Variations in fat content and lipid class composition in ten different mango varieties

The kernels of 10 different mango varieties were extracted. The physico-chemical characteristics and lipid class composition of fats were studied. The fat content of mango kernels grown under the soil and climatic conditions of Bangladesh varied from 7.1% to 10%, depending on the variety. The total lipid extracts were fractionated into lipid classes by a combination of column and thin layer chromatography (TLC). The hydrocarbon and sterol esters varied from 0.3% to 0.7%, triglycerides from 55.6% to 91.5%, partial glycerides from 2.3% to 4% and free sterol from 0.3% to 0.6%. Free fatty acids amounted to 3.0–37% as oleic; glycolipids were 0.6–1.2% and phospholipids 0.11–0.8%. The fatty acid composition of triglyceride (TG) fractions was analyzed by gas liquid chromatography (GLC). Palmitic acid varied from 7.9 molar % to 10.0 molar %, stearic from 38.2% to 40.2%, oleic from 41.1% to 43.8%, linoleic from 6.0% to 7.6%, linolenic from 0.6% to 1.0% and arachidic acid from 1.7% to 2.6%. TLC revealed the presence of lyso-phosphatidylcholine, phosphatidylcholine, phosphatidylinositol, phosphatidylethanolamine and phosphatidic acid in the phospholipid fraction.     

Multimedia framework to support eHealth applications

Limited bandwidth resources lead to a number of challenges especially for eHealth applications, which are communicated over IP and wireless networks. These multimedia services include high-resolution videos and have very large file sizes that require a high level of compression to overcome this limitation. Therefore, there is an acute demand for the research community to provide an efficient multimedia framework to encode medical videos with high quality specifically under the conditions of an error-prone environment. Both an affordable delivery framework and effective coding techniques are extremely desirable for the delivery of high-quality eHealth video applications for transmission over heterogeneous networks and devices. In this paper, we propose and demonstrate a multimedia framework to support eHealth applications, which has an improved coding scheme that uses an SVC-scalable extension of MPEC-4 AVC/H.264. Simulation results show that the proposed scheme achieves a significant improvement in terms of the PSNR-Y gain and reduces the picture quality degradation caused by artifacts and distortions, compared to the existing scheme.     

H ∞ filtering for singular bilinear systems with application to a single-link flexible-joint robot

In this paper, we consider the H _∞ filters design for singular bilinear systems. The approach is based on the parameterized solution of a set of constrained Sylvester equations. The exponential convergence and l ₂ gain attenuation problems are solved by using the bounded real lemma, which leads to linear matrix inequalities (LMI) formulation. Finally, a detailed design procedure is given for the estimation of the states of a flexible joint robot, which demonstrates the effectiveness of the proposed method.     

Exploiting Ontology for Software License Agreements

Software end-users need to sign licenses to seal an agreement with the product providers. Habitually, users agree with the license (i.e. terms and conditions) without fully understanding the agreement. To address this issue, an ontological model is developed to formulate the user requirements and license agreements formally. This paper, introduces ontological model that includes the abstract license ontology of common features found in di?erent license agreements. The abstract license ontology is then extended to a few real world license agreements. The resulting model can be used for di?erent purposes such as querying the appropriate licenses for a speciˉc requirement or checking the license terms and conditions with user requirements.     

Profile based routing in vehicular ad-hoc networks

One of the main problems in the VANET(vehicular ad-hoc network)routing algorithms is how to establish the stable routes.The link duration in these networks is often very short because of the frequent changes in the network topology.Short link duration reduce the network efficiency.Different speeds of the vehicles and choosing different directions by the vehicles in the junctions are the two reasons that lead to link breakage and a reduction in link duration.Several routing protocols have been proposed for VANET in order to improve the link duration,while none of them avoids the link breakages caused by the second reason.In this paper,a new method for routing algorithms is proposed based on the vehicles trips history.Here,each vehicle has a profile containing its movement patterns extracted from its trips history.The next direction which each vehicle may choose at the next junction is predicted using this profile and is sent to other vehicles.Afterward each vehicle selects a node the future direction of which is the same as its predicted direction.Our case study indicates that applying our proposed method to ROMSGP(receive on most stable group-path)routing protocol reduces the links breakages and increases the link duration time.     

Indoor positioning: “an image-based crowdsource machine learning approach”

Multimedia Tools and Applications - Various technologies have been utilized today for recognizing client or user in the indoor areas. These technologies incorporate RSSI, Bluetooth Low Energy...     

Synchronization of Fractional Order Neutral Type Fuzzy Cellular Neural Networks with Discrete and Distributed Delays via State Feedback Control

Neural Processing Letters - The motivation behind this paper is to explore the issue of synchronization of fractional order neutral type fuzzy cellular neural networks with state feedback control....     

Video compression using frame redundancy elimination and discrete cosine transform coefficient reduction

The need of human beings for better social media applications has increased tremendously. This increase has necessitated the need for a digital system with a larger storage capacity and more processing power. However, an increase in multimedia content size reduces the overall processing performance. This occurs because the process of storing and retrieving large files affects the execution time. Therefore, it is extremely important to reduce the multimedia content size. This reduction can be achieved by image and video compression. There are two types of image or video compression: lossy and lossless. In the latter compression, the decompressed image is an exact copy of the original image, while in the former compression, the original and the decompressed image differ from each other. Lossless compression is needed when every pixel matters. This can be found in autoimage processing applications. On the other hand, lossy compression is used in applications that are based on human visual system perception. In these applications, not every single pixel is important; rather, the overall image quality is important. Many video compression algorithms have been proposed. However, the balance between compression rate and video quality still needs further investigation. The algorithm developed in this research focuses on this balance. The proposed algorithm exhibits diversity of compression stages used for each type of information such as elimination of redundant and semi redundant frames, elimination by manipulating consecutive XORed frames, reducing the discrete cosine transform coefficients based on the wanted accuracy and compression ratio. Neural network is used to further reduce the frame size. The proposed method is a lossy compression type, but it can reach the near-lossless type in terms of image quality and compression ratio with comparable execution time.

     

Enhanced halftone-based secure and improved visual cryptography scheme for colour/binary Images

Visual Cryptography (VC) is gaining attraction during the past few years to secure the visual information in the transmission network. It enables the visual data i.e. handwritten notes, photos, printed text, etc. to encrypt in such a way that their decryption can be done through the human visual framework. Hence, no computational assistance is required for the decryption of the secret images they can be seen through naked eye. In this paper, a novel enhanced halftoning-based VC scheme is proposed that works for both binary and color images. Fake share is generated by the combination of random black and white pixels. The proposed algorithm consists of 3 stages i.e., detection, encryption, and decryption. Halftoning, Encryption, (2, 2) visual cryptography and the novel idea of fake share, make it even more secure and improved. As a result, it facilitates the original restored image to the authentic user, however, the one who enters the wrong password gets the combination of fake share with any real share. Both colored and black images can be processed with minimal capacity using the proposed scheme.