Search results for: PBX – Processor to Block Interface part of the Interconnection Network

Authors: Khojesta Kawish, Tetsuya Ando, Sayed Abdul Basir Samimi

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Bagh-e Dasht area is situated in the northern part of Herat, an old city in western Afghanistan located on the Silk Road which has received a strong influence from Persian culture. Initially, the Bagh-e Dasht area was developed for gardens and palaces near Joy-e Injil canal during the Timurid Empire in the 15^th century. It is assumed Bagh-e Dasht became a settlement in the 16^th century during the Safavid Empire. The oldest area is the southern part around the canal bank which is characterized by Dalans, sun-dried brick arcades above which houses are often constructed. Traditional houses in this area are built with domical vault roofs constructed with sun-dried bricks. Bagh-e Dasht is one of the best-preserved settlements of traditional houses in Herat. This study examines the transformation of the Bagh-e Dasht area with a focus on Dalans, where traditional houses with domical vault roofs have been well-preserved until today. The aim of the study is to examine the extent of physical changes to the area as well as changes to houses and the community. This research paper contains original results which have previously not been published in architectural history. The roof types of houses in the area are investigated through examining high resolution satellite images. The boundary of each building and space is determined by both a field survey and aerial photographs of the study area. A comprehensive field survey was then conducted to examine each space and building in the area. In addition, a questionnaire was distributed to the residents of the Dalan houses and interviews were conducted with the Wakil (Chief) of the area, a local historian, residents and traditional builders. The study finds that the oldest part of Bagh-e Dasht area, the south, contains both Dalans and domical vault roof houses. The next oldest part, which is the north, only has domical vault roof houses. The rest of the area only has houses with modernized flat roofs. This observation provides an insight into the process of historical development in the Bagh-e Dasht area.

Keywords: Afghanistan, Bagh-e Dasht, Dalan, Domical vault, Herat, over path house, traditional house.

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Authors: Lewis E. Hibell, Honghai Liu, David J. Brown

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This paper presents the results of enhancing images from a left and right stereo pair in order to increase the resolution of a 3D representation of a scene generated from that same pair. A new neural network structure known as a Self Delaying Dynamic Network (SDN) has been used to perform the enhancement. The advantage of SDNs over existing techniques such as bicubic interpolation is their ability to cope with motion and noise effects. SDNs are used to generate two high resolution images, one based on frames taken from the left view of the subject, and one based on the frames from the right. This new high resolution stereo pair is then processed by a disparity map generator. The disparity map generated is compared to two other disparity maps generated from the same scene. The first is a map generated from an original high resolution stereo pair and the second is a map generated using a stereo pair which has been enhanced using bicubic interpolation. The maps generated using the SDN enhanced pairs match more closely the target maps. The addition of extra noise into the input images is less problematic for the SDN system which is still able to out perform bicubic interpolation.

Keywords: Genetic Evolution, Image Enhancement, Neuron Networks, Stereo Vision

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Authors: S. M. Abbas, M. A. Hannan, S. A. Samad, A. Hussain

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This paper presented a modified efficient inductive powering link based on ASK modulator and proposed efficient class- E power amplifier. The design presents the external part which is located outside the body to transfer power and data to the implanted devices such as implanted Microsystems to stimulate and monitoring the nerves and muscles. The system operated with low band frequency 10MHZ according to industrial- scientific – medical (ISM) band to avoid the tissue heating. For external part, the modulation index is 11.1% and the modulation rate 7.2% with data rate 1 Mbit/s assuming Tbit = 1us. The system has been designed using 0.35-μm fabricated CMOS technology. The mathematical model is given and the design is simulated using OrCAD P Spice 16.2 software tool and for real-time simulation, the electronic workbench MULISIM 11 has been used.

Keywords: Implanted devices, ASK techniques, Class-E power amplifier, Inductive powering and low-frequency ISM band.

