Security Within and Between IoT Devices: A Survey

Several — Internet of things is promising to change the world to a better one with its tremendous applications in our daily lives where all physical objects will be connected to each other including humans. One major category of Internet of Things applications falls in the different industry like health, smart cities, Manufacture industries etc. Privacy is key parameter of communication between or with internet of things. This survey describes the IoT technologies and security issue and solution using different security algorithm

Mitral valve replacement with the pulmonary autograft: The Ross II procedure

AbstractJ Thorac Cardiovasc Surg 2001;122:378-

AN ELIXIR EFFECT OF DIET ON STHOULYA (MEDOROGA) IN AYURVEDA

Ayurveda is the ancient holistic science of life which gives us most detailed information on different Ahara (Diet) and lifestyles to be followed in different disease conditions as well as to maintain the optimum health of a healthy human being. Ayurveda states in full detail about the specific Ahara and lifestyles to be followed during different seasons under different climate circumstances and for different diseases. Ayurveda has scientific approach in planning the Ahara; therefore Acharya Charaka has included Ahara as first among the three supporting pillars of life. Ahara is an important component for the management of a disease in the same way as Ahara is considered as an important aid to protect the life and health. Sthoulya (Obesity/Medoroga) is a burning problem in present era due to improper Ahara and luxurious and competitive lifestyle. People have neither time nor interested to follow the dietetic regimens as well as daily regimens and seasonal regimens as described in classical texts of the Ayurveda

Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF

Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model) in distributed delay framework (DDF) for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI) distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered

Spiking Activity of a LIF Neuron in Distributed Delay Framework

Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF) neuron in distributed delay framework (DDF) is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel) function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD). Stationary state probability distribution of membrane potential (SPDV) for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1

A Comparison of AODV Routing Protocols to Prevent Black Hole Attack in Manet

Mobile ad hoc network (MANET) is a continuously self-configuring, infrastructure-less network of mobile devices connected wirelessly.Due to limited power supply, physical infrastructure and absence of central base station, malicious nodes can easily disguise themselves among the legitimate nodes. So MANET is vulnerable to many security threats, among which one is the blackhole attack. In this attack, the malicious node misuses the protocols to advertise the shortest path to destination node and drops the data packets subsequently. It deterioates the performance of the network, which is based on many factors including Packet Delivery Ratio and End-to-End Delay. Many effective techniques for detecting the blackhole attack have been devised. Among them are the solutions based on Ad-hoc On demand Distance Vector (AODV) Routing. In this review paper a comparison is done between three such solutions- CBDAODV, MOSAODV and DPRAODV based on two performance criteria mentioned above

A Gated Recurrent Unit Approach to Bitcoin Price Prediction

In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent neural network (RNN) and long short-term memory (LSTM) have been shown to perform better than traditional time series models in cryptocurrency price prediction. However, very few studies have applied sequence models with robust feature engineering to predict future pricing. in this study, we investigate a framework with a set of advanced machine learning methods with a fixed set of exogenous and endogenous factors to predict daily Bitcoin prices. We study and compare different approaches using the root mean squared error (RMSE). Experimental results show that gated recurring unit (GRU) model with recurrent dropout performs better better than popular existing models. We also show that simple trading strategies, when implemented with our proposed GRU model and with proper learning, can lead to financial gain.Comment: 8 figures, 16 page

MINING SINGLE NUCLEOTIDE POLYMORPHISM FROM PUBLICLY AVAILABLE ESTS OF BREAD WHEAT (TRITICUM AESTIVUM L.)

Objective: The present study was undertaken to discover Single Nucleotide Polymorphisms (SNPs) in bread wheat with reference to leaf rust disease.Methods: Next Generation Sequencing platform sequencing by Oligonucleotide Ligation and Detection (SOLiD) was performed on four Serial Analysis of Gene Expression (SAGE) libraries of mock and leaf rust pathogen infected near-isogenic lines HD2329±Lr28. CLC Genomics Workbench was used for computational prediction of the SNPs. The predicted SNPs were filtered by Blast using wheat Expressed Sequence Tags (ESTs). The SNP-containing ESTs were annotated, and their expression was checked in response to inoculation of Puccinia triticina.Results: We have identified 191 SNPs from data obtained through the These EST-SNPs participated in various physiological and biochemical processes that influence important traits, such as cell rescue, defense and disease resistance.Conclusion: Very little knowledge exists on SNPs in hexaploid bread wheat (Triticum aestivum L.) because of the difficulty to discern the true polymorphic loci. This study has revealed fast and costs effective approach for SNP discovery which will be helpful in molecular breeding with important agronomic traits.Â

Comparative Study on Ant Colony Optimization (ACO) and K-Means Clustering Approaches for Jobs Scheduling and Energy Optimization Model in Internet of Things (IoT)

The concept of Internet of Things (IoT) was proposed by Professor Kevin Ashton of the Massachusetts Institute of Technology (MIT) in 1999. IoT is an environment that people understand in many different ways depending on their requirement, point of view and purpose. When transmitting data in IoT environment, distribution of network traffic fluctuates frequently. If links of the network or nodes fail randomly, then automatically new nodes get added frequently. Heavy network traffic affects the response time of all system and it consumes more energy continuously. Minimization the network traffic/ by finding the shortest path from source to destination minimizes the response time of all system and also reduces the energy consumption cost. The ant colony optimization (ACO) and K-Means clustering algorithms characteristics conform to the auto-activator and optimistic response mechanism of the shortest route searching from source to destination. In this article, ACO and K-Means clustering algorithms are studied to search the shortest route path from source to destination by optimizing the Quality of Service (QoS) constraints. Resources are assumed in the active and varied IoT network atmosphere for these two algorithms. This work includes the study and comparison between ant colony optimization (ACO) and K-Means algorithms to plan a response time aware scheduling model for IoT. It is proposed to divide the IoT environment into various areas and a various number of clusters depending on the types of networks. It is noticed that this model is more efficient for the suggested routing algorithm in terms of response time, point-to-point delay, throughput and overhead of control bits

Multifunctional Nd3+ substituted Na0.5Bi0.5TiO3 as lead-free ceramics with enhanced luminescence, ferroelectric and energy harvesting properties

Herein, we present comprehensive investigations of the optical and electrical properties of Nd3+ substitution in sodium bismuth titanate ceramics (NBNT) with varying Nd3+ concentration. The room temperature photoluminescence (PL) emission for both unpoled and poled samples is observed to be a maximum for an Nd3+ substitution of 1 mol%. Upon poling, the PL intensity is observed to be quenched, consistent with the obtained XRD data, indicating an electric-field induced structural ordering towards higher symmetry, confirmed with the help of structural refinement. The evaluated ferroelectric to relaxor and antiferroelectric relaxor T(F–R) was observed clearly from the poled dielectric–loss curve for the 1 mol% of Nd3+ substitution. Furthermore, the optimized NBNT exhibited a lower Ec and a higher off-resonance figure of merit (FOMoff) for energy harvesting by 12% and 30%, respectively, in comparison with un-doped NBT