Search results for: Optimum sensor placement

Authors: Ahmed F. Azmy , Amal E. Saafan, Tamer M. Essam, Magdy A. Amin, Shaban H. Ahmed

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Bacterial strains capable of degradation of malathion from the domestic sewage were isolated by an enrichment culture technique. Three bacterial strains were screened and identified as Acinetobacter baumannii (AFA), Pseudomonas aeruginosa (PS1), and Pseudomonas mendocina (PS2) based on morphological, biochemical identification and 16S rRNA sequence analysis. Acinetobacter baumannii AFA was the most efficient malathion degrading bacterium, so used for further biodegradation study. AFA was able to grow in mineral salt medium (MSM) supplemented with malathion (100 mg/l) as a sole carbon source, and within 14 days, 84% of the initial dose was degraded by the isolate measured by high performance liquid chromatography. Strain AFA could also degrade other organophosphorus compounds including diazinon, chlorpyrifos and fenitrothion. The effect of different culture conditions on the degradation of malathion like inoculum density, other carbon or nitrogen sources, temperature and shaking were examined. Degradation of malathion and bacterial cell growth were accelerated when culture media were supplemented with yeast extract, glucose and citrate. The optimum conditions for malathion degradation by strain AFA were; an inoculum density of 1.5x 10^12CFU/ml at 30°C with shaking. A specific polymerase chain reaction primers were designed manually using multiple sequence alignment of the corresponding carboxylesterase enzymes of Acinetobacter species. Sequencing result of amplified PCR product and phylogenetic analysis showed low degree of homology with the other carboxylesterase enzymes of Acinetobacter strains, so we suggested that this enzyme is a novel esterase enzyme. Isolated bacterial strains may have potential role for use in bioremediation of malathion contaminated.

Keywords: Acinetobacter baumannii, biodegradation, Malathion, organophosphate pesticides.

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Authors: D. Zare, H. Naderi, A. A. Jafari

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Drying characteristics of rough rice (variety of lenjan) with an initial moisture content of 25% dry basis (db) was studied in a hot air dryer assisted by infrared heating. Three arrival air temperatures (30, 40 and 500C) and four infrared radiation intensities (0, 0.2 , 0.4 and 0.6 W/cm2) and three arrival air speeds (0.1, 0.15 and 0.2 m.s-1) were studied. Bending strength of brown rice kernel, percentage of cracked kernels and time of drying were measured and evaluated. The results showed that increasing the drying arrival air temperature and radiation intensity of infrared resulted decrease in drying time. High bending strength and low percentage of cracked kernel was obtained when paddy was dried by hot air assisted infrared dryer. Between this factors and their interactive effect were a significant difference (p<0.01). An intensity level of 0.2 W/cm2 was found to be optimum for radiation drying. Furthermore, in the present study, the application of Artificial Neural Network (ANN) for predicting the moisture content during drying (output parameter for ANN modeling) was investigated. Infrared Radiation intensity, drying air temperature, arrival air speed and drying time were considered as input parameters for the model. An ANN model with two hidden layers with 8 and 14 neurons were selected for studying the influence of transfer functions and training algorithms. The results revealed that a network with the Tansig (hyperbolic tangent sigmoid) transfer function and trainlm (Levenberg-Marquardt) back propagation algorithm made the most accurate predictions for the paddy drying system. Mean square error (MSE) was calculated and found that the random errors were within and acceptable range of ±5% with coefficient of determination (R2) of 99%.

Keywords: Rough rice, Infrared-hot air, Artificial Neural Network

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Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

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Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers’ equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile.

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Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

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Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: Lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS.

