An innovative technology named FinFET (Fin Field Effect Transistor) has been developed to offer better transistor circuit design and to compensate the necessity of superior storage system (SS). As... Show More

An innovative technology named FinFET (Fin Field Effect Transistor) has been developed to offer better transistor circuit design and to compensate the necessity of superior storage system (SS). As gate loses control over the channel, CMOS devices faces some major issues like increase in manufacturing cost, less reliability and yield, increase of ON current, short channel effects (SCEs), increase in leakage currents etc. However, it is necessary for the memory to have less power dissipation, short access time and low leakage current. The traditional design of SRAM (Static RAM) using CMOS technology represents severe performance degradation due to its higher power dissipation and leakage current. Thus, a Nano-scaled device named FinFET is introduced for designing SRAM since it has three dimensional design of the gate. FinFET has been used to improve the overall performance and has been chosen as a transistor of choice because it is not affected by SCEs. In this work, we have reviewed various FinFET based SRAM cells, performance metrics and the comparison over different technologies.

Maximum power point tracking(MPPT) control is an indispensable aspect of photovoltaic(PV) systems. Many MPPT techniques including a few based on soft-computing have been employed earlier. The... Show More

Maximum power point tracking(MPPT) control is an indispensable aspect of photovoltaic(PV) systems. Many MPPT techniques including a few based on soft-computing have been employed earlier. The soft-computing techniques include fuzzy-FSMs (Finite State Machines)which are integration of fuzzy logic (FL) into states or transitions of FSMs which are used for control and modeling of real-time systems. However, FSMs pose certain disadvantages as compared to its advanced variant called ‘statecharts’. In this work, statecharts with abstraction layers are proposed for MPPT control of PV system. An abstract-statechart MPPT(ASM) controller is developed and is verified with PV system using co-simulation. A C++ based FL MPPT program is also developed, which is independent of any predefined and simulation-only functions. A conceptual estimation of execution time of such a FL MPPT program is presented and compared with the execution times delivered by proposed ASM controller. It can be observed that the ASM controller gives accurate, fast tracking speeds, along with the advantage of abstraction.

The domain of fashion design evolves continuously and is highly personalised, demanding intelligent and customised recommendation. The traditional artificial intelligence-based systems offer... Show More

The domain of fashion design evolves continuously and is highly personalised, demanding intelligent and customised recommendation. The traditional artificial intelligence-based systems offer solutions based on stored knowledge; hence they can be quickly obsolete and require high effort. To meet the fashion designers’ needs and provide tailor-made recommendations effectively, a hybrid genetic-fuzzy system is proposed with interactive fitness functions. The system is based on generic hybrid architecture using fuzzy logic and genetic algorithm, which can be used to evolve various products in different domains and tested with interactive fuzzy fitness functions. The design of the generic architecture meets the research gap identified through an in-depth literature survey. To prove the utility of the architecture, an experiment is carried out showing encoding scheme, genetic operators, fuzzy membership functions, and fuzzy rules. The results are also discussed, along with the comparison, advantages, applications, and possible future enhancements.

In this article an effort is made to identify brain tumor disease such as neoplastic, cerebrovascular, Alzheimer's, lethal, sarcoma diseases by successful fusion of images from magnetic resonance... Show More

In this article an effort is made to identify brain tumor disease such as neoplastic, cerebrovascular, Alzheimer's, lethal, sarcoma diseases by successful fusion of images from magnetic resonance imaging (MRI) and computed tomography (CT). Two images are fused in three steps: The two images are independently segmented by hybrid combination of Particle swam optimization (PSO), Genetic algorithm and Symbiotic Organisms Search (SOS) named as hGAPSO-SOS by maximizing 2-dimensional Renyi entropy. Image thresholding with 2-D histogram is stronger in the segmentation than 1-D histogram. Remove the segmented regions with Scale Invariant Feature Transform (SIFT) algorithm. Also after image rotation and scaling, the SIFT algorithm is excellent at removing the features. The fusion laws are eventually rendered on the basis of type-2 blurry interval (IT2FL), where ambiguity effects are reduced unlike type-1. The uniqueness of the proposed study is evaluated on specific data collection of benchmark Image fusion and has proven stronger in all criteria of scale.