Position Of Segment Research Articles

Autonomous recognition and positioning of shield segments based on red, green, blue and depth information

Automatic shield segment assembly can reduce intensive labour and increase tunnel boring efficiency. However, insufficient lighting and multi-interference environments significantly affect segment recognition and positioning accuracy. This study develops a highly reliable and low-cost recognition and positioning system, including both hardware and software, for segment markers based on real-time monocular vision and light-insensitive depth measurements. An improved discrete wavelet transform based on the HSV channels and an adaptive multiscale Retinex algorithm with colour recovery are developed to enhance image brightness and colour contrast. Compared to traditional feature matching, support vector machine recognition and classification increase the real-time recognition accuracy. One hundred full-scale and field tests were performed under the original, insufficient, and interferential lighting environments. The recognition time was approximately 0.7 s, and the recognition accuracy was higher than 90%. A grasping experiment verified the feasibility of the system.

Whole-body movement analysis using principal component analysis: What is the internal consistency between outcomes originating from the same movement simultaneously recorded with different measurement devices?

A growing number of studies apply Principal Component Analysis (PCA) on whole-body kinematic data to facilitate an analysis of posture changes in human movement. An unanswered question is, how much the PCA outcomes depend on the chosen measurement device. This study aimed to assess the internal consistency of PCA outcomes from treadmill walking motion capture data simultaneously collected through laboratory-grade optical motion capture and field-suitable inertial-based motion tracking. Data was simultaneously collected using VICON (whole-body plug-in gait marker positions) and Xsens (body segment positions) from 20 participants during 2-min treadmill walking. Using PCA, Principal Movements (PMs) were determined using two commonly used practices: on an individual and a grouped basis. For both, correlation matrices were used to determine internal consistency between outcomes from either measurement system for each PM. Both individual and grouped approach showed excellent internal consistency between outcomes from the two systems among the lower order PMs. For the individual analysis, high correlations were only found along the diagonal of the correlation matrix while the grouped analysis also showed high off-diagonal correlations. These results have important implications for future application of PCA in terms of the independence of the resulting PM data, the way group-differences are expressed in higher-order PMs and the interpretation of movement complexity. Concluding, while PCA-outcomes from the two systems start to deviate in the higher order PMs, excellent internal consistency was found in the lower order PMs which already represent about 98% of the variance in the dataset.

An improved hidden Markov model-based map matching algorithm considering candidate point grouping and trajectory connectivity

ABSTRACT The hidden Markov model-based map matching algorithm (HMM-MM) is an effective method for online vehicle navigation and offline trajectory position correction. Common HMM-MMs are susceptible to the influence of adjacent road segment endpoints and similar parallel roads, because the multi-index probability model may ignore some indexes when the probability of other indexes is high. This makes the map-matching result not meet the assumption that vehicles always travel the shortest or optimal path, and it cannot guarantee that the trajectory points can match to the nearest position of the maximum likelihood road segment, resulting in poor accuracy. In this paper, an IHMM-MM is proposed. IHMM-MM (1) modifies the definition of transition probability and no longer takes the straight-line distance between trajectory points as the reference for the shortest path length between candidate point pairs. (2) supplements the definition of observation probability and introduces the point-line relation function to screen and group candidate points. (3) adds additional logic outside the HMM probability model to consider the trajectory connectivity and fill in the key trajectory points where the vehicles travel. Experiments show that the IHMM-MM can effectively improve the sampling frequency of trajectory data and has better performance in complex urban road environments.

