Recent advancements in the field of VLSI technology are derived by attempting aggressive scaling of MOS devices and subjecting them through various generations of technologies. The model in turn leads to outcomes such as higher integration density and performance. Moving forward with great evolutions, the VLSI technology adheres changes towards Nano-meter era. The same evolutions result in deeming the interconnect performance as the core element in determining the comprehensive performance of an Integrated Circuit. Carbon Nanotubes Field Effect Transistors (CNTFET) have acquired huge interest owing to its ability of transferring charge within the device channels. The properties exhibited by CNTFET materials are highly intriguing which are the thoroughly analysed in recent research works. Observing the full wave simulations have delivered promising results in terms of performance of devices, circuits and Systems. The proposed work encompasses an advanced design of CNTFET based model with compactness and high performance. The compact circuit is further deprived to extract significant and equivalent parameters. The model is evaluated by comparing simulations of different CNTFETs architectures, and careful investigation is carried out to highlight the differences between extracted fitting parameters. By reducing a promising fully functional description in SPICE, IC designers will be able to simulate more easily.

Traffic congestion is becoming a critical issue with the increasing usage of vehicles. The rapid increase in vehicles has naturally led to traffic congestion all over the world. The traffic congestion forcing people to sit idle in their vehicles, consuming more fuel, and increase of air pollution. Traffic light control policies are not optimized, leading vehicles to wait pointlessly for non- existent traffic to pass on the crossing road. The current traffic signal systems follow fixed timing patterns that are not adjusted depending up on the volume of vehicles present on the traffic junction. Traffic light control policies can be greatly improved by implementing Deep learning (DL) and Reinforcement Learning (RL) concepts. Reinforcement Learning has become a popular method for controlling traffic signals in recent times as it can learn the best control policies through practical experience. By using RL, this research work aims to enhance traffic control efficiency and minimize issues such as delays, traffic congestion, fuel consumption, and pollution. The goal of this proposed work is to reduce the cumulative waiting time of vehicles at the junctions. Waiting time, Reward, Queue Length are considered as performance metrics. Moreover, the proposed approach is designed to be cost-effective and can be implemented in real-time systems.

In addition to reducing malnutrition and improving education, smart anganwadi centers are essential for early childhood development. A growth monitoring system that detects and assists in reducing child malnutrition and maternal mortality, especially among low-income households enrolled in anganwadi centers, is proposed. Children, pregnant women, lactating women can be monitored and reported on their nutritional status in real-time. With the help of an IoT-based integrated growth monitoring system, Anganwadi Teachers can check growth activities with a single click through a mobile app, where data is updated in real time to a department portal and dashboard. The main objective of the proposed work is to develop a smart device for child and pregnancy women’s health monitoring. The proposed work will monitor the growth of child and automatically update it in the cloud server without any manual entry. This proposed work will avoid and reduce the burden of the anganwadi workers.

With the rapid growth of the technology, nowadays more IoT devices are enabled and more data is transferring from one device to another device. Due to huge data transmission from one node to another a traffic or collision may occur in IoT Assisted Smart devices in WSN. To avoid the issues an energy efficient routing protocol is used. In this regard, routing is a challenging task while transmitting the packets to some storage repositories. This paper presents the Energy Efficient Routing Approach (EERA) to identify the routing paths where less energy is consumed to enhances the network lifespan.

sensor nodes are vulnerable to various security threats and resource constraints. A wireless sensor network is very vulnerable because there is no centralized data repository, so data can be stolen by eavesdropping. The nodes in WSN are distributed or arranged in a network for a specific function. Sensors, processor and radio transceiver are the important components an important application of wireless networks. The main goal of the proposed work is to secure the data which is transfer from one node to another node. It uses a secure key to transfer the data. The proposed system uses a paillier algorithm to generate a key to secure the data during transmission.

The effect of hurtful toxins in the air on human wellbeing is an immense territory of exploration, forestalling or Controlling, and furthermore checking the poison is one of the important problems in daily life. Air pollution is caused by smoke from manufacturing industry, vehicles etc. Due to this more side effects and diseases are caused to human beings. This paper predicts the air pollution using IoT with machine learning algorithms with high accuracy. These sensors measure the air quality and store the sensed data in a cloud. The machine learning analysis the data which is send by the IoT devices. The accuracy is very high when compared with the existing algorithms. KeywordsAir pollution, NodeMCU, Air Quality Index, Data preprocessing, Regressive Model.

