Search results for: distributed rayleigh sensing

Authors: Raoudha Chaabane, Faouzi Askri, Sassi Ben Nasrallah

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A new numerical algorithm is developed to solve coupled convection-radiation heat transfer in a two dimensional enclosure. Radiative heat transfer in participating medium has been carried out using the control volume finite element method (CVFEM). The radiative transfer equations (RTE) are formulated for absorbing, emitting and scattering medium. The density, velocity and temperature fields are calculated using the two double population lattice Boltzmann equation (LBE). In order to test the efficiency of the developed method the Rayleigh Benard convection with and without radiative heat transfer is analyzed. The obtained results are validated against available works in literature and the proposed method is found to be efficient, accurate and numerically stable.

Keywords: participating media, LBM, CVFEM- radiation coupled with convection

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Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

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Authors: M. Yousaf, S. Usman

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The present study focused on the investigation of the effects of roughness elements on heat transfer during natural convection in a rectangular cavity using a numerical technique. Roughness elements were introduced on the bottom hot wall with a normalized amplitude (A*/H) of 0.1. Thermal and hydrodynamic behavior was studied using a computational method based on Lattice Boltzmann method (LBM). Numerical studies were performed for a laminar natural convection in the range of Rayleigh number (Ra) from 103 to 106 for a rectangular cavity of aspect ratio (L/H) 2 with a fluid of Prandtl number (Pr) 1.0. The presence of the sinusoidal roughness elements caused a minimum to the maximum decrease in the heat transfer as 7% to 17% respectively compared to the smooth enclosure. The results are presented for mean Nusselt number (Nu), isotherms, and streamlines.

Keywords: natural convection, Rayleigh number, surface roughness, Nusselt number, Lattice Boltzmann method

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Authors: Amin Hamrahi, Niloofar Moghaddam

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Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

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Authors: Moataz Ammar, Ahdab Elmorshedy

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The distributed generation hosting capacity of a distribution network is typically limited at a given connection point by the upper voltage limit that can be violated due to the injection of active power into the distribution network. The upper voltage limit violation concern becomes more important as the network equivalent resistance increases with respect to its equivalent reactance. This paper investigates the impact of modifying the distribution network equivalent reactance at the point of connection such that the upper voltage limit is violated at a higher distributed generation penetration, than it would without the addition of series reactive compensation. The results show that series reactive compensation proves efficient in certain situations (based on the ratio of equivalent network reactance to equivalent network resistance at the point of connection). As opposed to the conventional case of capacitive compensation of a distribution network to reduce voltage drop, inductive compensation is seen to be more appropriate for alleviation of distributed-generation-induced voltage rise.

Keywords: distributed generation, distribution networks, series compensation, voltage rise

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Authors: Zheng DianXun, Cheng Bo, Lin Hetong

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This paper focuses on the orbit avoidance strategies of optical remote sensing satellite. The optical remote sensing satellite, moving along the Sun-synchronous orbit, is equipped with laser warning equipment to alert CCD camera from laser attacks. There are three ways to protect the CCD camera: closing the camera cover, satellite attitude maneuver and satellite orbit avoidance. In order to enhance the safety of optical remote sensing satellite in orbit, this paper explores the strategy of satellite avoidance. The avoidance strategy is expressed as the evasion of pre-determined target points in the orbital coordinates of virtual satellite. The so-called virtual satellite is a passive vehicle which superposes the satellite at the initial stage of avoidance. The target points share the consistent cycle time and the same semi-major axis with the virtual satellite, which ensures the properties of the satellite’s Sun-synchronous orbit remain unchanged. Moreover, to further strengthen the avoidance capability of satellite, it can perform multi-target-points avoid maneuvers. On occasions of fulfilling the satellite orbit tasks, the orbit can be restored back to virtual satellite through orbit maneuvers. Thereinto, the avoid maneuvers adopts pulse guidance. And the fuel consumption is also optimized. The avoidance strategy discussed in this article is applicable to optical remote sensing satellite when it is encountered with hostile attack of space-based laser anti-satellite.

