Search results for: surface runoff network

Authors: M. Ravindra, R. Srinivasa Rao, V. Shanmukha Naga Raju

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This paper presents state estimation with Phasor Measurement Unit (PMU) allocation to obtain complete observability of network. A matrix is designed with modeling of zero injection constraints to minimize PMU allocations. State estimation algorithm is developed with optimal allocation of PMUs to find accurate states of network. The incorporation of PMU into traditional state estimation process improves accuracy and computational performance for large power systems. The nonlinearity integrated with zero injection (ZI) constraints is remodeled to linear frame to optimize number of PMUs. The problem of optimal PMU allocation is regarded with modeling of ZI constraints, PMU loss or line outage, cost factor and redundant measurements. The proposed state estimation with optimal PMU allocation has been compared with traditional state estimation process to show its importance. MATLAB programming on IEEE 14, 30, 57, and 118 bus networks is implemented out by Binary Integer Programming (BIP) method and compared with other methods to show its effectiveness.

Keywords: Observability, phasor measurement units, synchrophasors, SCADA measurements, zero injection bus.

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Authors: L. J. de Bessa Neto, M. R. B. Guerra Vale, F. K. O. M. Varella Guerra

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In recent years, solar energy has established itself as one of the main sources of renewable energy, gaining a large space in electricity generation around the world. However, due to the low performance of photovoltaic panels, technologies need to be sought to maximize the production of electricity. In this regard, the present study aims to develop a prototype of solar tracker for didactics applications, controlled with the Arduino® platform, that enables the movement of photovoltaic plates in relation to the sun positions throughout the day through an electromechanical system, optimizing, thus, the efficiency of solar photovoltaic generation and improvements for the photovoltaic effect. The solar tracking technology developed in this work was presented of the shape oral and practical in two middle schools in the municipality of Mossoró/RN, being one of the public network and other of the private network, always keeping the average age of the students, in the case, around 16 years, contemplating an average of 60 students in each of the visits. Thus, it is concluded that the present study contributed substantially to the dissemination of knowledge concerning the photovoltaic solar generation, as well as the study of solar trackers, thus arousing the interest and curiosity of the students regarding the thematic approached.

Keywords: Alternative energy, solar tracker, energy efficiency.

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Authors: Phillip Garrad, Saritha Unnikrishnan

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The increase in connected and autonomous vehicles (CAV) creates more opportunities for cyber-attacks. Cyber-attacks can be performed with malicious intent or for research and testing purposes. As connected vehicles approach full autonomy, the possible impact of these cyber-attacks also grows. This review analyses the challenges faced in CAV cybersecurity testing. This includes access and cost of the representative test setup and lack of experts in the field A review of potential solutions to overcome these challenges is presented. Studies have demonstrated Artificial Intelligence (AI) as a promising technique to reduce runtime, enhance effectiveness and comprehensively cover all the standard test aspects in penetration testing in other industries. However, this review has identified a significant gap in the systematic implementation of AI for penetration testing in the CAV cybersecurity domain. The expectation from this review is to investigate potential AI algorithms, which can demonstrate similar improvements in runtime and efficiency for a CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: Cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing.

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Authors: Irfan Z. Qureshi, Fareeha A., Wajid A. Khan

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Human amniotic membrane (HAM) is a useful biological material for the reconstruction of damaged ocular surface. The processing and preservation of HAM is critical to prevent the patients undergoing amniotic membrane transplant (AMT) from cross infections. For HAM preparation human placenta is obtained after an elective cesarean delivery. Before collection, the donor is screened for seronegativity of HCV, Hbs Ag, HIV and Syphilis. After collection, placenta is washed in balanced salt solution (BSS) in sterile environment. Amniotic membrane is then separated from the placenta as well as chorion while keeping the preparation in BSS. Scrapping of HAM is then carried out manually until all the debris is removed and clear transparent membrane is acquired. Nitrocellulose membrane filters are then placed on the stromal side of HAM, cut around the edges with little membrane folded towards other side making it easy to separate during surgery. HAM is finally stored in solution of glycerine and Dulbecco-s Modified Eagle Medium (DMEM) in 1:1 ratio containing antibiotics. The capped borosil vials containing HAM are kept at -80°C until use. This vial is thawed to room temperature and opened under sterile operation theatre conditions at the time of surgery.

