Vertical Projection Research Articles

A Conical Nanogenerator Consisted of Multi-Walled Carbon Nanotubes

The shift to an industrial ecosystem that operates with abundant water and sunlight on the earth is essential to the sustainability of mankind. One effort to do this is to produce freshwater utilizing solar energy, called solar steam generation. Here, we develop a dual-function ecosystem of the 3-dimensional conical structure consisted of multi-walled carbon nanotubes (MWNTs), which utilizes the solar energy to produce the fresh water from any pollutated water or saline water at the massive production rate and to generate the high electric power of hundreds mW·m-2 using evaporation-enhanced capillary water stream of the structure under ambient daylight conditions. Since this cone-shaped fluidic nanogenerator (CFN) acquires all energy required from the environment, it will find immediate applications in providing electricity and freshwater for living and system maintenance in water-abundant isolated locations such as islands or wetlands. The CFN of MWNTs has advantages in solar steam generation because it can be more exposed to the environment due to its high surface curvature and because it can be thermally isolated from the cold water by the inside air-pocket. A single CFN of which vertical projection area is 0.64 cm2 can show high water evaporation rate of 1.6 kg·m-2·h at 20 °C. Multilayers of functionalized MWNTs can have advantages in fluidic nanogenerator which can harvest large electric power with high open-circuit voltage (Voc) and current density (Jsc) by the double layer interaction of MWNTs with ions flowing in the evaporation-induced capillary water stream. The CFN of MWNTs can produce strong electric power due to the capillary water stream induced by the solar steam under 1 sun irradiation (1 kW·m-2) and the single CFN produces electric powers of 120.7 mW·m-2 (Voc: 0.5V, Jsc: 0.12 mA·cm-2) at the saline water and of 505.69 mW·m-2 (Voc:0.64 V, Jsc: 0.59 mA·cm-2) at the 0.6 M KCl aqueous solution.

Drop flow method: an iterative algorithm for complete segmentation of Devanagari ancient manuscripts

One of the major challenges of ancient manuscripts recognition is character segmentation. Because of many distinct features of ancient documents (thick characters, overlapping and touching characters), character segmentation is a very difficult task. Devanagari ancient manuscripts consist of vowels, consonants, modifiers, conjuncts and compound characters. Using existing techniques, segmentation of overlapping and touching characters is problematic. In this paper, an iterative character segmentation algorithm is presented for ancient documents in Devanagari script. At the beginning, the lines are extracted from the ancient documents by dividing the document image into vertical stripes and then using piecewise horizontal projection profiles. After that, these lines are segmented into words using vertical projection profiles and finally, words are segmented in characters using an iterative algorithm. In each iteration, character segmentation is refined. In the present work, we have proposed a new algorithm with the name ‘Drop Flow Method’ to find the segmentation path between touching components. The proposed algorithm can segment touching characters and 96.0% accuracy has been achieved for complete segmentation of Devanagari ancient manuscripts.

Generalised vertical projection histograms using multi‐plane homology

© The Institution of Engineering and Technology 2019 Vertical projection histograms are an efficient shape representation for 2D binary silhouettes and have been widely used in pedestrian localisation for video surveillance. The weakness of this method is that it is not invariant to rotation. In this Letter, a generalised vertical projection histogram is proposed to solve this problem, in which the homology transformations of the foreground silhouettes, for a set of parallel planes, are warped to, and accumulated, in the original foreground map. Then a method, similar to the vertical projection histogram, is carried out to localise the pedestrians in the foreground silhouettes. The algorithm applies an integrated approach using both image projection and geometric projection. Its value is demonstrated in a case study on pedestrian localisation with cast shadows.