Keywords: optical remote sensing satellite, satellite avoidance, virtual satellite, avoid target-point, avoid maneuver

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Authors: S. S. Chong, A. R. Abdul Aziz, S. W. Harun, H. Arof

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A miniaturized non-adiabatic silica microfiber is proposed for biological oxygen demand (BOD) ratio chemical oxygen demand (COD) sensing for the first time. BOD and COD are two main parameters to justify quality of wastewater. A ratio, BOD:COD can usually be established between the two analytical methods once COD and BOD value has been gathered. This ratio plays a vital role to determine appropriate strategy in wastewater treatment. A non-adiabatic microfiber sensor was formed by tapering the SMF to generate evanescent field where sensitive to perturbation of sensing medium. Because difference ratio BOD and COD contain in solution, this may induced changes of effective refractive index between microfiber and sensing medium. Attenuation wavelength shift to right with 0.5 nm and 3.5 nm while BOD:COD equal to 0.09 and 0.18 respectively. Significance difference wavelength shift may relate with the biodegradability of analyte. This proposed sensor is compact, reliable and feasible to determine the BOD:COD. Further research and investigation should be proceeded to enhance sensitivity and precision of the sensor for several of wastewater online monitoring.

Keywords: non-adiabatic fiber sensor, environmental sensing, biodegradability, evanescent field

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Authors: Dianxun Zheng, Wuxing Jing, Lin Hetong

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Optical remote sensing satellite, always running on the Sun-synchronous orbit, equipped laser warning equipment to alert CCD camera from laser attack. There have three ways to protect the CCD camera, closing the camera cover satellite attitude maneuver and satellite orbit avoidance. In order to enhance the safety of optical remote sensing satellite in orbit, this paper explores the strategy of satellite avoidance. The avoidance strategy is expressed as the evasion of pre-determined target points in the orbital coordinates of virtual satellite. The so-called virtual satellite is a passive vehicle which superposes a satellite at the initial stage of avoidance. The target points share the consistent cycle time and the same semi-major axis with the virtual satellite, which ensures the properties of the Sun-synchronous orbit remain unchanged. Moreover, to further strengthen the avoidance capability of satellite, it can perform multi-object avoid maneuvers. On occasions of fulfilling the orbit tasks of the satellite, the orbit can be restored back to virtual satellite through orbit maneuvers. There into, the avoid maneuvers adopts pulse guidance. and the fuel consumption is also optimized. The avoidance strategy discussed in this article is applicable to avoidance for optical remote sensing satellite when encounter the laser hostile attacks.

Keywords: optical remote sensing satellite, always running on the sun-synchronous

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Ekin Nurbaş

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One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

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Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

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Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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Authors: Sorayya Kazemi, Hamed Kharrati, Mehdi Abedinpour Fallah

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This paper presents the design and implementation of a novel electric pressure-sensitive toothbrush, capable of measuring the forces applied to the head of the brush. The developed device is used for gum recession measurement. In particular, the percentage of gum recession is measured by a Programmable Automation controller (PAC). Moreover, the brushing forces are measured by a Force Sensing Resistor (FSR) sensor. These forces are analog inputs of PAC. According to the applied forces during patient’s brushing and the patient’s percentage of gum recession, dentist sets the standard force range. The instrument alarms when the patient applies a force over the set range.

Keywords: gum recession, force sensing resistor, controller, toothbrush

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Authors: Ozgun Oktar, Sevilay Can, Cengiz V. Ekici

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The oil spill is a form of pollution caused by releasing of a liquid petroleum hydrocarbon into the marine environment. Considering the growth of ship traffic, increasing of off-shore oil drilling and seaside refineries affect the risk of oil spill upward. The oil spill is easy to spread to large areas when occurs especially on the sea surface. Remote sensing technology offers the easiest way to control/monitor the area of the oil spill in a large region. It’s usually easy to detect pollution when occurs by the ship accidents, however monitoring non-accidental pollution could be possible by remote sensing. It is also needed to observe specific regions daily and continuously by satellite solutions. Remote sensing satellites mostly and effectively used for monitoring oil pollution are RADARSAT, ENVISAT and MODIS. Spectral coverage and transition period of these satellites are not proper to monitor Marmara Sea and Istanbul Strait continuously. In this study, RASAT and GOKTURK-2 are suggested to use for monitoring Marmara Sea and Istanbul Strait. RASAT, with spectral resolution 420 – 730 nm, is the first Turkish-built satellite. GOKTURK-2’s resolution can reach up to 2,5 meters. This study aims to analyze the images from both satellites and produce maps to show the regions which have potentially affected by spills from shipping traffic.

