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The purpose of this paper is to present a novel laser pointer for manual coating robot teaching. The laser pointer has simple structure and no physical contact with substrate in teaching work. The sensitivity of visual detection in the design accuracy is guaranteed.

The strategy adopts two laser sources to form a triangle to achieve a fixed distance detection pointer for manual robot teaching. After optimizing the source, spot size and the incident angle of the lasers, the sensitivity of fixed-distance judgment is analyzed and compared with traditional pointers. In addition, the laser pointer adds the functions to simulate coating atomizer, including posture and overlap pitch. Finally, the laser pointer verified by coating application and measurement system analysis evaluation.

The laser pointer has been successfully applied to coating robot teaching by the authors’ team. From the simulation and experimental results, it can be concluded that the proposed approach is effective at improving manual teaching of coating robot, especially for the complex geometry.

The main function of the laser pointer often used for manual teaching in other purposes; for example, sealer etc. The paper innovatively considered and tested the laser pointer on robotic coating process.

Compared with the traditional hard straight stick pointer, the paper proposes a very simple construction for teaching pointer with laser feature. At the same time, the requirement of coating process simulation is considered.

The purpose of this paper is to monitor the backup indicators in case of indicator failure and to minimize the situations when the pilot may be unable to monitor the indicator effectively in emergency situations.

In this study, the pointer positions of different indicators were determined with a deep learning-based algorithm. Within the scope of the study, the pointer on the analog indicators obtained from aircraft cockpits was detected with the YOLOv4 object detector. Then, segmentation was made with the GrabCut algorithm to detect the pointer in the detected region more precisely. Finally, a line including the segmented pointer was found using the least-squares method, and the exact direction of the pointer was determined and the angle value of the pointer was obtained by using the inverse tangent function. In addition, to detect the pointer of the YOLOv4 object detection method and to test the designed method, a data set consisting of videos taken from aircraft cockpits was created and labeled.

The analog indicator pointers were detected with great accuracy by the YOLOv4 and YOLOv4-Tiny detectors. The experimental results show that the proposed method estimated the angle of the pointer with a high degree of accuracy. The developed method can reduce the workloads of both pilots and flight engineers. Similarly, the performance of pilots can be evaluated with this method.

The authors propose a novel real-time method which consists of detection, segmentation and line regression modules for mapping the angle of the pointers on analog indicators. A data set that includes analog indicators taken from aircraft cockpits was collected and labeled to train and test the proposed method.

This study investigates the perception of professionals in the field of accounting, and those associated with forensic auditing, about the knowledge and skills, experience and technique that a forensic auditor should possess to provide high-quality services in fraud detection. The study also shows the impact of forensic auditing tools on fraud detection.

With the use of a self-administered questionnaire, the study adopts a survey design in which 298 respondents participated. Data were subjected to descriptive statistics (ranking, mean and standard deviation), inferential statistics (binary logistic regression and ordinary least square regression).

The findings indicate that adequate knowledge of economic damage calculation and financial statement valuation is essential for forensic auditors' service. The results also reveal that forensic auditor skills and techniques is a significant predictor for fraud detection in the Nigerian public sector.

The paper draws attention of the federal government parastatals to the need to improve their internal control system to reduce the fraudulent practices in their parastatal. The study also draws the attention of the Nigeria University Commission and the Institute of Chartered Accountants of Nigeria on the needs for revision of the accounting curricular for the training of accounting graduates and professional accountants in Nigeria.

The paper is of importance to other developing nation as it provides empirical evidence on the needs to do periodic forensic audits of government corporations.

With the persistent increase in the number of fraudulent cases, current views of those associated with forensic auditing (judiciaries, parastatals, forensic auditors and academics) on mechanisms for timely detection of fraud are needed.

This case is based on using the fraud triangle, theoretical aspects like rationalization and motivation for understanding the financial pressures and corporate greed lead to accounting fraud. Building on the corporate governance’s weakness, the case explores the challenges and the changes that the company has to make to survive.

