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This study aims to evaluate the quality of information recorded in Behaviour Monitoring Charts (BMC) for Behaviours that Challenge (BtC) in dementia in an older adult inpatient dementia service in the North of England (Aim I) and to understand staff perceptions and experiences of completing BMC for BtC in dementia (Aim II).

Descriptive statistics and graphs were used to analyse and interpret quantitative data gathered from BMC (Aim I) and Likert-scale survey responses (Aim II). Thematic analysis (Braun and Clarke, 2006) was used to analyse and interpret qualitative data collected from responses to open-ended survey questions and, separately, focus group discussions (Aim II).

Analysis of the BMCs revealed that some of the data recorded relating to antecedents, behaviours and consequences lacked richness and used vague language (i.e. gave reassurance), which limited its clinical utility. Overall, participants and respondents found BMC to be problematic. For them, completing BMCs were not viewed as worthwhile, the processes that followed their completion were unclear, and they left staff feeling disempowered in the systemic hierarchy of an inpatient setting.

Functional analysis of BMC helps identify and inform appropriately tailored interventions for BtC in dementia. Understanding how BMCs are used and how staff perceive BMC provides a unique opportunity to improve them. Improving BMC will support better functional analysis of BtC, thus allowing for more tailored interventions to meet the needs of people with dementia.

The purpose of this paper is to propose a framework for the analysis of students’ ratings of teaching quality in higher education and the disclosure of risky issues undermining the quality of teaching and courses that require attention for continuous improvement. The framework integrates two decision-based methods: the standardized u-control chart and the ABC analysis using fuzzy weights. The control chart, using the students’ ratings, allows the identification of those courses requiring an improvement of teaching quality in the short-medium term. While the ABC analysis uses fuzzy weights to deal with the vagueness and uncertainty of students’ teaching evaluations and provides a risk map of the potential areas of teaching performances improvement in the long term. The proposed framework allows the identification of teaching and course quality aspects that need corrective actions in response to students’ criticisms in accordance with different levels of priority.

This study adopts two methods, commonly used in industrial applications, i.e. the u-control chart and ABC analysis. Combining the results of a literature review on teaching evaluation and the application of these two methods as building blocks for the assessment, a framework to detect potential risks reducing teaching quality in higher education is proposed. The application of the framework is shown through an action-based case study developed in an Italian public university.

The study proposes a framework that combines two methods, i.e. u-control chart and ABC analysis with fuzzy weights, to support the assessment of teaching and course quality. The framework is proposed as an assessment approach of the teaching performance in higher education with the purpose to continuously improve the quality of teaching and courses both in the short, medium and long term.

The study provides an original contribution to the understanding of how to analyze students’ evaluation of teaching performance in order to take proper and timely decisions on corrective actions in response to the need of continuously improving the level of teaching and course quality.

Some public sector organizations have decided to implement activity-based costing (ABC), a new cost calculation device and management accounting innovation initially designed for the private sector. The purpose of this study is to better understand the translation of this new calculation device in the context of a local government and to identify the trials of strength that actors faced during the implementation.

Building on actor-network theory and the concept of “trial of strength,” this study examines how a major change in a large local government’s structure, the merger of several cities, led to the adoption of ABC. This case study provides a setting for conducting a longitudinal analysis of the translation of a cost management innovation, ABC, in a public sector organization.

This study highlights how human and non-human actors interact when implementing a management accounting innovation in a local government and the trials of strength that they face. It also shows that although ABC helped the local government deal with issues such as setting fees, assessing outsourcing opportunities, increasing accountability and improving processes, the oversophistication of the technology used to implement the ABC model and the lack of links between the costing device and the budgeting process provoked a struggle among these two networks, leading actors to choose the budget over ABC.

This study’s findings extend the work on trials of strength of Christensen et al. (2019) and Laguecir et al. (2020). While those two studies focused on the struggles existing between opposing networks of human actors regarding the strategic orientation or the mission of public sector organizations, this study highlights that trials of strength may also occur when actors agree on the objectives of the new accounting innovation but not on how it is implemented.

The aim of this paper is to investigate the perceptions of Malaysian employees of ABC MSC (a Japanese company in Malaysia) in order to recommend changes in management practices.

