(N,N) Share Generation using Key Share approach for RGB image in VCS

Visual Cryptography is a secure and unique image encryption technique which protects image based secret. In visual cryptography image is encrypted into shares and in decryption process all or some of shares are super imposed with each other to decrypt the original secret image. In this technique no complex computation is needed for decryption of secret image which is the best advantage of Visual Cryptography Scheme. In this report various types of visual cryptographic techniques are discussed from previous research area. In this proposed system (N, N) VCS is used for encryption. It takes color image as an input and extracts in R, G and B components. After that it generates Key-Mask using Key-Mask generation algorithm which XOR-ed with R, G and B components and gives the key shares. Further XOR operation of these key shares with key mask generates the color shares. In decryption process image is recovered by XOR operation between key mask and color shares. It has a better security features compared to previous one

Effectiveness of Social Media Community Using Optimized Clustering Algorithm

Now-a-days social media is used to the introduce new issues and discussion on social media. More number of users participates in the discussion via social media. Different users belong to different kind of groups. Positive and negative comments will be posted by user and they will participate in discussion. Here we proposed system to group different kind of users and system specifies from which category they belong to. For example film industry, politician etc. Once the social media data such as a user messages are parsed and network relationships are identified, data mining techniques can be applied to group of different types of communities. We used K-Means clustering algorithm to cluster data. In this system we detect communities by the clustering messages from large streams of social data. Our proposed algorithm gives better a clustering result and provides a novel use-case of grouping user communities based on their activities. This application is used to the identify group of people who viewed the post and commented on the post. This helps to categorize the users

Mitigating Instability in Electric Drive Vehicles Due to Time Varying Delays with Optimised Controller

The instability in the Electric vehicle would reduce the performance and even severely damage the system. This instability is mainly due to the random time-varying delays occurring in CAN network and the improper efficiency of controllers. This uncertainty and error occurrence makes it difficult to design the electric vehicles considering the advantages of Electric Vehicles being, the future to reduce harmful emissions due to fossil fuels, the instability can be mitigated by using optimized H∞ controller. The results of Simulations through MATLAB demonstrate the Effectiveness of the improved controller by comparing with the normal PI controller. The results of comparison illustrate the strength of explicitly

Evaluation of selected South African ethnomedicinal plants as mosquito repellents against the Anopheles arabiensis mosquito in a rodent model

<p>Abstract</p> <p>Background</p> <p>This study was initiated to establish whether any South African ethnomedicinal plants (indigenous or exotic), that have been reported to be used traditionally to repel or kill mosquitoes, exhibit effective mosquito repellent properties.</p> <p>Methods</p> <p>Extracts of a selection of South African taxa were tested for repellency properties in an applicable mosquito feeding-probing assay using unfed female <it>Anopheles arabiensis</it>.</p> <p>Results</p> <p>Although a water extract of the roots of <it>Chenopodium opulifolium </it>was found to be 97% as effective as DEET after 2 mins, time lag studies revealed a substantial reduction in efficacy (to 30%) within two hours.</p> <p>Conclusions</p> <p>None of the plant extracts investigated exhibited residual repellencies >60% after three hours.</p

Investigation and correction of error in impedance tube using intelligent techniques

AbstractErrors arise in the measurement of sound absorption coefficient using impedance tube due to various factors. Minimizing the errors require additional hardware or proper calibration of certain components. This paper proposes a new intelligent error correction mechanism using mathematical modelling and soft computing paradigms. A low cost impedance tube is designed, developed and its performance is compared with a commercially available standard tube. A particle swarm optimization and neural network based system is developed to reduce the random and systematic errors in the developed impedance tube. The proposed system is tested using various porous and non-porous functional textile materials and the results are validated. A significant reduction in error is obtained at all frequency ranges with PSO based prediction method