The case study has been entirely based on published resources. The case explores out the reasons why the companies commit accounting fraud using the motivations, financial pressures and the opportunities exploited due to a weak governance system.

The case deals with a RMB 2.2bn accounting fraud at Luckin Coffee Inc. (L.K.), a US-listed Chinese company, which led to a steep fall in its share price by more than 80% in April 2020. The company’s CEO had to resign in light of the accounting fraud, which involved fabricating the transactions in 2019, the same year it got listed on the NASDAQ stock exchange. The case is a classic example of greed, corporate ambition and flaws in the corporate governance that led to the fraud while framing a course of action for the company moving forward. The case allows the learners to dive deep into the facts to find out why the fraud happened and its repercussions for the company and its various stakeholders. The case can be useful in Accounting, Corporate governance or Ethics modules for both undergraduate and postgraduate students.

The case can be used for both postgraduate and undergraduate financial accounting or corporate governance modules or the executive development programmes explicitly dealing with ethical challenges and accounting fraud.

A novel sensor system is described that can replace the need to use a touch screen, mouse or keyboard for use with either a thin film transistor (TFT) or cathode ray tube (CRT) screen.

A tri‐colour photodiode in a colour sensor pen (CSP) is used as an input to depict where a user is pointing by detecting a dynamic kaleidoscope of colours flashed onto the screen. The most easily detected colours are placed around the predicted position of the sensor. The output from the sensor is filtered and transmitted to a computer where colour is translated into a corresponding co‐ordinate. An artificial neural network (ANN) ensures that optimum colours are placed closest to the sensor by predicting future pointer position.

The CSP successfully provided an input that depicted where a user was pointing. Sensors tested were not able to differentiate more than 28 colours on a TFT screen but an ANN system made them more accurate. Hue and Saturation were successfully used to model colour in a two‐dimensional colour grid as they were unaffected by brightness. The sensor output was successfully converted into a co‐ordinate and used to move a cursor. The kaleidoscope of colours was dynamic as it changed size and colour to increase accuracy. The ANN successfully predicted future positions to assist the sensor in making optimum colour detections. The best predictions of future positions were obtained with four and eight hidden neurons and there did not appear to be any significant advantage in training with more than 2,000 epochs. The system has performed satisfactorily for various inputs.

The novel light pen works on TFT and CRT screens. Problems included the time that colours needed to be left on a screen to be detected and the limited number of colours that could reliably be detected. These were overcome by using a dynamic kaleidoscope of colours to improve colour detection and an ANN to predict future pointer positions, based on previous locations. This prediction was used to place optimum colours closest to the sensor in order to increase accuracy. Further testing is taking place to confirm that the sensor can be used at any angle.

The novel light pen type peripheral and intelligent colour sensing system can replace the need to use a touch screen, mouse or keyboard.

The new intelligent colour sensing system works on either a TFT or CRT screen. The use of the colour translation and sensor and the ANN to predict future pointer position are all novel.

Contact interaction and contact detection (CD) remain key components of any discontinua simulations. The methods of discontinua include combined finite-discrete element method (FDEM), discrete element method, molecular dynamics, etc. In recent years, a number of CD algorithms have been developed, such as Munjiza–Rougier (MR), Munjiza–Rougier–Schiava (MR-S), Munjiza-No Binary Search (NBS), Balanced Binary Tree Schiava (BBTS), 3D Discontinuous Deformation Analysis and many others. This work aims to conduct a numerical comparison of certain algorithms often used in FDEM for bodies of the same size. These include MR, MR-S, NBS and BBTS algorithms.

Computational simulations were used in this work.

In discrete element simulations where particles are introduced randomly or in which the relative position between particles is constantly changing, the MR and MR-S algorithms present an advantage in terms of CD times.

This paper presents a detailed comparison between CD algorithms. The comparisons are performed for problem cases with different lattices and distributions of particles in discrete element simulations. The comparison includes algorithms that have not been evaluated between them. Also, two new algorithms are presented in the paper, MR-S and BBTS.

