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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]

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]

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]

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]

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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]

A city mapping is essential to various applications such as planning, transport management, vehicle navigation, intervention in natural disasters, etc…. For convenience and efficiency, such applications are integrated in a Geographical Information System (GIS) (Bendouda and Berrached, in Etude et réalisation d’UREGIS un SIG pour la gestion du réseau routier urbain, Magister Thesis, University of Sciences and Technology of Oran Algeria 2009). GIS Map needs real time automatic updating and revisions of the road network databases. However, due to the extreme complexity of the urban environment, there are currently many methods involving the extraction of roads by means of automatic or semi-automatic approaches in rural and sub-urban areas; but in urban environment the majority of these methods failed, due to the complexity of this environment and the complex appearance of the road in the remotely sensed image. In this paper, we introduce a new approach to extract road network in urban area from low resolution satellite images. The proposed method is a modified version of the dynamic programming method for semi-automatic extraction of road network, based on the F* algorithm. The preliminary step is the seeding of points belonging to roads. F* detects the segments that may belong to a road by optimizing certain criteria. Given the complexity of urban areas and the existence of different road categories, we propose an improved version of the classical algorithm F* called PR-F*(Parallel Research-F*). It detects the road segments automatically in many directions. The obtained results are evaluated in terms of quality with respect to completeness and correctness. [ABSTRACT FROM AUTHOR]

Fit-for-purpose land administration aims to align cadastral policies, administration and technology selection with the prevailing societal needs and capacity within a country context. It seeks to support delivery of more rapid and low-cost cadastral boundary mapping - and ultimately more widespread land tenure security. The philosophy suggests that when high positional accuracies are not the primary concern, but when time pressure is, high-resolution satellite images can serve as a source for creating cadastral boundary information. This paper explores the potential of mean-shift segmentation plug-in in QGIS to semi-automatically extract cadastral boundaries in rural areas - based on the land cover information from WorldView-2 satellite images. The segmentation gives a vector file satisfying many cadastral boundary requirements and ready to be used in a GIS environment. The buffer overlay method was used to assess the quality of extracted boundaries. For a non-vegetated terrain having visible boundaries, the approach could be taken as an alternative to support existing, relatively slow, boundary mapping approaches by minimizing the effects of manual digitization and surveying. [ABSTRACT FROM AUTHOR]

This article summarizes some research results related to ontology enrichment specific to tourism domains from 2014 to 2017. Currently, some ontology enrichment approaches can use learning machinery such as support vector machine (SVM), Conditional Random Field (CRF) and kNN. Several studies have also been successful in evaluating ontology enrichment results with several parameters such as precision, recall and F-Measure. In addition, our research can enrich Dwipa Ontology II which has been successfully done by population to object/sample. The method used in this research is ontology enrichment method. This technique or method is used to show background knowledge (ontology) by adding new concepts and relationships through the extraction process. The enrichment process is done on semi-automated web document (corpus). The process using statistics and linguistics, by applying evaluation techniques by using reviewers in the field of tourism. The end result of Dwipa Ontology III (enriched ontology) contains 4 main classes, 15 subclasses and 199 samples/objects. The expansion of general concept/subclass knowledge under the attraction classes are: cultural parks, artists and monuments. [ABSTRACT FROM AUTHOR]

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It's well known that trends worldwide are towards automation. We look for having automatic, or worst case semi-automatic, processes, systems, machines, with the purpose to produce a finished good in the shortest time. Consider we have a semi-automatic system used to obtain air separation. The entire system is 'supervised' by a so called DCS (Distributed Control System) with the role to command several vanes with different functions. Human factor interferes with DCS only for digital data input. The system converts digital information in analogical signals in order to control pressure or flow. The issues of interest addressed in the present paper concern losses and gains brought by automation for this particular case of study. [ABSTRACT FROM AUTHOR]