Text Detection In Indonesian Identity Card Based On Maximally Stable Extremal Regions

Most of Indonesian organizations either it is government or non government sometime required their member to provide their identity card (E-KTP) as legal document collection in their database. This collection of image usually being used as manual verification method. These document images acquired by each person with their own device, there are variations of angles they are used to acquire the image. This situation created problems in text recognition by OCR softwares especially in text detection part, orientation and noise will affect their accuracy. These cases making the text detection more complex and cannot be solved by simple vertical projection profile of black pixels. This research proposed a method to improve text detection in identity document by fixing the orientation first, then using MSER regions to form text region. We fix the orientation using the line that made by Progressive Probabilistic Hough Transform. Then we used MSER to obtain all candidate regions and Horizontal RLSA acts as connector between those candidate. The orientation fixing strategy reach average of margin error 0.377o (in 360o system) and the text detection method reach 84.49% accuracy in best condition.

Creeping Gait Analysis and Simulation of a Quadruped Robot

A quadruped (four-legged) robot locomotion has the potential ability for using in different applications such as walking over soft and rough terrains and to grantee the mobility and flexibility. In general, quadruped robots have three main periodic gaits: creeping gait, running gait and galloping gait. The main problem of the quadruped robot during walking is the needing to be statically stable for slow gaits such as creeping gait. The statically stable walking as a condition depends on the stability margins that calculated particularly for this gait. In this paper, the creeping gait sequence analysis of each leg step during the swing and fixed phases has been carried out. The calculation of the minimum stability margins depends upon the forward and inverse kinematic models for each 3-DOF leg and depends on vertical geometrical projection during walking. Simulation and results verify the stability insurance after calculation the minimum margins which indicate clearly the robot COG (Center of Gravity) inside the supporting polygon resulted from the leg-tips.

Analysis of Segmentation Methods for Brahmi Script


 
 
 Segmentation is an important step for developing any optical character recognition (OCR) system, which has to be redesigned for each script having, non-uniform nature/property. It is used to decompose the image into its sub-units, which act as a basis for character recognition. Brahmi is a non-cursive ancient script, in which characters are not attached to each other and have some spacing between them. This study analyses various segmentation methods for different scripts to develop the best suitable segmentation method for Brahmi. MATLAB software was used for segmentation purpose in the experiment. The sample data belongs to Brahmi script-based ‘Rumandei inscription’. In this paper, we discuss a segmentation methodology for distinct components, namely text lines, words and characters of Rumandei inscription, written in Brahmi script. For segmenting distinct components of inscription different approach were used like horizontal projection profile, vertical projection profile and Relative minima approach. This is fundamental research on an inscription based on Brahmi script, which acts as a foundation for developing a segmentation module of an OCR solution/system of similar scripts in future. Information search and retrieval is an important activity of a library. So, to ensure this support for digitised documents written in ancient script, their character recognition is mandatory through the OCR system.
 
 

40Ar/39Argeochronology, fluid inclusions, and ore‐grade distribution of theJiawula Ag–Pb–Zndeposit,NE China:Implicationsfor deposit genesis and exploration

The Jiawula Ag–Pb–Zn deposit is located in the northern part of the Great Xing'an Range metallogenic belt within the eastern segment of the Central Asian Orogenic Belt. Here, we report results from muscovite40Ar/39Ar geochronology and fluid inclusion study and formulate a vertical projection map of the ore grade in this deposit. The muscovite from the Jiawula deposit yields a plateau age of 133.27 ± 0.66 Ma and a40Ar/39Ar isochron age of 131.88 ± 0.83 Ma. The muscovite40Ar/39Ar data indicate a discrete second hydrothermal event postdating the mineralization, which we correlate with post‐collisional extension after the subduction direction of the Palaeo‐Pacific Plate changed. Low‐salinity aqueous fluid inclusions in quartz from the Jiawula deposit represent meteoric water or groundwater. Based on the fluid inclusion study, the fluids were trapped during cooling and decompression, which may have resulted in metal precipitation. We envisage that the copper precipitated from a high‐temperature fluid in the southern domain whereas lead, zinc, and silver precipitated at a lower temperature in the north. The spatial distribution of the ore‐forming elements, therefore, reflects the ore fluid migration‐cooling path from the south to north.

Cobb Angle Measurement of Spine from X-Ray Images Using Convolutional Neural Network.