Anomaly detection of industrial control systems based on transfer learning

Industrial Control Systems (ICSs) are the lifeline of a country. Therefore, the anomaly detection of ICS traffic is an important endeavor. This paper proposes a model based on a deep residual Convolution Neural Network (CNN) to prevent gradient explosion or gradient disappearance and guarantee accuracy. The developed methodology addresses two limitations: most traditional machine learning methods can only detect known network attacks and deep learning algorithms require a long time to train. The utilization of transfer learning under the modification of the existing residual CNN structure guarantees the detection of unknown attacks. One-dimensional ICS flow data are converted into two-dimensional grayscale images to take full advantage of the features of CNN. Results show that the proposed method achieves a high score and solves the time problem associated with deep learning model training. The model can give reliable predictions for unknown or differently distributed abnormal data through short-term training. Thus, the proposed model ensures the safety of ICSs and verifies the feasibility of transfer learning for ICS anomaly detection. &nbsp

Opracowanie tuby impedancyjnej do pomiaru akustycznych właściwości materiałów tekstylnych

Measurement of the sound absorption coefficient using an impedance tube is prone to errors due to various reasons. Conventionally minimising the errors requires additional hardware or proper calibration of many components used for measurement. This paper proposes a new error correction mechanism using a filtering technique. A low cost impedance tube was designed, developed and its performance was compared with a commercially available high cost tube. The errors which arose during the measurement of the sound absorption coefficient were minimised using different types of filters (low pass, band pass, LMS filtering). The purpose of the filter is to eliminate unwanted signals or noise which occur during the processing of analogue signals in the experiment. The system proposed was tested using various porous and non-porous functional textile materials and the results validated. A significant reduction in error was obtained at all frequency ranges with digital filters.Pomiar współczynnika pochłaniania dźwięku za pomocą tuby impedancyjnej jest podatny na błędy. Konwencjonalne minimalizowanie błędów wymaga dodatkowego sprzętu lub odpowiedniej kalibracji wielu komponentów używanych do pomiaru. W artykule zaproponowano nowy mechanizm korekcji błędów za pomocą techniki filtrowania. Zaprojektowano i opracowano stosunkowo tani sposób wykonania nowego rodzaju tuby impedancyjnej i porównano jej działanie z dostępną na rynku tubą. Błędy, które powstały podczas pomiaru współczynnika pochłaniania dźwięku zostały zminimalizowane za pomocą różnych rodzajów filtrów (dolnoprzepustowym, środkowoprzepustowym, filtracyjnym LMS). Celem zastosowania filtra było wyeliminowanie niepożądanych sygnałów lub szumów, które występują podczas przetwarzania sygnałów analogowych podczas eksperymentów. Proponowany system został przetestowany przy zastosowaniu różnych porowatych i nieporowatych funkcjonalnych materiałów tekstylnych. Na podstawie uzyskanych wyników stwierdzono, że za pomocą filtrów cyfrowych można uzyskać znaczącą redukcję błędów we wszystkich zakresach częstotliwości

Smart Parking System Based on RFID & GSM Technology

In the modern world with about a billion vehicles present around the globe, and being in a densely populated country like India creates the need for an efficient parking system and with world advancing towards automation, there is also a need for an automated parking system. Mainly the problem of parking arises in big cities and this causes problems like traffic congestion, driver frustration &amp; air pollution, etc. The issue mainly arises from not knowing whether the parking spaces is available at any given point of time. Even if known, many vehicles may be competing for limited parking spaces causing severe traffic congestions. Even there are problems that can be caused with regards to the parking management. It may be difficult for the parking management to organise the parking of the vehicles in an orderly manner. Thus we are trying to resolve the problems stated by developing an RFID based smart parking system that monitors the availability of idle parking slots and guides the vehicle to the nearest such slot by sending a message to the mobile number registered in the vehicle’s RFID. The proposed system uses infrared transmitter-receiver pairs that remotely communicate the status of parking occupancy to the Arduino UNO microcontroller and displays the vacant slots on the display at the entrance of the parking so that the user gets to know the availability /unavailability of parking space prior to his/her entry into the parking place. Implementation involves minimal human interaction and provides a seamless parking experience thereby reducing a lot of time wasted by the user in parking his/her vehicle. Key Words:  Parking System, RFID, Arduino UN