Speech is always accompanied by noise when the speaker is talking in the environment. To improve the intelligibility of speech signal, noise should be reduced using noise reduction softwares. From the existing software the aim of the present study was to examine the effect of noise reduction technique on speaker identification using Mel Frequency Cepstral Co-Efficient (MFCC) on the long vowels in Kannada language. Ten Kannada speaking neuro-typical adults in the age range of 20-35 years (5 males and 5 females) participated in the study. Commonly occurring Kannada meaningful sentences with long vowels /a:/, /i:/, /u:/ was used for reading task. The same was recorded in two different conditions: Lab condition and Traffic condition. These samples were analyzed under two phases: Before noise reduction (BNR) and After noise reduction (ANR), using Sound Cleaner Software. Speech Science Lab Work bench software was used to extract MFCC for the truncated (PRAAT software) vowels. Results of the study revealed that in Lab condition, Traffic condition (BNR), Traffic condition (ANR), Lab condition verses traffic (BNR) and in Lab condition verses traffic condition (ANR), the vowel /i:/ is found to be better followed by /a:/ and /u:/ in the average percentage of correct speaker identification of the vowels. Overall results revealed vowel /i:/ is better for speaker identification. Hence, the `sound cleaner' has a significant effect on percent speaker identification by reducing the influence of noise without majorly affecting the acoustical parameter of certain vowel considered for the present study. [ABSTRACT FROM AUTHOR]

This paper examined whether FreeSurfer--generated data differed between a fully--automated, unedited pipeline and an edited pipeline that included the application of control points to correct errors in white matter segmentation. In a sample of 30 individuals, we compared the summary statistics of surface area, white matter volumes, and cortical thickness derived from edited and unedited datasets for the 34 regions of interest (ROIs) that FreeSurfer (FS) generates. To determine whether applying control points would alter the detection of significant differences between patient and typical groups, effect sizes between edited and unedited conditions in individuals with the genetic disorder, 22q11.2 deletion syndrome (22q11DS) were compared to neurotypical controls. Analyses were conducted with data that were generated from both a 1.5 tesla and a 3 tesla scanner. For 1.5 tesla data, mean area, volume, and thickness measures did not differ significantly between edited and unedited regions, with the exception of rostral anterior cingulate thickness, lateral orbitofrontal white matter, superior parietal white matter, and precentral gyral thickness. Results were similar for surface area and white matter volumes generated from the 3 tesla scanner. For cortical thickness measures however, seven edited ROI measures, primarily in frontal and temporal regions, differed significantly from their unedited counterparts, and three additional ROI measures approached significance. Mean effect sizes for edited ROIs did not differ from most unedited ROIs for either 1.5 or 3 tesla data. Taken together, these results suggest that although the application of control points may increase the validity of intensity normalization and, ultimately, segmentation, it may not affect the final, extracted metrics that FS generates. Potential exceptions to and limitations of these conclusions are discussed. [ABSTRACT FROM AUTHOR]

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Background and study aims: Natural orifice transluminal endoscopic surgery (NOTES) is an emerging surgical technique. We aimed to design, create, and evaluate a new semi-automatic snake robot for NOTES. Materials and methods: The snake robot employs the characteristics of both a manual endoscope and a multi-segment snake robot. This robot is inserted and retracted manually, like a classical endoscope, while its shape is controlled using embedded robot technology. The feasibility of a prototype robot for NOTES was evaluated in animals and human cadavers. Results: The transverse stiffness and maneuverability of the snake robot appeared satisfactory. It could be advanced through the anus as far as the peritoneal cavity without any injury to adjacent organs. Preclinical tests showed that the device could navigate the peritoneal cavity. Conclusions: The snake robot has advantages of high transverse force and intuitive control. This new robot may be clinically superior to conventional tools for transanal NOTES. [ABSTRACT FROM AUTHOR]

