Search results for: passive optical networks (PONs)

Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Liang Bai, Yandong Xiao, Haorang Wang, Songyang Lao

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The directedness of links is crucial to determine the controllability in complex networks. Even the edge directions can determine the controllability of complex networks. Obviously, for a given network, we wish to design its edge directions that make this network approach the optimal controllability. In this work, we firstly introduce two methods to enhance network by assigning edge directions. However, these two methods could not completely mitigate the negative effects of inaccessibility and dilations. Thus, to approach the optimal network controllability, the edge directions must mitigate the negative effects of inaccessibility and dilations as much as possible. Finally, we propose the edge direction for optimal controllability. The optimal method has been found to be successfully useful on real-world and synthetic networks.

Keywords: complex network, dynamics, network control, optimization

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Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

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In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: N. Bendimerad, M. Lemerini, A. Guen

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In this work, we propose to determine the density of neutral particles of an electric discharge peak - Plan types performed in air at atmospheric pressure by applying a technique based on laser interferometry. The experimental methods used so far as the shadowgraph or stereoscopy, give rather qualitative results with regard to the determination of the neutral density. The neutral rotational temperature has been subject of several studies but direct measurements of kinetic temperature are rare. The aim of our work is to determine quantitatively and experimentally depopulation with a Mach-Zehnder type interferometer. This purely optical appearance of the discharge is important when looking to know the refractive index of any gas for any physicochemical applications.

Keywords: laser source, Mach-Zehnder interferometer, refractive index, corona discharge

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Authors: B. Bouadjemi, S. Bentata, T. Lantri, Souidi Amel, W.Bensaali, A. Zitouni, Z. Aziz

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We performed first-principle calculations, the full-potential linearized augmented plane wave (FP-LAPW) method is used to calculate structural, optoelectronic and magnetic properties of cubic halide perovskites CsPbX3 (X= F,I). We employed for this study the GGA approach and for exchange is modeled using the modified Becke-Johnson (mBJ) potential to predicting the accurate band gap of these materials. The optical properties (namely: the real and imaginary parts of dielectric functions, optical conductivities and absorption coefficient absorption make this halide perovskites promising materials for solar cells applications.

Keywords: halide perovskites, mBJ, solar cells, FP-LAPW, optoelectronic properties, absorption coefficient

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Authors: Mehdi Sheikhi, Marjan Nassiri-Asl, Esmail Abbasi, Mahsa Shafiee

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Various synthetic derivatives of natural flavonoids are known to have neuroactive properties. The present study aimed to investigate the effects of vitexin (5, 7, 4-trihydroxyflavone-8-glucoside), a flavonoid found in such plants as tartary buckwheat sprouts, wheat leaves phenolome, Mimosa pudica Linn and Passiflora spp, on scopolamine-induced memory impairment in rats. To achieve this goal, we assessed the effects of vitexin on memory retrieval in the presence or absence of scopolamine using a step-through passive avoidance trial. In the first part of the study, vitexin (25, 50, and 100 μM) was administered intracerebroventricularly (i.c.v.) before acquisition trials. In the second part, vitexin, at the same doses, was administered before scopolamine (10 μg, i.c.v.) and before the acquisition trials. During retention tests, vitexin (100 μM) in the absence of scopolamine significantly increased the stepthrough latencies compared to scopolamine. In addition, vitexin (100 μM) significantly reversed the shorter step-through latencies induced by scopolamine (P < 0.05). These results indicate that vitexin has a potential role in enhancing memory retrieval. A possible mechanism is modulation of cholinergic receptors; however, other mechanisms may be involved in its effects in acute exposure.

Keywords: flavonoid, memory retrieval, passive avoidance, scopolamine, vitexin

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Authors: Salim Yusif

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Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper presents development results of usage of C-OTDR monitoring systems for rail traffic management. The C-OTDR method is based on vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes which take place due to microscopic seismoacoustic impacts on the optical fiber allows to determine seismoacoustic emission source positions and to identify their types. This approach proved successful for rail traffic management (moving block system, weigh- in-motion system etc).

