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Article
Publication date: 11 June 2018

Yuming Guan, Jingbo Mu, Hongwei Che, Xiaoliang Zhang and Zhixiao Zhang

The purpose of this study is to design carbon electrode materials for high performance electric double-layer capacitors (EDLCs) with pores that are large enough and have suitable…

177

Abstract

Purpose

The purpose of this study is to design carbon electrode materials for high performance electric double-layer capacitors (EDLCs) with pores that are large enough and have suitable pore size distribution for the electrolyte to access completely to improve EDLCs’ electrochemical performance.

Design/methodology/approach

This study develop an improved traditional KOH activation method, and a series of micro-meso hierarchical porous carbons have been successfully prepared from phenol formaldehyde resin by combining polyethylene glycol (PEG) and conventional KOH activation.

Findings

As evidenced by N2 adsorption/desorption tests, the obtained samples present Types IV and I-IV hybrid shape isotherms compared with KOH-activated resin (typical of Type I). The sample AC2-7-1, which the addition quantity of PEG is 25 per cent PF (weight ration) activated at 700? For 1 h is considered as the optimum preparation condition. It exhibits the highest specific capacitance value of 240 F/g in 30 wt% KOH aqueous electrolytes because of its higher specific surface area (2085 m2/g), greater pore volume (1.08 cm3/g) and the maximum mesoporosity (43 per cent). In addition, the capacity decay of this material is only 3.1 per cent after 1000 cycles.

Originality/value

The materials that are rich in micropores and mesopores show great potential in EDLC capacitors, particularly for applications where high power output and good high-frequency capacitive performances are required.

Details

World Journal of Engineering, vol. 15 no. 3
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 30 June 2023

Ruan Wang, Jun Deng, Xinhui Guan and Yuming He

With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data…

269

Abstract

Purpose

With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.

Design/methodology/approach

Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.

Findings

The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.

Originality/value

This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.

Details

Library Hi Tech, vol. 42 no. 6
Type: Research Article
ISSN: 0737-8831

Keywords

Available. Content available
Article
Publication date: 8 February 2013

Chrys Egan

516

Abstract

Details

Gender in Management: An International Journal, vol. 28 no. 1
Type: Research Article
ISSN: 1754-2413

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Article
Publication date: 10 September 2018

Muneer Shaik and Maheswaran S.

The purpose of this paper is twofold: first, to propose a new robust volatility ratio (RVR) that compares the intraday high–low volatility with that of the intraday open–close…

162

Abstract

Purpose

The purpose of this paper is twofold: first, to propose a new robust volatility ratio (RVR) that compares the intraday high–low volatility with that of the intraday open–close volatility estimator; and second, to empirically test the proposed RVR on the cross-sectional (CS) average of the constituent stocks of India’s BSE Sensex and US’s Dow Jones Industrial Average index to find the evidence of “excess volatility.”

Design/methodology/approach

The authors model the proposed RVR by assuming the logarithm of the price process to follow the Brownian motion. The authors have theoretically shown that the RVR is unbiased in the case of zero drift parameter. Moreover, the RVR is found to be an even function of the non-zero drift parameter.

Findings

The empirical results show that the analysis based on the RVR supports the existence of “excess volatility” in the CS average of the constituent stocks of India’s BSE Sensex and US’s Dow Jones index. In particular, the authors have observed that the CS average of individual constituent stocks of BSE Sensex is found to be more excessively volatile than the US’s Dow Jones index during the period of the study from January 2008 to September 2016, based on multiple k-day time window analysis.

Practical implications

The study has implications for the policy makers and practitioners who would like to understand the volatility behavior in the asset returns based on the RVR of this study. In general, the proposed model can be used as a specification tool to find whether the stock prices follow the random walk behavior or excessively volatile.

Originality/value

The authors contribute to the existing volatility literature in finance by proposing a new RVR based on extreme values of asset prices and absolute returns. The authors implement the bootstrap technique on RVR to find the estimates of mean and standard error for multiple k-day time windows. The RVR can capture the excess volatility by comparing two independent volatility estimators. This is possibly the first study to find the CS average of all the constituent stocks of BSE Sensex based on the RVR.

Details

Journal of Economic Studies, vol. 45 no. 4
Type: Research Article
ISSN: 0144-3585

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