Scoliosis is a common spinal condition where the spine curves to the side and thus deforms the spine. Curvature estimation provides a powerful index to evaluate the deformation severity of scoliosis. In current clinical diagnosis, the standard curvature estimation method for assessing the curvature quantitatively is done by measuring the Cobb angle, which is the angle between two lines, drawn perpendicular to the upper endplate of the uppermost vertebra involved and the lower endplate of the lowest vertebra involved. However, manual measurement of spine curvature requires considerable time and effort, along with associated problems such as interobserver and intraobserver variations. In this article, we propose an automatic system for measuring spine curvature using the anterior-posterior (AP) view spinal X-ray images. Due to the characteristic of AP view images, we first reduced the image size and then used horizontal and vertical intensity projection histograms to define the region of interest of the spine which is then cropped for sequential processing. Next, the boundaries of the spine, the central spinal curve line, and the spine foreground are detected by using intensity and gradient information of the region of interest, and a progressive thresholding approach is then employed to detect the locations of the vertebrae. In order to reduce the influences of inconsistent intensity distribution of vertebrae in the spine AP image, we applied the deep learning convolutional neural network (CNN) approaches which include the U-Net, the Dense U-Net, and Residual U-Net, to segment the vertebrae. Finally, the segmentation results of the vertebrae are reconstructed into a complete segmented spine image, and the spine curvature is calculated based on the Cobb angle criterion. In the experiments, we showed the results for spine segmentation and spine curvature; the results were then compared to manual measurements by specialists. The segmentation results of the Residual U-Net were superior to the other two convolutional neural networks. The one-way ANOVA test also demonstrated that the three measurements including the manual records of two different physicians and our proposed measured record were not significantly different in terms of spine curvature measurement. Looking forward, the proposed system can be applied in clinical diagnosis to assist doctors for a better understanding of scoliosis severity and for clinical treatments.

INFLUENCE OF THE AT "WINGLETS" TYPE ON THE LONGITUDINAL STATIC STABILITY OF ANGLE OF ATTACK OF THE AIRCRAFT

The effect of the aerodynamic AT winglets wingtips on the longitudinal static stability of the aircraft is investigated by the method of equations of a steady straight-line horizontal flight. The aerodynamic forces created by the upper and lower parts of the wingtip AT winglets are defined. Assuming that the vertical projections of the pressure centers of all parts of the wingtips intersect the transverse axis, the dive and kicking moments of these forces are determined. The aerodynamic forces created by all four parts of the wingtip AT winglets are determined and their pitch moments are calculated. The vector of the total aerodynamic force of the wingtips is represented in the form of components along the associated coordinate system. Equilibrium equations for the steady motion of an aircraft with wingtips of the AT winglets type in a horizontal flight are recorded. This method is used to calculate the expression for the longitudinal moment coefficient of an aircraft in the presence of aerodynamic wingtips. The forward and backward arrangements of the centers of pressure of the tips with respect to the vertical plane passing through the lateral coordinate axis are considered. The derivatives of the coefficients of the roll and yaw moment coefficients for the slip angle for the wing with the tips that enter the equation for the lateral oscillation of the aircraft are determined. The correspondence between the derivatives of the coefficients of the moments of roll and yaw for the wings without the tips and with the tips for the slip angle is established. Using this correspondence, from the known differential equation of the lateral oscillation of an airplane with a wing without a wingtip, the corresponding equation of lateral oscillation of the airplane is obtained for the aircraft for a wing with a wing with wingtips. The expression of the longitudinal moment and its coefficient for an aircraft taking into account the influence of aerodynamic wing tips is derived. With small changes in the angle of attack, the partial derivatives of the longitudinal moment coefficient with respect to the angle of attack and the coefficient of lift are calculated. The conditions for the longitudinal static stab

A comprehensive study of the thermal response of a long-span cable-stayed bridge: From monitoring phenomena to underlying mechanisms