Keywords: HAM, AMT, ocular transplant

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Authors: Faraj Farhat El Dabee, Rajab Abdullah Hokoma

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Supply Chain Management (SCM) is the integration between manufacturer, transporter and customer in order to form one seamless chain that allows smooth flow of raw materials, information and products throughout the entire network that help in minimizing all related efforts and costs. The main objective of this paper is to develop a model that can accept a specified number of spare-parts within the supply chain, simulating its inventory operations throughout all stages in order to minimize the inventory holding costs, base-stock, safety-stock, and to find the optimum quantity of inventory levels, thereby suggesting a way forward to adapt some factors of Just-In-Time to minimizing the inventory costs throughout the entire supply chain. The model has been developed using Micro- Soft Excel & Visual Basic in order to study inventory allocations in any network of the supply chain. The application and reproducibility of this model were tested by comparing the actual system that was implemented in the case study with the results of the developed model. The findings showed that the total inventory costs of the developed model are about 50% less than the actual costs of the inventory items within the case study.

Keywords: Holding Costs, Inventory, JIT, Modeling, SCM

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Authors: Mohammad Mahdi Paydar, Armin Cheraghalipour, Mostafa Hajiaghaei-Keshteli

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Nowadays, in advanced countries, agriculture as one of the most significant sectors of the economy, plays an important role in its political and economic independence. Due to farmers' lack of information about products' demand and lack of proper planning for harvest time, annually the considerable amount of products is corrupted. Besides, in this paper, we attempt to improve these unfavorable conditions via designing an effective supply chain network that tries to minimize total costs of agricultural products along with minimizing shortage in demand points. To validate the proposed model, a stochastic optimization approach by using a branch and bound solver of the LINGO software is utilized. Furthermore, to accumulate the data of parameters, a case study in Mazandaran province placed in the north of Iran has been applied. Finally, using ɛ-constraint approach, a Pareto front is obtained and one of its Pareto solutions as best solution is selected. Then, related results of this solution are explained. Finally, conclusions and suggestions for the future research are presented.

Keywords: Perishable products, stochastic optimization, agricultural supply chain, ɛ-constraint.

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Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read

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The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data.  This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI.  Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

Keywords: Wireless sensor networks, remote method invocation, transmission time.

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Authors: Hamed Rajabi, Naser Nematbakhsh, Naser Movahediniya

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IP multicasting is a key technology for many existing and emerging applications on the Internet. Furthermore, with increasing popularity of wireless devices and mobile equipment, it is necessary to determine the best way to provide this service in a wireless environment. IETF Mobile IP, that provides mobility for hosts in IP networks, proposes two approaches for mobile multicasting, namely, remote subscription (MIP-RS) and bi-directional tunneling (MIP-BT). In MIP-RS, a mobile host re-subscribes to the multicast groups each time it moves to a new foreign network. MIP-RS suffers from serious packet losses while mobile host handoff occurs. In MIP-BT, mobile hosts send and receive multicast packets by way of their home agents (HAs), using Mobile IP tunnels. Therefore, it suffers from inefficient routing and wastage of system resources. In this paper, we propose a protocol called Mobile Multicast support using Old Foreign Agent (MMOFA) for Mobile Hosts. MMOFA is derived from MIP-RS and with the assistance of Mobile host's Old foreign agent, routes the missing datagrams due to handoff in adjacent network via tunneling. Also, we studied the performance of the proposed protocol by simulation under ns-2.27. The results demonstrate that MMOFA has optimal routing efficiency and low delivery cost, as compared to other approaches.

Keywords: Mobile Multicast, Mobile IP, MMOFA, NS-2. 27.

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Authors: Anilkumar Kothalil Gopalakrishnan

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A subjectively influenced router for vehicles in a fourjunction traffic system is presented. The router is based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy routing procedure. The BPNN detects priorities of vehicles based on the subjective criteria. The subjective criteria and the routing procedure depend on the routing plan towards vehicles depending on the user. The routing procedure selects vehicles from their junctions based on their priorities and route them concurrently to the traffic system. That is, when the router is provided with a desired vehicles selection criteria and routing procedure, it routes vehicles with a reasonable junction clearing time. The cost evaluation of the router determines its efficiency. In the case of a routing conflict, the router will route the vehicles in a consecutive order and quarantine faulty vehicles. The simulations presented indicate that the presented approach is an effective strategy of structuring a subjective vehicle router.

