Search results for: mask fitting technique

Authors: Benoit Rougier, Alexandre Lefrancois, Herve Aubert

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Microwave interrogation in the range 10-100 GHz is identified as an advanced technique to investigate simultaneously shock and particle velocity measurements. However, it requires the understanding of electromagnetic wave propagation in a multi-layered moving media. The existing models limit their approach to wave guides or evaluate the velocities with a fitting method, restricting therefore the domain of validity and the precision of the results. Moreover, few data of permittivity on high explosives at these frequencies under dynamic compression have been reported. In this paper, shock and particle velocities are computed concurrently for steady and unsteady shocks for various inert and reactive materials, via a propagation model based on Doppler shifts and signal amplitude. Refractive index of the material under compression is also calculated. From experimental data processing, it is demonstrated that Hugoniot curve can be evaluated. The comparison with published results proves the accuracy of the proposed method. This microwave interrogation technique seems promising for shock and detonation waves studies.

Keywords: electromagnetic propagation, experimental setup, Hugoniot measurement, shock propagation

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Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Elzbieta Babula, Juhyun Park

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Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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Authors: Lingmao Xu, Hui Zhou

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Ge film is widely used in infrared optical systems. Because of the special requirements of space application, it is usually used in low temperature. The refractive index of Ge film is always changed with the temperature which has a great effect on the manufacture of high precision infrared optical film. Specimens of Ge single film were deposited at ZnSe substrates by EB-PVD method. During temperature range 80K ~ 300K, the transmittance of Ge single film within 2 ~ 15 μm were measured every 20K by PerkinElmer FTIR cryogenic testing system. By the full spectrum inversion method fitting, the relationship between refractive index and wavelength within 2 ~ 12μm at different temperatures was received. It can be seen the relationship consistent with the formula Cauchy, which can be fitted. Then the relationship between refractive index of the Ge film and temperature/wavelength was obtained by fitting method based on formula Cauchy. Finally, the designed value obtained by the formula and the measured spectrum were compared to verify the accuracy of the formula.

Keywords: infrared optical film, low temperature, thermal refractive coefficient, Ge film

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Authors: Kamal Kaushik, Dandpani Epili, Ajay G. V., Ashutosh, S. Pradhaan

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Introduction: Radiation therapy has come a long way over a period of decades, from 2-dimensional radiotherapy to intensity-modulated radiation therapy (IMRT) or VMAT. For advanced radiation therapy, we need better patient position reproducibility to deliver precise and quality treatment, which raises the need for better image guidance technologies for precise patient positioning. This study presents a two tattoo simulation with roll correction technique which is comparable to other advanced patient positioning techniques. Objective: This is a site-specific study is aimed to perform a comparison between various treatment positioning techniques used for the treatment of patients of Ca- Breast undergoing radiotherapy. In this study, we are comparing 5 different positioning methods used for the treatment of ca-breast, namely i) Vacloc with 3 tattoos, ii) Breast board with three tattoos, iii) Thermoplastic cast with three fiducials, iv) Breast board with a thermoplastic mask with 3 tattoo, v) Breast board with 2 tattoos – A roll correction method. Methods and material: All in one (AIO) solution immobilization was used in all patient positioning techniques for immobilization. The process of two tattoo simulations includes positioning of the patient with the help of a thoracic-abdomen wedge, armrest & knee rest. After proper patient positioning, we mark two tattoos on the treatment side of the patient. After positioning, place fiducials as per the clinical borders markers (1) sternum notch (lower border of clavicle head) (2) 2 cm below from contralateral breast (3) midline between 1 & 2 markers (4) mid axillary on the same axis of 3 markers (Marker 3 & 4 should be on the same axis). During plan implementation, a roll depth correction is applied as per the anterior and lateral positioning tattoos, followed by the shifts required for the Isocentre position. The shifts are then verified by SSD on the patient surface followed by radiographic verification using Cone Beam Computed Tomography (CBCT). Results: When all the five positioning techniques were compared all together, the produced shifts in Vertical, Longitudinal and lateral directions are as follows. The observations clearly suggest that the Longitudinal average shifts in two tattoo roll correction techniques are less than every other patient positioning technique. Vertical and lateral Shifts are also comparable to other modern positioning techniques. Concluded: The two tattoo simulation with roll correction technique provides us better patient setup with a technique that can be implemented easily in most of the radiotherapy centers across the developing nations where 3D verification techniques are not available along with delivery units as the shifts observed are quite minimal and are comparable to those with Vacloc and modern amenities.