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Authors: H. Ferfera-Harrar, N. Aiouaz, N. Dairi

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Superabsorbent polymers received much attention and are used in many fields because of their superior characters to traditional absorbents, e.g., sponge and cotton. So, it is very important but challenging to prepare highly and fast-swelling superabsorbents. A reliable, efficient and low-cost technique for removing heavy metal ions from wastewater is the adsorption using bio-adsorbents obtained from biological materials, such as polysaccharides-based hydrogels superabsorbents. In this study, novel multi-functional superabsorbent composites type semi-interpenetrating polymer networks (Semi-IPNs) were prepared via graft polymerization of acrylamide onto chitosan backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium persulfate and N,N’-methylene bisacrylamide as initiator and crosslinker, respectively. These hydrogels were also partially hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. The formation of the grafted network was evidenced by Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Thermogravimetric Analysis (TGA). The porous structures were observed by Scanning Electron Microscope (SEM). From TGA analysis, it was concluded that the incorporation of the Ge in the CTS-g-PAAm network has marginally affected its thermal stability. The effect of gelatin content on the swelling capacities of these superabsorbent composites was examined in various media (distilled water, saline and pH-solutions). The water absorbency was enhanced by adding Ge in the network, where the optimum value was reached at 2 wt. % of Ge. Their hydrolysis has not only greatly optimized their absorption capacity but also improved the swelling kinetic.These materials have also showed reswelling ability. We believe that these super-absorbing materials would be very effective for the adsorption of harmful metal ions from wastewater.

Keywords: Chitosan, gelatin, superabsorbent, water absorbency.

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Authors: S. Abdi Goudazri, R. Ziaie Moayed, A. Nazeri

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Loose soils normally are of weak bearing capacity due to their structural nature. Being exposed to heavy traffic loads, they would fail in most cases. To tackle the aforementioned issue, geotechnical engineers have come up with different approaches; one of which is making use of geosynthetic-reinforced soil-aggregate systems. As these polymeric reinforcements have highlighted economic and environmentally-friendly features, they have become widespread in practice during the last decades. The present research investigates the efficiency of four different types of these reinforcements in increasing the bearing capacity of two-layered soil sections using a series California Bearing Ratio (CBR) test. The studied sections are comprised of a 10 cm-thick layer of no. 161 Firouzkooh sand (weak subgrade) and a 10 cm-thick layer of compacted aggregate materials (base course) classified as SP and GW according to the United Soil Classification System (USCS), respectively. The aggregate layer was compacted to the relative density (Dr) of 95% at the optimum water content (Wopt) of 6.5%. The applied reinforcements were including two kinds of geocomposites (type A and B), a geotextile, and a geogrid that were embedded at the interface of the lower and the upper layers of the soil-aggregate system. As the standard CBR mold was not appropriate in height for this study, the mold used for soaked CBR tests were utilized. To make a comparison between the results of stress-settlement behavior in the studied specimens, CBR values pertinent to the penetrations of 2.5 mm and 5 mm were considered. The obtained results demonstrated 21% and 24.5% increments in the amount of CBR value in the presence of geocomposite type A and geogrid, respectively. On the other hand, the effect of both geotextile and geocomposite type B on CBR values was generally insignificant in this research.

Keywords: Geosynthetics, geogrid, geotextile, CBR test, increasing bearing capacity.

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: Hybrid electric vehicle, hybrid energy storage, battery state estimation, ate of charge, state of health.

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Authors: A. Rifa’i, Y. Takeshita, M. Komatsu

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After Yogyakarta earthquake in 2006, the main problem that occurred in the first yard of Prambanan Temple is ponding area that occurred after rainfall. Soil characterization needs to be determined by conducting several processes, especially permeability coefficient (k) in both saturated and unsaturated conditions to solve this problem. More accurate and efficient field testing procedure is required to obtain permeability data that present the field condition. One of the field permeability test equipment is Constant Discharge procedure to determine the permeability coefficient. Necessary adjustments of the Constant Discharge procedure are needed to be determined especially the value of geometric factor (F) to improve the corresponding value of permeability coefficient. The value of k will be correlated with the value of volumetric water content (θ) of an unsaturated condition until saturated condition. The principle procedure of Constant Discharge model provides a constant flow in permeameter tube that flows into the ground until the water level in the tube becomes constant. Constant water level in the tube is highly dependent on the tube dimension. Every tube dimension has a shape factor called the geometric factor that affects the result of the test. Geometric factor value is defined as the characteristic of shape and radius of the tube. This research has modified the geometric factor parameters by using empty material tube method so that the geometric factor will change. Saturation level is monitored by using soil moisture sensor. The field test results were compared with the results of laboratory tests to validate the results of the test. Field and laboratory test results of empty tube material method have an average difference of 3.33 x 10^-4 cm/sec. The test results showed that modified geometric factor provides more accurate data. The improved methods of constant discharge procedure provide more relevant results.

