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High packaging density in the present VLSI era builds an acute power crisis, which limits the use of MOSFET device as a constituent block in CMOS technology. This leads researchers in looking for alternative devices, which can replace the MOSFET in CMOS VLSI logic design. In a quest for alternative devices, tunnel field effect transistor emerged as a potential alternative in recent times. The purpose of this study is to enhance the performances of the proposed device structure and make it compatible with circuit implementation. Finally, the performances of that circuit are compared with CMOS circuit and a comparative study is made to find the superiority of the proposed circuit with respect to conventional CMOS circuit.

Silicon–germanium heterostructure is currently one of the most promising architectures for semiconductor devices such as tunnel field effect transistor. Analytical modeling is computed and programmed with MATLAB software. Two-dimensional device simulation is performed by using Silvaco TCAD (ATLAS). The modeled results are validated through the ATLAS simulation data. Therefore, an inverter circuit is implemented with the proposed device. The circuit is simulated with the Tanner EDA tool to evaluate its performances.

The proposed optimized device geometry delivers exceptionally low OFF current (order of 10^−18 A/um), fairly high ON current (5x10^−5 A/um) and a steep subthreshold slope (20 mV/decade) followed by excellent ON–OFF current ratio (order of 10^13) compared to the similar kind of heterostructures. With a very low threshold voltage, even lesser than 0.1 V, the proposed device emerged as a good replacement of MOSFET in CMOS-like digital circuits. Hence, the device is implemented to construct a resistive inverter to study the circuit performances. The resistive inverter circuit is compared with a resistive CMOS inverter circuit. Both the circuit performances are analyzed and compared in terms of power dissipation, propagation delay and power-delay product. The outcomes of the experiments prove that the performance matrices of heterojunction Tunnel FET (HTFET)-based inverter are way ahead of that of CMOS-based inverter.

Germanium–silicon HTFET with stack gate oxide is analytically modeled and optimized in terms of performance matrices. The device performances are appreciable in comparison with the device structures published in contemporary literature. CMOS-like resistive inverter circuit, implemented with this proposed device, performs well and outruns the circuit performances of the conventional CMOS circuit at 45-nm technological node.

Advancement in optimization of VLSI circuits involves reduction in chip size from micrometer to nanometer level as well as fabrication of a billions of transistors in a single die where global routing problem remains significant with a trade-off of power dissipation and interconnect delay. This paper aims to solve the increased complexity in VLSI chip by minimization of the wire length in VLSI circuits using a new approach based on nature-inspired meta-heuristic, invasive weed optimization (IWO). Further, this paper aims to achieve maximum circuit optimization using IWO hybridized with particle swarm optimization (PSO).

This paper projects the complexities of global routing process of VLSI circuit design in mapping it with a well-known NP-complete problem, the minimum rectilinear Steiner tree (MRST) problem. IWO meta-heuristic algorithm is proposed to meet the MRST problem more efficiently and thereby reducing the overall wire-length of interconnected nodes. Further, the proposed approach is hybridized with PSO, and a comparative analysis is performed with geosteiner 5.0.1 and existing PSO technique over minimization, consistency and convergence against available benchmark.

This paper provides high performance–enhanced IWO algorithm, which keeps in generating low MRST value, thereby successful wire length reduction of VLSI circuits is significantly achieved as evident from the experimental results as compared to PSO algorithm and also generates value nearer to geosteiner 5.0.1 benchmark. Even with big VLSI instances, hybrid IWO with PSO establishes its robustness over achieving improved optimization of overall wire length of VLSI circuits.

This paper includes implications in the areas of optimization of VLSI circuit design specifically in the arena of VLSI routing and the recent developments in routing optimization using meta-heuristic algorithms.

This paper fulfills an identified need to study optimization of VLSI circuits where minimization of overall interconnected wire length in global routing plays a significant role. Use of nature-based meta-heuristics in solving the global routing problem is projected to be an alternative approach other than conventional method.

The purpose of this paper is to introduce a model of decision-making problem in multi-criteria optimization domain for project selection. The model is built by combining the soft set theory and analytic hierarchical model under fuzziness. Soft set model gives us the opportunity to use parameterization properties. Here, the authors have proved that multiple alternatives can be reduced to make the selection process computationally efficient. Here, the authors illustrate the hybrid method by means of an application of the new mathematical model of soft set theory.