Keywords: Marmara Sea, monitoring, oil spill, satellite remote sensing

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Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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Authors: H. Akbari Khorami, P. Wild, N. Djilali

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This paper reports on the response of a fiber-optic sensing probe to small concentrations of hydrogen peroxide (H2O2) vapor at room temperature. H2O2 has extensive applications in industrial and medical environments. Conversely, H2O2 can be a health hazard by itself. For example, H2O2 induces cellular damage in human cells and its presence can be used to diagnose illnesses such as asthma and human breast cancer. Hence, development of reliable H2O2 sensor is of vital importance to detect and measure this species. Ferric ferrocyanide, referred to as Prussian blue (PB), was deposited on the tip of a multimode optical fiber through the single source precursor technique and served as an indicator of H2O2 in a spectroscopic manner. Sensing tests were performed in H2O2-H2O vapor mixtures with different concentrations of H2O2. The results of sensing tests show the sensor is able to detect H2O2 concentrations in the range of 50.6 ppm to 229.5 ppm. Furthermore, the sensor response to H2O2 concentrations is linear in a log-log scale with the adjacent R-square of 0.93. This sensing behavior allows us to detect and quantify the concentration of H2O2 in the vapor phase.

Keywords: chemical deposition, fiber-optic sensor, hydrogen peroxide vapor, prussian blue

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Authors: Yaner Yan, Ning Li, Yajun Qiao, Shuqing An

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Although most studies have focused on assessing and mapping terrestrial ecosystem services, there is still a knowledge gap on coastal ecosystem services and an urgent need to assess them. Lau (2013) clearly defined five types of costal ecosystem services: carbon sequestration, shoreline protection, fish nursery, biodiversity, and water quality. While high-resolution remote sensing can provide the more direct, spatially estimates of biophysical parameters, such as species distribution relating to biodiversity service, and Fluorescence information derived from remote sensing direct relate to photosynthesis, availing in estimation of carbon sequestration and the response to environmental changes in coastal wetland. Here, we review the capabilities of high-resolution and fluorescence remote sesing for describing biodiversity, vegetation condition, ecological processes and highlight how these prodicts may contribute to costal ecosystem service assessment. In so doing, we anticipate rapid progress to combine the high-resolution and fluorescence remote sesing to estimate the spatial pattern of costal ecosystem services.

Keywords: ecosystem services, high resolution, remote sensing, chlorophyll fluorescence

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Authors: Kadda Boumediene, Mohamed Ziani

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Mainly because of their good ratio stiffness/mass, and in addition to adjustable mechanical properties, composite materials are more and more often used as an alternative to traditional materials in several domains. Before using these materials in practical application, a detailed and precise characterization of their mechanical properties is necessary. In the present work, we will find a dynamic analyze of composite beam (natural frequencies and mode shape), an experimental vibration technique, which presents a powerful tool for the estimation of mechanical characteristics, is used to characterize a dissimilar beam of a Mortar/ natural mineral fiber. The study is completed by an analytic (Rayleigh & Rayleigh-Ritz), experimental and numerical application for non-uniform composite beam of a Mortar/ natural mineral fiber. The study is supported by a comparison between numerical and analytic results as well as a comparison between experimental and numerical results.

Keywords: composite beam, mortar/ natural mineral fiber, mechanical characteristics, natural frequencies, mode shape

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Authors: M. M. Othman, Walid El-Khattam, Y. G. Hegazy, A. Y. Abdelaziz

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This paper presents a method for finding the optimal location and capacity of dispatchable DGs connected to the distribution feeders for optimal planning for a specified power loss without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37-nodes feeder. The results that are validated by comparing it with results obtained from other competing methods show the effectiveness, accuracy and speed of the proposed method.

