Sampath Dakshina Murthy Achanta, Karthikeyan T. and Vinoth Kanna R.
The recent advancement in gait analysis combines internet of things that provides better observations of person living behavior. The biomechanical model used for elderly and…
Abstract
Purpose
The recent advancement in gait analysis combines internet of things that provides better observations of person living behavior. The biomechanical model used for elderly and physically challenged persons is related to gait-related parameters, and the accuracy of the existing systems significantly varies according to different person abilities and their challenges. The paper aims to discuss these issues.
Design/methodology/approach
Deployment of wearable sensors in gait analysis provides a better solution while tracking the changes of the personal style, and this proposed model uses an electronics system using force sensing resistor and body sensors.
Findings
Experimental results provide an average gait recognition of 95 percent compared to the existing neural network-based gait analysis model based on the walking speeds and threshold values.
Originality/value
The sensors are used to monitor and update the predicted values of a person for analysis. Using IoT a communication process is performed in the research work by identifying a physically challenged person even in crowded areas.
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Due to the large-size, non-uniform transactions per day, the money laundering detection (MLD) is a time-consuming and difficult process. The major purpose of the proposed…
Abstract
Purpose
Due to the large-size, non-uniform transactions per day, the money laundering detection (MLD) is a time-consuming and difficult process. The major purpose of the proposed auto-regressive (AR) outlier-based MLD (AROMLD) is to reduce the time consumption for handling large-sized non-uniform transactions.
Design/methodology/approach
The AR-based outlier design produces consistent asymptotic distributed results that enhance the demand-forecasting abilities. Besides, the inter-quartile range (IQR) formulations proposed in this paper support the detailed analysis of time-series data pairs.
Findings
The prediction of high-dimensionality and the difficulties in the relationship/difference between the data pairs makes the time-series mining as a complex task. The presence of domain invariance in time-series mining initiates the regressive formulation for outlier detection. The deep analysis of time-varying process and the demand of forecasting combine the AR and the IQR formulations for an effective outlier detection.
Research limitations/implications
The present research focuses on the detection of an outlier in the previous financial transaction, by using the AR model. Prediction of the possibility of an outlier in future transactions remains a major issue.
Originality/value
The lack of prior segmentation of ML detection suffers from dimensionality. Besides, the absence of boundary to isolate the normal and suspicious transactions induces the limitations. The lack of deep analysis and the time consumption are overwhelmed by using the regression formulation.
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Sivasankaran Sivanandam, Chandrapushpam Thangaraj and M. Bhuvaneswari
This study aims to present the consequences of activation energy and the chemical reactions on the unsteady MHD squeezing flow of an incompressible ternary hybrid nanofluid (THN…
Abstract
Purpose
This study aims to present the consequences of activation energy and the chemical reactions on the unsteady MHD squeezing flow of an incompressible ternary hybrid nanofluid (THN) comprising magnetite (FE3O4), multiwalled carbon nano-tubes (MWCNT) and copper (Cu) along with water (H2O) as the base fluid. This investigation is performed within the framework of two moving parallel plates under the influence of magnetic field and viscous dissipation.
Design/methodology/approach
Due to the complementary benefits of nanoparticles, THN is used to augment the heat transmit fluid’s efficacy. The flow situation is expressed as a system of dimensionless, nonlinear partial differential equations, which are reduced to a set of nonlinear ordinary differential equations (ODEs) by suitable similarity substitutions. These transformed ODEs are then solved through a semianalytical technique called differential transform method (DTM). The effects of several changing physical parameters on the flow, temperature, concentration and the substantial measures of interest have been deliberated through graphs. This study verifies the reliability of the results by performing a comparison analysis with prior researches.
Findings
The enhanced activation energy results in improved concentration distribution and declined Sherwood number. Enhancement in chemical reaction parameter causes disparities in concentration of the ternary nanofluid. When the Hartmann number is zero, value of skin friction is high, but Nusselt and Sherwood numbers values are small. Rising nanoparticles concentrations correspond to a boost in overall thermal conductivity, causing reduced temperature profile.