Abstract Structural deformation and variation in internal force are important considerations with regard to bridge health monitoring. Field measurements demonstrate that thermal effects of cable-stayed bridges—which represent high-order statically indeterminate structures—are extremely complex and nearly impossible to explicate in terms of temperature-limit states assumed during the design stage. Based on monitoring data recorded for the Shanghai Yangtze River Bridge—a steel box girder, twin-tower cable-stayed bridge with a 730 m central span—simultaneous investigations were performed concerning effects of seasonal as well as diurnal temperature variations on thermally induced changes in the mid-span vertical displacement ( D T ) and horizontal projection length ( L T ) of the girder, distance between the two tower tops ( S T ), structural total or elastic strains ( e M / e E ) at the mid-span section and average cable tensions of the longest centre-span cables ( F T ). In terms of variation amplitudes, correlations between temperature and structural response of a cable-stayed bridge can be classified into two modes. In the first mode, annual variation amplitudes are observed to be significantly larger compared with diurnal amplitudes. This applies to parameters L T , S T and e M . In the second mode, annual variation amplitudes approximately equal diurnal amplitudes. This is true for parameters D T , e E and F T . Temperature variables upon which structural response of cable-stayed bridges primarily depends usually differ from one another in that L T , S T and e M are governed exclusively by the average girder temperature while D T and F T are simultaneously determined by the cable and average girder temperatures; parameter e E is dominated by the temperature difference between the top and bottom plates of the girder. This study establishes a sound understanding of behavioural patterns in cable-stayed bridges to facilitate the determination of feasible measurement-point locations, useful with regards to bridge-monitoring systems, as well as selection of appropriate temperature variables for thermal-response modelling.

Video spatiotemporal mapping for human action recognition by convolutional neural network

In this paper, a 2D representation of a video clip called video spatiotemporal map (VSTM) is presented. VSTM is a compact representation of a video clip which incorporates its spatial and temporal properties. It is created by vertical concatenation of feature vectors generated from subsequent frames. The feature vector corresponding to each frame is generated by applying wavelet transform to that frame (or its subtraction from the subsequent frame) and computing vertical and horizontal projection of quantized coefficients of some specific wavelet subbands. VSTM enables convolutional neural networks (CNNs) to process a video clip for human action recognition (HAR). The proposed approach benefits from power of CNNs to analyze visual patterns and attempts to overcome some CNN challenges such as variable video length problem and lack of training data that leads to over-fitting. VSTM presents a sequence of frames to CNN without imposing any additional computational cost to the CNN learning algorithm. The experimental results of the proposed method on the KTH, Weizmann, and UCF Sports HAR benchmark datasets have shown the supremacy of the proposed method compared with the state-of-the-art methods that used CNN to solve HAR problem.

Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion

Interferometric synthetic aperture radar (InSAR) technology has been widely applied to measure Earth surface motions related to natural and anthropogenic crustal deformation phenomena. With the widespread uptake of data captured by the European Space Agency’s Sentinel-1 mission and other recently launched or planned space-borne SAR missions, the usage of the InSAR technique to detect and monitor Earth surface displacements will increase even more in the coming years. However, InSAR can only measure a one-dimensional motion along the radar line of sight (LOS), which makes interpretation and communication of InSAR measurements challenging, and can add ambiguity to the modelling process. Within this paper, we investigate the implications of the InSAR LOS geometry using simulated and observed deformation phenomena and describe a methodology for multi-geometry data fusion of LOS InSAR measurements from many viewing geometries. We find that projecting LOS measurements to the vertical direction using the incidence angle of the satellite sensor (and implicitly assuming no horizontal motions are present) may result in large errors depending on the magnitude of horizontal motion and on the steepness of the incidence angle. We quantify these errors as the maximum expected error from simulated LOS observations based on a Mogi deformation model. However, we recommend to use LOS observations from several image geometries wherever data are available, in order to solve for vertical and E–W oriented horizontal motion. For an anthropogenic deformation phenomenon observed in seven independent InSAR analyses of Envisat SAR data from the Sydney region, Australia, we find that the strong horizontal motion present could lead to misinterpretation of the actual motion direction when projecting LOS measurements to vertical (uplift instead of subsidence). In this example, the difference between multi-geometry data fusion and vertical projection of LOS measurements (at an incidence angle of 33.8°) reach up to 67% of the maximum vertical displacement rate. Furthermore, the position of maximum vertical motion is displaced horizontally by several hundred metres when the LOS measurements are projected.

