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Downstream pebble variability in river systems is assessed through various methods, with recent emphasis on efficient, time-saving semi-automatic processes involving photography and digital analysis. The Inaouène valley, however, lacked a comprehensive survey of its main channel using either manual or image-based methods. This study bridges this gap by combining both approaches to analyze the downstream evolution of surface pebbles' morphometric parameters along approximately 60 km of the Inaouène's middle reach. Our research focuses on two key aspects: grain size and particle shape. Results reveal a general downstream trend of size fining, increasing circularity and decreasing elongation, primarily attributed to abrasion and travel distance. Notably, this pattern is interrupted by localized variations associated with tributary inputs and sediment recycling processes. This study significantly contributes to the understanding of fluvial sediment dynamics in the Inaouène Valley. Its findings have broad implications, supporting ecological assessment and restoration efforts, while also informing decision-making in river engineering and management. By providing a comprehensive analysis of pebble characteristics and their downstream evolution, this research establishes a foundation for future geomorphological studies and practical applications in river system management. [ABSTRACT FROM AUTHOR]

Introduction: Shooting simulations provide an excellent opportunity to train use-of-force decisions in controlled environments. Recently, military and law enforcement organizations have expressed a growing desire to integrate physiological measurement into simulations for training and feedback purposes. Although participants can easily wear physiological monitors in these scenarios, direct implementation into training may not be simple. Theoretical problems exist in the ultra-short heart rate variability windows associated with use-offorce training, and practical problems emerge as existing scenario libraries at training organizations were not designed for physiological monitoring. Methods: The current study explored the challenges and possibilities associated with direct implementation of physiological monitoring into an existing library of firearms training scenarios. Participants completed scenarios in a shooting simulator using existing military training scenarios while wearing a device to monitor their heart rate. Results: The results revealed lower heart rate variability (approximately 6%) occurred in scenarios where participants did not have to fire weapons, indicating that don't-shoot scenarios may actually impose more cognitive stress on shooters. Additional evidence further demonstrated how both behavioral and physiological factors could be used concomitantly to predict unintentionally firing on non-hostile actors. However, behavioral measures were more predictive (e.g., χ = .221) than physiological measures (e.g., χ = -.132) when the latter metrics were limited to specific scenarios. Qualitative results suggest that simply applying physiological monitoring to existing shooting simulations may not yield optimal results because it would be difficult to directly integrate physiological measurement in a meaningful way without re-designing some elements of the simulations, the training procedure, or both. Discussion: Future use-of-force shooting simulations should consider designing novel scenarios around the physiological measurement rather than directly implementing physiological assessments into existing libraries of scenarios. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) technology has become an important means of flood monitoring because of its large coverage, repeated observation, and all-weather and all-time working capabilities. The commonly used thresholding and change detection methods in emergency monitoring can quickly and simply detect floods. However, these methods still have some problems: (1) thresholding methods are easily affected by low backscattering regions and speckle noise; (2) changes from multi-temporal information include urban renewal and seasonal variation, reducing the precision of flood monitoring. To solve these problems, this paper presents a new flood mapping framework that combines semi-automatic thresholding and change detection. First, multiple lines across land and water are drawn manually, and their local optimal thresholds are calculated automatically along these lines from two ends towards the middle. Using the average of these thresholds, the low backscattering regions are extracted to generate a preliminary inundation map. Then, the neighborhood-based change detection method combined with entropy thresholding is adopted to detect the changed areas. Finally, pixels in both the low backscattering regions and the changed regions are marked as inundated terrain. Two flood datasets, one from Sentinel-1 in the Wharfe and Ouse River basin and another from GF-3 in Chaohu are chosen to verify the effectiveness and practicality of the proposed method. [ABSTRACT FROM AUTHOR]