Keywords: Backpropagation Neural Network, Backpropagationalgorithm, Greedy routing procedure, Subjective criteria, Vehiclepriority, Cost evaluation, Route generation

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Authors: Tausif A. Ishtiaque, Zarrin T. Tasin, Kazi S. Akter

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Current trend of urban expansion, especially in the developing countries has caused significant changes in land cover, which is generating great concern due to its widespread environmental degradation. Energy consumption of the cities is also increasing with the aggravated heat island effect. Distribution of land surface temperature (LST) is one of the most significant climatic parameters affected by urban land cover change. Recent increasing trend of LST is causing elevated temperature profile of the built up area with less vegetative cover. Gradual change in land cover, especially decrease in vegetative cover is enhancing the Urban Heat Island (UHI) effect in the developing cities around the world. Increase in the amount of urban vegetation cover can be a useful solution for the reduction of UHI intensity. LST and Normalized Difference Vegetation Index (NDVI) have widely been accepted as reliable indicators of UHI and vegetation abundance respectively. Chittagong, the second largest city of Bangladesh, has been a growth center due to rapid urbanization over the last several decades. This study assesses the intensity of UHI in Chittagong city by analyzing the relationship between LST and NDVI based on the type of land use/land cover (LULC) in the study area applying an integrated approach of Geographic Information System (GIS), remote sensing (RS), and regression analysis. Land cover map is prepared through an interactive supervised classification using remotely sensed data from Landsat ETM+ image along with NDVI differencing using ArcGIS. LST and NDVI values are extracted from the same image. The regression analysis between LST and NDVI indicates that within the study area, UHI is directly correlated with LST while negatively correlated with NDVI. It interprets that surface temperature reduces with increase in vegetation cover along with reduction in UHI intensity. Moreover, there are noticeable differences in the relationship between LST and NDVI based on the type of LULC. In other words, depending on the type of land usage, increase in vegetation cover has a varying impact on the UHI intensity. This analysis will contribute to the formulation of sustainable urban land use planning decisions as well as suggesting suitable actions for mitigation of UHI intensity within the study area.

Keywords: Land cover change, land surface temperature, normalized difference vegetation index, urban heat island.

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Authors: Mehdi Saati, Mohammad Bagheri, Fatemeh Zamanian

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One of the most important parameters to develop and manage urban areas is appropriate selection of land surface to develop green spaces in these areas. In this study, in order to identify the most appropriate sites and areas cultivated for ornamental species in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images due to extract the most important effective climatic and adaphic parameters for growth ornamental species were used. After geometric and atmospheric corrections applied, to enhance accuracy of multi spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D panchromatic band (PAN) was performed. After field sampling to evaluate the correlation between different factors in surface soil sampling location and different bands digital number (DN) of ETM+ sensor on the same points, correlation tables formed using the best computational model and the map of physical and chemical parameters of soil was produced. Then the accuracy of them was investigated by using kappa coefficient. Finally, according to produced maps, the best areas for cultivation of recommended species were introduced.

Keywords: Locate ornamental species, Remote Sensing, Adaphic parameters, ETM+, Jiroft

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Authors: Ivan Živanović, Žužana Vaštag, Senka Popović, Ljiljana Popović, Draginja Peričin

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The present work represents an investigation of the hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein isolate (PuOC PI) by pepsin. To examine the effectiveness and suitability of pepsin towards PuOC PI the kinetic parameters for pepsin on PuOC PI were determined and then, the hydrolysis process was studied using Response Surface Methodology (RSM). The hydrolysis was carried out at temperature of 30°C and pH 3.00. Time and initial enzyme/substrate ratio (E/S) at three levels were selected as the independent parameters. The degree of hydrolysis, DH, was mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3 mA/mg proteins. Since the proposed second-order polynomial model showed good fit with the experimental data (R2 = 0.9822), the obtained mathematical model could be used for monitoring the hydrolysis of PuOC PI by pepsin, under studied experimental conditions, varying the time and initial E/S. To achieve the highest value of DH (39.13 %), the obtained optimum conditions for time and initial E/S were 30 min and 1.024 mA/mg proteins.

Keywords: Enzymatic hydrolysis, Pepsin, Pumpkin (CucurbitaPepo L.) oil cake protein isolate, Response surface methodology.