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Authors: Fatemeh Amiri, Caro Lucas, Nasser Yazdani

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As the network based technologies become omnipresent, demands to secure networks/systems against threat increase. One of the effective ways to achieve higher security is through the use of intrusion detection systems (IDS), which are a software tool to detect anomalous in the computer or network. In this paper, an IDS has been developed using an improved machine learning based algorithm, Locally Linear Neuro Fuzzy Model (LLNF) for classification whereas this model is originally used for system identification. A key technical challenge in IDS and LLNF learning is the curse of high dimensionality. Therefore a feature selection phase is proposed which is applicable to any IDS. While investigating the use of three feature selection algorithms, in this model, it is shown that adding feature selection phase reduces computational complexity of our model. Feature selection algorithms require the use of a feature goodness measure. The use of both a linear and a non-linear measure - linear correlation coefficient and mutual information- is investigated respectively

Keywords: anomaly Detection, feature selection, Locally Linear Neuro Fuzzy (LLNF), Mutual Information (MI), liner correlation coefficient.

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Authors: Lawrence N. Ngeh, John D. Orbell, Stephen W. Bigger, Kasup Munaweera, Peter Dann

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This research is part of a broad program aimed at advancing the science and technology involved in the rescue and rehabilitation of oiled wildlife. One aspect of this research involves the use of oil-sequestering magnetic particles for the removal of contaminants from plumage – so-called “magnetic cleansing". This treatment offers a number of advantages over conventional detergent-based methods including portability - which offers the possibility of providing a “quick clean" to the animal upon first encounter in the field. This could be particularly advantageous when the contaminant is toxic and/or corrosive and/or where there is a delay in transporting the victim to a treatment centre. The method could also be useful as part of a stabilization protocol when large numbers of affected animals are awaiting treatment. This presentation describes the design, development and testing of a prototype field kit for providing a “quick clean" to contaminated wildlife in the field.

Keywords: Magnetic Particles, Oiled Wildlife, Quick Clean, Wildlife Rehabilitation.

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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: 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: Purnomo Yustianto, Robin Doss

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As a process of developing a service system, the term ‘service engineering’ evolves in scope and definition. To achieve an integrated understanding of the process, a general framework and an ontology are required. This paper extends a previously built service engineering framework by exploring metamodels for the framework artefacts based on a foundational ontology and a metamodel landscape. The first part of this paper presents a correlation map between the proposed framework with the ontology as a form of evaluation for the conceptual coverage of the framework. The mapping also serves to characterize the artefacts to be produced for each activity in the framework. The second part describes potential metamodels to be used, from the metamodel landscape, as alternative formats of the framework artefacts. The results suggest that the framework sufficiently covers the ontological concepts, both from general service context and software service context. The metamodel exploration enriches the suggested artefact format from the original eighteen formats to thirty metamodel alternatives.

Keywords: Artefact, framework, service, metamodel.

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Authors: M. Kaggwa

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Technology or lack of it will play an important role in Africa-s effort to achieve inclusive development. Although a key determinant of competitiveness, new technology can exacerbate exclusion of the majority from the mainstream economic activities. To minimise potential technology exclusion while leveraging its critical role in African-s development, requires insight into technology diffusion process. Using system dynamics approach, a technology diffusion model is presented. The frequency of interaction of people exposed to and those not exposed to technology, and the technology adoption rate - the fraction of people who embrace new technologies once they are exposed, are identified as the broad factors critical to technology diffusion to wider society enabling more people to be part of the economic growth process. Based on simulation results, it is recommends that these two broad factors should form part of national policy aimed at achieving inclusive and sustainable development in Africa.

Keywords: Inclusive Development, System Dynamics, Technology, Technology diffusion.

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Authors: M. Rezvani, M. Ahangari, F. Zaefarian

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In a field experiment, growth parameters of soybean cultivars in different weeding regimes was investigated. The trial was split plot in a randomized complete block design. The four cultivars and two lines of soybean (Glycine max L.) including: Sahar, Hill, Sari, Telar, 032 and 033 in main plot and weeding regime consist of no weeding (control), one weeding (35 days after planting) and two weeding (35+20 days after planting) were randomized in sub plot. The results showed that during the growth season 033 had the highest dry matter in two weeding. In two weeding regime the dry matter decreased. ). In all weeding regimes 033 had the highest CGR (Figs. 3a, 3b and 3c), which cleared this cultivar ability compare to the others. This cultivar by increasing its leaf area could do more photosynthesis, so, have a higher CGR.

