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Cloud computing (CC) refers to the usage of virtualization technology to share computing resources through the internet. Task scheduling (TS) is used to assign computational resources to requests that have a high volume of pending processing. CC relies on load balancing to ensure that resources like servers and virtual machines (VMs) running on real servers share the same amount of load. VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data.

VMs are an important part of virtualization, where physical servers are transformed into VM and act as physical servers during the process. It is possible that a user’s request or data transmission in a cloud data centre may be the reason for the VM to be under or overloaded with data. With a large number of VM or jobs, this method has a long makespan and is very difficult. A new idea to cloud loads without decreasing implementation time or resource consumption is therefore encouraged. Equilibrium optimization is used to cluster the VM into underloaded and overloaded VMs initially in this research. Underloading VMs is used to improve load balance and resource utilization in the second stage. The hybrid algorithm of BAT and the artificial bee colony (ABC) helps with TS using a multi-objective-based system. The VM manager performs VM migration decisions to provide load balance among physical machines (PMs). When a PM is overburdened and another PM is underburdened, the decision to migrate VMs is made based on the appropriate conditions. Balanced load and reduced energy usage in PMs are achieved in the former case. Manta ray foraging (MRF) is used to migrate VMs, and its decisions are based on a variety of factors.

The proposed approach provides the best possible scheduling for both VMs and PMs. To complete the task, improved whale optimization algorithm for Cloud TS has 42 s of completion time, enhanced multi-verse optimizer has 48 s, hybrid electro search with a genetic algorithm has 50 s, adaptive benefit factor-based symbiotic organisms search has 38 s and, finally, the proposed model has 30 s, which shows better performance of the proposed model.

User’s request or data transmission in a cloud data centre may cause the VMs to be under or overloaded with data. To identify the load on VM, initially EQ algorithm is used for clustering process. To figure out how well the proposed method works when the system is very busy by implementing hybrid algorithm called BAT–ABC. After the TS process, VM migration is occurred at the final stage, where optimal VM is identified by using MRF algorithm. The experimental analysis is carried out by using various metrics such as execution time, transmission time, makespan for various iterations, resource utilization and load fairness. With its system load, the metric gives load fairness. How load fairness is worked out depends on how long each task takes to do. It has been added that a cloud system may be able to achieve more load fairness if tasks take less time to finish.

The purpose of this study is to examine the factors influencing the adoption and utilization of the online examination portal (OEP) in Indian universities. This study combines the Unified Theory of Acceptance and Usage of Technology (UTAUT) and Task Technology Fit (TTF) to explain the user's intention to use an OEP at an Indian University.

This study's methodology combines UTAUT as a theoretical framework with TTF. It is conceptualized that TTF has a moderating effect on UTAUT's primary construct. The authors collected the data from 182 graduate students from an Indian university. PLS-SEM is used to identify the causal relationship between the constructs using the structural equation modeling (SEM) technique.

The findings will demonstrate the applicability of the constructs of performance expectancy, effort expectancy and facilitating conditions in influencing the usage intention and behavior of students towards OEP. The outcome will also demonstrate the moderating effect of TTF on the predictors of intention to use OEP at an Indian University.

The sample respondents who participated in the study are students at the Indian University in Pune. The selection of samples was based on convenience sampling. Future research should be conducted at a variety of geographic locations, educational levels, undergraduate and graduate schools, as well as multiple universities. To increase the objectivity of sample selection, the probabilistic sampling method can be used to select samples. For future studies, larger sample sizes (more than 182) can be collected in order to increase the generalizability and applicability of the findings to other developing markets.

The study will aid Indian universities in enhancing the effectiveness of OEP. The study will also demonstrate the users' perception of the portal and their willingness to use it. It will also assist the university administration in finalizing the examination portal's implementation strategy.

Very few studies have been published on the factors influencing the acceptance and utilization of specific online examination systems. To address this underrepresentation, the current article investigates the factors and criteria that influence students' intent to use the OEP. The authors conceptualize the model using UTAUT as a theoretical foundation, which is absent from the published literature on the OEP. The study incorporated UTAUT and TTF to determine the impact on OEP usage and intent. In addition, the study contributes by testing the moderating effect of TTF on the UTAUT variables that influence the intention to use OEP.

The purpose of this paper is to empirically investigate the impact of board characteristics such as size, independence, busyness and duality on the extent of discretionary disclosures of listed Indian firms.

A disclosure index with 110 items was constructed to assess the discretionary disclosures in the annual reports of listed firms. The study measured disclosure using 1,024 firm-year observations over 8 years from 2009 to 2016. Board characteristics such as size, independence, busyness and duality have been used in the study as indicators of corporate governance.

The results indicate that while the proportion of independent directors positively impacts the extent of discretionary disclosures, boards with duality and the busyness of the director have a negative impact. The size of the board does not significantly impact the extent of disclosures.

This study examines the discretionary disclosures made only in the annual reports. Future studies could examine information disclosed in other media. Moreover, this study uses an un-weighted self-constructed disclosure index, which is subject to its inherent limitations.