Keywords: C-OTDR systems, moving block-sections, rail traffic management, Rayleigh backscattering, weigh-in-motion

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Ivan Maguire, Ciprian Briciu, Alan Barrett, Dara Kervick, Jens Ducrèe, Fiona Regan

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With the ever-increasing myriad of applications of which microfluidic devices are capable, reliable fluidic actuation development has remained fundamental to the success of these microfluidic platforms. There are a number of approaches which can be taken in order to integrate liquid actuation on microfluidic platforms, which can usually be split into two primary categories; active microvalves and passive microvalves. Active microvalves are microfluidic valves which require a physical parameter change by external, or separate interaction, for actuation to occur. Passive microvalves are microfluidic valves which don’t require external interaction for actuation due to the valve’s natural physical parameters, which can be overcome through sample interaction. The purpose of this paper is to illustrate how further improvements to past microvalve solutions can largely enhance systematic reliability and performance, with both novel active and passive microvalves demonstrated. Covered within this scope will be two alternative and novel microvalve solutions for centrifugal microfluidic platforms; a revamped pneumatic-dissolvable film active microvalve (PAM) strategy and a spray-on Sol-Gel based hydrophobic passive microvalve (HPM) approach. Both the PAM and the HPM mechanisms were demonstrated on a centrifugal microfluidic platform consisting of alternating layers of 1.5 mm poly(methyl methacrylate) (PMMA) (for reagent storage) sheets and ~150 μm pressure sensitive adhesive (PSA) (for microchannel fabrication) sheets. The PAM approach differs from previous SOLUBON™ dissolvable film methods by introducing a more reliable and predictable liquid delivery mechanism to microvalve site, thus significantly reducing premature activation. This approach has also shown excellent synchronicity when performed in a multiplexed form. The HPM method utilises a new spray-on and low curing temperature (70°C) sol-gel material. The resultant double layer coating comprises a PMMA adherent sol-gel as the bottom layer and an ultra hydrophobic silica nano-particles (SNPs) film as the top layer. The optimal coating was integrated to microfluidic channels with varying cross-sectional area for assessing microvalve burst frequencies consistency. It is hoped that these microvalving solutions, which can be easily added to centrifugal microfluidic platforms, will significantly improve automation reliability.

Keywords: centrifugal microfluidics, hydrophobic microvalves, lab-on-a-disc, pneumatic microvalves

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Authors: Jacob T. Liberty, Wilfred I. Okonkwo

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The present study designed and constructed a post-harvest passive solar tomato dryer of dimension 176 x 152 x 54cm for drying tomato. Quality of the dried crop was evaluated and compared with the fresh ones. The solar dryer consist of solar collector (air heater), 110 x 61 x 10 x 10cm, the drying chamber, 102 x54cm, removal heat storage unit, 40 x 35 x 13cm and drying trays, 43 x 42cm. The physicochemical properties of this crop were evaluated before and after drying. Physicochemical properties evaluated includes moisture, protein, fat, fibre, ash, carbohydrate and vitamin C, contents. The fresh, open and solar dried samples were analysed for their proximate composition using the recommended method of AOAC. Also, statistical analysis of the data was conducted using analysis of variance (ANOVA) using completely Randomize Design (CRD) and means were separated by Duncan’s New Multiple Range test (DNMRT). Proximate analysis showed that solar dried tomato had significantly (P < 0.05) higher protein, fibre, ash, carbohydrate and vitamin C except for the fat content that was significantly (P < 0.05) higher for all the open sun dried samples than the solar dried and fresh product. The nutrient which is highly affected by sun drying is vitamin C. Result indicates that moisture loss in solar dried tomato was faster and lower than the open dried samples and as such makes the solar dried products of lesser tendency to mould and bacterial growth. Also, the open sun dried samples had to be carried into the sheltered place each time it rained. The solar dried produce is of high quality. Further processing of the dried crops will involve packaging for commercial purposes. This will also help in making these agricultural product available in a relatively cheap price in off season and also avert micronutrient deficiencies in diet especially among the low-income groups in Nigeria.