Aim was to obtain the benchmark for speaker identifi cation using Mel Frequency Cepstral Coefficients (MFCC) on vowels following the nasal continuants in Kannada language. Participants chosen were twenty Kannada speaking male neuro-typical adults, in the age range of 20-30 years. Kannada meaningful words (30) with long vowels /a:/, /i:/, /u:/ following the nasal continuants /m/ and /n/ formed the material. Speech Science Lab Work bench, a Semi-Automatic vocabulary dependent speaker recognition software was used to extract MFCC for the trun-cated (PRAAT) long vowels. Results indicated higher percent correct identification for Condition I (live verse live recording). On comparison among the three vowels following the nasal continuant /m/, /i:/ is better followed by /a:/ and /u:/. Whereas for /n/ the vowel /a:/ is better followed by /i:/ and /u:/. On an average of percentage of correct speaker identification of three vowels compared between the nasal continuant, the vowels following the nasal /n/ (90%) and /m/ (90%) was similar. Condition II (Mobile verse Mobile) and Condition III (Mobile verse Live) was comparatively poorer than Condition I, thus the benchmark was obtained. Discussion concludes that during the transmission of voice signals through communication channels, the signals are reproduced with errors caused by distortions from the microphone and channel, and acoustical, electromagnetic interferences and noises affect the transmitting signal. Where speech coding algorithms that are part of Global System for Mobile compress speech signal before transmission, reduce the number of bits in digital representation but at the same time, maintain acceptable quality. [ABSTRACT FROM AUTHOR]

This letter presents a semi-automatic approach to delineating road networks from very high resolution satellite images. The proposed method consists of three main steps. First, the geodesic method is used to extract the initial road segments that link the road seed points prescribed in advance by users. Next, a road probability map is produced based on these coarse road segments and a further direct thresholding operation separates the image into two classes of surfaces: the road and nonroad classes. Using the road class image, a kernel density estimation map is generated, upon which the geodesic method is used once again to link the foregoing road seed points. Experiments demonstrate that this proposed method can extract smooth correct road centerlines. [ABSTRACT FROM PUBLISHER]

ABSTRACT This paper introduces the conversion of Euler's equation from a Cartesian coordinate system to a radial coordinate system, and then demonstrates that for sources of the type 1/rN (where r is the distance to the source, and N is the structural index) it can be solved at each point in space without the need for inversion, for a known structural index. It is shown that although the distance to the source that is obtained from Euler's equation depends on the structural index used, the direction to the source does not. For some models, such as the gravity and magnetic response of a contact, calculation of the analytic signal amplitude of the data is necessary prior to the application of the method. Effective noise attenuation strategies, such as the use of moving windows of data points, are also discussed. The method is applied to gravity and magnetic data from South Africa, and yields plausible results. [ABSTRACT FROM AUTHOR]

This paper describes a method that aims to find all instances of a certain object in Mobile Laser Scanner (MLS) data. In a user-assisted approach, a sample segment of an object is selected, and all similar objects are to be found. By selecting samples from multiple classes, a classification can be performed. Key assumption in this approach is that a one-to-one relationship exists between segments and objects. In this paper the focus is twofold: (1) to explain how to get proper segments, and (2) to describe how to find similar objects. Point attributes that help separating neighbouring objects are presented. These point attributes are used in an attributed connected component algorithm where segments are grown, based on proximity and attribute values. Per component, a feature vector is proposed that consists of two parts. The first is a height histogram, containing information on the height distribution of points within a component. The second contains size and shape information, based on the components' bounding box. A simple correlation function is used to find similarities between samples, as selected by a user, and other components. Our approach is tested on a MLS dataset, containing over 300 objects in 13 classes. Detection accuracies heavily depend on the success of the segmentation, and the number of selected samples in combination with the variety of object types in the scene. [ABSTRACT FROM AUTHOR]

Minimally invasive surgeries aiming to restore fractured vertebral body are increasing; therefore, our goals were to create a 3D vertebra reconstruction process and design clinical indices to assess the vertebral restoration in terms of heights, angles and volumes. Based on computed tomography (CT)-scan of the vertebral spine, a 3D reconstruction method as well as relevant clinical indices were developed. First, a vertebra initial solution requiring 5 min of manual adjustments is built. Then an image processing algorithm places this solution in the CT-scan images volume to adjust the model's nodes. On the vertebral body's anterior and posterior parts, nine robust heights, volume and endplate angle measurement methods were developed. These parameters were evaluated by reproducibility and accuracy studies. The vertebral body reconstruction accuracy was 1.0 mm; heights and volume accuracy were, respectively, 1.2 and 179 mm3. In conclusion, a 3D vertebra reconstruction process requiring little user time was proposed as well as 3D clinical indices assessing fractured and restored vertebra. [ABSTRACT FROM AUTHOR]