Keywords: distributed generators, firefly technique, optimization, power loss

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Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: N. Deepika, P. A. L. Narayana

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Linear stability analysis of double diffusive convection in a horizontal porous layer saturated with fluid is examined by considering the effects of viscous dissipation, concentration based internal heat source and vertical throughflow. The basic steady state solution for Governing equations is computed. Linear stability analysis has been implemented numerically by using Runge-kutta method. Critical thermal Rayleigh number Rac is obtained for various values of solutal Rayleigh number Sa, vertical Peclet number Pe, Gebhart number Ge, Lewis number Le and measure of concentration based internal heat source $\gamma$. It is observed that Ge has destabilizing effect for upward throughflow and stabilizing effect for downward throughflow. For sufficient value of Pe, $\gamma$ has considerable destabilizing effect for upward throughflow, insignificant destabilizing effect for downward throughflow.

Keywords: porous medium, concentration based internal heat source, vertical throughflow, viscous dissipation

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Authors: Zulkiflee Abd Latif, Sitinor Atikah Nordin, Alawi Sulaiman

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Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species

Keywords: Arenga Pinnata, pixel-based classification, object-based classification, remote sensing

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Authors: K. Jithendra Gowd, Ch. Sai Babu, S. Sivanagaraju

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Electric power systems are daily exposed to service interruption mainly due to faults and human accidental interference. Short circuit currents are responsible for several types of disturbances in power systems. The fault currents are high and the voltages are reduced at the time of fault. This paper presents two suitable methods, consideration of fault resistance and Distributed Generator are implemented and analyzed for the enhancement of voltage profile during fault conditions. Fault resistance is a critical parameter of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies and protection scheme efficiency. The effect of Distributed Generator is also considered. The proposed methods are tested on the IEEE 37 bus test systems and the results are compared.

Keywords: distributed generation, electrical distribution systems, fault resistance

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

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Authors: Elnaz Akbari, Zolkafle Buntat

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Today, the use of carbon-based materials such as graphene, carbon nanotubes, etc. in various applications is being extensively studied by researchers in the field. One of such applications is using them in gas sensors. While analytical investigations on the physical and chemical properties of carbon nanomaterials are the focal points in the studies, the need for experimental measurements on various physical characteristics of these materials is deeply felt. In this work, a set of experiments has been conducted using arc discharge Methane decomposition attempting to obtain carbonaceous materials (C-strands) formed between graphite electrodes. The current-voltage (I-V) characteristics of the fabricated C-strands have been investigated in the presence and absence of two different gases, NO2 and CO2. The results reveal that the current passing through the carbon films increases when the concentrations of gases are increased from 200 to 800 ppm. This phenomenon is a result of conductance changes and can be employed in sensing applications such as gas sensors.

Keywords: carbonaceous materials, gas sensing, methane arc discharge decomposition, I-V characteristics

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Authors: Chai Mingming, Li Lei, Lu Xiaoxia

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In this paper, the mechanism of stratified liquids’ mixing in a cylinder is investigated. It is focused on the effects of Rayleigh-Taylor Instability (RTI) and rotation of the cylinder on liquid interface mixing. For miscible liquids, Planar Laser Induced Fluorescence (PLIF) technique is applied to record the concentration field for one liquid. Intensity of Segregation (IOS) is used to describe the mixing status. For immiscible liquids, High Speed Camera is adopted to record the development of the interface. The experiment of RTI indicates that it plays a great role in the mixing process, and meanwhile the large-scale mixing is triggered, and subsequently the span of the stripes decreases, showing that the mesoscale mixing is coming into being. The rotation experiments show that the spin-down process has a great role in liquid mixing, during which the upper liquid falls down rapidly along the wall and crashes into the lower liquid. During this process, a lot of interface instabilities are excited. Liquids mix rapidly in the spin-down process. It can be concluded that no matter what ways have been adopted to speed up liquid mixing, the fundamental reason is the interface instabilities which increase the area of the interface between liquids and increase the relative velocity of the two liquids.

Keywords: interface instability, liquid mixing, Rayleigh-Taylor Instability, spin-down process, spin-up process

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Jamal R. Elbergali

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Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero-Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol (x ̃_(N_T )), then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, modulation, zero forcing (ZF), OSIC, ZF-IC, spatial multiplexing (SM)

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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