This paper discusses the issues involved in the development of combined finite/discrete element methods; both from a fundamental theoretical viewpoint and some related algorithmic considerations essential for the efficient numerical solution of large scale industrial problems. The finite element representation of the solid region is combined with progressive fracturing, which leads to the formation of discrete elements, which may be composed of one or more deformable finite elements. The applicability of the approach is demonstrated by the solution of a range of examples relevant to various industrial sections.

Realistic force sensation can help operators better feel and manipulate parts for virtual assembly (VA). Moreover, for VA of mechanical parts, it is necessary to consider their tolerance levels so as to apply proper assembly forces. Out of the three common assembly fit types, the type of clearance fit is the focus of virtual manual assembly, as parts with such fit type require precise force feedback to assist users’ assembly operations.

This study proposes a novel force rendering model for VA of mechanical parts with clearance fits. By decomposing an actual assembly operation into three consecutive states, the corresponding forces are formulated.

A prototype system is designed and developed to implement the model, and comparative case studies are conducted to investigate the users’ performance with the other three common approaches, namely, a typical WIMP (window-icon-menu-pointer) interface with CAD software, a physics simulation with collision detection and the approach that combines physics simulation and geometric constraints restriction. The results have shown that the proposed model is more realistic by providing continuous and realistic force feedback to the users.

The users’ feeling of immersion and their operational efficiency are greatly enhanced with the force sensation provided.

Monitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products with improved yield. The history of process monitoring fault detection (PMFD) strategies can be traced back to 1930s. Thereafter various tools, techniques and approaches were developed along with their application in diversified fields. The purpose of this paper is to make a review to categorize, describe and compare the various PMFD strategies.

Taxonomy was developed to categorize PMFD strategies. The basis for the categorization was the type of techniques being employed for devising the PMFD strategies. Further, PMFD strategies were discussed in detail along with emphasis on the areas of applications. Comparative evaluations of the PMFD strategies based on some commonly identified issues were also carried out. A general framework common to all the PMFD has been presented. And lastly a discussion into future scope of research was carried out.

The techniques employed for PMFD are primarily of three types, namely data driven techniques such as statistical model based and artificial intelligent based techniques, priori knowledge based techniques, and hybrid models, with a huge dominance of the first type. The factors that should be considered in developing a PMFD strategy are ease in development, diagnostic ability, fault detection speed, robustness to noise, generalization capability, and handling of nonlinearity. The review reveals that there is no single strategy that can address all aspects related to process monitoring and fault detection efficiently and there is a need to mesh the different techniques from various PMFD strategies to devise a more efficient PMFD strategy.

The review documents the existing strategies for PMFD with an emphasis on finding out the nature of the strategies, data requirements, model building steps, applicability and scope for amalgamation. The review helps future researchers and practitioners to choose appropriate techniques for PMFD studies for a given situation. Further, future researchers will get a comprehensive but precise report on PMFD strategies available in the literature to date.

The review starts with identifying key indicators of PMFD for review and taxonomy was proposed. An analysis was conducted to identify the pattern of published articles on PMFD followed by evolution of PMFD strategies. Finally, a general framework is given for PMFD strategies for future researchers and practitioners.

The purpose of this paper is to propose an approach to detect Indirect Memory‐Corruption Exploit (IMCE) at runtime on binary code, which is often caused by integer conversion error. Real‐world attacks were evaluated for experimentation.

Current dynamic analysis detects attacks by enforcing low level policy which can only detect control‐flow hijacking attack. The proposed approach detects IMCE with high level policy enforcement using dynamic taint analysis. Unlike low‐level policy enforced on instruction level, the authors' policy is imposed on memory operation routine. The authors implemented a fine‐grained taint analysis system with accurate taint propagation for detection.

Conversion errors are common and most of them are legitimate. Taint analysis with high‐level policy can accurately block IMCE but have false positives. Proper design of data structures to maintain taint tag can greatly improve overhead.

This paper proposes an approach to block IMCE with high‐level policy enforcement using taint analysis. It has very low false negatives, though still causes certain false positives. The authors made several implementation contributions to strengthen accuracy and performance.