Cellulose nanoparticles synthesised from potato peel for the development of active packaging film for enhancement of shelf life of raw prawns (Penaeus monodon) during frozen storage

In this study, the cellulose nanoparticles (CNP) isolated from potato peel were used for reinforcement of polyvinyl alcohol (PVA)-based active packaging film. The above film was used to pack the raw prawns (Penaeus monodon) at −20 °C, and the colour change, protein content, TVB-N, TMA and microbial analysis were done at regular interval for prawns stored in CNP-PVA active packaging film. A significant difference was observed in the quality of prawns stored in potato CNP-PVA film compared with prawns packed and stored in polyethylene film. The newly designed active packaging with CNP and fennel seed oil enhanced the shelf life of prawns up to two months for both HOSO (head on shell on) prawn and PD (peeled and deveined) prawn. Hence, the study recommends the potato peel CNP-PVA film with fennel seed oil as better choice to extend the shelf life of the prawns during storage compared with polyethylene packaging.     

A Hybrid Clustering Approach Based Q-Leach in TDMA to Optimize QOS-Parameters

An Orthogonal frequency part multiplexing suffers from a considerable challenge due to a high peak to average power ratio (PAPR). Hence, an effective method such as partial transmits sequence (PTS) can avert this defiance by limit the design of PAPR. Therefore, an improving PAPR reduction performance via a novel approach is proposed by detaching each subblock into two parts furthermore exchanges the first sample with the final selection in each portion of the subblock to generate a new partitioning scheme. Several typical traditional segmentation schemes are used to analyze and apply the presented algorithm, such as adjacent, interleaving, and pseudo-random schemes. Besides, two scenarios are adopted based on simulation software in which the number of subcarriers is set to 128 and 256. Based on the results, a superior PAPR reduction performance is achieved based on the improved segmentation schemes regarding traditional strategies in both systems. Moreover, the enhanced adjusted PTS scheme poses a low computational complexity compared with that of the conventional schemes.

     

Interference aware resource allocation for hybrid hierarchical wireless networks

This paper addresses the problem of interference aware resource allocation for OFDMA based hybrid hierarchical wireless networks. We develop two resource allocation algorithms considering the impact of wireless interference constraints using a weighted SINR conflict graph to quantify the interference among the various nodes: (1) interference aware routing using maximum concurrent flow optimization; and (2) rate adaptive joint subcarrier and power allocation algorithm under interference and QoS constraints. We exploit spatial reuse to allocate subcarriers in the network and show that an intelligent reuse of resources can improve throughput while mitigating interference. We provide a sub-optimal heuristic to solve the rate adaptive resource allocation problem. We demonstrate that aggressive spatial reuse and fine tuned-interference modeling garner advantages in terms of throughput, end-to-end delay and power distribution.     

A software architecture framework for on-line option pricing

The problem of growing computational complexity in the finance industry demands manageable, high-speed and real-time solutions in solving complex mathematical problems such as option pricing. In current option trading scenarios, determining a fair price for options “any time” and “anywhere” has become vital yet difficult computational problem. In this study, we have designed, implemented, and deployed an architecture for pricing options on-line using a hand-held device that is J2ME-based Mobile computing-enabled and is assisted by web mining tools. In our architecture, the client is a MIDP user interface, and the back end servlet runs on a standalone server bound to a known port address. In addition, the server uses table-mining techniques to mine real-time data from reliable web sources upon the mobile trader’s directive. The server performs all computations required for pricing options since mobile devices have limited battery power, low bandwidth, and low memory. We have parallelized and implemented various computational techniques such as binomial lattice and finite differencing. To the best of our knowledge, this is one of the first studies that facilitate the mobile-enabled-trader to compute the price of an option in ubiquitous fashion. This architecture aims at providing the trader with various computational techniques to avail (to provide results from approximate to accurate results) while on-the-go and to make important and effective trading decisions using the results that will ensure higher returns on investments in options.