This study has examined the impact of the “busyness” of the director on the extent of disclosures. This variable has not been explored in prior studies. The significance of the variable indicates that the number of directorships held impacts the efficiency with which a director performs his/her role in the board. The study reiterates the need for firms and policymakers to focus on improving board independence and to move away from leadership structures with duality.

The design phase is generally characterized with two-way multiple information exchanges/overlaps between the interdependent entities. In this paper, entity is a generic term to represent teams, components, activities or parameters. Existing approaches can either capture a single overlap or lack practical application in representing multiple overlaps. The beeline diagraming method (BDM) network is efficient in representing multiple overlaps for construction projects. However, it considers any entity as indivisible and cannot distinguish partial criticality of entities. In reality, the design phase in any construction project is driven by need basis and often has numerous interruptions. Hence, there is a need to develop an alternate network analysis for BDM for interruptible execution. The paper aims to discuss these issues.

A pilot study is conducted to formulate the hypothetical examples. Subsequently, these hypothetical BDM examples are analyzed to trace a pattern for criticality. This pattern study along with the existing precedence diagramming method network analysis enabled to derive new equations for forward pass, backward pass and float. Finally, the proposed concepts are applied to two design cases and reviewed with the design experts.

The proposed network analysis for BDM is efficient for interruptible entity execution.

The proposed BDM network is an information-intensive network that enables the design participants to view the project holistically. Application to two distinct cases emphasizes that the concept is generic and can be applied to any project that is characterized with beelines.

An alternate network analysis for BDM is investigated for interruptible entity execution. This study also clarifies the related concepts – interdependency, iteration, overlaps and multiple information exchanges/linkages.

Scheduling in information-driven design phase of construction projects is challenging due to multiple entity types (teams, components, deliverables, activities or parameters) and their dependencies/linkages. Established techniques such as dependency structure matrix (DSM), beeline diagramming method (BDM), multiple domain matrix (MDM), etc. have been independently utilized in past to model information dependencies/linkages and associated iteration. However, there has not been a holistic solution yet for scheduling multiple entity types and their relationships. Hence, an integrated solution needs to be developed that schedules information-driven projects accurately.

A case study data collection approach is utilized. With data from two projects, i.e. hostel design and highway design, a BDM–MDM integrated solution was developed and applied to the same. Feedback from experts was obtained for refinements.

The proposed solution is efficient for scheduling multiple entity types and their information dependencies/linkages.

The proposed integrated solution enables the project participants to schedule information-driven projects systematically. Application to two distinct design cases emphasizes that the concept is generic and can be applied to any information-driven project with multiple entity types.

The BDM–MDM integrated solution concept is investigated for scheduling multiple entity types in any information-driven projects. This study also explored the terminologies such as multiple entity types and information-driven scheduling.

The aim of this paper is to contribute to the services marketing literature by developing a scale based on Parasuraman’s SERVQUAL scale for the measurement of distributor perceived service quality at the distributor–manufacturer interface of the pharmaceutical supply chain.

Based on a literature review and discussions with experts, a questionnaire was designed basing on the widely used service quality measurement scale (SERVQUAL). Personal survey was conducted among selected distributors spread over three major cities of the Indian pharmaceutical market. The study used the exploratory factor analysis to identify the critical factors of service quality followed by the confirmatory factor analysis (AMOS 20).

A valid scale with four dimensions – (reliability, assurance, responsiveness and communication) and 13 items for measuring the distributor perceived service quality was developed which also satisfied all the reliability and validity tests. The findings of the present study indicate that distributor perceived service quality has an effect on satisfaction.

The proposed scale is an attempt to explore the less researched area. This study will give further insights to researchers to measure service quality at different phases of the pharmaceutical supply chain. The study is limited to three cities; it can be extended to other regions of the country. This study will be helpful to the practicing managers to measure the service quality and improve the performance in the pharmaceutical supply chain.

Service quality in pharmaceutical supply chain is very important, as it directly effects the health of the people, so the proposed scale can be used to control the quality of service.

The scale developed in this study can also be used for measuring distributor perceived service quality in other manufacturing sectors. This research provides direction and scope for further research to develop new concepts and models in measuring service quality in the supply chain.

The purpose of this paper is to develop a scale for the measurement of service quality at the manufacturer–doctor interface of the pharmaceutical supply chain and to study the impact of service quality on doctor’s satisfaction and doctor’s prescribing behavior. Doctors from two major states of South India were selected for the study. A doctor perceived service quality scale with three dimensions having eight items was developed through confirmatory factor analysis (CFA) in the pharmaceutical context. Structural equation modeling (SEM) technique was used to show the relationship between service quality, satisfaction and prescribing behavior. The critical factors of service quality were identified, and a model was developed showing the relationship between service quality, doctor’s satisfaction and doctor’s prescribing behavior which has not been explored in any research. This model will be helpful in further development of new concepts and for analyzing the reasons for the failure of doctors in providing quality service. 

