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Partial alignment for 3 D point sets is a challenging problem for laser calibration and robot calibration due to the unbalance of data sets, especially when the overlap of data sets is low. Geometric features can promote the accuracy of alignment. However, the corresponding feature extraction methods are time consuming. The purpose of this paper is to find a framework for partial alignment by an adaptive trimmed strategy.

First, the authors propose an adaptive trimmed strategy based on point feature histograms (PFH) coding. Second, they obtain an initial transformation based on this partition, which improves the accuracy of the normal direction weighted trimmed iterative closest point (ICP) method. Third, they conduct a series of GPU parallel implementations for time efficiency.

The initial partition based on PFH feature improves the accuracy of the partial registration significantly. Moreover, the parallel GPU algorithms accelerate the alignment process.

This study is applicable to rigid transformation so far. It could be extended to non-rigid transformation.

In practice, point set alignment for calibration is a technique widely used in the fields of aircraft assembly, industry examination, simultaneous localization and mapping and surgery navigation.

Point set calibration is a building block in the field of intelligent manufacturing.

The contributions are as follows: first, the authors introduce a novel coarse alignment as an initial calibration by PFH descriptor similarity, which can be viewed as a coarse trimmed process by partitioning the data to the almost overlap part and the rest part; second, they reduce the computation time by GPU parallel coding during the acquisition of feature descriptor; finally, they use the weighted trimmed ICP method to refine the transformation.

During the process of the robotic grinding and polishing operations on aero-engine blades, the key problem of calibration error lies in fixture error and uneven margin. To solve this problem, this paper aims to propose a novel method to achieve rapid online calibration of the workpiece coordinate system through laser-based measurement techniques.

The authors propose a calibration strategy based on point cloud registration algorithm. The main principle is presented as follows: aero blade mounted on clamping end-effector is hold by industry robot, the whole device is then scanned by a 3D laser scanner to obtain its surface point cloud, and a fast segmentation method is used to acquire the point cloud of the workpiece. Combining Super4PCS algorithm with trimmed iterative closest point, we can align the key points of the scanned point cloud and the sampled points of the blade model, thus obtaining the translation and rotation matrix for calculating the workpiece coordinate and machining allowance. The proposed calibration strategy is experimentally validated, and the positioning error, as well as the margin distribution, is finally analyzed.

The experimental results show that the algorithm can well accomplish the task of cross-source, partial data and similar local features of blade point cloud registration with high precision. The total time spent on point cloud alignment of 100,000 order of magnitude blade is about 4.2 s, and meanwhile, the average point cloud alignment error is reduced to below 0.05 mm.

An improved point cloud registration method is proposed and introduced into the calibration process of a robotic system. The online calibration technique improves the accuracy and efficiency of the calibration process and enhances the automation of the robotic grinding and polishing system.

The purpose of this study is to present reports on fabrication of silicon (Si) nanowires (NWs). The study consists of microwire formation on silicon-on-insulator (SOI) that was fabricated using a top-down approach which involved conventional photolithography coupled with shallow anisotropic etching.

A 5-inch p-type silicon-on-insulator (SOI) coated with 250nm layer and Photoresist (PR) with thickness of 400nm is coated in order to make pattern transfer via binary mask, after the exposure and development, a resist pattern between 3 μm-5 μm were obtained, Oxygen plasma spreen was used to reduce the size of the PR to 800 μm, after this, the wafer with 800 μm was loaded into SAMCO inductively coupled plasma (ICP)-RIE and got silicoon microwire was obtained. Next, the sample was put into an oxidation furnace for 15, 30, 45 and 60 minutes and the sample was removed and dipped into a buffered oxide etch solution for five minutes to remove all the SiO₂ ashes.

The morphological characterization was conducted using scanning electron microscopy and atomic force microscopy. At terminal two, gold electrodes which were designated as source and drain were fabricated on top of individual NWs using conventional lithography electrical and chemical response. Once the trimming process has been completed, the device's current–voltage (I-V) characteristic was measured by using a Keithley 4200 semiconductor parameter analyser. Devices with different width of wires approximately 20, 40, 60 and 80 nm were characterized. The wire current variation as a function of the pH variation in voltage was investigated: pH monitoring for variations of pH values between 5 and 9.

