Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

In recent times, the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security features. The IoT has shown wide adoption in various applications including smart cities, healthcare, trade, business, etc. Among these applications, fitness applications have been widely considered for smart fitness systems. The users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness facilities. Thus, scheduling such a huge number of requests for fitness exercise is a big challenge. Secondly, the user fitness data is critical thus securing the user fitness data from unauthorized access is also challenging. To overcome these issues, this work proposed a blockchain-based load-balanced task scheduling approach. A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling approaches. The proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’ requests and improve resource utilization. The performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection ratio. The obtained results confirm the efficiency of the proposed scheduling approach. For investigating the performance of the blockchain, various experiments are performed using the Hyperledger Caliper concerning latency, throughput, resource utilization. The Solo approach has shown an improvement of 32% and 26% in throughput as compared to Raft and Solo-Raft approaches respectively. The obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.     

Convolutional Neural Network Based Intelligent Handwritten Document Recognition

This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users. This technology is also helpful for the automatic data entry system. In the proposed system prepared a dataset of English language handwritten character images. The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents. In this research, multiple experiments get very worthy recognition results. The proposed system will first perform image pre-processing stages to prepare data for training using a convolutional neural network. After this processing, the input document is segmented using line, word and character segmentation. The proposed system get the accuracy during the character segmentation up to 86%. Then these segmented characters are sent to a convolutional neural network for their recognition. The recognition and segmentation technique proposed in this paper is providing the most acceptable accurate results on a given dataset. The proposed work approaches to the accuracy of the result during convolutional neural network training up to 93%, and for validation that accuracy slightly decreases with 90.42%.     

Co-delivery of gemcitabine and simvastatin through PLGA polymeric nanoparticles for the treatment of pancreatic cancer: in-vitro characterization,cellular uptake,and pharmacokinetic studies

Despite the ongoing extensive research, cancer therapeutics still remains an area with unmet needs which is hampered by shortfall in the development of newer medicines. The present study discusses a nano-based combinational approach for treating solid tumor. Dual-loaded nanoparticles encapsulating gemcitabine HCl (GM) and simvastatin (SV) were fabricated by double emulsion solvent evaporation method and optimized. Optimized nanoparticles showed a particle size of 258?±?2.4?nm, polydispersity index of 0.32?±?0.052, and zeta potential of ?12.5?mV. The size and the morphology of the particles wee further confirmed by transmission electron microscopy (TEM) and scanning electron microscopy, respectively of the particles. The entrapment efficiency of GM and SV in the nanoparticles was 38.5?±?4.5% and 72.2?±?5.6%, respectively. The in vitro release profile was studied for 60?h and showed Higuchi release pattern. The cell toxicity was done using MTT assay and lower IC₅₀ was obtained with the nanoparticles as compared to the pure drug. The bioavailability of GM and SV in PLGA nanoparticles was enhanced by 1.4-fold and 1.3-fold respectively, compared to drug solution. The results revealed that co-delivery of GM and SV could be used for its oral delivery for the effective treatment of pancreatic cancer.     

Citation burst prediction in a bibliometric network

Scientometrics - In the field of computer science, both journal and conference publications are considered valuable. The popularity of an author is mostly determined by the paper’s high...     

Fabrication of coplanar microheater platform for LPG sensing applications

Microsystem Technologies - The design and fabrication of nichrome based coplanar microheater for LPG sensing applications is presented in this work. Nichrome based coplanar microheater is...     

Enhancing Emergency Messages Dissemination in Vehicular Networks Using Network Coding

Vehicular ad-hoc networks play an important role in providing safety on the road. Vehicles generate and exchange emergency and control messages to avoid dangerous situations. According to IEEE 1609.4 standard, all these messages share the same control channel interval even if the emergency messages are with a highest priority. Besides that, network’s characteristics, such as vehicle density and high mobility, would make the diffusion of emergency messages a challenging task. Especially with the absence of acknowledgements and retransmission. Network coding could be seen as a solution where a block of data packets could be sent on the same transmission process. Firstly, we analyze the messages’ dissemination, and we propose a thoroughly model for success probability according to the emergency messages’ generation probabilities. Further, we propose a new network coding access scheme. The emergency messages take the priority in the channel access and it could be retransmitted several times. Thus, the scheme deals with the emergency messages’ loss and latency. NS-3 simulations show that our model increases emergency messages’ reliability.

     

A robust video watermarking based on feature regions and crowdsourcing

Multimedia Tools and Applications - Video watermarking technique aims at resolving insecurity problems. Recently, many approaches have been proposed in order to satisfy the new constraints of video...     

A temporal modal defeasible logic for formalizing social commitments in dialogue and argumentation models

In this paper, we extend a temporal defeasible logic with a modal operator Committed to formalize commitments that agents undertake as a consequence of communicative actions (speech acts) during dialogues. We represent commitments as modal sentences. The defeasible dual of the modal operator Committed is a modal operator called Exempted. The logical setting makes the social-commitment based semantics of speech acts verifiable and practical; it is possible to detect if, and when, a commitment is violated and/or complied with. One of the main advantages of the proposed system is that it allows for capturing the nonmonotonic behavior of the commitments induced by the relevant speech acts.     

Synthesis of poly(acrylonitrile‐co‐divinylbenzene‐co‐vinylbenzyl chloride)‐derived hypercrosslinked polymer microspheres and a preliminary evaluation of their potential for the solid‐phase capture of pharmaceuticals

Poly[acrylonitrile (AN)‐co‐divinylbenzene (DVB)‐co‐vinylbenzyl chloride (VBC)] terpolymers were synthesized by precipitation polymerization in the form of porous polymer microspheres. The poly(AN‐co‐DVB‐co‐VBC) polymers were then hypercrosslinked, via a Friedel‐Crafts reaction with FeCl₃ in nitrobenzene, to provide a significant uplift in the specific surface areas of the polymers. FTIR spectra of the hypercrosslinked poly(AN‐co‐DVB‐co‐VBC)s showed that the chloromethyl groups derived from VBC were consumed by the Friedel‐Crafts reactions, which was consistent with successful hypercrosslinking. Hypercrosslinking installed a number of new, small pores into the polymers, as evidenced by a dramatic increase in the specific surface areas upon hypercrosslinking (from ～530 to 1080 m² g^?1). The hypercrosslinked polymers are very interesting for a range of applications, not least of all for solid‐phase extraction (SPE) work, where the convenient physical form of the polymers (beaded format), their low mean particle diameters, and narrow particle size distributions, as well as their high specific surface areas and polar character (arising from the AN residues), make them attractive candidates as SPE sorbents. In this regard, in a preliminary study one of the hypercrosslinked polymers was utilized as an SPE sorbent for the capture of the polar pharmaceutical diclofenac from a polar environment. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45677.