Keywords: Constant discharge, geometric factor, permeability coefficient, unsaturated soils.

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Authors: M. Senthil Arumugam, M.V.C. Rao

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This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.

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Authors: Siqing Chen

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Megalopolis is a group of densely populated metropolitan areas that combine to form an urban complex. Since China introduced the economic reforms in late 1970s, the Chinese urban system has experienced unprecedented growth. The process of urbanisation prevailed in the 1980s, and the process of predominantly large city growth appeared to continue through 1990s and 2000s. In this study, the magnitude and pattern of urbanisation in China during 1990s were examined using remotely sensed imagery acquired by TM/ETM+ sensor onboard the Landsat satellites. The development of megalopolis areas in China was also studied based on the GIS analysis of the increases of urban and built-up area from 1990 to 2000. The analysis suggests that in the traditional agricultural zones in China, e.g., Huang-Huai-Hai Plains, Changjiang River Delta, Pearl River Delta and Sichuan Basin, the urban and built-up areas increased by 1.76 million hectares, of which 0.82 million hectares are expansion of urban areas, an increase of 24.78% compared with 1990 at the national scale. The Yellow River Delta, Changjiang River Delta and Pearl River Delta also saw an increase of urban and built-up area by 63.9%, 66.2% and 83.0% respectively. As a result, three major megalopolises were developed in China: the Guangzhou-Shenzhen-Hong Kong- Macau (Pearl River Delta: PRD) megalopolis area, the Shanghai- Nanjing-Hangzhou (Changjiang River Delta: CRD) megalopolis area and the Beijing-Tianjing-Tangshan-Qinhuangdao (Yellow River Delta-Bohai Sea Ring: YRD) megalopolis area. The relationship between the processed of megalopolisation and the inter-provincial population flow was also explored in the context of social-economic and transport infrastructure development in Post-reform China.

Keywords: Megalopolisation, Land use change, Spatial analysis, Post-reform China

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Authors: Amon Tunwannarux, Supanunt Tunwannarux

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This paper presents design features of a rescue robot, named CEO Mission II. Its body is designed to be the track wheel type with double front flippers for climbing over the collapse and the rough terrain. With 125 cm. long, 5-joint mechanical arm installed on the robot body, it is deployed not only for surveillance from the top view but also easier and faster access to the victims to get their vital signs. Two cameras and sensors for searching vital signs are set up at the tip of the multi-joint mechanical arm. The third camera is at the back of the robot for driving control. Hardware and software of the system, which controls and monitors the rescue robot, are explained. The control system is used for controlling the robot locomotion, the 5-joint mechanical arm, and for turning on/off devices. The monitoring system gathers all information from 7 distance sensors, IR temperature sensors, 3 CCD cameras, voice sensor, robot wheels encoders, yawn/pitch/roll angle sensors, laser range finder and 8 spare A/D inputs. All sensors and controlling data are communicated with a remote control station via IEEE 802.11b Wi-Fi. The audio and video data are compressed and sent via another IEEE 802.11g Wi-Fi transmitter for getting real-time response. At remote control station site, the robot locomotion and the mechanical arm are controlled by joystick. Moreover, the user-friendly GUI control program is developed based on the clicking and dragging method to easily control the movement of the arm. Robot traveling map is plotted from computing the information of wheel encoders and the yawn/pitch data. 2D Obstacle map is plotted from data of the laser range finder. The concept and design of this robot can be adapted to suit many other applications. As the Best Technique awardee from Thailand Rescue Robot Championship 2006, all testing results are satisfied.

Keywords: Controlling, monitoring, rescue robot, mechanicalarm.

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: Hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation.