Keywords: Ca. breast, breast board, roll correction technique, CBCT

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Authors: Abdulrahman S. Alturki, John S. Loomis

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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

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In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

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Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

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Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

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Authors: Hassan Eshkiki, Benjamin Mora

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The Neighbor Migrating Generator is a simple and efficient approach to finding the closest potential neighbor(s) with a different label for a given instance and so without the need to calibrate any kernel settings at all. This allows determining and explaining the most important features that will influence an AI model. It can be used to either migrate a specific sample to the class decision boundary of the original model within a close neighborhood of that sample or identify global features that can help localising neighbor classes. The proposed technique works by minimizing a loss function that is divided into two components which are independently weighted according to three parameters α, β, and ω, α being self-adjusting. Results show that this approach is superior to past techniques when detecting the smallest changes in the feature space and may also point out issues in models like over-fitting.

Keywords: explainable AI, EX AI, feature importance, counterfactual explanations

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Authors: W. H. Wan Zakiyatussariroh, A. A. Nasuhar, W. Y. Wan Fairos, Z. A. Nazatul Shahreen

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Forecasting dengue incidence in a population can provide useful information to facilitate the planning of the public health intervention. Many studies on dengue cases in Malaysia were conducted but are limited in modeling the outbreak and forecasting incidence. This article attempts to propose the most appropriate time series model to explain the behavior of dengue incidence in Malaysia for the purpose of forecasting future dengue outbreaks. Several seasonal auto-regressive integrated moving average (SARIMA) models were developed to model Malaysia’s number of dengue incidence on weekly data collected from January 2001 to December 2011. SARIMA (2,1,1)(1,1,1)52 model was found to be the most suitable model for Malaysia’s dengue incidence with the least value of Akaike information criteria (AIC) and Bayesian information criteria (BIC) for in-sample fitting. The models further evaluate out-sample forecast accuracy using four different accuracy measures. The results indicate that SARIMA (2,1,1)(1,1,1)52 performed well for both in-sample fitting and out-sample evaluation.

Keywords: time series modeling, Box-Jenkins, SARIMA, forecasting

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Authors: Nurudeen Oluwasola Lasisi

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The COVID-19 is an infection caused by coronavirus, which has been designated as a pandemic in the world. In this paper, we proposed a model to study the effect of distancing and wearing masks on the transmission of COVID-19 infection dynamics. The invariant region of the model is established. The COVID-19 free equilibrium and the reproduction number of the model were obtained. The local and global stability of the model is determined using the linearization technique method and Lyapunov method. It was found that COVID-19 free equilibrium state is locally asymptotically stable in feasible region Ω if R₀ < 1 and globally asymptomatically stable if R₀ < 1, otherwise unstable if R₀ > 1. More so, numerical analysis and simulations of the dynamics of the COVID-19 infection are presented.

Keywords: distancing, reproduction number, wearing of mask, local and global stability, modelling, transmission

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Hao-Su Liu, Jun-Qing Lei

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This study introduces the theory of modified particle swarm optimizer and its application in time-domain expressions for bridge self-excited aerodynamic forces. Based on the indicial function expression and the rational function expression in time-domain expression for bridge self-excited aerodynamic forces, the characteristics of the two methods, i.e. the modified particle swarm optimizer and conventional search method, are compared in flutter derivatives’ fitting process. Theoretical analysis and numerical results indicate that adopting whether the indicial function expression or the rational function expression, the fitting flutter derivatives obtained by modified particle swarm optimizer have better goodness of fit with ones obtained from experiment. As to the flutter derivatives which have higher nonlinearity, the self-excited aerodynamic forces, using the flutter derivatives obtained through modified particle swarm optimizer fitting process, are much closer to the ones simulated by the experimental. The modified particle swarm optimizer was used to recognize the parameters of time-domain expressions for flutter derivatives of an actual long-span highway-railway truss bridge with double decks at the wind attack angle of 0°, -3° and +3°. It was found that this method could solve the bounded problems of attenuation coefficient effectively in conventional search method, and had the ability of searching in unboundedly area. Accordingly, this study provides a method for engineering industry to frequently and efficiently obtain the time-domain expressions for bridge self-excited aerodynamic forces.