Backpack Effects on Two-Dimensional Gait Spatiotemporal and Kinematic Parameters

Loads could affect the body gait in various ways. Backpacks, sling bags, suitcases, and even trolleys could hugely affect human gait without us realizing it. The effects of these loads have been scientifically researched in biomechanics and sports science for the past few years. For instance, the comparison of walking with and without a backpack could easily reveal significant differences in body segments, which could be utilized for therapy and medicine development. The aim of this research is to determine the differences of the spatiotemporal kinematic parameters between a conventional human gait and a backpack-loaded gait. Some parameters to be highlighted are stride lengths, stride duration, joint angles, linear and angular segment positions, velocities, and accelerations. The method used for marker data acquisition is based on the 2-dimensional Direct Linear Transformation. The results demonstrate that the backpack increases stride lengths and reduces stride duration, contrast to the expected where backpacks would reduce stride lengths. It was observed that the angle between the bag and the body posterior affects the abdomen relative angle, which directly translates to stride lengths as well. During unloaded walking, increases in pelvic rotation contribute to increases in stride length with increasing walking speed. However, in loaded walking, the back angle is also a factor in determining kinematic parameters.

The proximal segment in sagittal split ramus osteotomy

Bilateral sagittal split ramus osteotomy is one of the most versatile techniques in orthognathic surgery that allows for the repositioning of the mandible in all directions. This osteotomy splits the mandible into two proximal condyle-bearing segments and one distal tooth-bearing segment. Intraoperatively, the surgeon is usually focused primarily on the proper positioning of the distal segment to achieve the planned amount of advancement or setback. However, particular attention should be paid to the position of the proximal segment, as improper positioning of the proximal segment during fixation gives rise to immediate or late relapse of the surgical outcomes. The goal of this paper is to provide some background knowledge about the proximal segment for the novice surgeons, based on a review of the relevant literature. What is the proper position of the proximal segment, and what is the best technique to guide the proximal segment into its proper position?. These questions do not have clear-cut answers that the majority of surgeons agree on.

Analysis of Segmentation Targetting and Positioning in Marketing Retail Development Indomaret VS Alfamart

The aims to study is to find out how the competition between Indomaret retail and Alfamart is by looking at the analysis of marketing strategies using STP marketing and the application of the marketing mix. The method of writing this article is descriptive analysis with a qualitative type. then use internet searching as an aid in finding data in writing this article. The results in this study will find out the application of STP Marketing and marketing mix in two phenomenal retail businesses, data on competition between Indomaret and Alfamart in their business activities from the marketing side to be offered to consumers throughout the community.

Alterations of the axon initial segment in multiple sclerosis grey matter.

Grey matter damage has been established as a key contributor to disability progression in multiple sclerosis. Aside from neuronal loss and axonal transections, which predominate in cortical demyelinated lesions, synaptic alterations have been detected in both demyelinated plaques and normal-appearing grey matter, resulting in functional neuronal damage. The axon initial segment is a key element of neuronal function, responsible for action potential initiation and maintenance of neuronal polarity. Despite several reports of profound axon initial segment alterations in different pathological models, among which experimental auto-immune encephalomyelitis, whether the axon initial segment is affected in multiple sclerosis is still unknown. Using immunohistochemistry, we analysed axon initial segments from control and multiple sclerosis tissue, focusing on layer 5/6 pyramidal neurons in the neocortex and Purkinje cells in the cerebellum and performed analysis on the parameters known to control neuronal excitability, i.e. axon initial segment length and position. We found that the axon initial segment length was increased only in pyramidal neurons of inactive demyelinated lesions, compared with normal appearing grey matter tissue. In contrast, in both cell types, the axon initial segment position was altered, with an increased soma-axon initial segment gap, in both active and inactive demyelinated lesions. In addition, using a computational model, we show that this increased gap between soma and axon initial segment might increase neuronal excitability. Taken together, these results show, for the first time, changes of axon initial segments in multiple sclerosis, in active as well as inactive grey matter lesions in both neocortex and cerebellum, which might alter neuronal function.

Identification of historical trackways in forests using contextual geospatial analyses

AbstractThis article demonstrates the application of the methods unravelling microtopographic features, specifically, sunken linear landforms indicating remains of historical trackways in forests. These are related to the ‘Magna Via’ route in the vicinity of the Deserted Castle and the Peťuša Castle in Central Slovakia. The microtopography validation dataset indicating sunken linear landforms was used to evaluate the data overlap of tracks identified by the global positioning and navigation system (GNSS) and a model of tracks created with the least cost path (LCP) algorithm. Microtopographic features derived from a digital relief model generated by high‐resolution Light Detection and Ranging (LiDAR) scans (density of 5 points/pixel) allowed us to determine the exact position (submeter total vertical and horizontal accuracy) of certain segments of the GNSS tracks and LCP overlapping the sunken linear landforms. Moreover, the LCP model shows the most efficient trackways considering the travel costs depending on the slope parameter.