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Authors: I. Grigoratos, R. Monteiro

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Regions with a significant percentage of non-seismically designed buildings and reduced urban planning are particularly vulnerable to natural hazards. In this context, the project ‘Improved Tools for Disaster Risk Mitigation in Algeria’ (ITERATE) aims at seismic risk mitigation in Algeria. Past earthquakes in North Algeria caused extensive damages, e.g. the El Asnam 1980 moment magnitude (Mw) 7.1 and Boumerdes 2003 Mw 6.8 earthquakes. This paper will address a number of proposed developments and considerations made towards a further improvement of the component of seismic hazard. In specific, an updated earthquake catalog (until year 2018) is compiled, and new conversion equations to moment magnitude are introduced. Furthermore, a network-based method for the estimation of the spatial and temporal distribution of the minimum magnitude of completeness is applied. We found relatively large values for M_c, due to the sparse network, and a nonlinear trend between M_w and body wave (m_b) or local magnitude (M_L), which are the most common scales reported in the region. Lastly, the resulting b-value of the Gutenberg-Richter distribution is sensitive to the declustering method.

Keywords: Conversion equation, magnitude of completeness, seismic events, seismic hazard.

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Authors: B. A. Lawal, A. G. Ojanuga, P. A. Tsado, A. Mohammed

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This work assessed some properties of three pedons on a toposequence in Ijah-Gbagyi district in Niger State, Nigeria. The pedons were designated as JG1, JG2 and JG3 representing the upper, middle and lower slopes respectively. The surface soil was characterized by dark yellowish brown (10YR3/4) color at the JG1 and JG2 and very dark grayish brown (10YR3/2) color at JG3. Sand dominated the mineral fraction and its content in the surface horizon decreased down the slope, whereas silt content increased down the slope due to sorting by geological and pedogenic processes. Although organic carbon (OC), total nitrogen (TN) and available phosphorus (P) were rated high, TN and available P decreased down the slope. High cation exchange capacity (CEC) was an indication that the soils have high potential for plant nutrients retention. The pedons were classified as Typic Haplustepts/ Haplic Cambisols (Eutric), Plinthic Petraquepts/ Petric Plinthosols (Abruptic) and Typic Endoaquepts/ Endogleyic Cambisols (Endoclayic).

Keywords: Ecological region, landscape positions, soil characterization, soil classification.

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Authors: Chiu-Wen Chen, Chih-Feng Chen, Cheng-Di Dong

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Surface sediment samples were collected from the Canon River mouth, Taiwan and analyzed for polycyclic aromatic hydrocarbons (PAHs). Total PAHs concentrations varied from 337 to 1,252 ng/g dry weight, with a mean concentration of 827 ng/g dry weight. The spatial distribution of PAHs reveals that the PAHs concentration is relatively high in the river mouth region, and gradually diminishes toward the harbor region. Diagnostic ratios showed that the possible source of PAHs in the Canon River mouth could be petroleum combustion. The toxic equivalent concentrations (TEQcarc) of PAHs varied from 47 to 112 ng TEQ/g dry weight. Higher total TEQcarc values were found in the river mouth region. As compared with the US Sediment Quality Guidelines (SQGs), the observed levels of PAHs at Canon River mouth were lower than the effects range low (ERL), and would probably not exert adverse biological effects.

Keywords: PAHs, sediment, river mouth, sediment quality guidelines (SQGs), toxic equivalent (TEQcarc)

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Authors: Y. M. Al-Wahaibi, S. N. Al-Bahry, A. E. Elshafie, A. S. Al-Bemani, S. J. Joshi, A. K. Al-Bahri

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Crude oil is a major source of global energy. The major problem is its widespread use and demand resulted is in increasing environmental pollution. One associated pollution problem is ‘oil spills’. Oil spills can be remediated with the use of chemical dispersants, microbial biodegradation and microbial metabolites such as biosurfactants. Four different minimal salt media for biosurfactant production by Bacillus isolated from oil contaminated sites from Oman were screened. These minimal salt media were supplemented with either glucose or sucrose as a carbon source. Among the isolates, W16 and B30 produced the most active biosurfactants. Isolate W16 produced better biosurfactant than the rest, and reduced surface tension (ST) and interfacial tension (IFT) to 25.26mN/m and 2.29mN/m respectively within 48h which are characteristics for removal of oil in contaminated sites. Biosurfactant was produced in bulk and extracted using acid precipitation method. Thin Layer Chromatography (TLC) of acid precipitate biosurfactant revealed two concentrated bands. Further studies of W16 biosurfactant in bioremediation of oil spills are recommended.