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Authors: Roberto Sabatini, Terry Moore, Chris Hill

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This paper presents a novel Global Navigation Satellite System (GNSS) Avionics Based Integrity Augmentation (ABIA) system architecture suitable for civil and military air platforms, including Unmanned Aircraft Systems (UAS). Taking the move from previous research on high-accuracy Differential GNSS (DGNSS) systems design, integration and experimental flight test activities conducted at the Italian Air Force Flight Test Centre (CSV-RSV), our research focused on the development of a novel approach to the problem of GNSS ABIA for mission- and safety-critical air vehicle applications and for multi-sensor avionics architectures based on GNSS. Detailed mathematical models were developed to describe the main causes of GNSS signal outages and degradation in flight, namely: antenna obscuration, multipath, fading due to adverse geometry and Doppler shift. Adopting these models in association with suitable integrity thresholds and guidance algorithms, the ABIA system is able to generate integrity cautions (predictive flags) and warnings (reactive flags), as well as providing steering information to the pilot and electronic commands to the aircraft/UAS flight control systems. These features allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. In other words, this novel ABIA system addresses all three cornerstones of GNSS integrity augmentation in mission- and safety-critical applications: prediction (caution flags), reaction (warning flags) and correction (alternate flight path computation).

Keywords: Global Navigation Satellite Systems (GNSS), Integrity Augmentation, Unmanned Aircraft Systems, Aircraft Based Augmentation, Avionics Based Integrity Augmentation, Safety-Critical Applications.

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Authors: Ogunduyile O. Oluwgbenga

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Recent advancements in sensor technologies and Wireless Body Area Networks (WBANs) have led to the development of cost-effective healthcare devices which can be used to monitor and analyse a person-s physiological parameters from remote locations. These advancements provides a unique opportunity to overcome current healthcare challenges of low quality service provisioning, lack of easy accessibility to service varieties, high costs of services and increasing population of the elderly experienced globally. This paper reports on a prototype implementation of an architecture that seamlessly integrates Wireless Body Area Network (WBAN) with Web services (WS) to proactively collect physiological data of remote patients to recommend diagnostic services. Technologies based upon WBAN and WS can provide ubiquitous accessibility to a variety of services by allowing distributed healthcare resources to be massively reused to provide cost-effective services without individuals physically moving to the locations of those resources. In addition, these technologies can reduce costs of healthcare services by allowing individuals to access services to support their healthcare. The prototype uses WBAN body sensors implemented on arduino fio platforms to be worn by the patient and an android smart phone as a personal server. The physiological data are collected and uploaded through GPRS/internet to the Medical Health Server (MHS) to be analysed. The prototype monitors the activities, location and physiological parameters such as SpO2 and Heart Rate of the elderly and patients in rehabilitation. Medical practitioners would have real time access to the uploaded information through a web application.

Keywords: Android Smart phone, Arduino Fio, Web application server, Wireless Body Area Networks.

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Authors: Nadia Belu, Laurentiu M. Ionescu, Agnieszka Misztal

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In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: Automotive industry, control plan, FMEA.

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Authors: F. Gholami, M. Torabi Angaji, Z. Gholami

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Fischer-Tropsch synthesis is one of the most important catalytic reactions that convert the synthetic gas to light and heavy hydrocarbons. One of the main issues is selecting the type of reactor. The slurry bubble reactor is suitable choice for Fischer- Tropsch synthesis because of its good qualification to transfer heat and mass, high durability of catalyst, low cost maintenance and repair. The more common catalysts for Fischer-Tropsch synthesis are Iron-based and Cobalt-based catalysts, the advantage of these catalysts on each other depends on which type of hydrocarbons we desire to produce. In this study, Fischer-Tropsch synthesis is modeled with Iron and Cobalt catalysts in a slurry bubble reactor considering mass and momentum balance and the hydrodynamic relations effect on the reactor behavior. Profiles of reactant conversion and reactant concentration in gas and liquid phases were determined as the functions of residence time in the reactor. The effects of temperature, pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid and liquid-solid mass transfer coefficients and kinetic coefficients on the reactant conversion have been studied. With 5% increase of liquid velocity (with Iron catalyst), H2 conversions increase about 6% and CO conversion increase about 4%, With 8% increase of liquid velocity (with Cobalt catalyst), H2 conversions increase about 26% and CO conversion increase about 4%. With 20% increase of gas-liquid mass transfer coefficient (with Iron catalyst), H2 conversions increase about 12% and CO conversion increase about 10% and with Cobalt catalyst H2 conversions increase about 10% and CO conversion increase about 6%. Results show that the process is sensitive to gas-liquid mass transfer coefficient and optimum condition operation occurs in maximum possible liquid velocity. This velocity must be more than minimum fluidization velocity and less than terminal velocity in such a way that avoid catalysts particles from leaving the fluidized bed.

