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Article
Publication date: 23 January 2009

Vandana Niranjan and Maneesha Gupta

Real‐time multiplication of two analog signals is one of the most important operations in analogue signal processing. Driven by low‐power and low‐voltage requirements for…

471

Abstract

Purpose

Real‐time multiplication of two analog signals is one of the most important operations in analogue signal processing. Driven by low‐power and low‐voltage requirements for integrated mixedsignal portable applications, the paper's aim is to propose a novel four‐quadrant low‐voltage analog multiplier using dynamic threshold MOS transistors (DTMOS).

Design/methodology/approach

The SPICE simulations were performed with 0.25 μm technology parameters and results verify the performance of the circuit. The multiplier is simulated at low‐supply voltage of ±0.5 V.

Findings

The proposed multiplier has high linearity and simple structure hence it is suitable for high‐performance and low‐power analog VLSI applications.

Originality/value

A new low‐voltage four quadrant analog multiplier using DTMOS circuit topology is presented in the paper.

Details

Microelectronics International, vol. 26 no. 1
Type: Research Article
ISSN: 1356-5362

Keywords

Available. Open Access. Open Access
Article
Publication date: 28 February 2024

Souresh Cornet, Saswat Barpanda, Marc-Antoine Diego Guidi and P.K. Viswanathan

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a…

2414

Abstract

Purpose

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

Design/methodology/approach

A case study method is used to document SI projects initiated by an HEI programme in rural India.

Findings

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

Originality/value

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

Details

International Journal of Sustainability in Higher Education, vol. 25 no. 9
Type: Research Article
ISSN: 1467-6370

Keywords

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Article
Publication date: 12 November 2024

Shokoofa Mostofi, Sohrab Kordrostami, Amir Hossein Refahi Sheikhani, Marzieh Faridi Masouleh and Soheil Shokri

This study aims to improve the detection and quantification of cardiac issues, which are a leading cause of mortality globally. By leveraging past data and using knowledge mining…

15

Abstract

Purpose

This study aims to improve the detection and quantification of cardiac issues, which are a leading cause of mortality globally. By leveraging past data and using knowledge mining strategies, this study seeks to develop a technique that could assess and predict the onset of cardiac sickness in real time. The use of a triple algorithm, combining particle swarm optimization (PSO), artificial bee colony (ABC) and support vector machine (SVM), is proposed to enhance the accuracy of predictions. The purpose is to contribute to the existing body of knowledge on cardiac disease prognosis and improve overall performance in health care.

Design/methodology/approach

This research uses a knowledge-mining strategy to enhance the detection and quantification of cardiac issues. Decision trees are used to form predictions of cardiovascular disorders, and these predictions are evaluated using training data and test results. The study has also introduced a novel triple algorithm that combines three different combination processes: PSO, ABC and SVM to process and merge the data. A neural network is then used to classify the data based on these three approaches. Real data on various aspects of cardiac disease are incorporated into the simulation.

Findings

The results of this study suggest that the proposed triple algorithm, using the combination of PSO, ABC and SVM, significantly improves the accuracy of predictions for cardiac disease. By processing and merging data using the triple algorithm, the neural network was able to effectively classify the data. The incorporation of real data on various aspects of cardiac disease in the simulation further enhanced the findings. This research contributes to the existing knowledge on cardiac disease prognosis and highlights the potential of leveraging past data for strategic forecasting in the health-care sector.

Originality/value

The originality of this research lies in the development of the triple algorithm, which combines multiple data mining strategies to improve prognosis accuracy for cardiac diseases. This approach differs from existing methods by using a combination of PSO, ABC, SVM, information gain, genetic algorithms and bacterial foraging optimization with the Gray Wolf Optimizer. The proposed technique offers a novel and valuable contribution to the field, enhancing the competitive position and overall performance of businesses in the health-care sector.

Details

Journal of Modelling in Management, vol. 20 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

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