Keywords: Oil contamination, remediation, Bacillus spp, biosurfactant, surface tension, interfacial tension.

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is coagulation, which uses alum and poly aluminum chloride (PACL). Therefore, determining the dosage of alum and PACL is the most important factor to be prescribed. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for chemical dose prediction, as used for coagulation, such as alum and PACL, with input data consisting of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of the Bangkhen Water Treatment Plant (BKWTP), under the authority of the Metropolitan Waterworks Authority of Thailand. The data were collected from 1 January 2019 to 31 December 2019 in order to cover the changing seasons of Thailand. The input data of ANN are divided into three groups: training set, test set, and validation set. The coefficient of determination and the mean absolute errors of the alum model are 0.73, 3.18 and the PACL model are 0.59, 3.21, respectively.

Keywords: Soft jar test, jar test, water treatment plant process, artificial neural network.

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Authors: Ali Rafiee, Ahad Salimi, Ali Reza Roosta

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Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.

Keywords: Prostate segmentation, stick filter, neural network, active contour.

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Authors: K.Sedhuraman, S.Himavathi, A.Muthuramalingam

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The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.

Keywords: Sensorless IM drives, rotor speed estimators, artificial neural network, feed- forward architecture, single neuron cascaded architecture.

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Authors: Elnasharty M., El Sharaby A., Nor El-din A.

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The gustatory system allows animals to distinguish varieties of food and affects greatly the consumption of food, hence the health and growth of animals. In the current study, we investigated the histogenesis of vallate papillae (VLP) in the rabbit tongue using light and scanning electron microscopy. Samples were obtained from rabbit embryos at the embryonic days 16-30 (E16-30), and from newborns until maturity; 6 months. At E16, the first primordia of vallate papillae were observed as small pits on the surface epithelium of the tongue-s root. At E18, the caudal part was prominent with loose mesenchymal tissue core; meanwhile the rostral part of the papilla was remained as a thick mass of epithelial cells. At E20-24, the side epithelium formed the primitive annular groove. At E26, the primitive taste buds appeared only at the papillary surface and reached their maturity by E28. The annular groove started to appear at E26 became more defined at E28. The definitive vallate papillae with substantial number of apparently mature taste buds were observed by the end of the second week. We conclude that the vallate papillae develop early and mature during the early postnatal life.

Keywords: Rabbit, vallate papillae, histogenesis, taste buds.

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Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma

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All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.

Keywords: MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.

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Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: ater management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network.

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Authors: M. Moslehpour, S. Khorsandi

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As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: NDP, SEND, CGA, modifier, malicious node.

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Authors: Minsoo Lee, Julee Choi, Sookyung Song

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The increasing interest on processing data created by sensor networks has evolved into approaches to implement sensor networks as databases. The aggregation operator, which calculates a value from a large group of data such as computing averages or sums, etc. is an essential function that needs to be provided when implementing such sensor network databases. This work proposes to add the DURING clause into TinySQL to calculate values during a specific long period and suggests a way to implement the aggregation service in sensor networks by applying materialized view and incremental view maintenance techniques that is used in data warehouses. In sensor networks, data values are passed from child nodes to parent nodes and an aggregation value is computed at the root node. As such root nodes need to be memory efficient and low powered, it becomes a problem to recompute aggregate values from all past and current data. Therefore, applying incremental view maintenance techniques can reduce the memory consumption and support fast computation of aggregate values.

Keywords: Aggregation, Incremental View Maintenance, Materialized view, Sensor Network.

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Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

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Authors: Marianna I. Triantou, Konstantina I. Stathi, Petroula A. Tarantili

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In the present study, the incorporation of graphene into blends of acrylonitrile-butadiene-styrene terpolymer with polypropylene (ABS/PP) was investigated focusing on the improvement of their thermomechanical characteristics and the effect on their rheological behavior. The blends were prepared by melt mixing in a twin-screw extruder and were characterized by measuring the MFI as well as by performing DSC, TGA and mechanical tests. The addition of graphene to ABS/PP blends tends to increase their melt viscosity, due to the confinement of polymer chains motion. Also, graphene causes an increment of the crystallization temperature (Tc), especially in blends with higher PP content, because of the reduction of surface energy of PP nucleation, which is a consequence of the attachment of PP chains to the surface of graphene through the intermolecular CH-π interaction. Moreover, the above nanofiller improves the thermal stability of PP and increases the residue of thermal degradation at all the investigated compositions of blends, due to the thermal isolation effect and the mass transport barrier effect. Regarding the mechanical properties, the addition of graphene improves the elastic modulus, because of its intrinsic mechanical characteristics and its rigidity, and this effect is particularly strong in the case of pure PP.