Quasi-static methods to evaluate seat strength in rear impacts

Objective Various methods have been used in the past 50 years to apply Quasi-static load to a seat in the rear direction and measure seat performance in rear impacts. This study compared five of the most-common test procedures to evaluate seats. In addition, occupant mass and center of gravity are discussed as important characteristics of rear loading of seats. Method Data was collected and analyzed from five different seat pull tests, including FMVSS 207, modified FMVSS 207, QST, body block and FRED II. Test data included peak force, moment and angle at peak moment. Occupant loading height of was determined using body segment weights and position in the forward (x) and vertical (z) directions based on anthropometry data. Results Some of the inherent differences in the tests are shown by comparing data with the same seat structure. The QST and FRED II use a lower height of loading than FMVSS 207. The QST and FRED II peak moment and force did not coincide with the same seatback angle as in FMVSS 207 and body block testing. Center of gravity height varies depending on whether the whole body or only the upper torso is considered. For the 50th male, it is 171.5 mm (6.8”) with the whole body and 246.7 mm (9.7”) with the upper torso. Conclusion Results from different tests cannot be readily compared because of different loading conditions, including body shape and height of load about the H-point, which can cause the seat structure to respond differently.

On the use of intraoperative 3D-RX C-arm imaging in orthognathic surgery: a prospective non-consecutive case series study.

Segment and osteosynthesis malposition resulting in patients' complaints (mainly about asymmetries) are encountered in orthofacial/orthognathic surgery. We planned to investigate the usefulness of intraoperative three-dimensional (3D) imaging concerning positioning and fixation of bone segments and osteosynthesis in orthognathic/orthofacial surgery. We performed a prospective study of non-consecutive cases. All patients receiving a bimaxillary osteotomy, genioplasty, and their combinations were included in the study from May 2016 to May 2020. Unilateral and bilateral sagittal split osteotomies were excluded. There were no gender and age limitations. All were intraoperatively examined using the BV Pulsera 3D-RX System (Philips Medical, Eindhoven, The Netherlands). The outcome variables were the percentage of revisions of segment positioning and osteosynthesis. Predictor variables were age, gender, type of surgery, timing (pre- and post-imaging), and surgeon experience (senior vs assistant). Forty female and twenty-two male patients were included (mean age 25.25years ± 7.52 and 29.1years ± 12.6 respectively). We evaluated 27 genioplasties and 34 Le Fort "type-I" osteotomies. Indications for segment repositioning and redo-osteosynthesis increased after intraoperative imaging as compared to operator's clinical judgment before intraoperative imaging (95% confidence interval; p < .001 and p = .002 respectively). Suboptimal positioning and fixation of bone segments or osteosynthesis were more apparent with 3D imaging. In addition, some satisfactory cases were also revised for an optimal outcome. As a result, surgeons were prompted to more revisions than judged necessary without intraoperative imaging.