Research limitations/implications
Due to its firm and simple nature, its implications are in various fields like chemical industry and medical industry for designing practical problems into mathematical models and experimental analysis.
Practical implications
Deployment of the squeezed flow of ternary nanofluid with activation energy has significant consideration in nuclear reactors, vehicles, manufacturing facilities and engineering environments.
Social implications
This study would be contributing significantly in the field of medical technology for treating cancer through hyperthermia treatment, and in industrial processes like water desalination and purification.
Originality/value
In this problem, a semianalytical approach called DTM is adopted to explore the consequences of activation energy and chemical reactions on the squeezing flow of ternary nanofluid.
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Dipanwita Chakraborty and Jitendra Mahakud
This paper aims to examine the impact of chief executive officer (CEO) attributes on foreign shareholdings from the perspective of an emerging economy.
Abstract
Purpose
This paper aims to examine the impact of chief executive officer (CEO) attributes on foreign shareholdings from the perspective of an emerging economy.
Design/methodology/approach
This study examined Bombay Stock Exchange listed firms from the Indian stock market and applied a balanced panel data approach with fixed effect estimation technique during the period 2010–2019.
Findings
The study shows that CEOs’ financial education and a higher level of education positively affect foreign shareholdings. The age and experience of CEO have a positive and significant impact on foreign shareholdings. Firms with male CEOs are preferred more by foreign investors. The effect of CEO busyness and CEO duality is negative on foreign shareholdings. Foreign investors prefer to invest in firms with foreign nationality CEOs. Furthermore, the robustness test reveals that the influence of CEO attributes on foreign shareholdings is stronger for new, small and stand-alone firms than for old, large and group-affiliated firms.
Practical implications
The study will be beneficial for a diverse audience ranging from firms’ board of directors, regulators and policymakers who are entrusted with the CEO recruitment process. Additionally, firms seeking external financing should disclose CEO information adequately and improve the reporting quality to attract foreign investors, as they consider CEO characteristics as a valuable signal before making investment decisions.
Originality/value
In light of the current legislative reforms, this study can be recognized as one of the early studies that explore the relationship between CEO attributes and foreign shareholdings in the context of an emerging economy.
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Padmavathi Koride, Sirish Venkatagiri and Ganesh L.
After completion of this case study, students will be able to apply the triple bottom line concept to a spice manufacturing and export company (RBT 3); to examine the options…
Abstract
Learning outcomes
After completion of this case study, students will be able to apply the triple bottom line concept to a spice manufacturing and export company (RBT 3); to examine the options before Value Ingredients Private Limited (VIPL), namely, to cultivate spices in the traditional way versus adopting integrated pest management (IPM) to cater to international markets (RBT 4); to analyse the returns for an IPM farmer vis-à-vis a conventional farmer, and to compare the returns therein (RBT 4); and to evaluate the ways and means of engaging farmers to change their way of cultivation (RBT 5)
Case overview/synopsis
The COVID-19 pandemic heightened awareness about the benefits of spices and buoyed its demand worldwide, which presented an opportunity to VIPL, a spice manufacturing company based in Chennai, to expand its business. However, the export markets demanded residue-free spices grown with little or no use of pesticides. Traditional farmers supplying spices to VIPL were accustomed to spraying pesticides whenever there was a pest attack. This case study discussed the options that the protagonist Mr Sijil Karim, managing director and CEO of VIPL, had, who wanted to onboard farmers for pesticide-free cultivation. The options before him were either to continue traditional farming or adopt IPM. This case study discussed the merits, demerits and challenges of each of these options.
The triple bottom line concept discussed three Ps – people, planet and prosperity – for this case as follows: The farmers and the consumers constituted the people in the spice supply chain. The farmers supplying organic, export-worthy spices under the guidance of VIPL gained 30% more than regular spice farmers, which were accrued through cost savings and better prices. The consumers benefitted from the pesticide-free, organic spices through accrued health gains. The manufacture of organic, pesticide-free spices helped the planet, as the process did not release hazardous chemicals into the atmosphere. VIPL manufactured pesticide-free spice with a focus on prosperity.