Keywords: Modeling, Fischer-Tropsch Synthesis, Slurry Bubble Column Reactor.

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Authors: Himali N. Balasooriya, Kithsiri B. Dassanayake, Saman Seneweera, Said Ajlouni

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Increase in atmospheric CO₂ concentration [CO₂] and ambient temperature associated with changing climatic conditions will have significant impacts on agriculture crop productivity and quality. Independent effects of the above two environmental variables on the growth, yield and quality of strawberry were well documented. Higher temperatures over the optimum range (20-25ºC) lead to crop failures, while elevated [CO₂] stimulated plant growth and yield but compromised the physical quality of fruits. However, there is very limited understanding of the interaction between these variables on the plant growth, yield and quality. Therefore, this study was designed to investigate the interactive effect of high temperature and elevated [CO₂] on growth, yield and quality of strawberries. Strawberry cultivars ‘Albion’ and ‘San Andreas’ were grown under six different combinations of two temperatures (25 and 30ºC) and three [CO₂] (400, 650 and 950 µmol mol^-1) in controlled-environmental growth chambers. Plant growth measurements such as plant height, canopy area, number of flowers, and fruit yield were measured during phonological development. Photosynthesis and transpiration, the ratio of intercellular to atmospheric [CO₂] (Ci/Ca) were measured to estimate the physiological adjustment to climate stress. The impact of temperature and [CO₂] interaction on growth and yield of strawberry was significant (p < 0.05). Across both cultivars, highest fruit yields were observed at 650 µmol mol^-1 [CO₂], which was particularly clear at 25°C. The fruit yield gradually decreased at 30°C under all the treatment combinations. However, photosynthesis rates were highest at 650 µmol mol^-1 [CO₂] but no increment was found at 900 µmol mol^-1 [CO₂]. Interestingly, Ci/Ca ratio increased with increasing atmospheric [CO₂] which was predominant at high temperature. Similarly, fruit yield was substantially reduced at high [CO₂] under high temperature. Our findings suggest that increased Ci/Ca ratio at high temperature is likely reduces the photosynthesis and thus yield response to elevated [CO₂].

Keywords: Atmospheric [CO2], fruit yield, strawberry, temperature.

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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Authors: Rifah Ediati, Jajang

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The quality of Ribbed Smoked Sheets (RSS) primarily based on color, dryness, and the presence or absence of fungus and bubbles. This quality is strongly influenced by the drying and fumigation process namely smoking process. Smoking that is held in high temperature long time will result scorched dark brown sheets, whereas if the temperature is too low or slow drying rate would resulted in less mature sheets and growth of fungus. Therefore need to find the time and temperature for optimum quality of sheets. Enhance, unmonitored heat and mass transfer during smoking process lead to high losses of energy balance. This research aims to generate simple empirical mathematical model describing the effect of smoking time and temperature to RSS quality of color, water content, fungus and bubbles. The second goal of study was to analyze energy balance during smoking process. Experimental study was conducted by measuring temperature, residence time and quality parameters of 16 sheets sample in smoking rooms. Data for energy consumption balance such as mass of fuel wood, mass of sheets being smoked, construction temperature, ambient temperature and relative humidity were taken directly along the smoking process. It was found that mathematical model correlating smoking temperature and time with color is Color = -169 - 0.184 T4 - 0.193 T3 - 0.160 0.405 T1 + T2 + 0.388 t1 +3.11 t2 + 3.92t3 + 0.215 t4 with R square 50.8% and with moisture is Moisture = -1.40-0.00123 T4 + 0.00032 T3 + 0.00260 T2 - 0.00292 T1 - 0.0105 t1 + 0.0290 t2 + 0.0452 t3 + 0.00061 t4 with R square of 49.9%. Smoking room energy analysis found useful energy was 27.8%. The energy stored in the material construction 7.3%. Lost of energy in conversion of wood combustion, ventilation and others were 16.6%. The energy flowed out through the contact of material construction with the ambient air was found to be the highest contribution to energy losses, it reached 48.3%.