Sonar signals recognition is one of the important detecting techniques to detect the objects under the sea. In military, sonar signals are used in lieu of visuals to navigate underwater and/or locate enemy submarines in proximity. In particular, classification algorithm in data mining has been applied in sonar signal recognition for recognizing the type of surfaces. This paper presents a machine learning technique to detect the object very fast with high accuracy. Simulation experiments are conducted and compared with the existing works.

Security is the main issue in WSN applications. One of the important attacks in WSN is Node Replication Attacks. The adversary can capture the genuine nodes. After capturing the node, the attacker collects all the information like keys and identity. In the existing method, the replica node is detected by the parameter's mobility speed, node id and energy. The parameters used in the existing system is not able to detect the exact replica node. Speedily detecting a replicated node will avoid the misbehavior activities such as collecting all the credentials, etc. The proposed approach (FEC) will overcome the issues of existing system. It detects the replica node with speed of the sensor node. The detection accuracy is high.

The 5G networks are about to deploy it all over the world. This 5G technologies support by connecting the devices with rapid growth in network capacity, high QoS. Apart from this feature, 5G has more advantages in security, decentralization, transparency, data interoperability. The 5G network has millions of IoT devices are connected. With higher speeds these devices are enabled and worked with high speed. Blockchain is an important technology in the current trend. The Blockchain technology is used in more fields such as online payments, healthcare, smart contracts etc. Extending the technology of block chain to Internet of things (IoT) can have more features. The important issues in 5G technology is security because millions of IoT devices are connected and more confidential data is transferred. This data should be more secure using blockchain technology. This proposed system is to secure the data in smart healthcare systems using blockchain in 5G networks to prevent the data from forgery.

The 5G networks are about to deploy it all over the world. This 5G technologies support by connecting the devices with rapid growth in network capacity, high QoS. Apart from this feature, 5G has more advantages in security, decentralization, transparency, data interoperability. The 5G network has millions of IoT devices are connected. With higher speeds these devices are enabled and worked with high speed. Blockchain is an important technology in the current trend. The Blockchain technology is used in more fields such as online payments, healthcare, smart contracts etc. Extending the technology of block chain to Internet of things (IoT) can have more features. The important issues in 5G technology is security because millions of IoT devices are connected and more confidential data is transferred. This data should be more secure using blockchain technology. This proposed system is to secure the data in smart healthcare systems using blockchain in 5G networks to prevent the data from forgery.

Security is an important problem in wireless sensor networks. There are more attacks in WSN. Node replication attack is an important attack in wireless sensor networks which can be easily captured by adversaries. In this attack, the node will behave as an original node and collect all the information which is transferred in the network and passes to the attacker node. Some existing schemes are proposed for predicting the replica nodes. In existing method, the detection rate is less, communication cost is high. To increase the detection accuracy and to increase the communication cost, a History of Neighbor Node (HNN) method is proposed. The proposed HNN approach detects the replicated node locally and globally. The HNN method detection accuracy is high in any speed limit. Another approach also proposed for static mobile sensor networks, FEC approach, the replicated node is detected based upon the speed, direction and location. In random time the base station verifies the node with the observed speed and direction. The verification is conducted by the SPRT technique. The SPRT technique tests the node which should be rejected (clone node) or accepted (genuine node). Once the clone node is found quickly, then it is removed from the network. The proposed system has high detection accuracy and less communication cost and less energy efficiency when compared with the existing system.

Security is the important problem in wireless sensor networks. The nodes are deployed in environment without any security measures. One of the important attacks in wireless sensor networks is node replication attack. The node replication attack will behave as an original node and hack the information. The proposed work is for detecting replica node in distributed networks. The drawback of the existing has less detection accuracy when replica node is less. The proposed work improves the detection accuracy when the replica node is less. The proposed work is detected in an efficient with less energy consumption and without any delay.

