IoT–smart contracts in data trusted exchange supplied chain based on block chain

Internet of Things (IoT) assumes a critical part in the advancement of different fields. The IoT data trusted exchange in recent year extend of uses influence an awesome request and increasing scale. In such a platform, exchange the data sets that they require and specialist organization can search. However, the enough trust as the third-party mediators for data exchange in centralized infrastructure cannot provide. This paper proposes a blockchain for IoT data trusted exchange based on decentralized solution. In particular, the fundamental standards of blockchain in verify manner, individuals can communicate with each other without a confided in mediator intermediary. Blockchain enable us to have a distributed, digital ledger. IoT (Internet of Things) sensor devices (zigbee) utilizing blockchain technology to assert public availability of temperature records, tracking location shipment, humidity, preventing damage, data immutability. The sensor devices looking the temperature, location, damage of each parcel during the shipment to completely guarantee directions. In blockchain all data is got moved from one position to another, where a smart contract assesses against the product attributes. Ethereum blockchain and smart contracts atlast it gets through knowledge a design to be copied and presents its decentralized distributed digital ledger, auditable, transparent, features visually

An enhanced kernel weighted collaborative recommended system to alleviate sparsity

User Reviews in the form of ratings giving an opportunity to judge the user interest on the available products and providing a chance to recommend new similar items to the customers. Personalized recommender techniques placing vital role in this grown ecommerce century to predict the users’ interest. Collaborative Filtering (CF) system is one of the widely used democratic recommender system where it completely rely on user ratings to provide recommendations for the users.  In this paper, an enhanced Collaborative Filtering system is proposed using Kernel Weighted K-means Clustering (KWKC) approach using Radial basis Functions (RBF) for eliminate the Sparsity problem where lack of rating is the challenge of providing the accurate recommendation to the user.  The proposed system having two phases of state transitions: Connected and Disconnected. During Connected state the form of transition will be ‘Recommended mode’ where the active user be given with the Predicted-recommended items. In Disconnected State the form of transition will be ‘Learning mode’ where the hybrid learning approach and user clusters will be used to define the similar user models. Disconnected State activities will be performed in hidden layer of RBF and Connected Sate activities will be performed in output Layer. Input Layer of RBF using original user Ratings. The proposed KWKC used to smoothen the sparse original rating matrix and define the similar user clusters. A benchmark comparative study also made with classical learning and prediction techniques in terms of accuracy and computational time. Experiential setup is made using MovieLens dataset

Healthcare information exchange using blockchain technology

Current trend in health-care industry is to shift its data on the cloud, to increase availability of Electronic Health Records (EHR) e.g. Patient’s medical history in real time, which will allow sharing of EHR with ease. However, this conventional cloud-based data sharing environment has data security and privacy issues. This paper proposes a distributed solution based on blockchain technology for trusted Health Information Exchange (HIE). In addition to exchange of EHR between patient and doctor, the proposed system is also used in other aspects of healthcare such as improving the insurance claim and making data available for research organizations. Medical data is very sensitive, in both social as well as legal aspects, so permissioned block-chain such as Hyperledger Fabric is used to retain the necessary privacy required in the proposed system. As, this is highly permissioned network where the owner of the network i.e. patient holds all the access rights, so in case of emergency situations the proposed system has a Backup Access System which will allow healthcare professionals to access partial EHR and this backup access is provided by using wearable IOT device

Quantum cryptography for secured communication networks

Quantum cryptography is a method for accessing data with the cryptosystem more efficiently. The network security and the cryptography are the two major properties in securing the data in the communication network. The quantum cryptography uses the single photon passing through the polarization of a photon. In Quantum Cryptography, it's impossible for the eavesdropper to copy or modify the encrypted messages in the quantum states in which we are sending through the optical fiber channels. Cryptography performed by using the protocols BB84 and B92 protocols. The two basic algorithms of quantum cryptography are Shor’s algorithm and the Grover’s’s algorithm. For finding the number of integer factorization of each photon, Shor’s algorithm is used. Grover’s’s algorithm used for searching the unsorted data. Shor’s algorithm overcomes RSA algorithm by high security. By the implementation of quantum cryptography, we are securing the information from the eavesdropper and thereby preventing data in the communication channel

Isolation, Identification, Morphological Studies and Lipid Granules Staining (Nile red) of Different Micro-Algae for Biodiesel Production from Fresh Water and Saline Water