Nylon is a type of plastic made into thin sheets or bags and used often as transference sheets for water proof packaging. The ease of cutting and sealing a nylon material, especially during mass production of nylon bags, has necessitated automating the process. This paper develops an affordable and effective low-cost semi-automatic nylon cutting and sealing machine that can be utilized by small-scale businesses. The 900 x 400 x 350 mm machine comprises sealing and cutting filament, transformer with wires, teflon tape, micro switch, electric motor, transmission shaft, aluminum casing, mild steel stand and microcontroller. The components were optimized for durability, yet simple one operator use and portability for small-scale business settings. A transmission shaft size 25.4 mm in diameter and 850 mm in length is placed on the machine. The size of the shaft is selected according to the size of the electric motor. Structural analysis through testing validated the structural integrity of key parts. The yield stress was 380 N/mm2 and the safety factor was considered to be 2, so the working stress was 190 N/mm2 and the permissible shear stress was 100.71 N/mm². The performance testing showed that the prototype semi-automatic cutting and sealing machine has efficiency of 80% while cutting and sealing nylon at a rate of 700 bags per hour. These results confirm the machine's ability to overcome the limitations of laborious manual methods through a continuous, high-output cutting and sealing process. Further, the machine is functional and possesses high performance efficiency with reasonable degree of accuracy. [ABSTRACT FROM AUTHOR]

Downstream pebble variability in river systems is assessed through various methods, with recent emphasis on efficient, time-saving semi-automatic processes involving photography and digital analysis. The Inaouène Valley, however, lacked a comprehensive survey of its main channel using either manual or image-based methods. This study bridges this gap by combining both approaches to analyze the downstream evolution of surface pebbles' morphometric parameters along approximately 60 km of the Inaouène's middle reach. Our research focuses on two key aspects: grain size and particle shape. Results reveal a general downstream trend of size fining, increasing circularity and decreasing elongation, primarily attributed to abrasion and travel distance. Notably, this pattern is interrupted by localized variations associated with tributary inputs and sediment recycling processes. This study significantly contributes to the understanding of fluvial sediment dynamics in the Inaouène Valley. Its findings have broad implications, supporting ecological assessment and restoration efforts, while also informing decision-making in river engineering and management. By providing a comprehensive analysis of pebble characteristics and their downstream evolution, this research establishes a foundation for future geomorphological studies and practical applications in river system management.

Through logical analysis of the phenomenon of recovery faults after train arrivals in a semi-automatic receiving station from a departure station, this paper confirms the lighting status of the indicator lights on the console displays of the two stations under fault conditions, observes the operation of the relays in the recovery circuits of the two stations during faults, tests the receiving and sending voltage values and amplitude of the distributing terminal boards in the signal mechanical rooms of the two stations during faults, and observes the time length of the pulse signal. This paper then makes full use of microcomputer to monitor and replay the fault phenomenon, browses and compares the voltage curve status, data, amplitude and pulse time curve status and curve lengths of the negative pulses sent and received by the two stations under the fault conditions, so as to accurately determine the fault range, confirm the fault point, and quickly deal with the fault. [ABSTRACT FROM AUTHOR]

IntroductionShooting simulations provide an excellent opportunity to train use-of-force decisions in controlled environments. Recently, military and law enforcement organizations have expressed a growing desire to integrate physiological measurement into simulations for training and feedback purposes. Although participants can easily wear physiological monitors in these scenarios, direct implementation into training may not be simple. Theoretical problems exist in the ultra-short heart rate variability windows associated with use-of-force training, and practical problems emerge as existing scenario libraries at training organizations were not designed for physiological monitoring.MethodsThe current study explored the challenges and possibilities associated with direct implementation of physiological monitoring into an existing library of firearms training scenarios. Participants completed scenarios in a shooting simulator using existing military training scenarios while wearing a device to monitor their heart rate.ResultsThe results revealed lower heart rate variability (approximately 6%) occurred in scenarios where participants did not have to fire weapons, indicating that don't-shoot scenarios may actually impose more cognitive stress on shooters. Additional evidence further demonstrated how both behavioral and physiological factors could be used concomitantly to predict unintentionally firing on non-hostile actors. However, behavioral measures were more predictive (e.g., β = .221) than physiological measures (e.g., β = −.132) when the latter metrics were limited to specific scenarios. Qualitative results suggest that simply applying physiological monitoring to existing shooting simulations may not yield optimal results because it would be difficult to directly integrate physiological measurement in a meaningful way without re-designing some elements of the simulations, the training procedure, or both.DiscussionFuture use-of-force shooting simulations should consider designing novel scenarios around the physiological measurement rather than directly implementing physiological assessments into existing libraries of scenarios.