Keywords: RSS quality, temperature, time, smoking room, energy

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Authors: Yousef Swesi, Asia Elmeshergi, Abdelati Elalem, Walid Alfoghy

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This paper involves a study of the heavy metal pollution of the soils around one of cement plants in Libya called Suk-Alkhameas and surrounding urban areas caused by cement kiln dust (CKD) emitted. Samples of soil was collected from sites at four directions around the cement factory at distances 250m, 1000m, and 3000m from the factory and at (0-10)cm deep in the soil. These samples are analyzed for Fe (iii), Zn(ii), and Pb (ii) as major pollutants. These values are compared with soils at 25 Km distances from the factory as a reference or control samples. The results show that the concentration of Fe ions in the surface soil was within the acceptable range of 1000ppm. However, for Zn and Pb ions the concentrations at the east and north sides of the factory were found six fold higher than the benchmark level. This high value was attributed to the wind which blows usually from south to north and from west to east. This work includes an investigation of the adsorption isotherms and adsorption efficiency of CKD as adsorbent of heavy metal ions (Fe (iii), Zn(ii), and Pb(ii)) from the polluted soils of Suk-Alkameas city. The investigation was conducted in batch and fixed bed column flow technique. The adsorption efficiency of the studied heavy metals ions removals onto CKD depends on the pH of the solution. The optimum pH values are found to be in the ranges of 8-10 and decreases at lower pH values. The removal efficiency of these heavy metals ions ranged from 93% for Pb, 94% for Zn, and 98% for Fe ions for 10 g.l^-1 adsorbent concentration. The maximum removal efficiency of these ions was achieved at 50-60 minutes contact times at which equilibrium is reached. Fixed bed column experimental measurements are also made to evaluate CKD as an adsorbent for the heavy metals. Results obtained are with good agreement with Langmuir and Drachsal assumption of multilayer formation on the adsorbent surface.

Keywords: Adsorption, Cement Kiln dust (CKD & CAC), Isotherms, Zn and Pb ions.

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Authors: Edison E. Haro, Akindele G. Odeshi, Jerzy A. Szpunar

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Hybrid bio-composites are developed for use in protective armor through positive hybridization offered by reinforcement of high-density polyethylene (HDPE) with Kevlar short fibers and palm wood micro-fillers. The manufacturing process involved a combination of extrusion and compression molding techniques. The mechanical behavior of Kevlar fiber reinforced HDPE with and without palm wood filler additions are compared. The effect of the weight fraction of the added palm wood micro-fillers is also determined. The Young modulus was found to increase as the weight fraction of organic micro-particles increased. However, the flexural strength decreased with increasing weight fraction of added micro-fillers. The interfacial interactions between the components were investigated using scanning electron microscopy. The influence of the size, random alignment and distribution of the natural micro-particles was evaluated. Ballistic impact and dynamic shock loading tests were performed to determine the optimum proportion of Kevlar short fibers and organic micro-fillers needed to improve impact strength of the HDPE. These results indicate a positive hybridization by deposition of organic micro-fillers on the surface of short Kevlar fibers used in reinforcing the thermoplastic matrix leading to enhancement of the mechanical strength and dynamic impact behavior of these materials. Therefore, these hybrid bio-composites can be promising materials for different applications against high velocity impacts.

Keywords: Hybrid bio-composites, organic nano-fillers, dynamic shocking loading, ballistic impacts, energy absorption.