This paper provides useful information on novel and yet simple cost-effective fabrication of SiNW; as such, it should be of interest to a broad readership, especially those interested in micro/nanofabrication.

To report on the evaluation of error of a face matching system consisting of a 3D sensor for obtaining the surface of the face, and a two‐stage matching algorithm that matches the sensed surface to a model surface.

Rigid mannikin face that was, otherwise, fairly realistic was obtained, and several sensing and matching experiments were performed. Pose position, lighting and face color were controlled.

The combined sensor‐matching system typically reported correct face surface matches with trimmed RMS error of 0.5 mm or less for a generous volume of parameters, including roll, pitch, yaw, position, lighting, and facecolor. Error accelerated beyond this “approximately frontal” set of parameters. Mannikin results are compared to results with thousands of cases of real faces. The sensor accuracy is not a limiting component of the system, but supports the application well.

The sensor supports the application well (except for the current cost). Equal error rates achieved appear to be practical for face verification.

No similar report is known for sensing faces.

This paper aims to propose an identification method based on monocular vision for cylindrical parts in cluttered scene, which solves the issue that iterative closest point (ICP) algorithm fails to obtain global optimal solution, as the deviation from scene point cloud to target CAD model is huge in nature.

The images of the parts are captured at three locations by a camera amounted on a robotic end effector to reconstruct initial scene point cloud. Color signatures of histogram of orientations (C-SHOT) local feature descriptors are extracted from the model and scene point cloud. Random sample consensus (RANSAC) algorithm is used to perform the first initial matching of point sets. Then, the second initial matching is conducted by proposed remote closest point (RCP) algorithm to make the model get close to the scene point cloud. Levenberg Marquardt (LM)-ICP is used to complete fine registration to obtain accurate pose estimation.

The experimental results in bolt-cluttered scene demonstrate that the accuracy of pose estimation obtained by the proposed method is higher than that obtained by two other methods. The position error is less than 0.92 mm and the orientation error is less than 0.86°. The average recognition rate is 96.67 per cent and the identification time of the single bolt does not exceed 3.5 s.

The presented approach can be applied or integrated into automatic sorting production lines in the factories.

The proposed method improves the efficiency and accuracy of the identification and classification of cylindrical parts using a robotic arm.

The study explored the relationship between buyer–seller interactions and customer satisfaction in the small apparel fashion enterprises in the emerging markets. The moderating role of COVID-19 protocols implementations on buyer–seller interactions and customer satisfaction was further examined.

Buyer–seller interactions affecting customer satisfaction were divided into three constructs, namely, interactions relating to the overall customers shopping experience, smooth payment process and in-store interactions, and the COVID-19 protocols implementations were used as a moderator. A convenient sampling strategy was adopted to survey 450 customers of apparel fashion enterprises within the four regions in Ghana, of which 397 were validly used for the analysis. Existing questionnaires were adapted to collect data from the respondents. The data collected was therefore analysed using SPSS and SmartPLS programme to ascertain the nature of the relationships among the variables.

The study found that, in-store interactions, shopping experience and smooth payment processes directly influence customer satisfaction. However, the implementation of COVID-19 protocols failed to moderate the relationship between buyer–seller interactions and customer satisfaction.

The limitations of the study involve its context-specific, focusing on the small apparel and fashion market. Also, future researchers can re-examine the model in other geographical jurisdictions, focusing on small apparel owners’ competencies and other variables that position buyer–seller interactions as precursors of customer satisfaction in the small apparel fashion industry. The theoretical and managerial relevance of the findings are also discussed.

The paper extends the domain of buyer–seller interactions and customer satisfaction phenomena within the apparel fashion industry. Its examination of the impact of COVID-19 protocols’ implementation on customer satisfaction provides an insight into managers regarding how the applications can affect customers in a typical shopping environment.

Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

The purpose of the paper is to study the effects of cooking on proximate composition, amino acids, fatty acids, minerals and total, heme and non‐heme iron content of camel meat.