Complexity academic level
The case study can be introduced in a course on sustainability while discussing the triple bottom line concept. This case study showed how a for-profit company grew without losing sight of the planet or its focus on people. This case is best suited for students who have preliminary knowledge of supply chain management, operations and sustainability. Therefore, it is suited for sophomore-year students of MBA.
Supplementary materials
Teaching notes are available for educators only.
Subject code
CSS 11: Strategy.
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Praveen Kumar Lendale and N.M. Nandhitha
Speckle noise removal in ultrasound images is one of the important tasks in biomedical-imaging applications. Many filtering -based despeckling methods are discussed in many…
Abstract
Purpose
Speckle noise removal in ultrasound images is one of the important tasks in biomedical-imaging applications. Many filtering -based despeckling methods are discussed in many existing works. Two-dimensional (2-D) transforms are also used enormously for the reduction of speckle noise in ultrasound medical images. In recent years, many soft computing-based intelligent techniques have been applied to noise removal and segmentation techniques. However, there is a requirement to improve the accuracy of despeckling using hybrid approaches.
Design/methodology/approach
The work focuses on double-bank anatomy with framelet transform combined with Gaussian filter (GF) and also consists of a fuzzy kind of clustering approach for despeckling ultrasound medical images. The presented transform efficiently rejects the speckle noise based on the gray scale relative thresholding where the directional filter group (DFB) preserves the edge information.
Findings
The proposed approach is evaluated by different performance indicators such as the mean square error (MSE), peak signal to noise ratio (PSNR) speckle suppression index (SSI), mean structural similarity and the edge preservation index (EPI) accordingly. It is found that the proposed methodology is superior in terms of all the above performance indicators.
Originality/value
Fuzzy kind clustering methods have been proved to be better than the conventional threshold methods for noise dismissal. The algorithm gives a reconcilable development as compared to other modern speckle reduction procedures, as it preserves the geometric features even after the noise dismissal.
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Kapil Bansal, Aseem Chandra Paliwal and Arun Kumar Singh
Technology advancement has changed how banks operate. Modernizing technology has, on the one hand, made it simpler for banks to do their daily business, but it has also increased…
Abstract
Purpose
Technology advancement has changed how banks operate. Modernizing technology has, on the one hand, made it simpler for banks to do their daily business, but it has also increased cyberattacks. The purpose of the study is to to determine the factors that have the most effects on online fraud detection and to evaluate the advantages of AI and human psychology research in preventing online transaction fraud. Artificial intelligence has been used to create new techniques for both detecting and preventing cybercrimes. Fraud has also been facilitated in some organizations via employee participation.
Design/methodology/approach
The main objective of the research approach is to guide the researcher at every stage to realize the main objectives of the study. This quantitative study used a survey-based methodology. Because it allows for both unbiased analysis of the relationship between components and prediction, a quantitative approach was adopted. The study of the body of literature, the design of research questions and the development of instruments and procedures for data collection, analysis and modeling are all part of the research process. The study evaluated the data using Matlab and a structured model analysis method. For reliability analysis and descriptive statistics, IBM SPSS Statistics was used. Reliability and validity were assessed using the measurement model, and the postulated relationship was investigated using the structural model.
Findings
There is a risk in scaling at a fast pace, 3D secure is used payer authentication has a maximum mean of 3.830 with SD of 0.7587 and 0.7638, and (CE2).
Originality/value
This study focused on investigating the benefits of artificial intelligence and human personality study in online transaction fraud and to determine the factors that affect something most strongly on online fraud detection. Artificial intelligence and human personality in the Indian banking industry have been emphasized by the current research. The study revealed the benefits of artificial intelligence and human personality like awareness, subjective norms, faster and more efficient detection and cost-effectiveness significantly impact (accept) online fraud detection in the Indian banking industry. Also, security measures and better prediction do not significantly impact (reject) online fraud detection in the Indian banking industry.
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Kai Yang, Mingli Jiao, Sifan Wang, Yuanyuan Yu, Quan Diao and Jian Cao
The purpose of this paper is to investigate thermoregulation properties of different composite phase change materials (PCMs), which could be used in the high temperature…
Abstract
Purpose
The purpose of this paper is to investigate thermoregulation properties of different composite phase change materials (PCMs), which could be used in the high temperature environmental conditions to protect human body against the extra heat flow.