Keywords: time-domain expressions, bridge self-excited aerodynamic forces, modified particle swarm optimizer, long-span highway-railway truss bridge

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Authors: Bhavita S. Dave, Jaimin Vaidya, Chandresh H. Solanki, Atul K.

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To measure the permeability of a soil specimen, one of the basic assumptions of Darcy's law is that the soil sample should be saturated. Unlike saturated soils, the permeability of unsaturated soils cannot be found using conventional methods as it does not follow Darcy's law. Many empirical models, such as the Van Genuchten Model and Fredlund-Xing Model were suggested to predict permeability value for unsaturated soil. Such models use data from the soil-freezing characteristic curve to find fitting parameters for frozen unsaturated soils. In this study, soil specimens were subjected to 0, 1, 3, and 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and its soil freezing characteristic curves were formulated for all F-T cycles. Changes in fitting parameters and relative permeability with subsequent F-T cycles are presented in this paper for both models.

Keywords: frozen unsaturated soil, Fredlund Xing model, soil-freezing characteristic curve, Van Genuchten model

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Authors: Kristina Ancutiene, Agne Lage, Ada Gulbiniene

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Virtual garment fitting has gotten considerable attention for researchers currently. Virtual try-on technologies provide the opportunity to check garment fit using various fabrics and sizes. Differences in fabric mechanical properties produce differences in garment fit. This research aimed to investigate the virtual garment fit concerning the fabric's mechanical properties by determining distance ease between the body and the garment. In this research, virtual women mannequin was covered with straight fit virtual dress stitched in Modaris 3D (CAD Lectra). Garment fitting was investigated using seven cotton/cotton blended plain weave fabrics. Ease allowance value at bust, waist and hip girths in 2D basic patterns was changed uniformly from 0 cm to 8 cm. The values of distance ease in 3D virtual garments at the three main girths were investigated. Distance ease distribution in the virtual garment was investigated also. It was defined that by increasing of 2D patterns ease allowance, 3D garment distance ease changes proportionally but differently using various fabrics. Correlation analysis between 3D garment ease and mechanical properties showed that tensile strain in weft direction had the strongest relation.

Keywords: 3D CAD, distance ease, fabric, garment fit, virtual try-on

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Authors: Vijaya K. Narne, Gerard Loquet, Tobias Piechowiak, Dorte Hammershoi, Jesper H. Schmidt

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BEAR, which stands for better hearing rehabilitation is a large-scale project in Denmark designed and executed by three national universities, three hospitals, and the hearing aid industry with the aim to improve hearing aid fitting. A total of 1963 hearing impaired people were included and were segmented into subgroups based on hearing-loss, demographics, audiological and questionnaires data (i.e., the speech, spatial and qualities of hearing scale [SSQ-12] and the International Outcome Inventory for Hearing-Aids [IOI-HA]). With the aim to provide a better hearing-aid fit to individual patients, we applied modern machine learning techniques with traditional audiograms rule-based systems. Results show that age, speech discrimination scores, and audiogram configurations were evolved as important parameters in characterizing sub-population from the data-set. The attempt to characterize sub-population reveal a clearer picture about the individual hearing difficulties encountered and the benefits derived from more individualized hearing aids.

Keywords: hearing loss, audiological data, machine learning, hearing aids

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Authors: Haolun Sun, Ping Wang, Mei Wu, Meng Zhang, Bin Hou, Ling Yang, Xiaohua Ma, Yue Hao

