Electronic devices portability requires major low power requirements and also high-speed requirements so there is high necessity for improving the circuits. Ternary logic these days is in high demand as most special algorithms such as fuzzy logic works on ternary logic so there is necessity of improving the performance of the ternary adder. In this thesis, we have proposed a new approach for Ternary Adder, in which tri-mode technique is used to improve the performance of the circuit and compared with a sleep transistor-based technique and the simple ternary adder. With this improvement it is seen that the proposed circuits give better performance in terms of Average Power, Delay, PDP and EDP. So, tri-mode technique and sleep mode technique have higher advantages in terms of performance metrics calculated. CNTFET has a high performance in terms of performances and is a better substitute for MOSFET in 32nm technology.

 The paper describes performance of solar water heating on Flat plate solar collector using Hexagonal reflector. Solar collector is main component of a solar water heating system. The collector gather sun's energy and convert this radiation into heat and then transfer the heat into a Fluid (water) which has many household or industrial applications .The solar Hexagonal type reflector used here with the solar collector to increase the reflectivity of the collector. Thus, the reflectors concentrate both direct and diffuse radiation of the sun toward the collector. To maximize the intensity of an incident radiation the reflector was allowed to changes its angle with day time. The radiation comes from sun's energy was converted into heat , and then heat was transferred to the collector Fluid (water). A prototype of a solar water heating system was constructed and obtained the improvement of the collector temperature and efficiency by using Hexagonal type reflector. Thus, the present solar water heating system has a best thermal performance compared to available system. 

In the recent past years there is a huge development in the field of Conservative source of energy due to reason that include the increase in fossil fuel prices and the decline in fossil fuel reservoirs. Among various renewable energy sources , due to abundance of source itself i.e. Sun, photovoltaic power generation is envisaged to an important source of energy of future .So the research work is directed to study, analyse and assess .Partial shading of PV reduce the power generated of PV system .The arrays have multiple peaks in the PV characteristic. The losses of shading are not proportional to shade area but it also depend on shading pattern, array configuration .This paper presents, a comprehensive study of research work done by different scholars on partial shading in Photovoltaic cells.

Electric vehicles are a new and upcoming technology in the transportation and power area that have numerous advantages as far as financial and ecological. This examination displays a writing audit of electric vehicles battery charger execution and charging station. An examination is made on the business and model electric vehicles as far as electric range, battery size, charger power and charging time.

Air conditioner and refrigerator is electrical device in these days it is frequently used in the world .these device is very costly in terms of electrical consumption and manufacturing. The poor people can’t afford. By modification of ordinary air cooler. these problem can be rectified. These modified air cooler gives sufficient amount of cold air as well as cold water. In this project by using of copper tube obtained cold water and cold air at very low cost. Modified Desert Air-coolers are generally used as a low in cost and suitable approach for cooling It is the Air Conditioner with fridge for that humans who can't manage to pay for equipments like air conditioner, fridge and distinctive such appliances. It has extra cooling impact compare to the Simple cooler. The modified wasteland cooler is diagram by way of the use of copper coil for presenting greater two cooling effect in contrast simple desert cooler. It also offers Chilled water in summer for consuming motive at very low value compared to Refrigerator with the help of modifies by means of using copper coil.

In recent time, the demand for multimedia data administrations has grown up quickly. One of the most encouraging multi-bearer framework, Orthogonal Frequency Division Multiplexing (OFDM) structures reason for all 4G remote correspondence frameworks because of its enormous ability to permit the quantity of subcarriers, high information rate and universal inclusion with high versatility. OFDM is essentially influenced by top to-average-control proportion (PAPR). Tragically, the high PAPR intrinsic to OFDM signal envelopes will once in a while drive high power speakers (HPAs) to work in the nonlinear area of their trademark bend. The nonlinearity of the HPA shows abundancy and stage contortions, which cause loss of symmetry among the subcarriers, and consequently, between bearer impedance (ICI) is presented in the transmitted sign. Not just that, high PAPR additionally prompts in-band mutilation and out-of band radiation. This paper accentuation predominantly on the PAPR decrease of MIMO-OFDM framework utilizing fractional transmits succession (PTS) and precoding procedures. Some different methods, for example, adequacy cutting, Artificial Bee Colony have low-unpredictability; then again, they experience the ill effects of different issues, for example, in-band mutilation and out-of-band development .

Machine Learning (ML) and Deep Learning (DL) techniques have found successful applications in forecasting stock price trends. Despite the advocacy by finance practitioners and academics for combining Fundamental Analysis (FA) and Technical Analysis (TA), ML research has predominantly focused on utilizing TA-based indicators. The primary aim of ML researchers has been to predict the next day's price for market indices or individual stocks. This study seeks to explore the impact on ML-based stock price forecasting by incorporating various inputs and considering the prevailing states of the stock market. A novel framework is proposed herein for effectively predicting stock price trends. This framework facilitates the identification of the best-performing model with pertinent inputs, while also accommodating the sensitivity of a stock's price to different market conditions. The proposed framework forecasts the next day's price movement, framing it as a buy-sell decision, achieving an accuracy rate of approximately 73%. Furthermore, the framework introduces a DL-based approach termed "Multi-step Stacked - Long Short Term Memory" (MS-LSTM) for forecasting future stock trends and prices.