Padmavati Shrivastava, K.K. Bhoyar and A.S. Zadgaonkar
The purpose of this paper is to build a classification system which mimics the perceptual ability of human vision, in gathering knowledge about the structure, content and the…
Abstract
Purpose
The purpose of this paper is to build a classification system which mimics the perceptual ability of human vision, in gathering knowledge about the structure, content and the surrounding environment of a real-world natural scene, at a quick glance accurately. This paper proposes a set of novel features to determine the gist of a given scene based on dominant color, dominant direction, openness and roughness features.
Design/methodology/approach
The classification system is designed at two different levels. At the first level, a set of low level features are extracted for each semantic feature. At the second level the extracted features are subjected to the process of feature evaluation, based on inter-class and intra-class distances. The most discriminating features are retained and used for training the support vector machine (SVM) classifier for two different data sets.
Findings
Accuracy of the proposed system has been evaluated on two data sets: the well-known Oliva-Torralba data set and the customized image data set comprising of high-resolution images of natural landscapes. The experimentation on these two data sets with the proposed novel feature set and SVM classifier has provided 92.68 percent average classification accuracy, using ten-fold cross validation approach. The set of proposed features efficiently represent visual information and are therefore capable of narrowing the semantic gap between low-level image representation and high-level human perception.
Originality/value
The method presented in this paper represents a new approach for extracting low-level features of reduced dimensionality that is able to model human perception for the task of scene classification. The methods of mapping primitive features to high-level features are intuitive to the user and are capable of reducing the semantic gap. The proposed feature evaluation technique is general and can be applied across any domain.
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Senda Belhaj Slimene, Hela Borgi and Hakim Ben Othman
The study aims to investigate the relationship between E-government and corruption. It also examines the moderator role of national culture through Hofstede’s dimensions on the…
Abstract
Purpose
The study aims to investigate the relationship between E-government and corruption. It also examines the moderator role of national culture through Hofstede’s dimensions on the association between E-government and corruption.
Design/methodology/approach
In addition to panel regression techniques, the authors use the random forest method to assess the order of importance of all significant variables in determining corruption. The sample of this study consists of 55 countries during 2008–2020 period.
Findings
The results show that E-government is negatively correlated with corruption. The authors also find that both economic and cultural variables play an important role in determining corruption. However, religion has no impact on corruption. The results can potentially assist regulators and policy-makers when trying to control corruption as they should take into consideration the cultural background of citizens when making rules and procedures that aim at reducing corruption.
Originality/value
The current study uses random forests model, which allows the regression of variables based on the construction of a multitude of decision trees. The main contribution of using this model compared to the other regression models used in prior studies is to extract the relative importance of each significant variable. More precisely, it evaluates the rank of importance for each significant variable that drives corruption rather than merely identifying variables that drive corruption regardless of their relative importance.
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Mohammad Mahdi Ershadi and Abbas Seifi
This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment. For this purpose, different classification methods…
Abstract
Purpose
This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment. For this purpose, different classification methods based on data, experts’ knowledge and both are considered in some cases. Besides, feature reduction and some clustering methods are used to improve their performance.
Design/methodology/approach
First, the performances of classification methods are evaluated for differential diagnosis of different diseases. Then, experts' knowledge is utilized to modify the Bayesian networks' structures. Analyses of the results show that using experts' knowledge is more effective than other algorithms for increasing the accuracy of Bayesian network classification. A total of ten different diseases are used for testing, taken from the Machine Learning Repository datasets of the University of California at Irvine (UCI).
Findings
The proposed method improves both the computation time and accuracy of the classification methods used in this paper. Bayesian networks based on experts' knowledge achieve a maximum average accuracy of 87 percent, with a minimum standard deviation average of 0.04 over the sample datasets among all classification methods.
Practical implications
The proposed methodology can be applied to perform disease differential diagnosis analysis.
Originality/value
This study presents the usefulness of experts' knowledge in the diagnosis while proposing an adopted improvement method for classifications. Besides, the Bayesian network based on experts' knowledge is useful for different diseases neglected by previous papers.