Keywords: tomato, passive solar dryer, physicochemical properties, removal heat storage

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Authors: José Anderson Rodrigues de Souza, Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, Jeronimo Silva Rocha

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Mobile devices are increasingly occupying sectors of society and one of its most important features is mobility. However, the use of mobile devices is subject to the lifetime of the batteries. Thus, the use of energy batteries has become an important issue in the study of wireless network technologies. In this context, new solutions that enable aggregate energy efficiency not only through energy saving, and principally they are evaluated from a more realistic model of energy discharge, if easy adaptation to existing protocols. This paper presents a study on the energy needed and the lifetime for Wireless Sensor Networks (WSN) using a heterogeneous network and applying the LEACH protocol.

Keywords: wireless sensor networks, energy efficiency, heterogeneous, LEACH protocol

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Authors: Wenting Zhang, Shishi Liu, Peihong Fu

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As an indicator of air quality and directly related to concentration of ground PM2.5, the spatial-temporal variation and impact factor analysis of Aerosol Optical Depth (AOD) have been a hot spot in air pollution. This paper concerns the non-stationarity and the autocorrelation (with Moran’s I index of 0.75) of the AOD in Wuhan agglomeration (WHA), in central China, uses the geographically weighted regression (GRW) to identify the spatial relationship of AOD and its impact factors. The 3 km AOD product of Moderate Resolution Imaging Spectrometer (MODIS) is used in this study. Beyond the economic-social factor, land use density factors, vegetable cover, and elevation, the landscape metric is also considered as one factor. The results suggest that the GWR model is capable of dealing with spatial varying relationship, with R square, corrected Akaike Information Criterion (AICc) and standard residual better than that of ordinary least square (OLS) model. The results of GWR suggest that the urban developing, forest, landscape metric, and elevation are the major driving factors of AOD. Generally, the higher AOD trends to located in the place with higher urban developing, less forest, and flat area.

Keywords: aerosol optical depth, geographically weighted regression, land use change, Wuhan agglomeration

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Authors: Bryce R. Jolley, Michael Uchic

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This study presents initial results toward the correlative characterization of inherent defects of Ti-6Al-4V additive manufacture (AM). X-Ray Computed Tomography (CT) defect data are compared and correlated with microscopic photographs obtained via automated serial sectioning. The metal AM specimen was manufactured out of Ti-6Al-4V virgin powder to specified dimensions. A post-contour was applied during the fabrication process with a speed of 1050 mm/s, power of 260 W, and a width of 140 µm. The specimen was stress relief heat-treated at 16°F for 3 hours. Microfocus CT imaging was accomplished on the specimen within a predetermined region of the build. Microfocus CT imaging was conducted with parameters optimized for Ti-6Al-4V additive manufacture. After CT imaging, a modified RoboMet. 3D version 2 was employed for serial sectioning and optical microscopy characterization of the same predetermined region. Automated montage capture with sub-micron resolution, bright-field reflection, 12-bit monochrome optical images were performed in an automated fashion. These optical images were post-processed to produce 2D and 3D data sets. This processing included thresholding and segmentation to improve visualization of defect features. The defects observed from optical imaging were compared and correlated with the defects observed from CT imaging over the same predetermined region of the specimen. Quantitative results of area fraction and equivalent pore diameters obtained via each method are presented for this correlation. It is shown that Microfocus CT imaging does not capture all inherent defects within this Ti-6Al-4V AM sample. Best practices for this correlative effort are also presented as well as the future direction of research resultant from this current study.