Estimating Pylon Height Using Differences in Shadows Between GF-2 Images

Information on height of pylon is important when planning the routes of unmanned aerial vehicles. This paper proposes a new automatic method for estimating pylon height using shadow differences between GF-2 satellite images taken at different times. Initially, the spectral distribution features and triangular shape of pylon shadows are used for shadow detection to enhance the difference from other land objects using images taken at a greater sun elevation angle. Then, the difference in the shadows of the same pylon in images taken at different times and shadow-imaging principles are used to estimate the vertical of the pylon top to avoid interference from complex land objects. Finally, the height of the pylon is approximated using the distance from the vertical projection point to the shadow point of the pylon top and sun elevation angle. GF-2 images were selected and included five pylons in the target area. The average error of the estimated height was 1.56 m, and the relative error was only 2.74%.

A Decision Method for Online Purchases Considering Dynamic Information Preference Based on Sentiment Orientation Classification and Discrete DIFWA Operators

Online reviews are crucial for evaluating product features and supporting consumers' purchase decisions. However, as a result of online buying behaviors, consumer habits, and discrete dynamic distribution characteristics of online reviews, and consumers typically randomly choose a limited number of reviews from discrete time frames among all reviews and give more weight to recent review information and less weight to earlier information to support their online purchase decisions; moreover, existing studies have ignored the discrete random dynamic characteristics and dynamic information preferences of consumers. To address this issue, this paper proposes a method based on sentiment orientation classification and discrete DIFWA (DDIFWA) operators for online purchase decisions considering dynamic information preferences. In this method, we transformed review texts from original discrete time slices to discrete random features, extracted product features based on the constructed feature and sentiment dictionaries, and matched pairs of features and sentiment phrases in the dictionaries. We subsequently employed three types of semantic orientation by defining semantic rules to extract the product features of each review. Of note, the semantic orientations were transformed from discrete time to semantic intuitionistic fuzzy numbers and semantic intuitionistic fuzzy information matrixes. Furthermore, we proposed two DDIFWA operators to aggregate the dynamic semantic intuitionistic fuzzy information. Specifically, we obtained the rankings of alternative products and their features to support consumers' purchase decisions using the intuitionistic fuzzy scoring function and the “vertical projection distance” method. Finally, comparisons and experiments are provided to demonstrate the plausibility of our methods.

Efficient Analysis of Vertical Projection Histogram to Segment Arabic Handwritten Characters

Efficient Analysis of Vertical Projection Histogram to Segment Arabic Handwritten Characters

Minimal graphs over Riemannian surfaces and harmonic diffeomorphisms

We construct a parabolic entire minimal graph $S$ over a finite topology complete Riemannian surface $\Sigma$ of curvature $-1$ and infinite area (thus of non-parabolic conformal type). The vertical projection of this graph yields a harmonic diffeomorphism from $S$ onto $\Sigma$. The proof uses the theory of divergence lines to construct minimal graphs. We also generalize a theorem of R. Schoen. Let $g_1$ and $g_2$ be two complete metrics on a orientable surface $S$ with compact boundary and suppose $$\int_{S_r^2}K_{g_2}^-d\sigma_{g_2}\le C\ln(2+r)$$ for some $C>0$ and all $r>0$. If there is a harmonic diffeomorphism from $(S,g_1)$ to $(S,g_2)$, then $(S,g_1)$ is parabolic.