We describe a system for robustly estimating synthetic depth maps in unconstrained images and videos, for semi-automatic conversion into stereoscopic 3D. Currently, this process is automatic or done manually by rotoscopers. Automatic is the least labor intensive, but makes user intervention or error correction difficult. Manual is the most accurate, but time consuming and costly. Noting the merits of both, a semi-automatic method blends them together, allowing for faster and accurate conversion. This requires user-defined strokes on the image, or over several keyframes for video, corresponding to a rough estimate of the depths. After, the rest of the depths are determined, creating depth maps to generate stereoscopic 3D content, with Depth Image Based Rendering to generate the artificial views. Depth map estimation can be considered as a multi-label segmentation problem: each class is a depth. For video, we allow the user to label only the first frame, and we propagate the strokes using computer vision techniques. We combine the merits of two well-respected segmentation algorithms: Graph Cuts and Random Walks. The diffusion from Random Walks, with the edge preserving of Graph Cuts should give good results. We generate good quality content, more suitable for perception, compared to a similar framework. [ABSTRACT FROM PUBLISHER]

SUMMARY Traditional industrial practice often involves the ad hoc reuse of source code that was not designed for that reuse. Such pragmatic reuse tasks play an important role in disciplined software development. Pragmatic reuse has been seen as problematic due to a lack of systematic support, and an inability to validate that the reused code continues to operate correctly within the target system. Although recent work has successfully systematized support for pragmatic reuse tasks, the issue of validation remains unaddressed. In this paper, we present a novel approach and tool to semi-automatically reuse and transform relevant portions of the test suite associated with pragmatically reused code, as a means to validate that the relevant constraints from the originating system continue to hold, while minimizing the burden on the developer. We conduct a formal experiment with experienced developers, to compare the application of our approach versus the use of a standard IDE (the 'manual approach'). We find that, relative to the manual approach, our approach: reduces task completion time; improves instruction coverage by the reused test cases; and improves the correctness of the reused test cases. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Road tracking is a promising technique to increase the efficiency of road mapping. In this paper, a semi-automatic road tracker, Parallel Angular Texture Signature (PATS), is presented. The tracker is object-oriented in some sense, because it makes best use of the texture signature of road primitives on high-resolution remotely sensed imagery. Our tracker uses parabolas to model the road trajectory and predicts the position of next road centerline point. It employs PATS to get the moving direction of current road centerline point, and it will move on one predefined step along the moving direction to reach a new position, and then it uses curvature change to verify the newly added road point. Moreover, we also build compactness of Angular Texture Signature polygon to check whether the PATS is suitable for subsequent tracking. Repeat the above steps until the whole task is finished. Extensive experiments demonstrate that the proposed tracker is capable of efficiently extracting most of main roads from medium and low resolution imagery, and reliably and robustly extracting most of ribbon roads from high resolution SAR and optical imagery. [ABSTRACT FROM AUTHOR]

This study assesses the global left ventricular function and volumes using dual-source computed tomography (DSCT) with improved temporal resolution (83 ms) by use of a semi-automatic software tool in comparison to invasive angiography (IVA). One hundred patients scheduled for invasive coronary angiography because of suspected or known coronary artery disease (80 men; 20 women, mean age 62 ± 10 years) were additionally examined by DSCT. Global left ventricular function (LVF), left ventricular end-diastolic volume (LVEDV), end-systolic volume (LVESV), and stroke volume (SV) were calculated by the use of semi-automatic post-processing software and results compared with those of IVA. Bland-Altman analysis revealed a good concordance between DSCT and IVA in terms of LVF: Pearson’s r 0.78, confidence interval [CI] 0.68–0.86, P < 0.0001, bias 7.1% ± 9.1%. The same was true for LVESV (Pearson’s r 0.78, CI 0.67–0.85, P < 0.0001, bias 15.0 ± 21.0 ml), whereas the agreement for LVEDV and SV was only moderate (LVEDV: Pearson’s r 0.59, CI 0.43–0.72, P < 0.0001, bias 13.0 ± 18.1 ml; SV: Pearson’s r 0.47, CI 0.28–0.62, P < 0.0001, bias −1.4 ± 28.4 ml). Semi-automatic evaluation of left ventricular parameters with DSCT revealed good correlation for LVF and LVESV, whereas LVEDV and SV showed only a moderate correlation. Moreover, LVF is systematically underestimated by DSCT. [ABSTRACT FROM AUTHOR]