Background: The correct positioning of brackets in the orthodontic field is a crucial step in orthodontic treatment. Various methods, including both direct and indirect approaches, are currently employed to achieve precise bracket placements. Each method has its own set of advantages and disadvantages in terms of accuracy and treatment duration. This study introduces a review of the previous researchers work in the field of different bracket placements techniques. Results: In comparison with direct bonding (16 mins and 47 secs), computer-aided indirect bonding required much less time in the clinical chair to bond half of a mouth (12 mins and 52 secs). Nevertheless, the overall bonding time (28 mins and 14 secs) for indirect bonding turned out to be longer than for direct bonding in a case when the time that is needed for digital bracket placement was taken into account. The direct bonding approach did not result in immediate debonding, while the indirect bonding approach resulted in the loss of 14 brackets (5.1%). Computer-aided indirect bonding has been shown to be more costly compared to the direct bonding after a cost-minimization analysis. Conclusions: Many papers are reviewed in bracket placement methods showing a strong need for a newly mechanism that has the feature of semi-automatic operations, that facilitates the time for treatment and in the same time reduce the cost and complexity of the treatment. [ABSTRACT FROM AUTHOR]

Image segmentation is a complex mathematical problem, especially for images that contain intensity inhomogeneity and tightly packed objects with missing boundaries in between. For instance, Magnetic Resonance (MR) muscle images often contain both issues, making muscle segmentation especially difficult. In this paper we propose a novel intensity correction and a semi-automatic active contour-based segmentation approach. The approach uses a geometric flow that incorporates a Reproducing Kernel Hilbert Space (RKHS) edge detector and a geodesic distance penalty term from a set of markers and antimarkers. We test the proposed scheme on MR muscle segmentation and compare with some state-of-the-art methods. To help deal with the intensity inhomogeneity in this kind of image, a new approach to estimate the bias field using a fat fraction image, called Prior Bias-Corrected Fuzzy C-means (PBCFCM), is introduced. Numerical experiments show that the proposed scheme leads to significantly better results than compared ones. The average dice values of the proposed method are 92.5%, 85.3%, 85.3% for quadriceps, hamstrings and other muscle groups while other approaches are at least 10% worse. [ABSTRACT FROM AUTHOR]

In the connection measurement of urban rail transit engineering, the traditional manual connection measurement methods have some drawbacks, such as low work efficiency and easy errors. Through practical research and analysis, this paper proposed a semi-automatic connection measurement method. Based on the "TSDI Multi-observation" airborne software, combined with the Leica total station and the traditional wire-steel method for manual connection measurement, the measurement and data recording were completed through the automatic positioning of the instrument, and then semi-automatic connection measurement was completed. At the same time, utilizing self-designed post-processing software, the data of traverse survey were checked, analyzed, and finally generated, which could be used for rigorous adjustment. A fast and effective method for obtaining high-quality connection measurement results was presented. Using the method in this paper, only 2 surveyors were needed to complete a set of shaft connection survey work, and all the survey work could be completed within 1 hour. Compared to traditional manual measurement, this method improves measurement efficiency by nearly four times, reduces the number of measurement personnel by nearly half, and avoids disadvantages of manual recording errors. [ABSTRACT FROM AUTHOR]

The application of Unmanned Aerial Vehicles (UAV) is becoming increasingly common in geological mapping. The acquired UAV images help in building a 3D virtual outcrop model after processing. In particular, the use of UAV provides a rapid and low-cost method for estimating planar discontinuity orientation in inaccessible outcrops. Several open-access software packages are now available for automatic extraction of the orientation of planar structures using point cloud data generated from UAV images. This study demonstrates software applications for extracting geological discontinuities and compares the results with direct field observations in the outer part of the Garhwal Lesser Himalaya. Two types of geological surfaces, namely, the bedding surface and the fracture surface, are tested by processing point clouds in the discontinuity set extractor (DSE) and the FACETS (cloudcompare) software. Both the DSE and the FACETS require the availability of distinct 3-D exposures and clean point clouds on virtual Outcrop models. Results from both the software deviate from the field observations by a few degrees. Between the two software, FACETS gives relatively more accurate results than the DSE. The compass tool is an additional advantage in the cloudcompare (FACETS). These techniques have been successfully demonstrated in rock mass characterization and slope stability studies. In general, the semi-automatic methods are useful in studies requiring the orientation of a well-exposed single surface or several surfaces in a small area that is inaccessible. These techniques, however, become time-intensive due to noisy data in geologically complex areas where the rocks are cut by multiple sets of discontinuities. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) technology has become an important means of flood monitoring because of its large coverage, repeated observation, and all-weather and all-time working capabilities. The commonly used thresholding and change detection methods in emergency monitoring can quickly and simply detect floods. However, these methods still have some problems: (1) thresholding methods are easily affected by low backscattering regions and speckle noise; (2) changes from multi-temporal information include urban renewal and seasonal variation, reducing the precision of flood monitoring. To solve these problems, this paper presents a new flood mapping framework that combines semi-automatic thresholding and change detection. First, multiple lines across land and water are drawn manually, and their local optimal thresholds are calculated automatically along these lines from two ends towards the middle. Using the average of these thresholds, the low backscattering regions are extracted to generate a preliminary inundation map. Then, the neighborhood-based change detection method combined with entropy thresholding is adopted to detect the changed areas. Finally, pixels in both the low backscattering regions and the changed regions are marked as inundated terrain. Two flood datasets, one from Sentinel-1 in the Wharfe and Ouse River basin and another from GF-3 in Chaohu are chosen to verify the effectiveness and practicality of the proposed method.

