Arslan Akram, Saba Ramzan, Akhtar Rasool, Arfan Jaffar, Usama Furqan and Wahab Javed
This paper aims to propose a novel splicing detection method using a discriminative robust local binary pattern (DRLBP) with a support vector machine (SVM). Reliable detection of…
Abstract
Purpose
This paper aims to propose a novel splicing detection method using a discriminative robust local binary pattern (DRLBP) with a support vector machine (SVM). Reliable detection of image splicing is of growing interest due to the extensive utilization of digital images as a communication medium and the availability of powerful image processing tools. Image splicing is a commonly used forgery technique in which a region of an image is copied and pasted to a different image to hide the original contents of the image.
Design/methodology/approach
The structural changes caused due to splicing are robustly described by DRLBP. The changes caused by image forgery are localized, so as a first step, localized description is divided into overlapping blocks by providing an image as input. DRLBP descriptor is calculated for each block, and the feature vector is created by concatenation. Finally, features are passed to the SVM classifier to predict whether the image is genuine or forged.
Findings
The performance and robustness of the method are evaluated on public domain benchmark data sets and achieved 98.95% prediction accuracy. The results are compared with state-of-the-art image splicing finding approaches, and it shows that the performance of the proposed method is improved using the given technique.
Originality/value
The proposed method is using DRLBP, an efficient texture descriptor, which combines both corner and inside design detail in a single representation. It produces discriminative and compact features in such a way that there is no need for the feature selection process to drop the redundant and insignificant features.
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Ayesha Afzal, Saba Fazal Firdousi and Kamil Mahmood
The purpose of this paper is to examine the relationship that exists between financial depth and economic growth in Poland for the years 1995–2019. This paper utilizes integration…
Abstract
Purpose
The purpose of this paper is to examine the relationship that exists between financial depth and economic growth in Poland for the years 1995–2019. This paper utilizes integration and co-integration techniques to capture the long-term and short-term linkages between various determinants of financial deepening, economic growth and a few selected growth variables. Financial depth is measured using two distinct measures: the monetization ratio (i.e. the ratio of broad money in the economy to the gross domestic product (GDP)) and the domestic credit provided to private sector by banks.
Design/methodology/approach
The paper uses a combination of Augmented Dickey–Fuller (ADF) and Phillips–Perron unit root tests, autoregressive distributive lag (ARDL) model and Granger causality tests to estimate results.
Findings
This paper finds that there is a bidirectional causal relationship between financial deepening and economic growth in the short run, but this relationship does not hold in the long run. The control variables comprising trade volume, investment, government spending and volatility in oil prices and inflation have a significant, positive relationship with economic development in the long run.
Originality/value
The findings are indicative of the need for further strengthening of the financial sector in Poland, such that the relationship between financial depth and economic growth is substantiated in the long run. This paper also finds room for more stringent regulation of the financial system and transparency in information available.
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Muhammad Zubair Alam, Ahmad Raza Bilal, Saba Sabir and Muhammad Ali Kaleem
The dynamic global environment has increased the requirement of multidisciplinary entrepreneurial engineers. While studying entrepreneurial aspects of engineers, researchers have…
Abstract
Purpose
The dynamic global environment has increased the requirement of multidisciplinary entrepreneurial engineers. While studying entrepreneurial aspects of engineers, researchers have not considered inherent variability due to engineering majors. This study investigates the impact of entrepreneurial motivation (EM) on entrepreneurial intentions (EIs), to analyse the inherent entrepreneurial potential of engineering majors. The impact of entrepreneurial education has also been studied to proffer recommendations for policymakers.
Design/methodology/approach
The design of this study is a survey conducted with 342 undergraduate students from three major engineering institutions in Pakistan using a close-structured questionnaire. Moderation analysis examines the entrepreneurial potential of different engineering majors. Analysis of variance (ANOVA) has been conducted to compare the EIs of different engineering majors and regarding the impact of entrepreneurial education on EIs.
Findings
The engineering major's role in the transformation of EM to EIs is multifaceted. EIs of students of a few engineering majors were found high. Entrepreneurship education improves the overall EIs of engineering students.
Practical implications
Outcomes of the study are useful for academia and policymakers to engage students of particular engineering majors, identified as entrepreneurial, in advanced entrepreneurial education and expose them to potential start-ups to have better value addition in specific sectors.