In light of the increasing availability of commercial high-resolution imaging sensors, automatic interpretation tools are needed to extract road features. Currently, many approaches for road extraction are available, but it is acknowledged that there is no single method that would be successful in extracting all types of roads from any remotely sensed imagery. In this paper, a novel classification of roads is proposed, based on both the roads' geometrical, radiometric properties and the characteristics of the sensors. Subsequently, a general road tracking framework is proposed, and one or more suitable road trackers are designed or combined for each type of roads. Extensive experiments are performed to extract roads from aerial/satellite imagery, and the results show that a combination strategy can automatically extract more than 60% of the total roads from very high resolution imagery such as QuickBird and DMC images, with a time-saving of approximately 20%, and acceptable spatial accuracy. It is proven that a combination of multiple algorithms is more reliable, more efficient and more robust for extracting road networks from multiple-source remotely sensed imagery than the individual algorithms. [ABSTRACT FROM AUTHOR]

Background: Delayed enhancement magnetic resonance imaging depicts scar in the left ventricle which can be quantitatively measured. Manual segmentation and scar determination is time consuming. The purpose of this study was to evaluate a software for infarct quantification, to compare with manual scar determination, and to measure the time saved. Methods: Delayed enhancement magnetic resonance imaging was performed in 40 patients where myocardial perfusion single photon emission computed tomography imaging showed irreversible uptake reduction suggesting a myocardial scar. After segmentation, the semi-automatic software was applied. A scar area was displayed, which could be corrected and compared with manual delineation. The different time steps were recorded with both methods. Results: The software shortened the average evaluation time by 12·4 min per cardiac exam, compared with manual delineation. There was good correlation of myocardial volume, infarct volume and infarct percentage (%) between the two methods, r = 0·95, r = 0·92 and r = 0·91 respectively. Conclusion: A computer software for myocardial volume and infarct size determination cut the evaluation time by more than 50% compared with manual assessment, with maintained clinical accuracy. [ABSTRACT FROM AUTHOR]

Automatic extraction of roads from digital images has been an active research subject for over a decade because its significant role in many application area, like Intelligent Transportation Systems (ITS) and transportation navigation as well as GIS applications. Especially, road network is one of most important features in GIS layer. Traditionally, surveying and photogrammetry are the only ways to map details in urban areas even though it is well known that they are resource and time consuming. Recently, high-resolution satellite image has become widely available, and moreover, several high-resolution satellite images have become commercially available for civilian applications, due to the development of remote sensors and satellite technologies. This shows an opportunity for so-called urban remote sensing to challenge the topic of urban details mapping. The focus of this paper is on developing an approach for extracting urban and suburban road network from high-resolution satellite image. “Road mask” is defined in this research as a mask of road pixels, which are discriminated from others using commercial remote sensing software. “Road seed” is defined in this research as a directional point, indicating that a road is passing through the point along the direction. Road seeds are extracted from edge pixels. Road line extraction is conducted in a semi-automatic way by fusing both road mask and road seeds. Experiments are conducted using an IKONOS image with a ground resolution of 1 meter, and four bands, i.e. red, green, blue, and near infrared. Experimental results show that the method is valid in extracting main roads in high dense building area and most of the roads in countryside efficiently. Besides the general description of the approach, this paper describes the newly proposed line segment match method in detail. [ABSTRACT FROM AUTHOR]

In this study, the lengths of the main links of the transplanting device of a semi-automatic vegetable transplanter were optimized to reduce the weight at the same planting trajectory. The theoretical planting trajectory was obtained from the kinematic analysis for the link structure of the transplanting device and verified through kinematic simulation using commercial software and actual measurement using high-speed camera. Then, the lengths of the main links that have a great influence on the planting trajectory were optimized to have a minimum total length at the same planting trajectory. A genetic algorithm was used as an optimization tool. As a result, with the optimal lengths of the main links, the same planting trajectory was maintained while reducing the total length by 18.32% compared to the conventional one. The transplanting device with the optimal main link lengths would have benefits in terms of agricultural economy by reducing manufacturing and fuel costs. [ABSTRACT FROM AUTHOR]