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Gallium nitride (GaN) is an attractive material for next-generation power devices. It is noted that the performance of GaN-based high electron mobility transistors (HEMTs) is always limited by the self-heating effect. In response to the problem, integrating devices with polycrystalline diamond (PCD) has been demonstrated to be an efficient way to alleviate the self-heating issue of the GaN-based HEMTs. Among all the heat-spreading schemes, using PCD to cap the epitaxial layer before the HEMTs process is one of the most effective schemes. Now, the mainstream method of fabricating the PCD-capped HEMTs is to deposit the diamond heat-spreading layer on the AlGaN surface, which is covered by a thin nucleation dielectric/passivation layer. To achieve the pattern etching of the diamond heat spreader and device preparation, we selected SiN as the hard mask for diamond etching, which was deposited by plasma-enhanced chemical vapor deposition (PECVD). The conventional diamond etching method first uses F-based etching to remove the SiN from the special window region, followed by using O₂/Ar plasma to etch the diamond. However, the results of the scanning electron microscope (SEM) and focused ion beam microscopy (FIB) show that there are lots of diamond pillars on the etched diamond surface. Through our study, we found that it was caused by the high roughness of the diamond surface and the existence of the overlap between the diamond grains, which makes the etching of the SiN hard mask insufficient and leaves micro-masks on the diamond surface. Thus, a cyclic etching method was proposed to solve the problem of the residual SiN, which was left in the F-based etching. We used F-based etching during the first step to remove the SiN hard mask in the specific region; then, the O₂/Ar plasma was introduced to etch the diamond in the corresponding region. These two etching steps were set as one cycle. After the first cycle, we further used cyclic etching to clear the pillars, in which the F-based etching was used to remove the residual SiN, and then the O₂/Ar plasma was used to etch the diamond. Whether to take the next cyclic etching depends on whether there are still SiN micro-masks left. By using this method, we eventually achieved the self-terminated etching of the diamond and the smooth surface after the etching. These results demonstrate that the cyclic etching method can be successfully applied to the integrated preparation of polycrystalline diamond thin films and GaN HEMTs.

Keywords: AlGaN/GaN heterojunction, O₂/Ar plasma, cyclic etching, polycrystalline diamond

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Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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Authors: B. Pavan Kumar Reddy, P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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In this work, the fabrication and characterization of copper-doped zinc oxide (Cu:ZnO) based memristor devices with aluminum (Al) and indium tin oxide (ITO) metal electrodes are reported. The thin films of Cu:ZnO was synthesized using low-cost and low-temperature chemical process. The Cu:ZnO was then deposited onto ITO bottom electrodes using spin-coater technique, whereas the top electrode Al was deposited utilizing physical vapor evaporation technique. Ellipsometer was employed in order to measure the Cu:ZnO thickness and it was found to be 50 nm. Several surface and materials characterization techniques were used to study the thin-film properties of Cu:ZnO. To ascertain the efficacy of Cu:ZnO for memristor applications, electrical characterizations such as current-voltage (I-V), data retention and endurance were obtained, all being the critical parameters for next-generation memory. The I-V characteristic exhibits switching behavior with asymmetrical hysteresis loops. This work imputes the resistance switching to the positional drift of oxygen vacancies associated with respect to the Al/Cu:ZnO junction. Further, a non-linear curve fitting regression techniques were utilized to determine the equivalent circuit for the fabricated Cu:ZnO memristors. Efforts were also devoted in order to establish its potentiality for different electronic applications.

Keywords: copper doped, metal-oxides, oxygen vacancies, resistive switching

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Authors: Hajnalka Szarvas

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The research examines the effectiveness of e-participation tools and methods from a point of view of cultural fitting to the Hungarian community traditions. Participation can have very different meanings depending on the local cultural and historical traditions, experiences of the certain societies. Generally when it is about e-democracy or e-participation tools most of the researches are dealing with its technological sides and novelties, but there is not much said about the cultural and social context of the different platforms. However from the perspective of their success it would be essential to look at the human factor too, the actual users, how the certain DMS or any online platform is fitting to the way of thought, the way of functioning of the certain society. Therefore the paper will explore that to what extent the different online platforms like Loomio, Democracy OS, Your Priorities EVoks, Populus, miutcank.hu, Liquid Democracy, Brain Bar Budapest Lab are compatible with the Hungarian mental structures and community traditions, the contents of collective mind about community functioning. As a result the influence of cultural embeddedness of the logic of e-participation development tools on success of these methods will be clearly seen. Furthermore the most crucial factors in general which determine the efficiency of e-participation development tools in Hungary will be demonstrated.

