Search results for: Efficient resources use

Authors: M. Culman, O. Lengerke

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To provide an efficient solar generation system, the embodiment design of a two axis solar tracker for an array of photovoltaic (PV) panels destiny to supply the power demand on off-the-grid areas was developed. Photovoltaic cells have high costs in relation to t low efficiency; and while a lot of research and investment has been made to increases its efficiency a few points, there is a profitable solution that increases by 30-40% the annual power production: two axis solar trackers. A solar tracker is a device that supports a load in a perpendicular position toward the sun during daylight. Mounted on solar trackers, the solar panels remain perpendicular to the incoming sunlight at day and seasons so the maximum amount of energy is outputted. Through a preview research done it was justified why the generation of solar energy through photovoltaic panels mounted on dual axis structures is an attractive solution to bring electricity to remote off-the-grid areas. The work results are the embodiment design of an azimuth-altitude solar tracker to guide an array of photovoltaic panels based on a specific design methodology. The designed solar tracker is mounted on a pedestal that uses two slewing drives‚ with a nominal torque of 1950 Nm‚ to move a solar array that provides 3720 W from 12 PV panels.

Keywords: Azimuth-altitude sun tracker, dual-axis solar tracker, photovoltaic system, solar energy, stand-alone power system.

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Authors: M.S. Mazăre, A. M. Pană, L. M. Ştefan, M. Silion, M. Bălan, G. Bandur, L. M. Rusnac

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In the last decade, carbohydrates have attracted great attention as renewable resources for the chemical industry. Carbohydrates are abundantly found in nature in the form of monomers, oligomers and polymers, or as components of biopolymers and other naturally occurring substances. As natural products, they play important roles in conferring certain physical, chemical, and biological properties to their carrier molecules.The synthesis of this particular carbohydrate glycomonomer is part of our work to obtain biodegradable polymers. Our current paper describes the synthesis and characterization of a novel carbohydrate glycomonomer starting from D-glucose, in several synthesis steps, that involve the protection/deprotection of the D-glucose ring via acetylation, tritylation, then selective deprotection of the aromaticaliphatic protective group, in order to obtain 1,2,3,4-tetra-O-acetyl- 6-O-allyl-β-D-glucopyranose. The glycomonomer was then obtained by the allylation in drastic conditions of 1,2,3,4-tetra-O-acetyl-6-Oallyl- β-D-glucopyranose with allylic alcohol in the presence of stannic chloride, in methylene chloride, at room temperature. The proposed structure of the glycomonomer, 2,3,4-tri-O-acetyl-1,6-di- O-allyl-β-D-glucopyranose, was confirmed by FTIR, NMR and HPLC-MS spectrometry. This glycomonomer will be further submitted to copolymerization with certain acrylic or methacrylic monomers in order to obtain competitive plastic materials for applications in the biomedical field.

Keywords: allylation, D-glucose, glycomonomer, trityl chloride

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Authors: Julian B. García, Virginie Q. R. Pinto, André P. Assis

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This paper presents numerical flow and slope stability simulations in three typical sections of earth dams built in tropical regions, two homogeneous with different slope inclinations, and the other one heterogeneous with impermeable core. The geotechnical material parameters used in this work were obtained from a lab testing of physical characterization, compaction, consolidation, variable load permeability and saturated triaxial type CD for compacted soil samples with standard proctor energy at optimum moisture content (23%), optimum moisture content + 2% and optimum moisture content +5%. The objective is to analyze the general behavior of earth dams built in rainy regions where optimum moisture is exceeded. The factor of safety is satisfactory for the three sections compacted in all moisture content during the stages of operation and end of construction. On The other hand, the rapid drawdown condition is the critical phase for homogeneus dams configuration, the factor of safety obtained were unsatisfactory. In general, the heterogeneous dam behavior is more efficient due to the fact that the slopes are made up of gravel, which favors the dissipation of pore pressures during the rapid drawdown. For the critical phase, the slopes should have lower inclinations of the upstream and downstream slopes to guarantee stability, although it increases the costs.

Keywords: Earth dams, flow, moisture content, slope stability.

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: Prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy.

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

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Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

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Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: Social networks, community detection, modularity optimization, geographically dispersed communities.