Analisis Robustness Teks Captcha Paypal HIP Menggunakan Template Matching

CAPTCHA refer to Completely Automated Public Turing test to tell Computers and Humans Apart. CAPTCHA are used to ensure that the operators are human not robots. The basic idea of using CAPTCHA is segmentation and recognition. Random characters, graphic images, or CAPTCHA audio become possible solutions to improve security and resilience for protection systems. In this paper used CAPTCHA random characters. However the CAPTCHA text needs to be analyzed again whether it is still solved by the computer or not it needs to be analyzed, improved, and developed to avoid automatic interference. Data set of text CAPTCHA paypal or so-called paypal HIP with 20 pieces of training data to get the template as much as 36 images that is from the numbers 0-9 and the letter A-Z. This particular paypal HIP data is limited by not using numbers 0 and 1 with the letters O and Q because of the similarity between the data. The method used starts from pre-processing, segmentation, and classification. Pre-processing techniques used consist of removing noise by tresholding and using cleaning techniques. We use bounding box and padding for segmentation method. And then for classification used counting pixel, vertical projections, horizontal projections, dan template correlation. By using these methods will be known which method can recognize CAPTCHA text accurately so as to affect the robustness of the CAPTCHA text.

Skew detection based on vertical projection in latin character recognition of text document image

The accuracy of Optical Character Recognition is deeply affected by the skew of the image. Skew detection & correction is one of the steps in OCR preprocessing to detect and correct the skew of document image. This research measures the effect of Combined Vertical Projection skew detection method to the accuracy of OCR. Accuracy of OCR is measured in Character Error Rate, Word Error Rate, and Word Error Rate (Order Independent). This research also measures the computational time needed in Combined Vertical Projection with different iteration. The experiment of Combined Vertical Projection is conducted by using iteration 0.5, 1, and 2 with rotation angle within -10 until 10 degrees. The experiment results show that the use of Combined Vertical Projection could lower the Character Error Rate, Word Error Rate, and Word Error Rate (Order Independent) up to 35.53, 34.51, and 32.74 percent, respectively. Using higher iteration value could lower the computational time but also decrease the accuracy of OCR.

Rail Surface Area Localization Based on Vertical Projection

In order to shorten the time-consuming of the image preprocessing stage and improve the accuracy of the rail area positioning, a new method is proposed. First, the image is converted into a binary image, then the image is divided into the same distance in a horizontal direction, and finally the rail boundary is determined based on the abrupt change of the gray value on the bisector. Compared with horizontal projection method, searching for the H value mutation method, Prewitt operator and other algorithms, the new method has obvious improvement in time and precision.

Beam Walking to Assess Dynamic Balance in Health and Disease: A Protocol for the “BEAM” Multicenter Observational Study

Background: Dynamic balance keeps the vertical projection of the center of mass within the base of support while walking. Dynamic balance tests are used to predict the risks of falls and eventual falls. The psychometric properties of most dynamic balance tests are unsatisfactory and do not comprise an actual loss of balance while walking. Objectives: Using beam walking distance as a measure of dynamic balance, the BEAM consortium will determine the psychometric properties, lifespan and patient reference values, the relationship with selected “dynamic balance tests,” and the accuracy of beam walking distance to predict falls. Methods: This cross-sectional observational study will examine healthy adults in 7 decades (n = 432) at 4 centers. Center 5 will examine patients (n = 100) diagnosed with Parkinson’s disease, multiple sclerosis, stroke, and balance disorders. In test 1, all participants will be measured for demographics, medical history, muscle strength, gait, static balance, dynamic balance using beam walking under single (beam walking only) and dual task conditions (beam walking while concurrently performing an arithmetic task), and several cognitive functions. Patients and healthy participants age 50 years or older will be additionally measured for fear of falling, history of falls, miniBESTest, functional reach on a force platform, timed up and go, and reactive balance. All participants age 50 years or older will be recalled to report fear of falling and fall history 6 and 12 months after test 1. In test 2, seven to ten days after test 1, healthy young adults and age 50 years or older (n = 40) will be retested for reliability of beam walking performance. Conclusion: We expect to find that beam walking performance vis-à-vis the traditionally used balance outcomes predicts more accurately fall risks and falls. Clinical Trial Registration Number: NCT03532984.