Keywords: cultural embeddedness, e-participation, local community traditions, mental structures

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Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

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Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

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Authors: Leng Jian-Wei, Wang Lai-Jun, Li Ye

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In order to measure and analyze the transportation situation within the counties of Shaanxi province over a certain period of time and to promote the province's future transportation planning and development, this paper proposes a reasonable layout plan and compares model rationality. The study uses entropy weight method to measure the transportation advantages of 107 counties in Shaanxi province from three dimensions: road network density, trunk line influence and location advantage in 2013 and 2021, and applies spatial autocorrelation analysis method to analyze the spatial layout and development trend of county-level transportation, and conducts ordinary least square (OLS)regression on transportation impact factors and other influencing factors. The paper also compares the regression fitting degree of the Geographically weighted regression(GWR) model and the OLS model. The results show that spatially, the transportation advantages of Shaanxi province generally show a decreasing trend from the Weihe Plain to the surrounding areas and mainly exhibit high-high clustering phenomenon. Temporally, transportation advantages show an overall upward trend, and the phenomenon of spatial imbalance gradually decreases. People's travel demands have changed to some extent, and the demand for rapid transportation has increased overall. The GWR model regression fitting degree of transportation advantages is 0.74, which is higher than the OLS regression model's fitting degree of 0.64. Based on the evolution of transportation advantages, it is predicted that this trend will continue for a period of time in the future. To improve the transportation advantages of Shaanxi province increasing the layout of rapid transportation can effectively enhance the transportation advantages of Shaanxi province. When analyzing spatial heterogeneity, geographic factors should be considered to establish a more reliable model

Keywords: traffic dominance, GWR model, spatial autocorrelation analysis, temporal and spatial evolution

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Authors: Monika Ksiezopolska-Gocalska, Pawel Albrycht, Robert Holyst

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Surface Enhanced Raman Spectroscopy (SERS) is a technique used to analyze very low concentrations of substances in solutions, even in aqueous solutions - which is its advantage over IR. This technique can be used in the pharmacy (to check the purity of products); forensics (whether at a crime scene there were any illegal substances); or medicine (serving as a medical test) and lots more. Due to the high potential of this technique, its increasing popularity in analytical laboratories, and simultaneously - the absence of appropriate platforms enhancing the SERS signal (crucial to observe the Raman effect at low analyte concentration in solutions (1 ppm)), we decided to invent our own SERS platforms. As an enhancing layer, we have chosen gold and silver nanoparticles, because these two have the best SERS properties, and each has an affinity for the other kind of particles, which increases the range of research capabilities. The next step was to commercialize them, which resulted in the creation of the company ‘SERSitive.eu’ focusing on production of highly sensitive (Ef = 10⁵ – 10⁶), homogeneous and reproducible (70 - 80%) substrates. SERStive SERS substrates are made using the electrodeposition of silver or silver-gold nanoparticles technique. Thanks to a very detailed analysis of data based on studies optimizing such parameters as deposition time, temperature of the reaction solution, applied potential, used reducer, or reagent concentrations using a standardized compound - p-mercaptobenzoic acid (PMBA) at a concentration of 10⁻⁶ M, we have developed a high-performance process for depositing precious metal nanoparticles on the surface of ITO glass. In order to check a quality of the SERSitive platforms, we examined the wide range of the chemical compounds and the biological substances. Apart from analytes that have great affinity to the metal surfaces (e.g. PMBA) we obtained very good results for those fitting less the SERS measurements. Successfully we received intensive, and what’s more important - very repetitive spectra for; amino acids (phenyloalanine, 10⁻³ M), drugs (amphetamine, 10⁻⁴ M), designer drugs (cathinone derivatives, 10⁻³ M), medicines and ending with bacteria (Listeria, Salmonella, Escherichia coli) and fungi.

Keywords: nanoparticles, Raman spectroscopy, SERS, SERS applications, SERS substrates, SERSitive

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Authors: Wen-Jye Shyr, Chia-Ming Lin, Hung-Yun Feng

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The purpose of this study was to develop an energy management system for university campuses based on the Internet of Things (IoT) technique. The proposed IoT technique based on WebAccess is used via network browser Internet Explore and applies TCP/IP protocol. The case study of IoT for lighting energy usage management system was proposed. Structure of proposed IoT technique included perception layer, equipment layer, control layer, application layer and network layer.