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Authors: Maumita Bhattacharya

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Optimization is often a critical issue for most system design problems. Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, finding optimal solution to complex high dimensional, multimodal problems often require highly computationally expensive function evaluations and hence are practically prohibitive. The Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model presented in our earlier work [14] reduced computation time by controlled use of meta-models to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the meta-model are generated from a single uniform model. Situations like model formation involving variable input dimensions and noisy data certainly can not be covered by this assumption. In this paper we present an enhanced version of DAFHEA that incorporates a multiple-model based learning approach for the SVM approximator. DAFHEA-II (the enhanced version of the DAFHEA framework) also overcomes the high computational expense involved with additional clustering requirements of the original DAFHEA framework. The proposed framework has been tested on several benchmark functions and the empirical results illustrate the advantages of the proposed technique.

Keywords: Evolutionary algorithm, Fitness function, Optimization, Meta-model, Stochastic method.

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Authors: Amira Kheriji Abbes, Faouzi Bouani, Mekki Ksouri

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Model Predictive Control (MPC) is an established control technique in a wide range of process industries. The reason for this success is its ability to handle multivariable systems and systems having input, output or state constraints. Neverthless comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprisers as well as a transformer of organizations and markets. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In this paper, we propose an efficient firmware for the implementation of constrained MPC in the performed STM32 microcontroller using interior point method. Indeed, performances study shows good execution speed and low computational burden. These results encourage to develop predictive control algorithms to be programmed in industrial standard processes. The PID anti windup controller was also implemented in the STM32 in order to make a performance comparison with the MPC. The main features of the proposed constrained MPC framework are illustrated through two examples.

Keywords: Embedded software, microcontroller, constrainedModel Predictive Control, interior point method, PID antiwindup, Keil tool, C/Cµ language.

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Authors: S. A. Che Osmi, W. M. F. Wan Ishak, H. Kim, M. A. Azman, M. A. Ramli

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River is one of important water sources for many activities including industrial and domestic usage such as daily usage, transportation, power supply and recreational activities. However, increasing activities in a river has grown the sources of pollutant enters the water bodies, and degraded the water quality of the river. It becomes a challenge to develop an effective river management to ensure the water sources of the river are well managed and regulated. In Malaysia, several approaches for river management have been implemented such as Integrated River Basin Management (IRBM) program for coordinating the management of resources in a natural environment based on river basin to ensure their sustainability lead by Department of Drainage and Irrigation (DID), Malaysia. Nowadays, Total Maximum Daily Load (TMDL) is one of the best approaches for river management in Malaysia. TMDL implementation is regulated and implemented in the United States. A study on the development of TMDL in Malacca River has been carried out by doing water quality monitoring, the development of water quality model by using Environmental Fluid Dynamic Codes (EFDC), and TMDL implementation plan. The implementation of TMDL will help the stakeholders and regulators to control and improve the water quality of the river. It is one of the good approaches for river management in Malaysia.

Keywords: EFDC, river management, TMDL, water quality modelling.

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Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

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For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: Differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization.

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Authors: Karunakar A K, Manohara Pai M M

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In 3D-wavelet video coding framework temporal filtering is done along the trajectory of motion using Motion Compensated Temporal Filtering (MCTF). Hence computationally efficient motion estimation technique is the need of MCTF. In this paper a predictive technique is proposed in order to reduce the computational complexity of the MCTF framework, by exploiting the high correlation among the frames in a Group Of Picture (GOP). The proposed technique applies coarse and fine searches of any fast block based motion estimation, only to the first pair of frames in a GOP. The generated motion vectors are supplied to the next consecutive frames, even to subsequent temporal levels and only fine search is carried out around those predicted motion vectors. Hence coarse search is skipped for all the motion estimation in a GOP except for the first pair of frames. The technique has been tested for different fast block based motion estimation algorithms over different standard test sequences using MC-EZBC, a state-of-the-art scalable video coder. The simulation result reveals substantial reduction (i.e. 20.75% to 38.24%) in the number of search points during motion estimation, without compromising the quality of the reconstructed video compared to non-predictive techniques. Since the motion vectors of all the pair of frames in a GOP except the first pair will have value ±1 around the motion vectors of the previous pair of frames, the number of bits required for motion vectors is also reduced by 50%.