Due to the large workload of manual annotation of datasets, uneven data quality and high professional thresholds have been a problem. Based on the idea of semi-automatic annotation, this article discusses the method use of interactive methods to obtain accurate annotations of objects. We propose a method of human–machine interactive object annotation based on one-click guidance. Specifically, we click on a point close to the center of the object and use the prior information of this point to give a guide to the model. The advantages of our method are fourfold: (1) the simulated click method is transferable and can be labeled across datasets; (2) clicks help to eliminate irrelevant areas within the bounding box; (3) the operation is more convenient and does not require artificial boxes, we only need to give the relevant location information; (4) our method supports additional click annotations for further correction. To verify the effectiveness of the proposed method, we conducted a lot of experiments on the KITTI and PASCAL VOC2012 datasets, and the results proved that our model has improved average IoU by 18.1% and 14.6% compared with Anno-Mage and CVAT, respectively. Our method focuses on improving the accuracy and efficiency of annotation, and provides a new idea for the field of semi-automatic annotation. [ABSTRACT FROM AUTHOR]

tomatic search for the most contrast images using a given reference, the experimental data for which were obtained using the analytical technique of X-ray phase contrast imaging. The projections of the biological object were obtained by applying free space propagation of coherent radiation when no additional optical elements are placed between the sample and the detector equipped with a YAG:Ce scintillator to exploit the interference effects characteristic of the method due to the high-intensity characteristics of the X-ray light of the SOLEIL synchrotron. The energy of the X-ray photons was 10 keV, and the distance between the sample and the detector was 16.5 cm. We consider the use of standard Matlab tools for algorithmic correction of inhomogeneities of the detector and probing light beam used to build an image of the internal structure of the object and to evaluate the contrast of a group of images, by choosing such common quality criteria as PSNR and SSIM. The program is able to generate such a set of images depending on the parameters entered by the user for a subjective search for contrast images. Numerical estimates well confirm the visual results of the algorithmic search and allow us to reach the most informative image from the generated array, which is created by the user using the interface. The aim of this work is to familiarize with the use of the developed software product and the concept of semi-automatic search among the dataset of digital phase-contrast images. [ABSTRACT FROM AUTHOR]

Colony forming units counting is a conventional process carry out in bacteriological laboratories, and it is used to follow the behavior of bacteria in different conditions. Currently exist different systems, automatic or semiautomatic, to counting colony forming units exits, but, in general, many laboratories continue using manual counting, which consumes considerable time and effort from researchers and laboratory employees. This paper presents a mathematical model carry out to segment the colony forming units and, in this way, counting them from a digital image of the sample. The method uses the color space information of some points in the image and shows good behavior for images with many or few colony forming units in the sample, according to manual counting. The results show efficiencies close to 98% with MacConkey agar. [ABSTRACT FROM AUTHOR]

Low accuracy of global land cover (LC) products at local and regional scales is concerning, because of its huge impact on downstream applications. Therefore, developing a method for high accuracy LC maps at local and regional scale is of utmost importance. Taking Mongolia as a case study, we proposed a simple, fast, and accurate method to produce annual LC maps with 250 m spatial resolution from 2001 to 2020 using MODIS data. Our products have higher spatial resolution and higher accuracy (Overall Accuracy ~90%) compared to MCD12Q1. These new maps are critical e.g., for land degradation research, and desertification/forest cover monitoring. Especially, information on grassland ecosystems is of utmost importance for Mongolia since more than half of the country economically depends on grassland resources. Therefore, Mongolia will benefit from the new dataset. Furthermore, due to the simplicity of the method, it can be easily applied and transferred to other regions. [ABSTRACT FROM AUTHOR]