Keywords: Acrylonitrile-butadiene-styrene terpolymer, blends, graphene, polypropylene.

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Authors: S. Tangjuank, N. Insuk , J. Tontrakoon , V. Udeye

Abstract:

Cashew nut shells were converted into activated carbon powders using KOH activation plus CO2 gasification at 1027 K. The increase both of impregnation ratio and activation time, there was swiftly the development of mesoporous structure with increasing of mesopore volume ratio from 20-28% and 27-45% for activated carbon with ratio of KOH per char equal to 1 and 4, respectively. Activated carbon derived from KOH/char ratio equal to 1 and CO2 gasification time from 20 to 150 minutes were exhibited the BET surface area increasing from 222 to 627 m2.g-1. And those were derived from KOH/char ratio of 4 with activation time from 20 to 150 minutes exhibited high BET surface area from 682 to 1026 m2.g-1. The adsorption of Lead(II) and Cadmium(II) ion was investigated. This adsorbent exhibited excellent adsorption for Lead(II) and Cadmium(II) ion. Maximum adsorption presented at 99.61% at pH 6.5 and 98.87% at optimum conditions. The experimental data was calculated from Freundlich isotherm and Langmuir isotherm model. The maximum capacity of Pb2+ and Cd2+ ions was found to be 28.90 m2.g-1 and 14.29 m2.g-1, respectively.

Keywords: Activated carbon, cashew nut shell, heavy metals, adsorption.

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Authors: Robert Koch, Mario Golling, Gabi Dreo Rodosek

Abstract:

Tracing and locating the geographical location of users (Geolocation) is used extensively in todays Internet. Whenever we, e.g., request a page from google we are - unless there was a specific configuration made - automatically forwarded to the page with the relevant language and amongst others, dependent on our location identified, specific commercials are presented. Especially within the area of Network Security, Geolocation has a significant impact. Because of the way the Internet works, attacks can be executed from almost everywhere. Therefore, for an attribution, knowledge of the origination of an attack - and thus Geolocation - is mandatory in order to be able to trace back an attacker. In addition, Geolocation can also be used very successfully to increase the security of a network during operation (i.e. before an intrusion actually has taken place). Similar to greylisting in emails, Geolocation allows to (i) correlate attacks detected with new connections and (ii) as a consequence to classify traffic a priori as more suspicious (thus particularly allowing to inspect this traffic in more detail). Although numerous techniques for Geolocation are existing, each strategy is subject to certain restrictions. Following the ideas of Endo et al., this publication tries to overcome these shortcomings with a combined solution of different methods to allow improved and optimized Geolocation. Thus, we present our architecture for improved Geolocation, by designing a new algorithm, which combines several Geolocation techniques to increase the accuracy.

Keywords: IP geolocation, prosecution of computer fraud, attack attribution, target-analysis

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.

Keywords: Distributes estimation, sensor networks, adaptive filter, IDLMS.

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Authors: Morteza Talebi, Jianan Wang, Zhihua Qu

Abstract:

The security of power systems against malicious cyberphysical data attacks becomes an important issue. The adversary always attempts to manipulate the information structure of the power system and inject malicious data to deviate state variables while evading the existing detection techniques based on residual test. The solutions proposed in the literature are capable of immunizing the power system against false data injection but they might be too costly and physically not practical in the expansive distribution network. To this end, we define an algebraic condition for trustworthy power system to evade malicious data injection. The proposed protection scheme secures the power system by deterministically reconfiguring the information structure and corresponding residual test. More importantly, it does not require any physical effort in either microgrid or network level. The identification scheme of finding meters being attacked is proposed as well. Eventually, a well-known IEEE 30-bus system is adopted to demonstrate the effectiveness of the proposed schemes.

Keywords: Algebraic Criterion, Malicious Cyber-Physical Data Injection, Protection and Identification, Trustworthy Power System.

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