A total of 200 doctors from three major cities of South India were selected. A doctor perceived service quality scale with three dimensions having eight items was developed through CFA using Parasuraman Service quality scale (Parasuraman, 1985, 1986, 1988) as the basis in the pharmaceutical context after focus group discussions with company experts, retailers, doctors and academicians. SEM technique was used to examine the impact of service quality on doctor’s satisfaction and prescribing behavior.

There is no universal set of dimensions and items that determine service quality in manufacturing industries, especially at the manufacturer–doctor interface of the pharmaceutical supply chain though service quality plays a very important role in affecting the performance of manufacturing industries. The critical factors affecting the quality of service for a pharmaceutical company at the manufacturer–doctor interface of the supply chain were identified, and its impact on doctor’s satisfaction and their prescribing behavior were studied.

This research contributes to the development of service quality scale for measuring service quality in pharmaceutical manufacturing company, especially with reference to manufacturer–doctor interface of the supply chain which was not thoroughly explored earlier. A model was developed showing the positive relationship between service quality and doctor’s satisfaction and doctor’s prescribing behavior in pharmaceutical supply chain which is a new concept not proved experimentally.

The study is very useful for the pharmaceutical manufacturing companies to identify the service quality factors affecting doctor’s satisfaction and their prescribing behavior thereby leading to development of new measures for improving the performance of the pharmaceutical supply chain. This study can lead to identification of problems involved in pharmaceutical supply chain and also leads to generation of new ideas and development of new concepts for influencing doctor’s satisfaction and doctor’s prescribing behavior which in turn can help in providing better health.

This study actually has a direct impact on the society. If factors affecting doctor’s satisfaction and prescribing behavior are identified automatically, the end consumer, i.e. patient, can be satisfied in a better way, and better medical care can be provided. If doctor’s problems are identified, then better solutions can be provided to patients; this in turn has a lot of positive impact on the pharmaceutical company and society in general.

This research will act as a base for generating ideas relating to how quality service provided by a company will have an impact on doctor’s satisfaction and his prescribing behavior in pharmaceutical supply chain .To the best of the authors’ knowledge, this study is the first of its kind of the conceptual aspects of service quality, satisfaction and loyalty explained in terms of pharmaceutical supply chain as service quality, doctor’s satisfaction and doctor’s prescribing behavior and proved experimentally.

The purpose of this paper is to discuss and analyze a microstrip feed equilateral triangular microstrip array antenna (ETMPAA) that is proposed for S band (3 GHz) applications.

The ETMPAA comprises three equilateral triangular patches with equal distance. The size of the antenna is 49.4 mm (0.0494 m)×18.4 mm (0.184 m). The proposed antenna has been designed by etching triangular shape structure on glass epoxy substrate (FR4).

The simulated result shows that ETMPAA has the impedance bandwidth of 900 MHz and the bandwidth can be achieved by controlling the gap between the patch antennas. The antenna is fed by microstrip feeding technique. Design of an antenna using advanced design system (ADS), based on finite element methods (FEM) has been used to analyze and optimize the antenna. Based on the measurement results an antenna proposed with maximum efficiency and maximum gain.

This paper fulfils an identified need to study a microstrip feed ETMPAA is proposed for S band (3 GHz) applications.

In this work, a true random number generator is designed by sampling the double-scroll analog continuous-time chaotic circuit signals.

A Chua circuit based on memristance simulator is designed to obtain a non-linear term for a chaotic dynamic system. It is implemented on the board by using commercially available integrated circuits and passive elements. A low precision ADC which is commonly found in the market is used to sample the chaotic signals. The mathematical analysis of the chaotic circuit is verified by experimental results.

It is aimed to be one of the pioneering studies (including low precision ADC) in the literature on the implementation of memristive chaotic random number generators.

Two new methods are proposed for post-processing and creating random bit array using XOR operator and J-K flip flop. The bit stream obtained by a full-hardware implementation successfully passed the NIST-800-22 test. In this respect, the availability of the memristance simulator circuit, memristive chaotic double-scroll attractor, proposed random bit algorithm and the randomness of the memristive analog continuous-time chaotic true number generator were also verified.

The purpose of this paper is to demonstrate that by utilizing the relationship between redundant hardware components, inherent in parallel machinery, vibration-based fault detection methods can be made more robust to changes in operational conditions. This work reports on a study of fault detection on bearings operating in two parallel subsystems that experience identical changes in speed and load.

This study was carried out using two identical subsystems that operate on the same duty cycle. The systems were run with both healthy and a variety of common bearing faults. The faults were detected by analyzing the residual between the features of the two vibration signatures from the two subsystems.

This work found that by utilizing this relationship in parallel operating machinery the fault detection process can be improved. The study looked at several different types of feature vector and found that, in this case, features based on envelope analysis or autoregressive model work the best, whereas basic statistical features did not work as well.

The proposed method can be a computationally efficient and simple solution to monitoring non-stationary machinery where there is hardware redundancy present. This method is shown to have some advantages over non-parallel approaches.