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Authors: M. A. Wijewardane, S. A. N. C. Sudasinghe, H. K. G. Punchihewa, W. K. D. L. Wickramasinghe, S. A. Philip, M. R. S. U. Kumara

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Visual comfort is one of the major parameters that can be taken to measure the human comfort in any environment. If the provided illuminance level in a working environment does not meet the workers visual comfort, it will lead to eye-strain, fatigue, headache, stress, accidents and finally, poor productivity. However, improvements in lighting do not necessarily mean that the workplace requires more light. Unnecessarily higher illuminance levels will also cause poor visual comfort and health risks. In addition, more power consumption on lighting will also result in higher energy costs. So, during this study, visual comfort and the illuminance requirement for the workers in textile/apparel industry were studied to perform different tasks (i.e. cutting, sewing and knitting) at their workplace. Experimental studies were designed to identify the optimum illuminance requirement depending upon the varied fabric colour and type and finally, energy saving potentials due to controlled illuminance level depending on the workforce requirement were analysed. Visual performance of workers during the sewing operation was studied using the ‘landolt ring experiment’. It was revealed that around 36.3% of the workers would like to work if the illuminance level varies from 601 lux to 850 lux illuminance level and 45.9% of the workers are not happy to work if the illuminance level reduces less than 600 lux and greater than 850 lux. Moreover, more than 65% of the workers who do not satisfy with the existing illuminance levels of the production floors suggested that they have headache, eye diseases, or both diseases due to poor visual comfort. In addition, findings of the energy analysis revealed that the energy-saving potential of 5%, 10%, 24%, 8% and 16% can be anticipated for fabric colours, red, blue, yellow, black and white respectively, when the 800 lux is the prevailing illuminance level for sewing operation.

Keywords: Landolt ring experiment, lighting energy consumption, illuminance, textile and apparel industry, visual comfort.

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Authors: Charles Chikwendu Okpala, Christopher Chukwutoo Ihueze

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As a technique that reduces variation in a product by lessening the sensitivity of the design to sources of variation, rather than by controlling their sources, Taguchi Robust Design entails the designing of ideal goods, by developing a product that has minimal variance in its characteristics and also meets the desired exact performance. This paper examined the concept of the manufacturing approach and its application to brake pad product of an automotive parts manufacturing company. Although the firm claimed that only defects, excess inventory, and over-production were the few wastes that grossly affect their productivity and profitability, a careful study and analysis of their manufacturing processes with the application of Single Minute Exchange of Dies (SMED) tool showed that the waste of waiting is the fourth waste that bedevils the firm. The selection of the Taguchi L9 orthogonal array which is based on the four parameters and the three levels of variation for each parameter revealed that with a range of 2.17, that waiting is the major waste that the company must reduce in order to continue to be viable. Also, to enhance the company’s throughput and profitability, the wastes of over-production, excess inventory, and defects with ranges of 2.01, 1.46, and 0.82, ranking second, third, and fourth respectively must also be reduced to the barest minimum. After proposing -33.84 as the highest optimum Signal-to-Noise ratio to be maintained for the waste of waiting, the paper advocated for the adoption of all the tools and techniques of Lean Production System (LPS), and Continuous Improvement (CI), and concluded by recommending SMED in order to drastically reduce set up time which leads to unnecessary waiting.

Keywords: Taguchi Robust Design, signal to noise ratio, Single Minute Exchange of Dies, lean production system, waste.

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Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

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The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: Building information management, BIM, economic order quantity, fixed order point, BIM 4D, BIM 5D.

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Authors: S. A. Razavi Alavi, M. Torabi Angaji, Z. Gholami