Keywords: Crop growth rate, Density, Leaf area index

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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: M.Sushanth Babu, P.Krishna, U.Venu, M.Ranjith

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In this paper, we evaluate the choice of suitable quantization characteristics for both the decoder messages and the received samples in Low Density Parity Check (LDPC) coded systems using M-QAM (Quadrature Amplitude Modulation) schemes. The analysis involves the demapper block that provides initial likelihood values for the decoder, by relating its quantization strategy of the decoder. A mapping strategy refers to the grouping of bits within a codeword, where each m-bit group is used to select a 2m-ary signal in accordance with the signal labels. Further we evaluate the system with mapping strategies like Consecutive-Bit (CB) and Bit-Reliability (BR). A new demapper version, based on approximate expressions, is also presented to yield a low complexity hardware implementation.

Keywords: Low Density parity Check, Mapping, Demapping, Quantization, Quadrature Amplitude Modulation

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Authors: Morten Willatzen, Mikhail Vladimirovich Deryabin

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The governing two-dimensional equations of a heterogeneous material composed of a fluid (allowed to flow in the absence of acoustic excitations) and a crystalline piezoelectric cubic solid stacked one-dimensionally (along the z direction) are derived and special emphasis is given to the discussion of acoustic group velocity for the structure as a function of the wavenumber component perpendicular to the stacking direction (being the x axis). Variations in physical parameters with y are neglected assuming infinite material homogeneity along the y direction and the flow velocity is assumed to be directed along the x direction. In the first part of the paper, the governing set of differential equations are derived as well as the imposed boundary conditions. Solutions are provided using Hamilton-s equations for the wavenumber vs. frequency as a function of the number and thickness of solid layers and fluid layers in cases with and without flow (also the case of a position-dependent flow in the fluid layer is considered). In the first part of the paper, emphasis is given to the small-frequency case. Boundary conditions at the bottom and top parts of the full structure are left unspecified in the general solution but examples are provided for the case where these are subject to rigid-wall conditions (Neumann boundary conditions in the acoustic pressure). In the second part of the paper, emphasis is given to the general case of larger frequencies and wavenumber-frequency bandstructure formation. A wavenumber condition for an arbitrary set of consecutive solid and fluid layers, involving four propagating waves in each solid region, is obtained again using the monodromy matrix method. Case examples are finally discussed.

Keywords: Flow, acoustics, solid-fluid structures, periodicity.

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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: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: Pattern recognition, partitional clustering, K-means clustering, Manhattan distance, terrorism data analysis.

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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: 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: 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: AbdulLateef A. Olanrewaju, Mohd F. Khamidi, Arazi Idrus

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This paper is part of an ongoing research on the development of systemic maintenance management model Malaysian university buildings. In order to achieve this aim, there is a need to develop a performance model against which services are measure. Measuring performance is a significant part of maintenance management service delivery. Maintenance organization needs to know where they are in order to provide user-driven services and to enhance productivity. The aim of this paper is to formulate a template or model for university maintenance organization in Malaysia. The model is based on literature review and survey questionnaire and has been validated. Through grounded theory, this paper developed a 8 points matrix for the university maintenance organizations for measuring and improving their service delivery. The potential of the model is guide and assists towards providing value added service delivery through initiating maintenance according to user value system rather than on the condition of the building.

Keywords: Performance matrix, university buildings, users, maintenance organization

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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: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

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The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: Combinatorial problems, Sequential Pattern Mining, Estimation of Distribution Algorithms, Artificial Chromosomes.

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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: 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

Abstract:

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: Carsten Röcker

Abstract:

This paper provides an introduction into the evolution of information and communication technology and illustrates its usage in the work domain. The paper is sub-divided into two parts. The first part gives an overview over the different phases of information processing in the work domain. It starts by charting the past and present usage of computers in work environments and shows current technological trends, which are likely to influence future business applications. The second part starts by briefly describing, how the usage of computers changed business processes in the past, and presents first Ambient Intelligence applications based on identification and localization information, which are already used in the production and retail sector. Based on current systems and prototype applications, the paper gives an outlook of how Ambient Intelligence technologies could change business processes in the future.

Keywords: Ambient Intelligence, Ubiquitous Computing, Business Applications, Radio Frequency Identification (RFID).

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