Type 2 myocardial infarction: Diagnostic features in real clinical practice

Purpose. To determine the incidence of type 2 myocardial infarction (MI) diagnosis (according to the Fourth Universal Definition) and the features of patient management in real clinical practice.Material and Methods. A retrospective study was performed by analyzing the case histories of 153 patients diagnosed with acute coronary syndrome (ACS). Inclusion criteria were the presence of ACS at admission followed by a confirmed diagnosis of MI during the hospital period according to the Fourth Universal Definition of MI and the age of patients &gt; 18 years. Patients with severe comorbidities affecting the immediate prognosis and/or being an alternative to the diagnosis of MI were not included in the study.Results. The study showed that emergency coronary angiography was performed in 151 patients (98.7%). A decrease in the renal filtration function in the presence of chronic kidney disease was a contraindication to this study found in 1.3% of cases; 12 (8%) patients did not have coronary artery disease or had stenoses of less than 50%; these patients comprised the group of patients with type 2 MI. While analyzing the results of examination in patients with type 2 MI, ST segment elevation was detected in seven patients (58.4%) according to electrocardiography; ST segment depression was observed in one patient (8.3%); complete left bundle-branch block was found also in 1 case (8.3%), three individuals (25%) did not have any changes in the position of ST segment, but had a negative T wave. Analysis of possible etiological factors in the development of type 2 MI showed the presence of sinus tachycardia in two patients (16.7%), severe sinus bradycardia in one patient (8.3%), fl utter paroxysm and atrial fibrillation with tachysystole throughout the ventricles in two patients (16.7%), and history of atrial fibrillation in one patient (8.3%).Conclusion. Type 2 MI was diagnosed in 8% of patients with ACS with and without ST segment elevation where cardiac arrhythmias including sinus arrhythmias may be the potential etiological factors. Limited capabilities of assessing the stability of atherosclerotic plaque in the coronary artery including that in the presence of plaque thrombosis represent a significant negative factor for establishing diagnosis in routine clinical practice.

Strategi Pemasaran Minuman Probiotik Olahan Buah Naga Dan Analisis Tingkat Kepuasan Terhadap Atribut Produk Di Koto Panjang Nagari Kapau, Sumatera Barat

Efforts to improve the community's economy and the use of out-of-grade dragon fruit, the Nagari Regional Government and the Al-Barokah group are willing to carry out research-based community economic empowerment, namely diversification of processed dragon fruit. Innovation can be done through diversification of processed dragon fruit into biofruit drinks that are nutritious for health (Albrobiofruit drinks). It is important to have a strategy to introduce and market the product. This research aims to analyze the segmentation, target and market position of dragon fruit beverage products, as well as measure the consumer satisfaction index on product attributes. Respondents were decided purposively about 111 people. The analytical method implemented is the Customer Satisfaction Index (CSI) method to identify the level of buyer satisfaction, segmentation, targeting, and positioning (STP) of Albrobiofruit beverage products. According to the results of the study, the level of buyer satisfaction was achieved from the CSI calculation of 82.89% which described the level of buyer satisfaction with the quality attributes of Albrobifruit products referred to in the "very satisfied" category. Determination of Segmentation, Targeting, and Positioning based on demographic characteristics and buyer ratings. The strategic formulation of the analysis for Albrobiofruit products is to add product promotions so that they are recognized by the entire group, monitor product quality and provide good service. Not only that, it is necessary to carry out efforts to knit and defend cooperation with government and private factions to support product promotions

The phonetic realization of the plain uvular /q/ in a variety of South Bolivian Quechua

This paper presents an acoustic description of the production of the plain uvular /q/ in the speech of eight speakers of South Bolivian Quechua. While this sound patterns phonologically as a stop, its primary realization is as a voiced continuant. Variation is documented with respect to segmental and prosodic position. Segmentally, a voiced continuant is the most common realization intervocalically and after a rhotic, while a voiceless continuant is comparatively more frequent after a voiceless sibilant, and voiced stops are most common after a nasal. In post-pausal position, voiced continuant productions are still attested and are particularly common for certain speakers, suggesting that this sound category has been reanalyzed as a continuant. For other speakers, voiceless stop productions are common or preferred in post-pausal position, reflecting a standard prosodically conditioned lenition pattern. Interestingly, voiced stops also show increased frequency in post-pausal position. The production of the plain uvular is analyzed in spontaneous speech collected in an interview format, as well as in scripted speech from a word list task. A second analysis compares the realization of /q/ to the other three stops /p t k/ in the language in spontaneous speech, and finds significantly more continuant productions for /q/.