A total of ten longissimus thoracis muscles (500 grams) were collected between the tenth and twelfth ribs of the left side. Samples were randomly collected from two to three year old camel carcasses chilled (1‐3°C) for 48 hours then stored at −20°C. The first portion was kept fresh while the second one was placed in plastic bags and cooked by immersion in a water bath at 70°C for 90 minutes. Both samples were freeze‐dried, and then ground to a homogeneous mass to be used for chemical analyses.

Cooked samples had significantly (p<0.05) higher dry matter by 27.7 per cent, protein by 31.1 per cent and fat by 22.2 per cent, but lower ash content by 8.3 per cent than the raw ones. Cooking had no significant effect on amino acid and fatty acid composition of the meat. The components of camel meat most significantly affected by cooking were macro‐ and micro‐minerals, which ranged between 13.1 and 52.5 per cent, respectively. Cooking resulted in a significant decrease in total, heme and non‐heme iron contents by 4.3, 8.7 and 4.0 per cent, respectively.

The research is restricted to camel meat but it is an exploratory study. The issue of research outcome as only longissimus thoracic muscle is another limitation. Further investigation is needed to include different muscles, temperatures, durations and cooking methods.

Amino acids and fatty acids of camel meat are not affected by cooking, while heating accelerated total and heme iron oxidation suggest camel meat to be a rich source of heme iron.

The paper is original in its findings and useful for both researchers and academics in the field of meat science.

The purpose of this paper is to determine the long‐term corrosion behavior of cast iron coupons in the Jubail Industrial City (JIC), Saudi Arabia.

The samples were exposed under atmospheric, underground, and splash zone conditions, at Khaleej Mardumah Test Station (KMTS) in Jubail. Soil, groundwater, seawater and air particulate samples were collected at the exposure sites and were analyzed. Secondary electron microscopy (SEM), X‐ray diffraction (XRD) and X‐ray fluorescence (XRF) were used to examine the surface morphology of the test coupons and identify the corrosion products developed on the surface of the metals. The corrosion rates of the coupons were determined by weight loss method.

The results showed that the atmosphere, underground and splash zone conditions all were very corrosive to cast iron, due to temperature and humidity variations as well as the high chloride and sulfate concentrations in the region. The splash zone was the most corrosive regime of the three test zones. The main corrosive ions in the environments were identified as chloride and sulfate. The maximum chloride and sulfate concentrations were measured to be 8.94 and 49.65 μg/m³ in atmosphere, 8,040 and 1,410 ppm in soil, and 29,500 and 5,770 mg/l in seawater, respectively. The corrosion rates of cast irons were found to be 343‐536 μm/y in splash zone, 90‐214 μm/y in underground, and 22‐27 μm/y in atmosphere. Compared to other parts of the world, the soil, marine and atmospheric environments at the selected test site are very corrosive.

In this paper, corrosion of cast iron is presented in atmospheric, soil and splash zone conditions along the eastern coast of the Arabian Gulf.

Since the execution of National Health Insurance system in Taiwan, the competition of medical industry is becoming more and more severe. The ways the hospital operate knowledge management (KM) concept, combine current human resources and professional knowledge by information techniques and upgrade the competitiveness through reinvention of organizational culture have become the important issues. This research is based on the relationship between KM and organizational operation, integrates the characteristic of medical institutions and framework of medical knowledge cycle and starts the research subject by questionnaires from three dimensions: current situation of KM construction in medical organizations, executive effect of KM activities and the challenges faced by KM; subsequently, from qualitative interview, this research attempts to understand how a medical organization executes and adjusts in the consideration of theory and reality as well as quality and costs when actually operates the organization. This research accesses to KM system application of medical institutions and the empirical executive benefits and difficulties through questionnaires. The research results are as follows: (1) having initial understanding toward current KM establishment of medical institutions; (2) confirming the most important items of KM establishment of medical organizations; (3) understanding the most difficulty which the medical organizations encounter when executing KM; (4) establishing medical knowledge cycle figure of the hospitals receiving interviews. Through case interview, this research profoundly accessed to the actual operation of KM application of medical organizations. The target hospitals intended to try many medical KM measures; however, during to complicated hospital organizations and cultural characteristics, the promotion was not successful and the results were not apparent. The most difficulty was to change the employees’ behavior. The targets believed that only the continuous promotion of KM can allow it to be an important aspect of organizational culture and the competitiveness could constant be upgraded.