Background: Mass shootings account for a small fraction of annual worldwide murders, yet disproportionately affect society and influence policy. Evidence suggesting a link between mass shootings and severe mental illness (i.e. involving psychosis) is often misrepresented, generating stigma. Thus, the actual prevalence constitutes a key public health concern. Methods: We examined global personal-cause mass murders from 1900 to 2019, amassed by review of 14 785 murders publicly described in English in print or online, and collected information regarding perpetrator, demographics, legal history, drug use and alcohol misuse, and history of symptoms of psychiatric or neurologic illness using standardized methods. We distinguished whether firearms were or were not used, and, if so, the type (non-automatic v. semi- or fully-automatic). Results: We identified 1315 mass murders, 65% of which involved firearms. Lifetime psychotic symptoms were noted among 11% of perpetrators, consistent with previous reports, including 18% of mass murderers who did not use firearms and 8% of those who did (χ2 = 28.0, p < 0.01). US-based mass shooters were more likely to have legal histories, use recreational drugs or misuse alcohol, or have histories of non-psychotic psychiatric or neurologic symptoms. US-based mass shooters with symptoms of any psychiatric or neurologic illness more frequently used semi-or fully-automatic firearms. Conclusions: These results suggest that policies aimed at preventing mass shootings by focusing on serious mental illness, characterized by psychotic symptoms, may have limited impact. Policies such as those targeting firearm access, recreational drug use and alcohol misuse, legal history, and non-psychotic psychopathology might yield more substantial results. [ABSTRACT FROM AUTHOR]

Urban road network information is an important part of modern spatial information infrastructure and is crucial for high-precision navigation map production and unmanned driving. Synthetic aperture radar (SAR) is a widely used remote-sensing data source, but the complex structure of road networks and the noises in images make it very difficult to extract road information through SAR images. We developed a new method of extracting road network information from SAR images by considering angular (A) and texture (T) features in the sliding windows and points of interest (POIs, or P), and we named this method ATP-ROAD. ATP-ROAD is a sliding window-based semi-automatic approach that uses the grayscale mean, grayscale variance, and binary segmentation information of SAR images as texture features in each sliding window. Since POIs have much-duplicated information, this study also eliminates duplicated POIs considering distance and then selects a combination of POI linkages by discerning the direction of these POIs to initially determine the road direction. The ATP-ROAD method was applied to three experimental areas in Shanghai to extract the road network using China's Gaofen-3 imagery. The experimental results show that the extracted road network information is relatively complete and matches the actual road conditions, and the result accuracy is high in the three different regions, i.e., 89.57% for Area-I, 96.88% for Area-II, and 92.65% for Area-III. Our method together with our extraction software can be applied to extract information about road networks from SAR images, providing an alternative for enriching the variety of road information. [ABSTRACT FROM AUTHOR]

Passive acoustic surveys are becoming increasingly popular as a means of surveying for cetaceans and other marine species. These surveys yield large amounts of data, the analysis of which is time consuming and can account for a substantial proportion of the survey budget. Semi‐automatic processes enable the bulk of processing to be conducted automatically while allowing analyst time to be reserved for validating and correcting detections and classifications.Existing modules within the Passive Acoustic Monitoring software PAMGuard were used to process a large (25.4 Terabyte) dataset collected during towed acoustic ship transits. The recently developed 'Multi‐Hypothesis Tracking Click Train Detector' and the 'Whistle and Moan Detector' modules were used to identify occasions within the dataset at which vocalising toothed whales (odontocetes) were likely to be acoustically present. These putative detections were then reviewed by an analyst, with false positives being corrected. Target motion analysis provided a perpendicular distance to odontocete click events enabling the estimation of detection functions for both sperm whales and delphinids. Detected whistles were assigned to the lowest taxonomical level possible using the PAMGuard 'Whistle Classifier' module.After an initial tuning process, this semi‐automatic method required 91 hr of an analyst's time to manually review both automatic click train and whistle detections from 1,696 hr of survey data. Use of the 'Multi‐Hypothesis Tracking Click Train Detector' reduced the amount of data for the analyst to search by 74.5%, while the 'Whistle and Moan Detector' reduced data to search by 85.9%. In total, 443 odontocete groups were detected, of which 55 were from sperm whale groups, six were from beaked whales, two were from porpoise and the remaining 380 were identified to the level of delphinid group. An effective survey strip half width of 3,277 and 699 m was estimated for sperm whales and delphinids respectively.The semi‐automatic workflow proved successful, reducing the amount of analyst time required to process the data, significantly reducing overall project costs. The workflow presented here makes use of existing modules within PAMGuard, a freely available and open‐source software, readily accessible to acoustic analysts. [ABSTRACT FROM AUTHOR]