Design/methodology/approach
Three kinds of composite PCM samples were prepared using the selected pure PCMs, including n-hexadecane, n-octadecane and n-eicosane. The DSC experiment was performed to get the samples’ phase change temperature range and enthalpy. The simulated high temperature experiments were performed using human arms in three different high temperature conditions (40°C, 45°C, 50°C), and the skin temperature variation curves varying with time were obtained. Then a comprehensive index TGP was introduced from the curves and calculated to evaluate the thermoregulation properties of different composite PCM samples comprehensively.
Findings
Results show that the composite PCM samples could provide much help to the high temperature human body. It could decrease the skin temperature quickly in a short time and it will not cause the over-cooling phenomenon. Comparing with other two composite PCM samples, the thermoregulation properties of the n-hexadecane and n-eicosane composite PCM is the best.
Originality/value
Using the n-hexadecane and n-eicosane composite PCM may provide people with better protection against the high temperature conditions, which is significative for the manufacture of functional thermoregulating textiles, garments or equipments.
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The purpose of this paper is to look at the contemporaneous movement of the stock market indices of the five most COVID-infected countries, namely, the USA, Brazil, Russia, India…
Abstract
Purpose
The purpose of this paper is to look at the contemporaneous movement of the stock market indices of the five most COVID-infected countries, namely, the USA, Brazil, Russia, India and UK after the first wave along with market indices of the three least affected countries, namely, Hong Kong, South Korea and New Zealand during the first wave.
Design/methodology/approach
Data have been collected from the website of Yahoo finance on daily closing values of five indices. Augmented Dickey–Fuller test with its three forms has been applied to check the stationarity of the select five indices at the level and at the first difference before the pandemic, during the pandemic and post-first wave of the pandemic. Johansen cointegration test is applied to find out that there is no cointegration among the select five indices.
Findings
The five countries do neither fall in the same economic and political zone nor do they have the same economic status. But during the period of pandemic and the new-normal period, the cointegration is very distinct. The developing and developed nations thus stood at an indifferentiable stage of the economic crisis which is well reflected in their stock markets. However, the least three COVID-affected countries do not show any cointegration during the pandemic time.
Originality/value
The comovement even seen during the normal time in the other studies is not compared to a similar period in earlier years. But, in this study to look into the exclusive effect of COVID pandemic, the period most affected with it is compared with the period after it and that in the immediate past year had no effect.
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The purpose of this study is to present a comprehensive review of the fundamental concepts and terminologies pertaining to different types of aluminium metal matrix composites…
Abstract
Purpose
The purpose of this study is to present a comprehensive review of the fundamental concepts and terminologies pertaining to different types of aluminium metal matrix composites, their joining techniques and challenges, friction stir welding (FSW) process, post-welding characterizations and basic control theory of FSW, followed by the discussions on the research reports in these areas.
Design/methodology/approach
Joining of aluminium metal matrix composites (Al-MMC) poses many challenges. These materials have their demanding applications in versatile domains, and hence it is essential to understand their weldability and material characteristics. FSW is a feasible choice for joining of Al-MMC over the fusion welding because of the formation of narrow heat affected zone and minimizing the formation of intermetallic compounds at weld interface. The goal in FSW is to generate enough thermal energy by friction between the workpiece and rotating tool. Heat energy is generated by mechanical interaction because of the difference in velocity between the workpiece and rotating tool. In the present work, a detailed survey is done on the above topics and an organised conceptual context is presented. A complete discussion on significance of FSW process parameters, control schemes, parameter optimization and weld quality monitoring are presented, along with the analysis on relation between the interdependent parameters.
Findings
Results from the study present the research gaps in the FSW studies for joining of the aluminium-based metal matrix composites, and they highlight further scope of studies pertaining to this domain.
Originality/value
It is observed that the survey done on FSW of Al-MMCs and their control theory give an insight into the fundamental concepts pertaining to this research area to enhance interdisciplinary technology exploration.