Optimization of PbS thin films using different metal ion sources for photovoltaic applications

An extensive study on the influence of metal ion sources on the properties of chemical bath deposited lead sulphide thin films is reported in this paper. Four different lead sources namely lead nitrate, lead acetate, lead chloride and lead sulphate in alkaline medium have been used for the synthesis along with thiourea as sulphur source. The influence of lead sources on structural, surface morphological optical and electrical properties is investigated for photovoltaic applications. According to X-ray diffraction studies, all the films are poly crystalline with face centered cubic structure. The average crystallite sizes are found to be in the range 13–24 nm. The SEM photographs showed diverse morphology. The optical band gap is found to be very sensitive to the metal sources used. The direct band gap energy values obtained are in the range of 1.862–2.609 eV. The electrical conductivity varies in the range 33.6 ?7.62 × 10^?9 (Ω cm)^?1. Photosensitivity is closely linked to surface morphology. In this work, we established that the cationic precursor sources have significant role in physical properties of as-deposited PbS thin films. Samples prepared using nitrate as metal source are found to be most suitable to be used as solar control coating and the samples with lead acetate can be used as absorber layers for solar cell fabrication.     

Finding a Path Subject to Many Additive QoS Constraints

A fundamental problem in quality-of-service (QoS) routing is to find a path between a source-destination node pair that satisfies two or more end-to-end QoS constraints. We model this problem using a graph with n vertices and m edges with K additive QoS parameters associated with each edge, for any constant Kges2. This problem is known to be NP-hard. Fully polynomial time approximation schemes (FPTAS) for the case of K=2 have been reported in the literature. We concentrate on the general case and make the following contributions. 1) We present a very simple (Km+nlogn) time K-approximation algorithm that can be used in hop-by-hop routing protocols. 2) We present an FPTAS for one optimization version of the QoS routing problem with a time complexity of O(m(n/epsi)^K-1). 3) We present an FPTAS for another optimization version of the QoS routing problem with a time complexity of O(nlogn+m(H/epsi)^K-1) when there exists an H-hop path satisfying all QoS constraints. When K is reduced to 2, our results compare favorably with existing algorithms. The results of this paper hold for both directed and undirected graphs. For ease of presentation, undirected graph is used     

Enhancing performance of failure-prone clusters by adaptive provisioning of cloud resources

In this paper, we investigate Cloud computing resource provisioning to extend the computing capacity of local clusters in the presence of failures. We consider three steps in the resource provisioning including resource brokering, dispatch sequences, and scheduling. The proposed brokering strategy is based on the stochastic analysis of routing in distributed parallel queues and takes into account the response time of the Cloud provider and the local cluster while considering computing cost of both sides. Moreover, we propose dispatching with probabilistic and deterministic sequences to redirect requests to the resource providers. We also incorporate checkpointing in some well-known scheduling algorithms to provide a fault-tolerant environment. We propose two cost-aware and failure-aware provisioning policies that can be utilized by an organization that operates a cluster managed by virtual machine technology, and seeks to use resources from a public Cloud provider. Simulation results demonstrate that the proposed policies improve the response time of users’ requests by a factor of 4.10 under a moderate load with a limited cost on a public Cloud.     

Pathological brain detection in MRI scanning via Hu moment invariants and machine learning

Abstract

Background: We proposed a new automatic and rapid computer-aided diagnosis system to detect pathological brain images obtained in the scans of magnetic resonance imaging (MRI). Methods: For simplification, we transformed the problem to a binary classification task (pathological or normal). It consisted of two steps: first, Hu moment invariants (HMI) were extracted from a specific MR brain image; then, seven HMI features were fed into two classifiers: twin support vector machine (TSVM) and generalised eigenvalue proximal SVM (GEPSVM). Results: Then, a 5 × 5-fold cross validation on a data set containing 90 MR brain images, demonstrated that the proposed methods “HMI + GEPSVM” and “HMI + TSVM” achieved classification accuracy of 98.89%, higher than eight state-of-the-art methods: “DWT + PCA + BP-NN”, “DWT + PCA + RBF-NN”, “DWT + PCA + PSO-KSVM”, “WE + BP-NN”, “WE + KSVM”, “DWT + PCA + GA-KSVM”, “WE + PSO-KSVM” and “WE + BBO-KSVM”. Conclusion: The proposed methods are superior to other methods on pathological brain detection (p < 0.05).     

Violence detection in videos for an intelligent surveillance system using MoBSIFT and movement filtering algorithm

Pattern Analysis and Applications - Action recognition is an active research area in computer vision as it has enormous applications in today’s world, out of which, recognizing violent action...