This research presents the design and fabrication of a semi-automatic paper petal compression machine with a pneumatic system to crease paper petals for making artificial flowers. The description comprises the procedures of defining operating characteristics for the machine, drawing its function diagram, designing the pneumatic circuit and the electrical circuit, calculating and choosing the dimensions of pneumatic components, and studying optimum paper petal compression conditions and appearances of creases on the paper petals. The machine can be used to compress the paper petals in four positions at the same time. The experimental materials were the paper of 55 and 65 gsm which was cut in the petal shape. The experiments were done by rolling 6, 8, 10, 12, 14, and 16 pieces of paper petals into hollow cylinders of which four rolls of those with the same number of paper petals were compressed simultaneously at the operating pressure of 0.6 MPa. The results showed that the machine could be used to compress the paper petals of 55 gsm to provide quite noticeable and consistent creases in the range of 6 to 14 pieces per roll, while the paper petals of 65 gsm were in the range of 6 to 12 pieces per roll. [ABSTRACT FROM AUTHOR]

Road network extraction plays a critical role in data updating, urban development, and decision support. To improve the efficiency of labeling road datasets and addressing the problems of traditional methods of manually extracting road networks from high-resolution images, such as their slow speed and heavy workload, this paper proposes a semi-automatic method of road network extraction from high-resolution remote-sensing images. The proposed method needs only a few points to extract a single road in the image. After the roads are extracted one by one, the road network is generated according to the width of each road and the spatial relationships among the roads. For this purpose, we use regional growth, morphology, vector tracking, vector simplification, endpoint modification, road connections, and intersection connections to generate road networks. Experiments on four images with different terrains and different resolutions show that this method has high extraction accuracy under different image conditions. The comparisons with the semi-automatic GVF-snake method based on regional growth also showed its advantages and potentiality. The proposed method is a novel form of semi-automatic road network extraction, and it significantly increases the efficiency of road network extraction. [ABSTRACT FROM AUTHOR]

Purpose The aims of this study were to evaluate a semi-automatic segmentation software for assessment of ablation zone geometry in computed tomography (CT)-guided microwave ablation (MWA) of liver tumors and to compare two different MWA systems. Material and Methods 27 patients with 40 hepatic tumors (primary liver tumor n = 20, metastases n = 20) referred for CT-guided MWA were included in this retrospective IRB-approved study. MWA was performed using two systems (system 1: 915 MHz; n = 20; system 2: 2.45 GHz; n = 20). Ablation zone segmentation and ellipticity index calculations were performed using SAFIR (Software Assistant for Interventional Radiology). To validate semi-automatic software calculations, results (2 perpendicular diameters, ellipticity index, volume) were compared with those of manual analysis (intraclass correlation, Pearson’s correlation, Mann–Whitney U test; p

