Comparative study of cryptography and steganography techniques shows that they have some strong and weak points when they used alone. But as we know from soft computing techniques (neural, genetic, and fuzzy computing), that when combining (hybridizing), more than one techniques, by the suitable way to do a job, the outcome will be a better technique with more strong points and less weak points.  Work of this paper represents an attempt to prove that combining cryptography with steganography techniques will result in hard transmitting system to break and thus enforcing security issues of secret text data transmitting over public channels. Matlab programs are written to encrypt plain text secret information following AES encrypt/decrypt algorithm with a key of 128 bits long and then hide/extract the text according to LSB insertion method with a key of 128 bits long too. System tests show that both techniques enforce each other and private data transmitting become more secure.

Nonpolluting, renewable energy can be harnessed from the sun using solar thermal concentrator and photovoltaic systems. A novel asymmetric oblique compound conical solar concentrator was designed and constructed with automatic solar tracking system. The experimental study of the developed system was carried out to inspect the efficiency of the designed solar concentrator and automatic azimuth and altitude tracking. In this solar tracking, the RTC (Real Time clock) based active solar tracking method is used to track the sun in order to attain the maximum temperature. A simple microcontroller based control system is used to control this open loop solar tracking system, further the concentrated thermal power was measured using both the K-type temperature sensor and thermometer gun. The temperature obtained at the receiver of solar concentrator is sent to the measurement unit using GSM wireless module available at remote location. The monitoring unit receives the temperature values and recoded them regularly. Besides, the maximum average solar thermal power of the system was observed to be during 10.00 AM to 3.00 PM. This temperature is useful for various heating applications.

CMOS is a technology that has revolutionized the field of electronics. Over the time the processing technologies and design methodologies of CMOS devices have proved to be in full swing with the Moore’s law and the miniaturization paradigm. However, after surviving for more than five decades, CMOS is now facing challenges to live through the submicron ranges. The scaling in CMOS has reached a higher limit, showing adverse effects not only from physical and technological point of view but also from material and economical perspective. This drift inspires the researchers to look for new promising alternatives to CMOS which vow better performance, density and power consumption. One of the promising alternatives to digital designing in CMOS is the Quantum-dot Cellular Automata (QCA). QCA is a technology that involves no current transfer but works on electronic interaction between the cells. The QCA cell basically consists of quantum dots separated by certain distance and the entire transmission of information occurs via the interaction between the electrons localized in these quantum dots. In this paper the limitations to CMOS in submicron range and concepts for designing in QCA have been discussed. Further the building blocks are explained theoretically as well as using QCA Designer implementations with focus on cell interaction and clocking mechanisms.

A detailed design description of a stand-alone, auto-frequency select, ultrasonic brand of electronic pest control device that is unique in the sense that: it is solar powered, pest specific, field/farm operated, audio back-up, auto-frequency select and multi-directional in nature was hitherto presented using design calculations and analysis supported by circuit diagrams and component specifications. In this work, the conceptualized design was physically realized to specification using electronic construction technology. Implemented section by section on breadboard before soldering onto a veroboard, the cased device was made to sit on a fabricated adjustable stand to provide the needed exposure both to crops and solar insolation. Result shows that the assembled device saturates the vicinity of broadcast with ultrasound capable of deterring weaver birds. Recommendation was made for a performance evaluation of the device in weaver birds infested farms.

With the consistent development of remote sensor systems and Internet of Things (IoT) different parts of life will benefit. IoT based pervasive human services framework can possibly give blunder free restorative information and alarming system in basic conditions with constant checking. The device will minimize the need of devoted medicinal staff for patient checking and help the ailing to lead an ordinary life other than furnishing them with great restorative medical aid. This paper presents the working model which fuses sensors to gauge parameters like body temperature, blood pressure level & pulse. A microcontroller board is utilized for examining the inputs from the patient. Additionally all the procedure parameters inside of an interim selectable by the patient are monitored. This is extremely valuable for future examination and survey of feeble wellbeing condition. For more flexible restorative applications, this venture can be extemporized, by consolidating continuous parameter observing parameters respiratory thoracic extension belt sensors and annunciation frameworks, in this manner making it valuable in clinics as an exceptionally effective and committed aid consideration unit.

Face recognition (FR), the process of identifying people through facial images, has numerous practical applications in the area of biometrics, information security, access control, law enforcement, smart cards and surveillance system. Convolutional Neural Networks (CovNets), a type of deep networks has been proved to be successful for FR. For real-time systems, some preprocessing steps like sampling needs to be done before using to CovNets. But then also complete images (all the pixel values) are passed as input to CovNets and all the steps (feature selection, feature extraction, training) are performed by the network. This is the reason that implementing CovNets are sometimes complex and time consuming. CovNets are at the nascent stage and the accuracies obtained are very high, so they have a long way to go. The paper proposes a new way of using a deep neural network (another type of deep network) for face recognition. In this approach, instead of providing raw pixel values as input, only the extracted facial features are provided. This lowers the complexity of while providing the accuracy of 97.05% on Yale faces dataset.