In the present study, the algal samples were collected from temple tanks, saline water in Chennai, Mahapaliburam and Kovallam. Collections were carried out during the month of September 2010 and February 2011. Samples were studied in the laboratory and identified. In their surveyed the population, identification, morphological, and examined the Nile red method with microalgae genus of various classes. Various physical and chemical treatments were applied to the existing Nile red method to improve the effectiveness and efficiency. The following algae were present Chlorella vulgaris, Nannnochloropsis, Dunaliella tertiolecta, Tetraselmis suecica, Chlorococcum humicolo, Scenedesmus acuminatus, Amphora coffeaformis, and Nitzschia longissima. Algae are described with photographs

(4S)-4-(3,4-Dichloro­phen­yl)-1′-methyl-4′-phenyl-3,4-dihydronaphthalene-2-spiro-3′-pyrrolidine-2′-spiro-1′′-acenaphthyl­ene-1,2′′(2H,1′′H)-dione

In the title compound, C37H27Cl2NO2, the 3,4-dichloro­phenyl ring makes a dihedral angle of 46.66 (6)° with the phenyl ring. The mol­ecular structure is stabilized by weak intra­molecular C—H⋯O inter­actions and the crystal structure is stabilized by weak inter­molecular C—H⋯O inter­actions. The C–C–C–C–C five-membered ring is planar, while the C–C–C–C–N five-membered ring adopts a half-chair conformation

Effect of lateral crushing on tensile property of bamboo, modal and tencel fibres

The effect of lateral crushing on the tensile properties of bamboo, modal and tencel fibres has been investigated. A fibre crushing apparatus has been used for the purpose of lateral crushing of fibres. The influence of transverse compression on the axial mechanical properties of these fibres has been analysed. The study reveals that modal fibre sustained a higher loss in tensile properties compared to bamboo and tencel. The general phenomenon obtained from the study is that the percentage loss of strength and breaking extension varies from one fibre to another based on the fibre type and morphology

A time efficient and accurate retrieval of range aggregate queries using fuzzy clustering means (FCM) approach

Massive growth in the big data makes difficult to analyse and retrieve the useful information from the set of available data’s. Statistical analysis: Existing approaches cannot guarantee an efficient retrieval of data from the database. In the existing work stratified sampling is used to partition the tables in terms of static variables. However k means clustering algorithm cannot guarantees an efficient retrieval where the choosing centroid in the large volume of data would be difficult. And less knowledge about the static variable might leads to the less efficient partitioning of tables. Findings: This problem is overcome in the proposed methodology by introducing the FCM clustering instead of k means clustering which can cluster the large volume of data which are similar in nature. Stratification problem is overcome by introducing the post stratification approach which will leads to efficient selection of static variable. Improvements: This methodology leads to an efficient retrieval process in terms of user query within less time and more accuracy

Enhancement of bulk second-harmonic generation from silicon nitride films by material composition

We present a comprehensive tensorial characterization of second-harmonic generation from silicon nitride films with varying composition. The samples were fabricated using plasma-enhanced chemical vapor deposition, and the material composition was varied by the reactive gas mixture in the process. We found a six-fold enhancement between the lowest and highest second-order susceptibility, with the highest value of approximately 5 pm/V from the most silicon-rich sample. Moreover, the optical losses were found to be sufficiently small (below 6 dB/cm) for applications. The tensorial results show that all samples retain in-plane isotropy independent of silicon content, highlighting the controllability of the fabrication process.Comment: 4 pages, 3 figures, 2 tables; Re-submitted to Optics Letter

Efficiency of universal barcode gene (Cox1) on morphologically cryptic Mugilidae fishes delineation.

An effort was made to assess the utility of 650 bp partial Cytochrome C oxidase subunit I (DNA barcode) gene in delineating the members of taxonomically ambiguous marine fin fishes (Family: Mugilidae). To address the issue we used all the 95 barcode sequences of Mugilidae family available at NCBI (National Centre for Biotechnological Information) along with the barcode data generated from Mugilidae fishes of Parangipettai coastal waters. The average GC content of Mugilidae was found to be 46.46%. Crenimugil crenilabis showed less GC content (44.55%) whereas Liza macrolepis showed high GC content (48.53%) among the mullet species studied. The phylogenetic and genetic distance data showed that Mugil platanus and M. liza represent the continuum of same species. Among the members of family Mugilidae, the genus Mugil might possibly contains more haplotype diversity as revealed by intra-species genetic distance data. Species within genera of Mugilidae family invariably clustered in single clade with high bootstrap value. We conclude that partial COI sequencing (barcoding) in identifying the members of the family and that way has resolved the taxonomic ambiguity among the members of the family Mugilidae