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In the process of polyethylene extrusion polymer material similar to powder or granule is under compression, melting and transmission operation and on base of special form, extrudate has been produced. Twin-screw extruders are applicable in industries because of their high capacity. The powder mixing with chemical additives and melting with thermal and mechanical energy in three zones (feed, compression and metering zone) and because of gear pump and screw's pressure, converting to final product in latest plate. Extruders with twin-screw and short distance between screws are better than other types because of their high capacity and good thermal and mechanical stress. In this paper, process of polyethylene extrusion and various tapes of extruders are studied. It is necessary to have an exact control on process to producing high quality products with safe operation and optimum energy consumption. The granule size is depending on granulator motor speed. Results show at constant feed rate a decrease in granule size was found whit Increase in motor speed. Relationships between HDPE feed rate and speed of granulator motor, main motor and gear pump are calculated following as: x = HDPE feed flow rate, yM = Main motor speed yM = (-3.6076e-3) x^4+ (0.24597) x^3+ (-5.49003) x^2+ (64.22092) x+61.66786 (1) x = HDPE feed flow rate, yG = Gear pump speed yG = (-2.4996e-3) x^4+ (0.18018) x^3+ (-4.22794) x^2+ (48.45536) x+18.78880 (2) x = HDPE feed flow rate, y = Granulator motor speed 10th Degree Polynomial Fit: y = a+bx+cx^2+dx^3... (3) a = 1.2751, b = 282.4655, c = -165.2098, d = 48.3106, e = -8.18715, f = 0.84997 g = -0.056094, h = 0.002358, i = -6.11816e-5 j = 8.919726e-7, k = -5.59050e-9

Keywords: Extrusion, Extruder, Granule, HDPE, Polymer, Twin-Screw extruder.

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Authors: Saeed Asiri

Abstract:

This research is to design and implement a new kind of agitators called differential agitator. The Differential Agitator is an electro- mechanic set consists of two shafts. The first shaft is the bearing axis while the second shaft is the axis of the quartet upper bearing impellers group and the triple lower group which are called as agitating group. The agitating group is located inside a cylindrical container equipped especially to contain square directors for the liquid entrance and square directors called fixing group for the liquid exit. The fixing group is installed containing the agitating group inside any tank whether from upper or lower position. The agitating process occurs through the agitating group bearing causing a lower pressure over the upper group leading to withdrawing the liquid from the square directors of the liquid entering and consequently the liquid moves to the denser place under the quartet upper group. Then, the liquid moves to the so high pressure area under the agitating group causing the liquid to exit from the square directors in the bottom of the container. For improving efficiency, parametric study and shape optimization has been carried out. A numerical analysis, manufacturing and laboratory experiments were conducted to design and implement the differential agitator. Knowing the material prosperities and the loading conditions, the FEM using ANSYS11 was used to get the optimum design of the geometrical parameters of the differential agitator elements while the experimental test was performed to validate the advantages of the differential agitators to give a high agitation performance of lime in the water as an example. In addition, the experimental work has been done to express the internal container shape in the agitation efficiency. The study ended up with conclusions to maximize agitator performance and optimize the geometrical parameters to be used for manufacturing the differential agitator

Keywords: Differential Agitators, Parametric Optimization, Shape Optimization, Agitation, FEM, ANSYS11.

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Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain

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This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.

Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: Artificial Neural Network, Decision Support System, drug abuse, drug addiction, Multilayer Perceptron.

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Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Superstructures like offshore platforms, tall buildings, transition towers, skyscrapers and bridges are normally designed to resist compression, uplift and lateral forces from wind waves, negative skin friction, ship impact and other applied loads. Better understanding and the precise simulation of the response of batter piles under the action of independent uplift loads is a vital topic and an area of active research in the field of geotechnical engineering. This paper investigates the use of finite element code (FEC) to examine the behaviour of model batter piles penetrated in dense sand, subjected to pull-out pressure by means of numerical modelling. The concept of the Winkler Model (beam on elastic foundation) has been used in which the interaction between the pile embedded depth and adjacent soil in the bearing zone is simulated by nonlinear p-y curves. The analysis was conducted on different pile slenderness ratios (lc⁄d) ranging from 7.5, 15.22 and 30 respectively. In addition, the optimum batter angle for a model steel pile penetrated in dense sand has been chosen to be 20° as this is the best angle for this simulation as demonstrated by other researcher published in literature. In this numerical analysis, the soil response is idealized as elasto-plastic and the model piles are described as elastic materials for the purpose of simulation. The results revealed that the applied loads affect the pullout pile capacity as well as the lateral pile response for dense sand together with varying shear strength parameters linked to the pile critical depth. Furthermore, the pile pull-out capacity increases with increasing the pile aspect ratios.

Keywords: Slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), pull-out capacity.

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