Originality/value
This is the first study in which engineering majors have been examined to bring insights about inherent entrepreneurial potential. This inherent entrepreneurial potential needs further exploration by academic researchers. The study has provided the base for future studies to institutionalize entrepreneurial education for different engineering majors.
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Gangadhar Kotha, Keziya Kukkamalla and S.M. Ibrahim
The purpose of this paper is to examine the magneto hydrodynamic flow and heat transfer of nanofluids over a permeable wedge based on engine oil which is under the effects of…
Abstract
Purpose
The purpose of this paper is to examine the magneto hydrodynamic flow and heat transfer of nanofluids over a permeable wedge based on engine oil which is under the effects of thermal radiation and convective heating.
Design/methodology/approach
The equations governing the flow are transformed into differential equations by applying similarity transformations. Keller box method is used to bring out the numerical solution.
Findings
The discovery interprets that temperature as well as the velocity of Ag-engine oil nanofluids are more noticeable than Cu-engine oil nanofluids. Thermal boundary layer increases for radiation parameter as well as Biot number. Fluctuations of co-efficient of drag skin friction as well heat transfer rate at the wall are also tested.
Originality/value
Till now, no numerical studies are reported on the heat transfer enhancement of the permeable wedge under thermal radiation on engine oil nanofluid flow by considering convective heating.
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To elucidate the factors influencing suboptimal food (SF) purchase intention among Taiwanese consumers, this study extended the theory of planned behaviour (TPB) model by…
Abstract
Purpose
To elucidate the factors influencing suboptimal food (SF) purchase intention among Taiwanese consumers, this study extended the theory of planned behaviour (TPB) model by incorporating driving factors that encourage purchasing of SFs, that is, incorporating food waste awareness and personal norms. The inhibiting moderator of health consciousness and facilitating moderator of price consciousness were also considered.
Design/methodology/approach
A total of 305 online questionnaire responses were analysed. Moderated regression analysis was performed to test the hypotheses proposed in this study.
Findings
Consumer attitudes toward purchasing SFs and perceived behavioural control as well as their food waste awareness and personal norms are determinants of their SF purchase intention. Health consciousness inhibits SF purchase intention, and price consciousness promotes SF purchase intention. In addition, the moderating effect of health consciousness reverses the positive relationship between personal norms and SF purchase intention, turning the relationship negative. However, the moderating effect of price consciousness strengthens the positive relationship between personal norms and SF purchase intention.
Originality/value
In addition to extending the TPB model, this study considered the main effects and moderating effects of health consciousness and price consciousness on consumers’ intention to purchase SF. The research findings contribute to the understanding of the relevant factors that influence Taiwanese consumers’ SF purchase intention. The study also outlines the implications of its findings in terms of encouraging consumers to purchase SFs to reduce food waste.
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Shenlong Wang, Kaixin Han and Jiafeng Jin
In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The term of…
Abstract
Purpose
In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The term of feature extraction is used in two cases: application-based feature expression and mathematical approaches for dimensionality reduction. Feature expression is a technique of describing the image color, texture and shape information with feature descriptors; thus, obtaining effective image features expression is the key to extracting high-level semantic information. However, most of the previous studies regarding image feature extraction and expression methods in the CBIR have not performed systematic research. This paper aims to introduce the basic image low-level feature expression techniques for color, texture and shape features that have been developed in recent years.
Design/methodology/approach
First, this review outlines the development process and expounds the principle of various image feature extraction methods, such as color, texture and shape feature expression. Second, some of the most commonly used image low-level expression algorithms are implemented, and the benefits and drawbacks are summarized. Third, the effectiveness of the global and local features in image retrieval, including some classical models and their illustrations provided by part of our experiment, are analyzed. Fourth, the sparse representation and similarity measurement methods are introduced, and the retrieval performance of statistical methods is evaluated and compared.
Findings
The core of this survey is to review the state of the image low-level expression methods and study the pros and cons of each method, their applicable occasions and certain implementation measures. This review notes that image peculiarities of single-feature descriptions may lead to unsatisfactory image retrieval capabilities, which have significant singularity and considerable limitations and challenges in the CBIR.
Originality/value
A comprehensive review of the latest developments in image retrieval using low-level feature expression techniques is provided in this paper. This review not only introduces the major approaches for image low-level feature expression but also supplies a pertinent reference for those engaging in research regarding image feature extraction.