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The purpose of this research paper is to develop and analyze micro-electro-mechanical systems sensor for vibration monitoring of pumping aggregate.

The system is based on smart sensor and smart mobile phone.

The numerous measurements on a wide range of turbo aggregates were performed to establish the operating condition of pumping aggregates.

Afterwards, the influence of vibration at different positions on the output vibration of the pumping aggregate was analyzed by adaptive neuro fuzzy inference system method.

The present study was carried out with the purpose of establishing a model of effective board governance in Uganda's service sector firms.

This study is cross‐sectional. The analysis was conducted using Analysis of Moment Structures (AMOS) software on a sample of 128 service firms in Uganda. The perceived effective board governance in Uganda was measured by the perceptions of 128 respondents who are managers or directors in each of those service firms. Three confirmatory factor analysis models were tested and fitted.

The three‐dimensional model of effective board governance in Uganda – consisting of control and meetings’ organization, board activity and effective communication – was determined to be the best fitting model. Evidence in support of relevant theories of board governance was adduced.

Although plenty of literature on corporate governance exists, there is scarce literature on effective board governance conceptualization and this together with imprecise terminology regarding this area may have affected the authors’ conceptualization of the study. The authors’ study was limited to the service sector firms registered and operating in Kampala, Uganda and it is possible that their results are only applicable to this sector in Uganda. Nevertheless, policy makers of Uganda dealing with financial markets, academicians, company directors, company owners and even general readers interested in the area of effective board governance might find this paper handy.

The authors believe that application of their model should improve the quality of board governance in Uganda and can also apply to other sectors of Uganda's firms to help avert the problem of ineffective boards as evidenced by consistent firm failures in Uganda. By improving the quality of board governance, Ugandan boards will demonstrate their relevance in company direction and improvement of company value to the benefit of all stakeholders.

The present study provides one of the few studies that have analysed with confirmatory factor analysis (CFA) using AMOS to test effective board governance measurement model and provides a benchmark for Uganda's service firms yearning to leverage the use of their boards.

The purpose of this paper is to establish the relationship between corporate governance, ethical culture, Internal Controls over Financial Reporting (ICFR) and compliance with International Financial Reporting Standards (IFRS) by microfinance institutions (MFIs).

This is a cross-sectional survey based on a sample of 85 MFIs in Uganda. Hypotheses were tested using partial least squares (PLS) analysis technique. An unweighed IFRS compliance index to capture the level of compliance with IFRS was constructed. Yet to capture corporate governance, ethical culture and ICFR variables, the perceptions of top management of MFIs have been taken into consideration.

Corporate governance, ethical culture and ICFR, each makes a significant contribution to compliance with IFRS. Also both corporate governance and ethical culture are significantly associated with ICFR. However, compliance with IFRS by MFIs is better enhanced by corporate governance and ethical culture through ICFR.

Results support the idea that in terms of agency and virtue ethics theories, the board should support ICFR to minimize egocentric managers and other employees and also inculcate an ethical culture to achieve better compliance with IFRS because corporate governance and ethical culture are associated with sound ICFR which in turn lead to compliance with IFRS.

Boards of MFIs should encourage investments that improve ICFR. At the same time, regulators should ensure that boards are composed of members with financial expertise, with no conflict of interest and introduce mechanisms that encourage boards to perform their roles.

The study contributes towards a methodological position by showing that the behavioural perspective of corporate governance can be an alternative to the boards’ structural variables in investigating compliance with IFRS. A direct association of ethical culture and compliance with IFRS and an indirect association through ICFR can be envisaged.

Examines the fourteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The prediction of by-product gas is an important guarantee for the full utilization of resources. The purpose of this research is to predict gas consumption to provide a basis for gas dispatch and reduce the production cost of enterprises.

In this paper, a new method using the ensemble empirical mode decomposition (EEMD) and the back propagation neural network is proposed. Unfortunately, this method does not achieve the ideal prediction. Further, using the advantages of long short-term memory (LSTM) neural network for long-term dependence, a prediction method based on EEMD and LSTM is proposed. In this model, the gas consumption series is decomposed into several intrinsic mode functions and a residual term (r(t)) by EEMD. Second, each component is predicted by LSTM. The predicted values of all components are added together to get the final prediction result.

The results show that the root mean square error is reduced to 0.35%, the average absolute error is reduced to 1.852 and the R-squared is reached to 0.963.