Fieldwork was conducted using participant observation and interviews. Participant observation was conducted to investigate the flow of information, the implementation of decisions made by the top Japanese managers, problem resolution, and the reaction of the local staff to management practices. The interviews highlighted communication problems which have existed between the Japanese CEO and the local telecommunications companies since the company started operations in 1997.

Even thought the company is backed by a financially strong parent company in Japan and has a lot of growth potential, this potential remains partially untapped due to management strategies of the company headquarters.

Japan remains an important Foreign Direct Investment country in Malaysia. The perceptions of employees of Japanese companies in Malaysia are worth investigating since changes of management strategies in the home country affect the direction and operations of the overseas subsidiaries. Further research should be carried out in other Japanese companies in Malaysia.

Suggestions to improve the management strategies are discussed.

It is believed that no other Japanese company in Malaysia has been investigated in this way before. This paper's findings should be useful to many expatriate managers in Malaysia.

This paper aims to propose a multi-dimensional hierarchical K-means clustering algorithm for the purpose of intrusion detection. Initially, the clustering set of rules is proposed to shape some of clusters in the network and then the most beneficial clusters are decided on by the use of Cuckoo search optimization set of rules. Finally, an Artificial Bee Colony primarily based selection tree (ABC-DT) classifier is rented to classify the regular and unusual instances present in the network with the aid of the extracted features.

Intrusion detection system (IDS) is crucial for the network system; the intruder can take sensitive details about the network. IDS are said to be more effective when it has both high intrusion detection rate and low false alarm rate. Numerous strategies including gadget mastering, records mining and statistical techniques were tested for IDS mission. Recent study reveals that combining multiple classifiers, i.e. classifiers ensemble, can also own better performance than unmarried classifier. In this paper, a comparative study is conducted of the overall performance of four classifiers, i.e. hybrid ABC-DT particle swarm optimization-based K-means clustering (PSO-KM), help vector device (SVM) and K-Nearest neighbour (KNN). All the four classifiers are tested with exceptional packet sizes 1470, 1024, 512 and 256. The experiment is carried out for the speed ranging from turned into done for the velocity ranging from 250Mbps, 500Mbps, 750Mbps, 1.0Gpbs, 1.5Gbps, and 2.0Gbps in terms of accuracy, detection charge, specificity, false alarm charge and computational time. The experimental results reveals that the hybridization of classifiers performs better than the base classifiers in all scenarios.

This study analyses the performance of hybrid ABC-DT classifier and compares the performance against three well-known classifiers such as PSO-KM, SVM and K-NN. The performances of all the four classifiers are tested with Discovery in Data Mining (KDD) CUP 99 dataset with different packet sizes 1470, 1024, 512 and 256. The results show the classifier performance variations with different speed ranges. From the experimental results and analysis, the hybridization of classifiers such as ABC-DT outperforms the base classifiers in all scenarios.

The novel approach in this paper is used to study the hybrid ABC-DT classifier and compare the performance against three well-known classifiers such as PSO-KM, SVM and K-NN. The discussed concept is used within the network to monitor the traffic to and from all the devices connected in that network.

The purpose of this paper is to contribute to the debate on the current economic crisis and to highlight the importance of the counter‐party credit risk, which was surprisingly neglected by the Basel Committee on Banking Supervision in its proposed enhancements to the Basel II framework. The paper supports the proposition that there is an incentive for synergy between bank management, corporate management and auditors as long as all these parties' remuneration schemes are based on the same principles.

In this paper an advanced IRB corporate credit‐rating system is constructed in accordance with the Basel II framework and the current literature. The impact of common creative accounting and banking practices on the manipulation of that system is explored.

The paper shows how creative accounting and banking practices can be used in manipulating an advanced IRB corporate credit‐rating system, and thus presenting a high‐risk corporation as a highly attractive (low‐risk) bank customer.

The regulatory authorities should take into consideration the inability of rating agencies to ascertain the risk associated with the US sub‐prime mortgage market and the decline of auditors' independence.

The contribution of the paper is the propositions made to the Basel Committee on Banking Supervision in order to enhance the Basel II framework, and avoid repetition of the current economic crisis in the future.

This paper aims to investigate the impact of adopting lean manufacturing principles on operational efficiency by eliminating seven major lean wastes (or Muda) in a Malaysian stationery manufacturer. Much of the research on lean considers its application to larger organisations with stable demand patterns. This research examines a small- and medium-sized enterprise (SME) with a volatile demand pattern.