Keywords: additive manufacture, automated serial sectioning, computed tomography, nondestructive evaluation

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Authors: P. K. Guha Thakurta, Shouvik Roy, Bhawana Raj

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A congestion control scheme in mobile networks is proposed in this paper through a verification based model. The model proposed in this work is represented through performance metric like buffer Occupancy, latency and packet loss rate. Based on pre-defined values, each of the metric is introduced in terms of three different states. A Markov chain based model for the proposed work is introduced to monitor the occurrence of the corresponding state transitions. Thus, the estimation of the network status is obtained in terms of performance metric. In addition, the improved performance of our proposed model over existing works is shown with experimental results.

Keywords: congestion, mobile networks, buffer, delay, call drop, markov chain

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Mustafa Öztas, Metin Bedir, Yahya Özdemir

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Boron doped of In2O3 films were prepared by spray pyrolysis technique at 350 °C substrate temperature, which is a low cost and large area technique to be well-suited for the manufacture of solar cells, using boric acid (H3BO3) as dopant source, and their properties were investigated as a function of doping concentration. X-ray analysis showed that the films were polycrystalline fitting well with a hexagonal structure and have preferred orientation in (220) direction. The changes observed in the energy band gap and structural properties of the films related to the boric acid concentration are discussed in detail.

Keywords: spray pyrolysis, In2O3, boron, optical properties, boric acid

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Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques

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Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.

Keywords: artificial neural networks, biodiesel, iodine value, prediction

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

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Authors: N. Ojaroudi Parchin, H. Jahanbakhsh Basherlou, Y. Al-Yasir, A. M. Abdulkhaleq, R. A. Abd-Alhameed, P. S. Excell

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A compact design of multi-sector patch antenna array for 60 GHz applications is presented and discussed in details. The proposed design combines five 1×8 linear patch antenna arrays, referred to as sectors, in a multi-sector configuration. The coaxial-fed radiation elements of the multi-sector array are designed on 0.2 mm Rogers RT5880 dielectrics. The array operates in the frequency range of 58-62 GHz and provides switchable directional/omnidirectional radiation beams with high gain and high directivity characteristics. The designed multi-sector array exhibits good performances and could be used in the fifth generation (5G) cellular networks.

Keywords: mm-wave communications, multi-sector array, patch antenna, small cell networks

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Authors: Bilal Haider, Farhan Aadil

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A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

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Authors: Soban Najam, S. M. Jahanzeb, Ahmed Sohail, Faraz Idris Khan

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With the recent increase in reliance on Gas as the primary source of energy across the world, there has been a lot of research conducted on gas distribution networks. As the complexity and size of these networks grow, so does the leakage of gas in the distribution network. One of the most crucial factors in the production and distribution of gas is UFG or Unaccounted for Gas. The presence of UFG signifies that there is a difference between the amount of gas distributed, and the amount of gas billed. Our approach is to use information that we acquire from several specified points in the network. This information will be used to calculate the loss occurring in the network using the developed algorithm. The Algorithm can also identify the leakages at any point of the pipeline so we can easily detect faults and rectify them within minimal time, minimal efforts and minimal resources.

Keywords: FLA, fault location analysis, GDN, gas distribution network, GIS, geographic information system, NMS, network Management system, OMS, outage management system, SSGC, Sui Southern gas company, UFG, unaccounted for gas

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Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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Authors: Chungyu Chen, Hui-Ju Chang, Pei-Shan Guo, Huei-Ling Jhan, Yi-Ping Lin