Today’s advent in the medical industry have given numerous chances to improve the quality of detection and reporting the diseases at the early stages for a better diagnosis. Diabetes mellitus is one such disease which is predominant among a global population which ultimately leads to blindness and death in some cases. The model proposed in this system attempts to design and deliver an intelligent solution for predicting diabetes in the early stages and address the problem of late detection and diagnosis. Intensive research is carried out in many tropical countries for automating this process through a machine learning model. The accuracy of machine learning algorithms is more than satisfactory in detection of Type 2 diabetes from the dataset of PIMA Indians Diabetes Dataset. An additional feature of hereditary factor is implemented to the existing multiple objective fuzzy classifiers. The proposed model has improved the accuracy to 83% in the training and tested datasets when compared to existing method.                                                                                                                               Keywords-Fuzzy classifiers, Diabetes Dataset, machine learning, Gestational diabetes

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief. The article is a somewhat extended version of a paper that has already been published in IJRRSET, Volume 3, Issue 1 (2015), 30-37. However, the main contents are virtually the same. Only three new figures in Section 4 and their explanation were added as the extension. The authors did not declare that this was an extended version of the paper published in IJRRSET in 2015, nor included the original paper as a reference in the extended version. One of the conditions of submission of a paper for publication is that authors declare explicitly that the paper has not been previously published and is not under consideration for publication elsewhere. As such this article represents a misuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

Real processing components along with component simulators are combined together to construct a new virtual prototyping system. The increase in component simulators result in degraded performance of the simulation in distributed systems. The speed of simulation can be increased by doing parallel simulation techniques. Prime number test and Image edge detection are chosen to implement the parallel simulation techniques and achieved the expected results while implementing in real time applications. The prime number test calculates the number of processors in a system and the image edge detection can be done in two stages by Canny Edge detection and Sobel Edge detection. The Canny Edge detection is used to detect the edges in the images by using a multi-stage algorithm. The smaller, separable and integer valued filter in images are combined in horizontal and vertical directions by using the Sobel edge detection resulting in reduction of implementation cost. The tool named OpenMP is used for implementing the parallel simulation techniques by combining both the canny edge and Sobel edge detection. An add-on named MPI is used along with the OpenMP to reduce the implementation time in parallel processing.

This paper shows the improvisation of manually operated petrol bunks, as of this process the automated petrol bunks using cloud communications and Arduino along with RFID reader is proposed. Every step is made user friendly,where computerized RFID reader is installed at the bunk and postpaid cards are issued to every person along with vehicle registration certificate.It is that when the user approaches the petrol bunk and swipes the card at the RFID reader, it shows therespective user details. Then, after verifying the details and password is entered just to verify the user and then the required amount of fuel is entered,then the relay sensor gets activated and fuel gets released. When the quantity assigned is filled the filling gets stopped automatically, after this process the message of transaction details is automatically sent to registered mobile number of theuser.

For the past years, using of public transport especially local buses has lost the number of passengers getting into the buses due to lack of bus availability, time constraints and change(Rupees) constraint. The objective of this application is to attract passengers by implementing new technologies like Android and Secure Key Generation instead of using old technologies like QR Scanners and RFID readers which has some security problems. It totally has two android applications one is Passenger application and another is for Conductor. Through Passenger application he/she has to generate a unique four digit code which will be valid for 3 minutes. The unique four digit code will be generated automatically in a Passenger application after logging in with details which they used while registering in the application. Whereas in Conductor application, Conductor has to enter the 4 digit code generated in an Passenger application in order to identify the passenger. Now conductor has to enter the Source and Destination location of the passenger and Number of passengers. The Fare will be calculated based on Number of passengers and Price from the source to destination which is the value already stored in a database by an administrator. This fare will be debited automatically from Passenger application wallet and Ticket will be generated with a ID which will be sent to passenger via a notification and an SMS.

Security is more important in many sensor applications. The node replication attack is a major issue on sensor networks. The replicated node can capture all node details. Node Replication attacks use its secret cryptographic key to successfully produce the networks with clone nodes and also it creates duplicate nodes to build up various attacks. The replication attacks will affect in routing, more energy consumption, packet loss, misbehavior detection, etc. In this paper, a Secure-Efficient Centralized approach is proposed for detecting a Node Replication Attacks in Wireless Sensor Networks for Static Networks. The proposed system easily detects the replication attacks in an effective manner. In this approach Secure Cluster Election is used to prevent from node replication attack and Secure Efficient Centralized Approach is used to detect if any replicated node present in the network. When comparing with the existing approach the detection ratio, energy consumption performs better.

Network on chip (NoC) router plays an important role in packet forwarding from router to network interface module. In this paper, a low power packet encoding technique for multi port network on chip router is designed. The proposed packet encoding technique consists of table mapper unit and differential coding unit. The table mapper unit is used to encode the address and control signals of the packet and differential coding unit is used to encode the data flits in the packet. The proposed methodology is tested on different Virtex family and achieved 26.79mW of power consumption.