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Aircraft assembly is the crucial part of aircraft manufacturing, and to meet the high-precision and high-efficiency requirements, cooperative measurement consisting of multiple measurement instruments and automatic assisted devices is being adopted. To achieve the complete data of all assembly features, measurement devices need to be placed at different positions, and the flexible and efficient transfer relies on Automated Guided Vehicles (AGVs) and robots in the large-size space and close range. This paper aims to improve the automatic station transfer in accuracy and flexibility.

A transferring system with Light Detection and Ranging (LiDAR) and markers is established. The map coupling for navigation is optimized. Markers are distributed according to the accumulated uncertainties. The path planning method applied to the collaborative measurement is proposed for better accuracy. The motion planning method is optimized for better positioning accuracy.

A transferring system is constructed and the system is verified in the laboratory. Experimental results show that the proposed system effectively improves positioning accuracy and efficiency, which improves the station transfer for the cooperative measurement.

A Transferring system for collaborative measurement is proposed. The optimized navigation method extends the application of visual markers. With this system, AGV is capable of the cooperative measurement of large aircraft structural parts.

This study aims to treat the development and application of sequence characterised amplified region (SCAR) markers for the detection of plant based adulterants (dried red beet pulp and powdered Ziziphus nummularia fruits) in traded ground chilli.

Adulterant‐specific DNA fragments (red beet pulp specific – “Beet 01” and Z. nummularia specific – “Ziz 01”) identified by random amplified polymorphic DNA polymerase chain reaction (RAPD‐PCR) analysis were cloned and sequenced for SCAR marker development. Red beet pulp specific SCAR primer pair, B1, and Z. nummularia specific SCAR primer pair, Z1, were designed from the corresponding RAPD marker sequences to amplify SCAR markers of 320 bp and 389 bp, respectively. The utility of the SCAR markers for adulterant detection was verified in model blends of chilli powder with the adulterants. Six commercial samples of ground chilli powder were analysed using the SCAR markers.

SCAR markers could detect the adulterants at a concentration as low as 10 g adulterant kg⁻¹ of blended sample. The Z. nummularia SCAR marker could detect the presence of Z. nummularia fruit adulteration in one of the commercial samples. All the market samples tested were free from red beet pulp adulteration.

The PCR‐based method developed in the study is simple, rapid, and sensitive and has the potential to be developed into a quantitative analytical method and for commercial PCR kits for the large‐scale screening of ground chilli to detect and prevent plant‐based adulterants. The work has public health significance too, as ground chilli is one of the major spices consumed worldwide.

The study is the first report on the development of SCAR markers for adulterant detection in ground chilli. This work has relevance, as adulteration is a major concern of the sanitary and phytosanitary issues of the World Trade Organization (WTO) agreement.

The purpose of this paper is to propose a novel method to analyze Table of Contents (TOC) in Chinese books automatically based on the hierarchy organization rules which gained by investigation.

This paper analyzed the main literature in this field first, then hierarchy organization rules of Chinese book TOC were generated and the method parsing TOC automatically based on these rules was proposed. A prototype system implementing the method was also developed. The method was evaluated through processing a corpus on the prototype system, and the results were checked with calculation of precision and recall.

The experiment result illustrated the superiority (extensive application, recall is 95.34 percent and precision is 94.44 percent) of the method.

The result can help Chinese libraries deal with electronic texts from four aspects. First, it can be used to complement or enhance current digitization and optical character recognition methods and cut the financial and labor cost of Chinese libraries. Second, it can help libraries to keep information on indexing words as well as chapters, sections and subsections in Chinese book databases, which ensures easy retrieval and extract any intended portion as demanded by user. Third, it helps to enrich the services and then enhances the user experiences in Chinese libraries. Fourth, it improves the specification and policy of digitalizing Chinese books.

The paper provided insight into the hierarchy organization of TOCs in Chinese books, the method based on the rules has extensive application than other methods. This method for Chinese book TOC automatic analysis is also as reference for English book TOC automatic analysis.

Describes the history of CAD systems as well as their benefits and costs for a clothing company. Presents and analyses results of a survey concerning the use of CAD systems for marker making in the clothing industry of the USA. Describes environmental and cost aspects of CAD marker making and makes recommendations for small clothing manufacturers.

Reports the results of a study undertaken to determine the technical and economic feasibility of improving the state‐of‐the‐art in marker making systems for the apparel industry. The study concentrates on three primary areas: an assessment of the current state of the art in marker making software; an extensive literature search; analysis of the cutting stock problem and its application to the marker making problem; and other approaches to solving the marker making problem. Explores the economic viability of increasing marker making automation. Conclusions and recommendations are presented.

The purpose of this paper is to present an approach for forecasting mental health conditions and emotions of a given population during the COVID-19 pandemic in Argentina based on social media contents.

Mental health conditions and emotions are captured via markers, which link social media contents with lexicons. First, the authors build time series models that describe the evolution of markers and their correlation with crisis events. Second, the authors use the time series for forecasting markers and identifying high prevalence points for the estimated markers.

The authors evaluated different forecasting strategies that yielded different performance and capabilities. In the best scenario, high prevalence periods of emotions and mental health issues can be satisfactorily predicted with a neural network strategy, even at early stages of a crisis (e.g. a training period of seven days).