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The purpose of this study was to investigate the effect of the amount of acutely static stretching on muscular strength and power. There were 15 males, and 7 females recruited voluntarily as the participants in the study. The mean age, body height, and weight of participants were 23.4 ± 2.8 years old, 171.0 ± 7.2 cm, and 65.7 ± 8.7 kg, respectively. Participants were repeated to stretch hamstring muscles 2 or 6 30-s bouts randomly on a separate day spaced 5-7 days apart in a passive, static, sit-and-reach stretching exercise. Before and after acutely static stretching, the Biodex System 4 Pro was used to acquire the peak torque, power, total work, and range of motion for right knee under the loading of 180 deg/s. The 2 (test-retest) × 2 (number of stretches) repeated measures two-way analysis of variance were used to compare the parameters of muscular strength/power (α = .05). The results showed that the peak torque, power, and total work increased significantly after acutely passive static stretching (ps < .05) in flexor and extensor of knee. But there were no significant differences found between the 2 and 6 30-s bouts hamstring muscles stretching (ps > .05). It indicated that the performance of muscular strength and power in knee flexion and extension do not inhibit following the increase of amount of stretching.

Keywords: knee, power, flexibility, strength

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Authors: P. R. Dushantha Chaminda, Peng Kai

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In this review paper, we enclose the thought of wireless ad hoc networks and particularly mobile ad hoc network (MANET), their field of study, intention, concern, benefit and disadvantages, modifications, with relation of AODV routing protocol. Mobile computing is developing speedily with progression in wireless communications and wireless networking protocols. Making communication easy, we function most wireless network devices and sensor networks, movable, battery-powered, thus control on a highly constrained energy budget. However, progress in battery technology presents that only little improvements in battery volume can be expected in the near future. Moreover, recharging or substitution batteries is costly or unworkable, it is preferable to support energy waste level of devices low.

Keywords: wireless ad hoc network, energy efficient routing protocols, AODV, EOAODV, AODVEA, AODVM, AOMDV, FF-AOMDV, AOMR-LM

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Authors: Harmel Meriem

Abstract:

The optoelectronic properties and high power conversion efficiency make lead halide perovskites ideal material for solar cell applications. However, the toxic nature of lead and the instability of organic cation are the two key challenges in the emerging perovskite solar cells. To overcome these challenges, we present our study about finding potential alternatives to lead in the form of A2BX6 perovskite using the first principles DFT-based calculations. The highly accurate modified Becke Johnson (mBJ) and hybrid functional (HSE06) have been used to investigate the Main Document Click here to view linked References to optoelectronic and thermoelectric properties of A2PdBr6 (A = K, Rb, and Cs) perovskite. The results indicate that different A-cations in A2PdBr6 can significantly alter their electronic and optical properties. Calculated band structures indicate semiconducting nature, with band gap values of 1.84, 1.53, and 1.54 eV for K2PdBr6, Rb2PdBr6, and Cs2PdBr6, respectively. We find strong optical absorption in the visible region with small effective masses for A2PdBr6. The ideal band gap and optimum light absorption suggest Rb2PdBr6 and Cs2PdBr6 potential candidates for the light absorption layer in perovskite solar cells. Additionally.

Keywords: soler cell, double perovskite, optoelectronic properties, ab-inotio study

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Authors: Guiheng Zhang, Wei Zhang, Jun Fu, Yudong Wang

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A 900 MHz three-stage SiGe power amplifier (PA) with high power gain is presented in this paper. Volterra Series is applied to analyze nonlinearity sources of SiGe HBT device model clearly. Meanwhile, the influence of operating current to IMD3 is discussed. Then a β-helper current mirror bias circuit is applied to improve linearity, since the β-helper current mirror bias circuit can offer stable base biasing voltage. Meanwhile, it can also work as predistortion circuit when biasing voltages of three bias circuits are fine-tuned, by this way, the power gain and operating current of PA are optimized for best linearity. The three power stages which fabricated by 0.18 μm SiGe technology are bonded to the printed circuit board (PCB) to obtain impedances by Load-Pull system, then matching networks are done for best linearity with discrete passive components on PCB. The final measured three-stage PA exhibits 21.1 dBm of output power at 1 dB compression point (OP1dB) with power added efficiency (PAE) of 20.6% and 33 dB power gain under 3.3 V power supply voltage.

Keywords: high gain power amplifier, linearization bias circuit, SiGe HBT model, Volterra series

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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