Keywords: energy management, IoT technique, sensor, WebAccess

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Authors: Rui Zhao, Dongxu Zhang, Min Wan

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Composite materials are widely used in the fields of aviation, aerospace, and transportation due to their lightweight and high strength. Functionalization of composite structures is a hot topic in the future development of composite materials. This article proposed a polyimide-resin based composite material with a sensing function. This material can serve as a sensor to achieve deformation monitoring of metal sheets in room temperature environments. In the deformation process of metal sheets, the slope of the linear fitting line for the corresponding material resistance change rate is different in the elastic stage and the plastic strengthening stage. Therefore, the slope of the material resistance change rate can be used to characterize the deformation stage of the metal sheet. In addition, the resistance change rate of the material exhibited a good negative linear relationship with temperature in a high-temperature environment, and the determination coefficient of the linear fitting line for the change rate of material resistance in the range of 520-650℃ was 0.99. These results indicate that the material has the potential to be applied in the monitoring of mechanical properties of structural materials and temperature monitoring of high-temperature environments.

Keywords: polyimide, composite, sensing, resistance change rate

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Authors: Thiago Brito Bezerra

Abstract:

This paper presents a novel approach to reduce power consumption of digital filters based on dynamic bypassing of partial products in their multipliers. The bypassing elements incorporated into the multiplier hardware eliminate redundant signal transitions, which appear within the carry-save adders when the partial product is zero. This technique reduces the power consumption by around 20%. The circuit implementation was made using the AMS 0.18 um technology. The bypassing technique applied to the circuits is outlined.

Keywords: digital filter, low-power, bypassing technique, low-pass filter

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Authors: Angely Sim Jia Wun, Sasa Arsovski

Abstract:

Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Adhinarayanan Venkatasubramanian

Abstract:

For design of high speed digital circuit wave pipeline is the best approach this can be operated at higher operating frequencies by adjusting clock periods and skews so as latch the o/p of combinational logic circuit at the stable period. In this paper, there are two methods are proposed in automation task one is BIST (Built in self test) and second method is Reconfigurable technique. For the above two approaches dedicated AND gate (multiplier) by applying wave pipeline technique. BIST approach is implemented by Xilinx Spartan-II device. In reconfigurable technique done by ASIC. From the results, wave pipeline circuits are faster than nonpipeline circuit and area, power dissipation are reduced by reconfigurable technique.

Keywords: SOC, wave-pipelining, FPGA, self-testing, reconfigurable, ASIC

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Authors: Shaolin Allen Liao, Hual-Te Chien

Abstract:

Various THz phase extraction algorithms have been developed for a novel THz Modulating Interferometric Doppler Radar (THz-MIDR) developed recently by the author. The THz-MIDR differs from the well-known FTIR technique in that it introduces a continuously modulating reference branch, compared to the time-consuming discrete FTIR stepping reference branch. Such change allows real-time tracking of a moving object and capturing of its Doppler signature. The working principle of the THz-MIDR is similar to the FTIR technique: the incoming THz emission from the scene is split by a beam splitter/combiner; one of the beams is continuously modulated by a vibrating mirror or phase modulator and the other split beam is reflected by a reflection mirror; finally both the modulated reference beam and reflected beam are combined by the same beam splitter/combiner and detected by a THz intensity detector (for example, a pyroelectric detector). In order to extract THz phase from the single intensity measurement signal, we have derived rigorous mathematical formulas for 3 Frequency Banded (FB) signals: 1) DC Low-Frequency Banded (LFB) signal; 2) Fundamental Frequency Banded (FFB) signal; and 3) Harmonic Frequency Banded (HFB) signal. The THz phase extraction algorithms are then developed based combinations of 2 or all of these 3 FB signals with efficient algorithms such as Levenberg-Marquardt nonlinear fitting algorithm. Numerical simulation has also been performed in Matlab with simulated THz-MIDR interferometric signal of various Signal to Noise Ratio (SNR) to verify the algorithms.

Keywords: algorithm, modulation, THz phase, THz interferometry doppler radar

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