Academic literature on the topic 'FEM-WI'

Inexpensive (<$300) real-time particulate matter monitors (IRMs), using laser as a light source, have been introduced for use with a Wi-Fi function enabling networking with a smartphone. However, the information of measurement error of these inexpensive but convenient IRMs are still limited. Using ESCORTAIR (ESCORT, Seoul, Korea) and PurpleAir (PA) (PurpleAir U.S.A.), we evaluated the performance of these two devices compared with the U.S. Environmental Protection Agency (EPA) Federal Equivalent Monitoring (FEM) devices, that is, GRIMM180 (GRIMM Aerosol, Germany) for the indoor measurement of pork panfrying or secondhand tobacco smoking (SHS) and Beta-ray attenuation monitor (BAM) (MetOne, Grants Pass, OR) for outdoor measurement at the national particulate matter (PM2.5) monitoring site near an urban traffic hotspot in Daejeon, South Korea, respectively. The PM2.5 concentrations measured by ESCORTAIR and PA were strongly correlated to FEM (r = 0.97 and 0.97 from indoor pan frying; 0.92 and 0.86 from indoor SHS; 0.85 and 0.88 from outdoor urban traffic hotspot). The two IRMs showed that PM2.5 mass concentrations were increased with increased outdoor relative humidity (RH) levels. However, after applying correction factors for RH, the Median (Interquartile range) of difference compared to FEM was (14.5 (6.1~23.5) %) for PA and 16.3 (8.5–28.0) % for ESCORTAIR, supporting their usage in the home or near urban hotspots.

A non-planar electromagnetic band gap (EBG) structured antenna is proposed in this paper for wireless communication applications. The proposed design consists of coplanar waveguide (CPW) fed square patch antenna embedded with triangular EBG backing on FR-4 substrate material for 2.4 GHz (Wi-Fi, LTE) and 5.2 GHz (WLAN) applications. Gain is improved from 2.8 dB to 13.9 dB by adding EBG structure in the proposed antenna and the parametric analysis is done for optimizing the antenna performance characteristics. The proposed antenna provides a maximum efficiency of 82.5% in the resonating frequencies. The prototyped antenna is having good correlation with the simulation results obtained from Finite Element Method (FEM) based Anyss-HFSS. High Frequency Structure Simulator is used to analyze the antenna parameters and the simulated and measured results are correlating well with each other with a slight change in frequencies.

В статье предложена многодиапазонная антенна с копланарным волноводным питанием для Wi-Fi и 5G приложений. Для получения требуемых частот в работе использовался инновационный метод, включающий в себя использование полос частотного сдвига FSS (frequency shifting strips) и U-образной щели. Для моделирования спроектированной антенны использовано программное обеспечение ANSYS HFSS, где моделирование электромагнитного поля выполнялось методом конечных элементов FEM (finite elements method). Разработанная антенна предназначена для работы в диапазонах частот 5G: 28, 35 и 37 ГГц с максимальным усилением 11,61 дБ и коэффициентом полезного действия 92%. Для проверки эффективности моделированного проекта результаты сравнивались с результатами измерений. В данной работе проведено сравнение характеристик предлагаемой антенны с характеристиками других существующих антенн. В работе представлена информация об усилении антенны, КСВН, распределениях поля, ширине полосы, распределениях поверхностного тока (поля E и H), и других характеристиках разработанной антенны.

This study evaluates an innovative reinforcement method for cold-formed steel (CFS) upright sections through finite element assessment as well as prediction of the normalized ultimate load and deflection of the profiles by artificial intelligence (AI) and machine learning (ML) techniques. Following the previous experimental studies, several CFS upright profiles with different lengths, thicknesses and reinforcement spacings are modeled and analyzed under flexural loading. The finite element method (FEM) is employed to evaluate the proposed reinforcement method in different upright sections and to provide a valid database for the analytical study. To detect the most influential factor on flexural strength, the “feature selection” method is performed on the FEM results. Then, by using the feature selection method, a hybrid neural network (a combination of multi-layer perceptron algorithm and particle swarm optimization method) is developed for the prediction of normalized ultimate load. The correlation coefficient (R), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), mean absolute error (MAE) and Wilmot’s index of agreement (WI) are used as the measure of precision. The results show that the geometrical parameters have almost the same contribution in the flexural capacity and deflection of the specimens. According to the performance evaluation indexes, the best model is detected and optimized by tuning other algorithm parameters. The results indicate that the hybrid neural network can successfully predict the normalized ultimate load and deflection.

