Influence of bed temperature on performance of silica gel/methanol adsorption refrigeration system at adsorption equilibrium

Sur, Anirban; Pandya, Sharnil; Sah, Ramesh P.; Kotecha, Ketan; Narkhede, Swapnil

doi:10.1080/02726351.2020.1778145

Cited by 19 publications

(8 citation statements)

References 21 publications

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“…Are both the individuals and the activities the selling type focused on a high degree of interest. In this method, the leader discusses choices and offers the subjects the ability to raise concerns, clarify and appreciate the activities [59].…”

Section: Contingency Approachmentioning

confidence: 99%

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

et al. 2021

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Successful leaders are facilitators who specifically target skilled and committed workers. Studies in organizational psychology and the research on an organization's actions suggest that management styles and staff motivation are key factors of business performance or failure. This study aimed to study the influence of leadership on the performance of employers in the education ministry and higher education of Somaliland and to define four types, namely, autocratic, transformational, democratic and transactional leadership. This study analyzed the effects of leadership styles on employee efficiency. The final findings have shown that the autocratic leadership model has a detrimental effect on the department's efficiency,

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Section: Contingency Approachmentioning

confidence: 99%

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

et al. 2021

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“…The best results were obtained without the LS-SVM dependent Wavelet kernel. Xing, Cambria & Welsch (2018b) and Sur, Pandya & Sah (2020) present the scope of Natural language based financial forecasting (NLFF) by using Natural Language processing or programmatic study. NLP techniques are quickly growing, progressively establishing an area of research dealing with of financial forecasting focused on NLFF or SM analysis from the application point of view.…”

Section: Related Workmentioning

confidence: 99%

Harvesting social media sentiment analysis to enhance stock market prediction using deep learning

Mehta

Pandya

Kotecha

2021

PeerJ Computer Science

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Information gathering has become an integral part of assessing people’s behaviors and actions. The Internet is used as an online learning site for sharing and exchanging ideas. People can actively give their reviews and recommendations for variety of products and services using popular social sites and personal blogs. Social networking sites, including Twitter, Facebook, and Google+, are examples of the sites used to share opinion. The stock market (SM) is an essential area of the economy and plays a significant role in trade and industry development. Predicting SM movements is a well-known and area of interest to researchers. Social networking perfectly reflects the public’s views of current affairs. Financial news stories are thought to have an impact on the return of stock trend prices and many data mining techniques are used address fluctuations in the SM. Machine learning can provide a more accurate and robust approach to handle SM-related predictions. We sought to identify how movements in a company’s stock prices correlate with the expressed opinions (sentiments) of the public about that company. We designed and implemented a stock price prediction accuracy tool considering public sentiment apart from other parameters. The proposed algorithm considers public sentiment, opinions, news and historical stock prices to forecast future stock prices. Our experiments were performed using machine-learning and deep-learning methods including Support Vector Machine, MNB classifier, linear regression, Naïve Bayes and Long Short-Term Memory. Our results validate the success of the proposed methodology.

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“…Sharma, Manik, et al [7] proposed an entropy-based genetic algorithm to optimize query execution plan in distributed database systems in terms of system size and query complexity. Prableen Kaur and Manik Sharma [8] have provided an extensive review of soft computing-based optimization algorithms for diabetes pre-processing and diagnosis [35][36][37][38][39][40][41]. Also, the rate of accuracy is analyzed in detail for data mining and hybrid optimization techniques [42][43][44][45][46].…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of Fractional Earthworm Optimization Algorithm for Optimal Routing in Wireless Sensor Networks

Pasupuleti¹,

Balaswamy²

2018

ICST Transactions on Scalable Information Systems

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In Wireless Sensor Networks (WSNs), the data transmission from the sensing node to the sink node consumes a lot of energy as the number of communications increases, so the battery life of nodes is limited, and the network also has a limited lifetime. Recent studies show that the bio-inspired meta-heuristic algorithms for solving engineering problems such as energy reduction in autonomous networks in the multidisciplinary areas of WSN, Internet of Things (IoT) and Machine learning models. Hence to increase Network lifetime, optimized clustering and energy-efficient routing techniques are required. In all applications of WSN, not only energy-efficient but also delay and throughput of the network are important for efficient transmission of data to the destination. This paper analyses optimized clustering by selecting cluster heads based on fractional calculus earthworm optimization algorithm (FEWA). The route from cluster heads to sink node is selected based on the fit factor. This paper's main intention is to provide an extensive comparative study of the FEWA with all standard optimization-based clustering and routing techniques. This method's performance is compared with existing optimized clustering methods like GA, PSO, ACO, DE and EWO in terms of the number of energy, delay, and throughput. At the end of 1000 iterations, the analysis shows that the FEWA outperforms existing methods with maximum average remaining energy of the nodes as 0.216J, the minimum average delay of 0.208 sec and maximum average throughput of 88.57% for 100 nodes.

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Influence of bed temperature on performance of silica gel/methanol adsorption refrigeration system at adsorption equilibrium

Cited by 19 publications

References 21 publications

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

The Impact of Leadership Styles on Employees Productivity in Organizations: A Comparative Study Among Leadership Styles

Harvesting social media sentiment analysis to enhance stock market prediction using deep learning

Performance Analysis of Fractional Earthworm Optimization Algorithm for Optimal Routing in Wireless Sensor Networks

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