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Innovation and entrepreneurship are regarded as the key drivers to steer the engine of economic development in any nation. As a result, to understand the context and process of…
Abstract
Purpose
Innovation and entrepreneurship are regarded as the key drivers to steer the engine of economic development in any nation. As a result, to understand the context and process of innovation and entrepreneurship there has been a steady rise in scientific literature and empirical studies. The purpose of this paper is to study the trends and progress of academic research on innovation and entrepreneurship in India by identifying the key articles, journals, authors and institutions.
Design/methodology/approach
Scientometric methods especially bibliometrics is used, for measuring the maturity of this research field in the country. The paper studies the research landscape in innovation and entrepreneurship in India by doing a bibliometric analysis using data from publications indexed in the Scopus database from the year 2000 to 2018. The study takes a multidisciplinary review of the literature in innovation and entrepreneurship research in India and could be used as a reference for future studies in this theme.
Findings
The study finds an increase in the scholarly studies in innovation and entrepreneurship in India in the last decade. It was also found that a large number of publications were joint-authored and collaborations between Indian and foreign universities is happening. The paper also highlights the authorship patterns, top journals and the most cited papers.
Research limitations/implications
A major limitation of this study is that it has considered publications which are indexed in Scopus. This paper has contributed by highlighting the growth of studies in the field of innovation and entrepreneurship in the Indian context. The results can be used by future studies in this area as a starting point to highlight the nature of this research area.
Originality/value
The study attempts to present a trend analysis of published literature on innovation and entrepreneurship in India.
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Anuj Kumar, Arya Kumar, Sanjay Bhoyar and Ashutosh Kumar Mishra
This paper analyzes the ethics of integrating Artificial Intelligence (AI), particularly regarding AI-generated educational content in academia. It attempts to explore how AI…
Abstract
Purpose
This paper analyzes the ethics of integrating Artificial Intelligence (AI), particularly regarding AI-generated educational content in academia. It attempts to explore how AI customization mimics human interaction and behavior in education, investigate ethical concerns in educational AI adoption, and assess ChatGPT’s ethical use for nurturing curiosity and maintaining academic integrity in education.
Design/methodology/approach
Fictional tales may help us think critically and creatively to uncover hidden truths. The narratives are analyzed to determine the affordances and drawbacks of Artificial Intelligence in Education (AIEd).
Findings
The study highlights the imperative for innovative, ethically grounded strategies in harnessing AI/GPT technology for education. AI can enhance learning, and human educators’ irreplaceable role is even more prominent, emphasizing the need to harmonize technology with pedagogical principles. However, ensuring the ethical integration of AI/GPT technology demands a delicate balance where the potential benefits of technology should not eclipse the essential role of human educators in the learning process.
Originality/value
This paper presents futuristic academic scenarios to explore critical dimensions and their impact on 21st century learning. As AI assumes tasks once exclusive to human educators, it is essential to redefine the roles of both technology and human teachers, focusing on the future.
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Hannah R. Marston, Linda Shore, Laura Stoops and Robbie S. Turner
Rajiv Gopalkrishna Divekar, Pradnya Vishwas Chitrao and Pravin Kumar Bhoyar
Strategic marketing, Downturn, Optimal utilisation of minimal resources, Consolidating profitability, Focus shift from features to benefits and cost savings.
Abstract
Subject area
Strategic marketing, Downturn, Optimal utilisation of minimal resources, Consolidating profitability, Focus shift from features to benefits and cost savings.
Study level/applicability
Management students who have knowledge of basic concepts of management discipline to derive the maximum benefit and understand the applicability; budding entrepreneurs; middle- and senior-level executives in an executive development program; people running family-owned businesses.