Abstract In order to cut off the connection between the mobile terminal and mobile communication base stations or Wi-Fi, it is necessary to improve the electromagnetic shielding efficiency of the mobile phone shielding cabinet. This paper analyzes the resonant characteristics of mobile phone shielding cabinets. The test method of electromagnetic shielding has been introduced. Through Maxwell wave equation and boundary conditions, the cavity resonant frequency of every small drawer on the mobile phone shielding cabinet has been derived, and the rectangular cavity research model was established. Using the high-frequency finite element method (FEM) simulation to calculate the cut-off frequency of the first 10-order high-order mode in the cavity, the resonant standing wave field distribution of every small drawer on the mobile phone shielding cabinet has been analyzed. This paper can offer a theory instruction for the product design of mobile phone shielding.

В работе представлена уникальная миниатюризированная и оптимизированная многополосная антенна с питанием от копланарного волновода CPW (coplanar waveguide) для современных беспроводных коммуникаций. Новая методика использования модифицированной структуры заземления MGS (modified ground structure) и полос частотного сдвига FSS (frequency shifting strips) наряду со структурой заземления с дефектом DGS (defected ground structure) и нагрузкой метаматериалом MTM (metamaterial) применяется в данной конструкции с тем, чтобы обеспечить многочастотную работу. Предлагаемая антенна генерирует четыре отдельные полосы пропускания, определяемые по входному импедансу, и охватывает минимально необходимые частотные диапазоны сетей GSM 1800/1900, Wi-Fi/WLAN 5,2/5,5 ГГц и WiMAX 3,3/10,3 ГГц. Антенна имеет сравнительно небольшие размеры 17×20 мм2 и работает в частотных диапазонах 1,45–2,08; 2,87–3,44; 5,01–5,58 и 8,89–10,69 ГГц. Разработанная антенна смоделирована в программе Ansoft HFSS при помощи метода конечных элементов FEM (finite element method). В работе представлены характеристики этой антенны, включая коэффициент отражения, коэффициент усиления, КСВН, распределения поверхностного тока и электрического поля. Также исследованы основные структурные параметры антенны и их влияние на характеристики антенны.

There is a need of low profile and multiband antennas in various fields of wireless communication lower band applications. Suitable gain with higher data rates for future communication modules in compact range is most challenging for design engineers. In this paper, Log Periodic Dipole Array antenna was designed and proposed for frequency range from 900 MHz to 2.6 GHz, operating frequency for the proposed antenna is 0.9 GHz (GSM), 2.1 GHz (PCS) and 2.4 GHz Industry standard Medical (ISM) and Wi-Fi applications. The modelled antenna constructed on FR4 substrate with height of 1.6mm, and analysed with electromagnetic simulation software like Magus, CST (Computer Simulation Technology) and HFSS (High Frequency structure simulator) tools. The proposed antenna has advantages like wideband, simple design, antenna results indicate the reflection coefficient value below -10dB for whole band from 900 MHz to 2600 MHz. The proposed antenna showing overall gain of 6 dB. Several antenna parameters are evaluated in Finite Element Method (FEM) and Finite Difference Time Domain (FDTD) and provided comparative analysis in this work.