A process activity mapping (PAM) methodology was utilized to identify the potential for waste elimination. PAM is a visual tool that considers every step in a production process. Value-added and non-value-added activities are therefore examined to understand hidden wastes and their sources.

The results revealed that the adopted lean principles significantly reduce the waiting times. This time reduction resulted in savings (reduction of cycle time) and to a certain extent, can be a crucial driver in continuous improvement sustainability in the production process.

The study focuses on a single case study and provides a springboard for further research. Future studies examining the results across a broader sample of organisations would develop the findings further.

The extant literature cites mixed success for lean implementation programmes. The results demonstrate that lean is still recognised as a powerful approach to improving operations in SMEs.

This paper reflects on the application of lean in a real case study showing the impact of lean on operational performance of an SME.

The purpose of the paper is to solve hydrothermal scheduling (HTS) problem for energy-efficient management by allocating the optimal real power outputs for thermal and hydroelectric generators.

HTS can be formulated as a complex and non-linear optimization problem which minimizes the total fuel cost and emissions of thermal generators subject to various physical and operational constraints. As the artificial bee colony algorithm has proven its ability to solve various engineering optimization problems, it has been used as a main optimization tool to solve the fixed-head HTS problem.

A meta-heuristic search technique-based algorithm has been implemented for hydrothermal energy management, and the simulation results show that this approach can provide trade-off between conflict objectives and keep a rapid convergence speed.

The proposed methodology is implemented on the standard test system, and the numerical results comparison indicates a considerable saving in total fuel cost and reduction in emission.

This study aims to use sensing technology to observe the learning status of learners in a teaching and learning environment. In a general instruction environment, teachers often encounter some teaching problems. These are frequently related to the fact that the teacher cannot clearly know the learning status of students, such as their degree of learning concentration and capacity to absorb knowledge. In order to deal with this situation, this study uses a learning concentration detection system (LCDS), combining sensor technology and an artificial intelligence method, to better understand the learning concentration of students in a learning environment.

The proposed system uses sensing technology to collect information about the learning behavior of the students, analyzes their concentration levels, and applies an artificial intelligence method to combine this information for use by the teacher. This system includes a pressure detection sensor and facial detection sensor to detect facial expressions, eye activities and body movements. The system utilizes an artificial bee colony (ABC) algorithm to optimize the system performance to help teachers immediately understand the degree of concentration and learning status of their students. Based on this, instructors can give appropriate guidance to several unfocused students at the same time.

The fitness value and computation time were used to evaluate the LCDS. Comparing the results of the proposed ABC algorithm with those from the random search method, the algorithm was found to obtain better solutions. The experimental results demonstrate that the ABC algorithm can quickly obtain near optimal solutions within a reasonable time.

A learning concentration detection method of integrating context-aware technologies and an ABC algorithm is presented in this paper. Using this learning concentration detection method, teachers can keep abreast of their students' learning status in a teaching environment and thus provide more appropriate instruction.

The purpose of this paper is to develop and validate an extended Define-Measure-Analyze-Improve-Control (DMAIC) based framework through a case study of an Indian fasteners manufacturing organization.

Research methodology is established on the development of the existing DMAIC framework through an extensive literature review of 25 LSS/DMAIC based frameworks and discussions held with practitioners. This paper also depicts a case study of Indian manufacturing organization for validation of the developed framework.

The study proposed an extended DMAIC based framework for effective implementation of Lean Six Sigma (LSS) methodology. Furthermore, this framework has been implemented successfully in the Indian manufacturing organization and showed encouraging results. The in-house rejections of Nut Cylinder Head (NCH) were brought down to 966 from 2910 PPM and sigma level was improved by 0.40. The case organization has achieved significant improvements in the process capability, customer satisfaction, and cost savings of US$ 0.25 million in one financial year. Intangible benefits like improvements in employee's morale, communication, housekeeping and decision-making capabilities were also observed significantly.

The proposed DMAIC based framework has been implemented successfully in the Indian case organization, and the results will enable the policymakers, specifically practitioners, to strategically leverage the resources for successful implementation of the LSS in healthcare, aerospace, service sectors etc.

This research develops a DMAIC based framework which can be used to implement LSS effectively in different industries. Moreover, the pre (initial/introduction) and post (validation/verification) implementation phase provides the top management, an edge to think strategically into broader improvement areas.