Numerical Investigation on Hybrid Rocket Motors with Star-Segmented Rotation Grain

A novel fuel grain configuration comprising two star-segmented grains is proposed. The effect of the rotation, mid-chamber length, and segmented position on the fuel regression rate and the combustion efficiency in hybrid rocket motors with star-segmented grains is investigated in this paper. To this end, 90% hydrogen peroxide (H2O2) and hydroxyl-terminated polybutadiene (HTPB) are selected as the propellant combination in this research. Three-dimensional numerical simulations of the star-segmented grain configuration are conducted. A firing test of a lab-scale hybrid rocket motor was conducted to verify the accuracy of the numerical model, and the errors between simulation data and experimental results are no more than 4.5%. The case without segmented grain configuration is regarded as the base case. The simulation results demonstrate that the combustion flow field structure of the motor could be ameliorated by the segmented rotation grain configuration. Compared with the base case, the rotation of aft-section grain has little effect on the regression rate in the fore-section grain, while the average regression rate in aft-section grain increases, with a maximum increase of 25.04%. The combustion efficiency of the motor with the segmented rotation grain configuration is higher than the base case. Compared with the base case, the combustion efficiency of segmented rotation grain case with mid-chamber length 40 mm and segmented position of 1/2 is raised by 4.06%. The average fuel regression rate and the combustion efficiency of hybrid rocket motors with segmented rotation grains are higher than those in the base case during the entire period of operation, and the combustion efficiency is increased by 1.40–4.21% during the motor operation. The research findings of this paper can provide valuable guidance for the performance improvement of hybrid rocket motors with star grain.

Optimisation Configuration of Overhead-Line Segmentation Switch of a Distribution Network Based on Global Combination Criterion

Under certain constraints, the optimisation of the position and number of sectional switches in overhead lines in distribution networks can improve the reliability and economy of the power supply. Therefore, a global combination criterion is proposed to simultaneously evaluate the combination performance of multiple switch positions, which avoids the tedious traditional problem of adjusting only one switch position at a time and that can possibly fall into a local-optimum problem. We directly determine the optimal solution and ensure a global optimum. Firstly, the optimal switching position in each line segment is analysed as an alternative switching position. Subsequently, the optimal installation-position combination that corresponds to a given number of switches is determined according to the global combination criterion. If the constraints are satisfied, the number of switches is increased by one, and the optimal installation-position combination is then determined until the constraints are not satisfied. This process ensures not only the global optimum of the switch position but also the optimum number of switches. Finally, examples are given to demonstrate that the proposed method can further optimise the switch configuration. The utility model effectively improves the device utilisation rate, reduces the influence range of the fault, and improves power supply reliability.

A XGBoost-Based Lane Change Prediction on Time Series Data Using Feature Engineering for Autopilot Vehicles

Road accidents wreck lives. Could technology stop them from happening? Driving better road safety with technology and artificial intelligence are the key elements considered by several carmakers. The key aspect of transportation in the future is to build an ecosystem comprising autonomous, connected, electric and shared mobility. The evolution of autonomous vehicles (AVs) can potentially aid transportation to people and be deployed to resolve mobility-related pain for drivers and safety on roads while changing lanes. Thus, the intelligent assistance system should be smart enough to track such vehicles while deviating into another lane. In this paper, we propose a lane change prediction framework for feature learning, with the aim to have a deep and comprehensive understanding of lane change behaviors, meanwhile, reach a high performance based on the selected features. A time-step dataset with more than 1000 features is constructed from vehicle trajectory data. To identify the key features involved in the original feature set, an XGBoost-based three-step feature learning algorithm is proposed, which integrates the feature importance ranking, metric selection and recursive feature elimination. After analyzing the accuracy of test data from different time segment positions, the sliding window method is applied on a time-step dataset with filtered features to properly select time segments, which are flattened into corresponding time-series dataset for model prediction. In our case studies, a publicly available dataset, Next Generation SIMulation (NGSIM), is adopted to conduct experiments of feature learning and lane change prediction, where we achieved a new state-of-art accuracy with 97.6% under the time-series data of 75 selected features and 1-second window size with predictor XGBoost after adopting proposed three-step method, which is superior to the other state-of-the-art feature selection methods.