Background: We study dual-task performance with marker-free video recordings of Timed Up-and-Go tests (TUG) and TUG combined with a cognitive/verbal task (TUG dual-task, TUGdt).Research Question: Can gait parameters be accurately estimated from video-recorded TUG tests by a new semi-automatic method aided by a technique for human 2D pose estimation based on deep learning?Methods: Thirty persons aged 60-85 years participated in the study, conducted in a laboratory environment. Data were collected by two synchronous video-cameras and a marker-based optoelectronic motion capture system as gold standard, to evaluate the gait parameters step length (SL), step width (SW), step duration (SD), single-stance duration (SSD) and double-stance duration (DSD). For reliability evaluations, data processing aided by a deep neural network model, involved three raters who conducted three repetitions of identifying anatomical keypoints in recordings of one randomly selected step from each of the participants. Validity was analysed using 95 % confidence intervals (CI) and p-values for method differences and Bland-Altman plots with limits of agreement. Inter- and intra-rater reliability were calculated as intraclass correlation coefficients (ICC) and standard errors of measurement. Smallest detectable change was calculated for inter-rater reliability.Results: Mean ddifferences between video and the motion capture system data for SW, DSD, and SSD were significant (p < 0.001). However, mean differences for all parameters were small (-6.4%-13.0% of motion capture system) indicating good validity. Concerning reliability, almost all 95 % CI of the ICC estimates exceeded 0.90, indicating excellent reliability. Only inter-rater reliability for SW (95 % CI = 0.892;0.973) and one rater's intra-rater reliability for SSD (95 % CI = 0.793;0.951) were lower, but still showed good to excellent reliability.Significance: The presented method for extraction of gait parameters from video appears suitable for valid and reliable quantification of gait. This opens up for analyses that may contribute to the knowledge of cognitive-motor interference in dual-task testing. [ABSTRACT FROM AUTHOR]

Urban road network information is an important part of modern spatial information infrastructure and is crucial for high-precision navigation map production and unmanned driving. Synthetic aperture radar (SAR) is a widely used remote-sensing data source, but the complex structure of road networks and the noises in images make it very difficult to extract road information through SAR images. We developed a new method of extracting road network information from SAR images by considering angular (A) and texture (T) features in the sliding windows and points of interest (POIs, or P), and we named this method ATP-ROAD. ATP-ROAD is a sliding window-based semi-automatic approach that uses the grayscale mean, grayscale variance, and binary segmentation information of SAR images as texture features in each sliding window. Since POIs have much-duplicated information, this study also eliminates duplicated POIs considering distance and then selects a combination of POI linkages by discerning the direction of these POIs to initially determine the road direction. The ATP-ROAD method was applied to three experimental areas in Shanghai to extract the road network using China’s Gaofen-3 imagery. The experimental results show that the extracted road network information is relatively complete and matches the actual road conditions, and the result accuracy is high in the three different regions, i.e., 89.57% for Area-I, 96.88% for Area-II, and 92.65% for Area-III. Our method together with our extraction software can be applied to extract information about road networks from SAR images, providing an alternative for enriching the variety of road information.

Deep learning has delivered promising results for automatic polyp detection and segmentation. However, deep learning is known for being data-hungry, and its performance is correlated with the amount of available training data. The lack of large labeled polyp training images is one of the major obstacles in performance improvement of automatic polyp detection and segmentation. Labeling is typically performed by an endoscopist, who performs pixel-level annotation of polyps. Manual polyp labeling of a video sequence is difficult and time-consuming. We propose a semi-automatic annotation framework powered by a convolutional neural network (CNN) to speed up polyp annotation in video-based datasets. Our CNN network requires only ground-truth (manually annotated masks) of a few frames in a video for training and annotating the rest of the frames in a semi-supervised manner. To generate masks similar to the ground-truth masks, we use some pre and post-processing steps such as different data augmentation strategies, morphological operations, Fourier descriptors, and a second stage fine-tuning. We use Fourier coefficients of the ground-truth masks to select similar generated output masks. The results show that it is possible to 1) produce ~ 96% of Dice similarity score between the polyp masks provided by clinicians and the masks generated by our framework, and 2) save clinicians time as they need to manually annotate only a few frames instead of annotating the entire video, frame-by-frame.

Road network extraction plays a critical role in data updating, urban development, and decision support. To improve the efficiency of labeling road datasets and addressing the problems of traditional methods of manually extracting road networks from high-resolution images, such as their slow speed and heavy workload, this paper proposes a semi-automatic method of road network extraction from high-resolution remote-sensing images. The proposed method needs only a few points to extract a single road in the image. After the roads are extracted one by one, the road network is generated according to the width of each road and the spatial relationships among the roads. For this purpose, we use regional growth, morphology, vector tracking, vector simplification, endpoint modification, road connections, and intersection connections to generate road networks. Experiments on four images with different terrains and different resolutions show that this method has high extraction accuracy under different image conditions. The comparisons with the semi-automatic GVF-snake method based on regional growth also showed its advantages and potentiality. The proposed method is a novel form of semi-automatic road network extraction, and it significantly increases the efficiency of road network extraction.