This paper is designed to excel a decision support system with multiple criteria analysis tool, analytic hierarchy process combined with soft set theory under fuzziness.

In this paper, the authors have taken four projects P1, P2, P3 and P4. As per chosen parameters of softest theory the result of the illustrative example reveals that P2 is the best project. The ranking the authors get is in the order of P2, P3, P4 and P1. The algorithm leads the authors to maximize the proper choice in the environment of imprecise information. The main advantage of this method compare to others is that this hybrid method is very simple in terms of calculation and the computational complexity of the proposed algorithm is low.

This proposed decision support strategy for an intended project manager helped to take decision in the perspective environment.

Cost estimation based on expert's judgment is not an ideal approach, since human decisions are usually determined according to general attributes of limited and unstructured experience. The purpose of this paper is to develop a generic model of intelligence and cognitive science‐based method that can play an active role in process cost prediction within the shortest possible time.

In this paper, an intelligent system was conceived for prediction of total process cost of the product. The system is based on the concept of case‐based reasoning. It is a method for solving problems by making use of previous (source cases), similar situations and reusing information and knowledge about such situations. The source case data are generated by Taguchi technique and the cost function calculates the corresponding cost of each experiment in the economic time scale. The target case consists of the process variables whose cost needs to be determined. The cost for the source cases, consisting of the process variables of the already manufactured products are known in priori. The system calculates the similarities between the source cases and target cases and calculates the optimum cost. The fuzzy‐C‐means clustering method provides the model connecting the process parameters with total costs searched for.

The results show that the quality of predictions made by the intelligent system is comparable to the quality assured by the experienced expert. The proposed expert system is superior to traditional cost accounting system and assists inexperienced users in predicting the optimum process cost within the shortest possible time.

The research was limited to the traditional machining process.

The paper can be applied to any process industry and will have immense practical value.

This is the first time an expert system has been developed for the process industry that can calculate the process cost within a few days or a few hours before making an offer to a buyer.

The primary aim in this paper is to develop and demonstrate a theory of constraints (TOC) model in which constraint resource prevents the throughput of the organization.

In this paper, the authors propose an integrated model by combining Laplace criterion and TOC into a single evaluation model in a multiproduct constraint resource environment. A case study is illustrated to demonstrate the effectiveness of this model. The outsourcing decision model compares three alternatives: standard cost accounting, standard theory‐of‐constraints, and our own solution.

The numerical results show that the new approach is superior to Standard cost accounting and Theory of Constraints and presents a more realistic state of optimum allocation of resources and measures the performance of the model.

This research is limited to the production processes that do not have multiple constraints.

This is the first time that the integrated model comprising of Laplace‐TOC model has been used to maximize the product throughput. Instead of calculating $return per constraint minute, this method decides the priority of product that maximizes the product throughput in the constraint resource environment. It makes a significant contribution to the manufacturing Organization where one can compare the financial performance of the Organization by selecting the right decision model.

After working through the case, the students should be able to understand Indian political economy and the brand building process of NaMo; identify the media mix strategies used to build the brand NaMo in India; evaluate possible future growth strategies for brand NaMo; and compare and contrast brand NaMo with business brands.

Narendra Modi popularly called as NaMo was the current Prime Minister of India. He belonged to Bhartiya Janata Party (BJP) which won India’s general elections in two consecutive terms 2014 and 2019. NaMo was recognised worldwide for his prudence in leading the country to greater heights of achievement. NaMo started his political journey as the worker of BJP at a tender age. His rise in political career was akin to flagship brand overtaking the parent brand. All the steps taken in the past to position himself as a cult brand, will it fortify to NaMo’s victory in 2024 general elections? Business firms may follow NaMo’s strategies. What can the business brands emulate from NaMo to market and position themselves? Can political success be transpired to business success?

This case is designed for use in a graduate-/postgraduate-level marketing course in segments on brand management, brand expansion and the marketing strategies of a market leader. The case can also be used in a brand management course to discuss brand management models (e.g. Keller’s brand resonance pyramid and brand value chain). This case has particular application for classes that focus on brand equity, STP for any brand (segmentation, targeting and positioning) and brand value chain. The case looks in detail at the Indian political market and brand building process of NaMo and examines competitive moves since its inception. This case can be used in brand management, media management courses. The dilemma can be explained as part of a marketing course for postgraduate and executive programmes.

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CSS 8: Marketing.