Case overview
In 2008-2009, the Indian manufacturing sector was facing stiff competition from China on account of the latter's ability to provide cheap labour and handle large volumes. The 2008-2009 economic down turn saw consumers cut down on their requirements with manufacturing companies getting fewer orders. Manufacturing companies therefore adopted the principle of optimal utilisation of minimal resources. Millennium Company Ltd (MCL) also succeeded in overcoming the 2008-2009 downturns through a shift in focus during the recession of 2009 from achieving pure revenue to consolidating its profitability. MCL is probably the only company in the world to have extensive expertise in both steam and control instrumentation. The dual expertise allows them to engineer industry-specific systems that focus on energy efficiency and utilities management for sectors as diverse as textiles, food processing, paper, power and chemicals etc. The company shifted its attention from features to benefits, cost savings, and profitability. MCL trained its people as to what to talk to whom. Today, MCL is a leader in India in process efficiency and energy conservation through technology tie-ups and focused investments in manufacturing and research.
Expected learning outcomes
The purpose of this case is to enable student managers to evaluate effectiveness of corporate strategies; make the student managers understand the resources–businesses–systems framework and the need for focused connection between these three through appropriate coordination and control mechanisms for a corporate strategy to deliver value; encourage students to apply their knowledge of Turnkey Projects, BCG/Porters/SWOT/Mackensys Model; encourage the students to research and find out how other companies in this field fared and what were the strategies adopted by them to overcome the recession and compete with MCL in a highly competitive market like that of India; and encourage student managers to go on field visits with the institute's help to similar organisations within the same city and if possible get live projects.
Supplementary materials
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Shahala Sheikh, Lalsingh Khalsa and Vinod Varghese
The influence of the temperature discrepancy parameter and higher order of the time-derivative is discussed. Classical coupled and generalized hygrothermoelasticity models are…
Abstract
Purpose
The influence of the temperature discrepancy parameter and higher order of the time-derivative is discussed. Classical coupled and generalized hygrothermoelasticity models are recovered by considering the various special cases and illustrated graphically.
Design/methodology/approach
The theory of integral transformations has been used to study a new hygrothermal model that includes higher-order time derivatives with three-phase-lags and memory-dependent derivatives (MDD). This model considers the microscopic structure’s influence on a non-simple hygrothermoelastic infinitely long cylinder. The generalized Fourier and Fick’s law was adopted to derive the linearly coupled partial differential equations with higher-order time-differential with the two-phase lag model, including memory-dependent derivatives for the hygrothermal field. The investigation of microstructural interactions and the subsequent hygrothermal change has been undertaken as a result of the delay time and relaxation time translations.
Findings
These two-phase-lag models are also practically applicable in modeling nanoscale heat and moisture transport problems applied to almost all important devices. This work will enable future investigators to gain insight into non-simple hygrothermoelasticity with different phase delays of higher order in detail.
Originality/value
To the best of my knowledge, and after completing an intensive search of the relevant literature, the author could not learn any published research that presents a general solution for a higher-order time-fractional three-phase-lag hygrothermoelastic infinite circular cylinder with memory memory-dependent derivative.
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Trish - Oberweis, Abigail Keller and Michael Lewis
In the absence of new funding dedicated to cold case investigation, innovation is required.
Abstract
Purpose
In the absence of new funding dedicated to cold case investigation, innovation is required.
Design/methodology/approach
The number of unresolved homicides in the USA has surpassed a quarter million, and the figure grows by thousands every year. Homicides that do not yield a quick arrest are time and labor intensive. This creates a staffing and resource dilemma for law enforcement administrators, as allocating time for older cases comes at the expense of investigating current ones, and vice versa.
Findings
Universities offer the enthusiastic labor of college students to “defrost” cold cases. One such partnership has been in place for nearly three years in an unusual collaboration between a state police agency and a regional state university. Small groups of students systematically organize, review and present case files. They create investigative recommendations and prioritize cases by solvability. Investigators can then select a case that may be relatively close to an arrest, access the case details very quickly and have the investigative recommendations as a place to begin a renewed investigation. Additionally, cases that are appropriate for new forensic testing or new forensic tools are identified and advanced.
Originality/value
Partnerships such the one described here are rare but lucrative. We recommend new collaborations like ours to reduce the number of unresolved homicide cases.