR_FRF) obtained from blue-green (447 nm) and far-red (685 nm) emission signal by using ultraviolet (UV) light emitting diode as excitation light source. The novel contribution of this research is to prove that the oil palm FFB maturity can be determined using the Blue-to-Red Fluorescence ratio index. This is based to our finding of a significant difference among the three categories of ripeness based on the parameter. Classification and Regression Tree (C&RT) method was proposed in this paper. Hundred-fifty samples were used to develop the model by trained it using C&RT method and the remaining sixty samples for the test component. By using the C&RT method, the results show the best accuracy of overall testing classification is 90%. This research will be useful for future development of non-destructive, automatic and real time oil palm FFB grading system.     

TiO2/Al2O3 membrane reactor equipped with a methanol recovery unit to produce palm oil biodiesel

In this study, the central composite design of the response surface methodology was employed to investigate the effects of reaction temperature, catalyst concentration and cross flow circulation velocity on the production of biodiesel in a TiO₂/Al₂O₃ membrane reactor. High‐quality palm oil biodiesel was produced by combination of alkali transesterification and separation processes in the ceramic membrane reactor. The optimum conditions for the conversion of palm oil to biodiesel in the ceramic membrane reactor were as follows: 70°C reaction temperature, 1.12 wt% catalyst concentration and 0.211 cm s^{? 1} cross flow circulation velocity. The physical and chemical properties of the produced biodiesel were determined and compared with the standard specifications. Copyright © 2010 John Wiley & Sons, Ltd.     

A robust learning based evolutionary approach for thermal-economic optimization of compact heat exchangers

This paper presents a robust, efficient and parameter-setting-free evolutionary approach for the optimal design of compact heat exchangers. A learning automata based particle swarm optimization (LAPSO) is developed for optimization task. Seven design parameters, including discreet and continuous ones, are considered as optimization variables. To make the constraint handling straightforward, a self-adaptive penalty function method is employed. The efficiency and the accuracy of the proposed method are demonstrated through two illustrative examples that include three objectives, namely minimum total annual cost, minimum weight and minimum number of entropy generation units. Numerical results indicate that the presented approach generates the optimum configuration with higher accuracy and a higher success rate when compared with genetic algorithms (GAs) and particle swarm optimization (PSO).