Macadamia is the king of nuts and popular around the world. Cracking is vital to extract the whole nut and increases the commercial value of the product. Therefore, a semi-automatic macadamia cracking machinewas designed and assessed.It was modified froma manual nut cracker. Such a machine was expected to have a higher throughputand produce a higher quality output. The key part of this machine consisted of a drive blade set and a nut discharge set, which were both upgradedso that they weredriven by an electric motor. In extant machines, both these tasks are manual. We tested blade speeds of up to 22 rpm, macadamia nut diameters from 21 to 27 mm and the method to feed the nuts into the cracking section. The optimum cracking condition was found to be a 19 rpm blade speed or 19 cracking strokes per minute. The feeder handled 99% of the nuts successfully leading to a nut throughputof 10.6 kg/h, with 88% whole kernels. The best cracking performance was found on nut diameters in the range of 25 to 27 mm with a blade compression depth of 2.5 mm.

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This study assesses the performance of selected intersections in Akure, Nigeria. The identified intersections were Road block, Bye-pass and Cathedral intersections. Data for this study which included traffic volumes was collected through semi-automatic method, personal observations and questioning of individuals. The results of the data analysis revealed that the Level of Service (LOS) for Road block intersection was critically low (LOS = F) due to on-street parking and the absence of traffic signals to aid drivers. Likewise, the LOS for Cathedral intersection is low (LOS = E) while that of Byepass (LOS = C) appears to be adequate. [ABSTRACT FROM AUTHOR]

Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed approach gives high accuracy and specificity values. A significant advantage of the proposed method is the ability to deal with discontinuities in the lesion. [ABSTRACT FROM AUTHOR]

The aims of this study were to evaluate a semi-automatic segmentation software for assessment of ablation zone geometry in computed tomography (CT)-guided microwave ablation (MWA) of liver tumors and to compare two different MWA systems. 27 patients with 40 hepatic tumors (primary liver tumor n = 20, metastases n = 20) referred for CT-guided MWA were included in this retrospective IRB-approved study. MWA was performed using two systems (system 1: 915 MHz; n = 20; system 2: 2.45 GHz; n = 20). Ablation zone segmentation and ellipticity index calculations were performed using SAFIR (Software Assistant for Interventional Radiology). To validate semi-automatic software calculations, results (2 perpendicular diameters, ellipticity index, volume) were compared with those of manual analysis (intraclass correlation, Pearson’s correlation, Mann–Whitney U test; p < 0.05 deemed significant. Manual measurements of mean maximum ablation zone diameters were 43 mm (system 1) and 34 mm (system 2), respectively. Correlations between manual and semi-automatic measurements were r = 0.72 and r = 0.66 (both p < 0.0001) for perpendicular diameters, and r = 0.98 (p < 0.001) for volume. Manual analysis demonstrated that ablation zones created with system 2 had a significantly lower ellipticity index compared to system 1 (mean 1.17 vs. 1.86, p < 0.0001). Results correlated significantly with semi-automatic software measurements (r = 0.71, p < 0.0001). Semi-automatic assessment of ablation zone geometry using SAFIR is feasible. Software-assisted evaluation of ablation zones may prove beneficial with complex ablation procedures, especially for less experienced operators. The 2.45 GHz MWA system generated a significantly more spherical ablation zone compared to the 915 MHz system. The choice of a specific MWA system significantly influences ablation zone geometry. [ABSTRACT FROM AUTHOR]

Macadamia is the king of nuts and popular around the world. Cracking is vital to extract the whole nut and increases the commercial value of the product. Therefore, a semi-automatic macadamia cracking machine was designed and assessed. It was modified from a manual nut cracker. Such a machine was expected to have a higher throughput and produce a higher quality output. The key part of this machine consisted of a drive blade set and a nut discharge set, which were both upgraded so that they were driven by an electric motor. In extant machines, both these tasks are manual. We tested blade speeds of up to 22 rpm, macadamia nut diameters from 21 to 27 mm and the method to feed the nuts into the cracking section. The optimum cracking condition was found to be a 19 rpm blade speed or 19 cracking strokes per minute. The feeder handled 99% of the nuts successfully leading to a nut throughput of 10.6 kg/h, with 88% whole kernels. The best cracking performance was found on nut diameters in the range of 25 to 27 mm with a blade compression depth of 2.5 mm. [ABSTRACT FROM AUTHOR]