This work contributes to a better understanding of how psychological processes related to crises manifest in social media, and this is a valuable asset for the design, implementation and monitoring of health prevention and communication policies.

Although there have been previous efforts to predict mental states of individuals, the analysis of mental health at the collective level has received scarce attention. The authors take a step forward by proposing a forecasting approach for analyzing the mental health of a given population at a larger scale.

This paper presents a reclassification of markers for mixed reality environments that is also applicable to the use of markers in robot navigation systems and 3D modelling. In the case of Augmented Reality (AR) mixed reality environments, markers are used to integrate computer generated (virtual) objects into a predominantly real world, while in Augmented Virtuality (AV) mixed reality environments, the goal is to integrate real objects into a predominantly virtual (computer generated) world. Apart from AR/AV classifications, mixed reality environments have also been classified by reality; output technology/display devices; immersiveness as well as by visibility of markers.

The approach adopted consists of presenting six existing classifications of mixed reality environments and then extending them to define new categories of abstract, blended, virtual augmented, active and smart markers. This is supported with results/examples taken from the joint Mixed Augmented and Virtual Reality Laboratory (MAVRLAB) of the Ulster University, Belfast, Northern Ireland; the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy and Santasco SrL, Regio Emilia/Milan, Italy.

Existing classification of markers and mixed reality environments are mainly binary in nature and do not adequately capture the contextual relationship between markers and their use and application. The reclassification of markers into abstract, blended and virtual categories captures the context for simple use and applications while the categories of augmented, active and smart markers captures the relationship for enhanced or more complex use of markers. The new classifications are capable of improving the definitions of existing simple marker and markerless mixed reality environments as well as supporting more complex features within mixed reality environments such as co-location of objects, advanced interactivity, personalised user experience.

It is thought that applications and devices in mixed reality environments when properly developed and deployed enhances the real environment by making invisible information visible to the user. The current work only marginally covers the use of internet of things (IoT) devices in mixed reality environments as well as potential implications for robot navigation systems and 3D modelling.

The use of these reclassifications enables researchers, developers and users of mixed reality environments to select and make informed decisions on best tools and environment for their respective application, while conveying information with additional clarity and accuracy. The development and application of more complex markers would contribute in no small measure to attaining greater advancements in extending current knowledge and developing applications to positively impact entertainment, business and health while minimizing costs and maximizing benefits.

The originality of this paper lies in the approach adopted in reclassifying markers. This is supported with results and work carried out at the MAV Reality Laboratory of Ulster University, Belfast–UK, the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste-Italy and Santasco SrL, Regio Emilia, Milan–Italy. The value of present research lies in the definitions of new categories as well as the discussions of how they improve mixed reality environments and application especially in the health and education sectors.

Describes the history of CAD systems as well as their benefits and costs for a clothing company. Presents and analyses results of a survey concerning the use of CAD systems for marker making in the clothing industry of the United States. Describes and evaluates the functions of CAD marker making with the help of a case study.

The purpose of this paper is to create an assembly verification system that is capable of verifying complete assembly and torque for each individual fastener.

The 3D position of the tool used to torque the fastener and the assembly pallet will be tracked using an infrared (IR) tracking system. A set of retro‐reflective markers are attached to the tool and assembly while being tracked by multiple IR cameras. Software is used to triangulate the relative position of the tool in order to identify the fastener being torqued. The torque value is obtained from the tool controller device. By combining the location of the tool and the torque value from the tool controller, assembly of each individual fastener can be verified and its achieved torque recorded.

The IR tracking is capable of tracking within 2‐3 mm for each tracking ball, with a resulting practical resolution of 24 mm distance between fasteners while maintaining 99.9999 per cent reliability without false positive fastener identification.

This experiment was run under simulated assembly line lighting conditions.

By being able to verify assembly reliably, the need for manual torque check is eliminate and hence yield significant cost savings. This will also allow programming electric tools according in real time based on the fastener in proximity identification.

Currently, assembly verification is only done using the torque values. In automated assembly line, each process might involve fastening multiple fasteners. Using this system, a new level of assembly verification is achieved by recording the assembled fastener and its associated torque.

This corpus-based study provides a descriptive account of the distribution of the polysemous noun nafs in two Arabic varieties, Modern Standard Arabic (MSA) and Classical Arabic (CA). The research objective is to survey the use of nafs as a reflexive marker in local binding domains and as a self-intensifier in NP-adjoined positions.

The consulted corpora are Timespamped JSI Web corpus for MSA and Quran corpus for CA. While attending to corpora size differences, MSA and CA exhibit a pattern of difference and similarity in nafs diffusion.

In the modern variety, nafs is pervasively used as reflexive marker in canonical binding domains, along with a less frequent, yet notable, intensifier user, and these uses are partially and cautiously attributed to the specific genre in which they occur. In CA, nafs is mainly recurrent as a polysemous noun, along with extensive use as a reflexive marker in local binding settings. As an intensifier, nafs is totally non-existent in the CA corpus, in the same way as it is in absentia in VP-constituent extraction in MSA.

Examining whether nafs, as a reflexive marker, deviates from canonical binding in Arabic the way English reflexive pronouns do. Building a general account of this distribution is relevant in understanding the explicit (syntactic) and implicit (discourse-based) dimensions of reflexive marker and self-intensifier processing and interpretation in Arabic as a first and second language.