Power Pylon Reconstruction from Airborne LiDAR Data Based on Component Segmentation and Model Matching

In recent years, with the rapid growth of State Grid digitization, it has become necessary to perform three-dimensional (3D) reconstruction of power elements with high efficiency and precision to achieve full coverage when simulating important transmission lines. Limited by the performance of acquisition equipment and the environment, the actual scanned point cloud usually has problems such as noise interference and data loss, presenting a great challenge for 3D reconstruction. This study proposes a model-driven 3D reconstruction method based on Airborne LiDAR point cloud data. Firstly, power pylon redirection is realized based on the Principal Component Analysis (PCA) algorithm. Secondly, the vertical and horizontal distribution characteristics of the power pylon point cloud and the graphical characteristics of the overall two-dimensional (2D) orthographic projection are analyzed to determine segmentation positions and the key segmentation position of the power pylon. The 2D alpha shape algorithm is adopted to obtain the pylon body contour points, and then the pylon feature points are extracted and corrected. Based on feature points, the components of original pylon and model pylon are registered, and the distance between the original point cloud and the model point cloud is calculated at the same time. Finally, the model with the highest matching degree is regarded as the reconstructed model of the pylon. The main advantages of the proposed method include: (1) identifying the key segmentation position according to the graphical characteristics; (2) for some pylons with much missing data, the complete model can be accurately reconstructed. The average RMSE (Root-Mean-Square Error) of all power pylon components in this study was 15.4 cm. The experimental results reveal that the effects of power pylon structure segmentation and reconstruction are satisfactory, which provides method and model support for digital management and security analysis of transmission lines.

Research on Tourism Short Video Marketing Strategy Based on STP Theory

In recent years, major social platforms have launched short video applications, which not only add a lot of fun to people's lives, but also provide effective marketing opportunities for businesses in all walks of life. Affected by the COVID-19 epidemic, the global tourism industry suffered heavy losses. Short video marketing of tourism brings new opportunities for the recovery of tourism. Based on STP theory, this research studies the marketing strategy of short video in tourism. Specifically, this study analyzes the current situation, strategies and existing problems of short video marketing of tourist destination merchants from three dimensions: market segmentation, target market and market positioning. Finally, the research conclusion is drawn, and the corresponding innovative development suggestions are put forward for the future prospects of tourist destinations.

Research on Tourism Short Video Marketing Strategy Based on STP Theory

In recent years, major social platforms have launched short video applications, which not only add a lot of fun to people's lives, but also provide effective marketing opportunities for businesses in all walks of life. Affected by the COVID-19 epidemic, the global tourism industry suffered heavy losses. Short video marketing of tourism brings new opportunities for the recovery of tourism. Based on STP theory, this research studies the marketing strategy of short video in tourism. Specifically, this study analyzes the current situation, strategies and existing problems of short video marketing of tourist destination merchants from three dimensions: market segmentation, target market and market positioning. Finally, the research conclusion is drawn, and the corresponding innovative development suggestions are put forward for the future prospects of tourist destinations.

Study on the Segmentation Method of the Improved DeepLabv3+ Algorithm in the Basketball Scene

Aiming at the weak robustness and low segmentation accuracy of traditional basketball scene segmentation methods, this study proposed an improved basketball scene semantic segmentation model based on DeepLabv3+ for the purpose of basketball scene segmentation and accurate positioning of players. In this model, a relatively complex decoder is designed based on the DeepLabv3+ network. Multiple feature fusion is used to restore the semantic information of the image, and the convolutional block attention mechanism is introduced to optimize the channel weight and position information, reduce the computational complexity of the model, and improve the edge sensitivity. Experimental results show that the proposed model is 21.8% better than FCN’s full convolution model and 1.9% better than DeepLabv3+. At the speed of segmentation, it can process 6 pictures per second, greatly improving the accuracy of semantic segmentation for basketball scenes. In the future, real-time detection of sports such as basketball using computer vision methods will become more and more important.