A new gas consumption prediction method is proposed in this paper. The production data collected in the actual production process is non-linear, unstable and contains a lot of noise. But the EEMD method has the unique superiority in the analysis data aspect and may solve these questions well. The prediction of gas consumption is the result of long-term training and needs a lot of prior knowledge. Relying on LSTM can solve the problem of long-term dependence.

Examines the seventeenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

This paper uses a cognitive analytics management approach to analyze, understand and solve the problems facing the implementation of information systems and help management do the needed changes to enhance such a critical process; the emergency management system in the health industry is analyzed as a case study.

Cognitive analytics management (CAM) framework (Osman and Anouz, 2014) is used. Cognitive process: The right questions are asked to understand the behavior of every process and the flow of its corresponding data; critical data variables were identified, guidelines for identifying data sources were set. Analytics process: Techniques of data analytics were applied to the selected data sets, problems were identified in user–system interaction and in the system design. The analysis process helped the management in the management process to make right decisions for the right change.

Using the CAM framework, the analysis to the Lebanese Red Cross case study identified system user-behavior problems and also system design problems. It identified cases where distributed subsystems are vulnerable to time keeping errors and helped the management make knowledgeable decisions to overcome major obstacles by implementing several changes related to hardware design, software implementation, human resource training, operational and human-technology changes. CAM is a novel and feasible software engineering approach for handling system failures.

The paper uses CAM framework as an approach to overcome system failures and help management do the needed changes to enhance such a critical process. This work contributes to the software engineering literature by introducing CAM as a new agile methodology to be used when dealing with system failures. Furthermore, this study is an action research that validated the CAM theoretical framework in a health emergency context in Lebanon.

The aim of the study is to determine the perception of general public on the Serbian police behaviors in combating COVID-19 pandemic, as well as the perception of the citizens how successful the police units were in fulfilling their tasks.

Due to the state of emergency declared due to COVID-19 pandemic, in particular the restriction of movement and the need for social distance, the data collection for this study had to be conducted via the online survey platform (Google.doc). The study was conducted during March–April 2020, only four weeks after the state of emergency was declared. The participants were invited to complete the online questionnaire in their native language by using the snowball sampling strategy focused on recruiting the general public via social media tools.

Considering the fact that police officers are not sufficiently prepared and trained to respond in these specific circumstances, it is necessary to improve their engagement in the future by conducting appropriate training, procuring adequate resources, implementing adequate planning activities, etc. The results of the multivariate regressions of public perception preparedness subscale show that the most important predictor is gender and it explains 23.6% of the variance in preparedness subscale. The remaining variables did not have significant effects on preparedness. This model with all mentioned independent variables explains 6.1% of the variance of preparedness subscale.

Bearing in mind that there were no completed studies on public perception of police behaviors about the COVID-19 disaster in Serbia, the research has a considerable scientific and social importance.

The purpose of this study is to investigate the current literature that has explored project success in the information and communication technology (ICT) sector.

The literature search was carried out for related articles in three databases: the Web of Science, Scopus and Ebscohost. Using a systematic literature review (SLR) methodology, 75 related articles were sorted out. Furthermore, the methods of frequency and content analysis were used to identify, categorize and arrange critical success factors (CSF) of ICT projects based on their importance, interrelation and cultural regions.

The findings in this study revealed that interest in researching success in ICT projects has increased significantly during the last five years. Through reviewing the selected articles, 25 CSF were identified. User participation, stakeholder relationship, project manager emotional intelligence, communication skills, and leadership skills, and top management support in the project emerged as the most important factors for ICT projects. Furthermore, we found that each regional group gives different level of importance to different CSF.

This study gives the opportunity to practitioners to control the highest value CSF to increase the success rate of ICT projects carried out in different cultural regions.

As the first study of its type, CSF were divided for different cultural regional groups. This paper further explained that certain CSF have different levels of importance in different culture regions. This study suggests that regional culture needs consideration during the evaluation of CSF.

This paper deals with the optimization of coal handling system performability for a thermal power plant.

Coal handling system comprises of five subsystems, namely Wagon Tippler, Crusher, Bunker, Feeder and Coal Mill. The partial differential equations are derived on the behalf of transition diagram by using the Markov approach. These partial differential equations are further solved to obtain the performance model with the help of normalization condition. Numerous performability levels are achieved by putting the appropriate combinations of failure and repair rates (FRRs) in performance model. Performability optimization for coal handling system is obtained by varying the population and generation size.

Highest performability level, that is, 93.33 at population size of 40 and 93.31 at generation size of 70, is observed.

The findings of this paper highlight the optimum value of performability level and FRRs for numerous subsystems. These findings are highly beneficial for plant administration to decide about the maintenance planning.