Historical manuscripts are valuable resources for historical information about the distant past. From them culture, education, and ways of life in the past can be gleaned. Due to advancement of Information Communication and Technology (ICT), most of the historical manuscripts have been digitized via scanning devices to electronic formats like digital images. This has resulted in large amounts of historical manuscripts available to public as digital images and other electronic forms. Historical manuscript images (HMI) are easier to manage (by sharing, handling, storage, and processing) compared to actual manuscript documents. In addition, this helps to preserve actual historical manuscripts since they are seldom needed physically. Due to the proliferation of large amounts of HMI, their management and processing is the main focus. HMI management involves a range of tasks and processes carried out on HMI like curation, provenance, indexing and archiving, storage, restoration, retrieval, and classi fication among others. This thesis focuses on development of computer-based framework to index, archive, and classify HMI. First of all, a number of pre-processing tasks are carried out to enhance visual quality of HMI and in turn increase output performance. The pre processing tasks carried out include denoising, binarization, word segmentation and word image normalization. Due to degradations in most of HMI, a model-based binarization technique is proposed to enhance them. In this technique, HMI pixels are modelled to foreground and background pixels by training multilayer perceptron (MLP) classifier using various handcrafted features with high discriminating powers. The features are extracted from HMI. A component tracing and association (CTA) technique has been developed for efficient word vi segmentation of HMI. The merit of the method is in segmenting overlapping and crossing words. Using the concept that short sections of a continuous stroke joined at a common point are symmetric or near symmetric about the common joining point, crossing strokes are identified and separated using (MD − DTWD) multi-dimensional dynamic time warping with dependence. method. A segmentation-based handwritten word spotting (HWS) technique has been developed for indexing HMI. Integral histogram of oriented displacement (IHOD) feature descriptor is used to develop MLP-based HWS system. IHOD descriptor is obtained by computing displace ments of foreground pixels w.r.t centers of their respective m × m cells where m = 15 pixels. Cells are obtained by sub-dividing entire HMI. A fragmented long short-term memory (Frag-LSTM) method is proposed for language iden tification (LID) of textual content of HMI. 3 LSTM networks are used to learn and extract local and global features from input text word. A combined feature vector is obtained by concatenating global and local features. This combined feature vector is then used for LID. Bi-directional fragment network (BiD-FragNet) is proposed for prediction of era or pro duction time of HMI. BiD-FragNet consists of 2 convolution neural network (CNN)-based channels; main and fragment channels. The main channel learns and extracts global fea tures by processing full patches of HMI. Fragment channel is used to learn and extract local features by processing fragments (sub-patches) of HMI. Both channels share information in both directions at various levels. Global and local features learnt are then concatenated to one feature vector which is used with classification layer to give final classification output. Classification output is obtained by voting and averaging schemes. Funnelling ensemble method for writer identification (FEM-WI) has been proposed for HMI. It is a 2-level system of classifier ensembles. in this system, first, 5 newly proposed features (also called base features) are extracted from segmented handwritten words. In level 1, each feature is used to train individual base classifier (MLP). Meta features are then obtained as outputs of level 1 (base) classifiers via k-fold cross validation (KFCV) method. A single level 2 meta classifier that gives final output is trained using the meta features. FEM-WI works by leveraging on different base features for same input word image funnelled to a common vii feature space in level 2 classifier. Thus, writer identification of query word using any one of the base features benefits from all other features used to train meta classifier, hence giving improved output performance.

Wind Turbines are one of the most promising technologies to exploit renewable energy sources, and maybe the one which is the closest to achieve grid parity. Many modeling and experimental research activities are carried out in order to continuously improve devices performance. Another promising sector is small scale turbines, below 100kW installed power, for small installation, domestic use, and to be installed on ships. Moving within this scenario, a 1,5 kW turbine was tested inside a wind tunnel, and the following were measured: forces applied to the tower, angular speed, electric power output, mechanical power involved, and stress induced on the blades. Moreover, the cut in rotor speed and the turbine’s efficiency came as outputs of the activity. After some simple forecast calculations, to establish expected maximum values of physical quantities, the experiment was designed. The method used for acquiring all the values at one time involves a wi-fi device, attached to the rotor, in order to acquire signals coming from strain-gauges placed on the blades, avoiding long and cumbersome transmission lines towards the DAQ, coupled to anemometers, load cells, and a wattmeter. Coordination of operators during the tests had a crucial role in carrying out the procedure correctly. Since the main objects of study were blades, rotor and electric generator, the tower has been replaced with a robust support structure, designed to host and protect load cells and signal conditioners from accidental damage, thus permitting a correct measurement of axial force applied to the rotor and reacting momentum of the generator. The wi-fi device was linked to the rotor, in order to affect its mass and inertia characteristics as less as possible. This required the design of a proper linking structure, which was light and well balanced despite being mechanically resistant. Measured quantities are useful to evaluate the turbine’s performance (efficiency, power curve, cut in speed), and also to validate some fem and multi physics predictive models, that are currently under development, as possible tools for general wind turbines design. The outputs of these tests satisfy the need for a wide range of experimental data. This way of designing tests, the physical quantities involved and the schedule of experiments can be suggested as a valuable operative procedure.