Keywords: Motion Compensated Temporal Filtering, predictivemotion estimation, lifted wavelet transform, motion vector

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Authors: Saeid Rabiei Majd, Motahareh Alvandi, Mehrad Rabiei

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The rapid economic and technological development of any country depends on access to cheap sources of energy. Competition for access to petroleum resources is always accompanied by numerous environmental risks. These factors have caused more attention to environmental issues and sustainable development in petroleum contracts and activities. Nowadays, a sign of developed countries is adhering to the principles and rules of international environmental law and sustainable development of commercial contracts. China has entered into play through the massive project plan, One Belt, One Road. China is becoming a new emerging power in the world. China's bilateral investment treaties have an impact on environmental rights and sustainable development through regional and international foreign direct investment. The aim of this research is to examine China's key position to promote and improve environmental principles and international law and sustainable development in the energy sector in the world through the initiative, One Belt, One Road. Based on this hypothesis, it seems that in the near future, China's investment bilateral investment treaties will become popular investment model used in global trade, especially in the field of energy and sustainable development. They will replace the European and American models. The research method is including literature review, analytical and descriptive methods.

Keywords: Principles of sustainable development, oil and gas law, Chinas BITs, one belt one road, environmental rights.

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Authors: F. Rashno Seydari, M. Nikafrooz

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This paper intends to study needs analysis of hearing-impaired students’ teachers in elementary schools all over Iran. The subjects of this study were 275 teachers who were teaching hearing-impaired students in elementary schools. The participants were selected by a quota sampling method. To collect the data, questionnaires of training needs consisting of 41 knowledge items and 31 performance items were used. The collected data were analyzed by using SPSS software in the form of descriptive analyses (frequency and mean) and inferential analyses (one sample t-test, paired t-test, independent t-test, and Pearson correlation coefficient). The findings of the study indicated that teachers generally have considerable needs in knowledge and performance domains. In 32 items out of the total 41 knowledge domain items and in the 27 items out of the total 31 performance domain items, the teachers had considerable needs. From the quantitative point of view, the needs of the performance domain were more than those of the knowledge domain, so they have to be considered as the first priority in training these teachers. There was no difference between the level of the needs of male and female teachers. There was a significant difference between the knowledge and performance domain needs and the teachers’ teaching experience, 0.354 and 0.322 respectively. The teachers who had been trained in working with hearing-impaired students expressed more training needs (both knowledge and performance).

Keywords: Needs analysis, hearing impaired students, hearing impaired students’ teachers, knowledge domain, performance domain.

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Authors: Bahman Ramezani Gourabi

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Drought is one of the most important natural disasters which is probable to occur in all regions with completely different climates and in addition to causing death. It results in many economic losses and social consequences. For this reason. Studying the effects and losses caused by drought which include limitation or shortage of agricultural and drinking water resources. Decreased rainfall and increased evapotranspiration. Limited plant growth and decreased agricultural products. Especially those of dry-farming. Lower levels of surface and ground waters and increased immigrations. Etc. in the country is statistical period (1988-2007) for six stations in Roudbar town were used for statistical analysis and calculating humid and dry years. The dependable rainfall index (DRI) was the main method used in this research. Results showed that during the said statistical period and also during the years 1996-1998 and 2007. more than half of the stations had faced drought. With consideration of the conducted studies. Drawing diagrams and comparing the available data with those of dry and humid years it was found that drought affected agricultural products (e.g.olive) in a way that during the year 1996 1996 drought. Olive groves of Roudbar suffered the greatest damages. Whereupon about 70% of the crops were lost.

Keywords: Dependable rainfall, drought, annual rainfall, roudbar, olive, gilan.

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Authors: Saud A. Taj

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Employer branding is considered as a useful tool for addressing the global-local problem facing complex organisations that have operations scattered across the globe and face challenges of dealing with the local environment alongside. Despite being an established field of study within the Western developed world, there is little empirical evidence concerning the relevance of employer branding to global companies that operate in the under-developed economies. This paper fills this gap by gaining rich insight into the implementation of employer branding programs in a foreign multinational operating in Pakistan dealing with the global-local problem. The study is qualitative in nature and employs semistructured and focus group interviews with senior/middle managers and local frontline employees to deeply examine the phenomenon in case organisation. Findings suggest that authenticity is required in employer brands to enable them to respond to the local needs thereby leading to the resolution of the global-local problem. However, the role of signaling theory is key to the development of authentic employer brands as it stresses on the need to establish an efficient and effective signaling environment where in signals travel in both directions (from signal designers to receivers and backwards) and facilitate firms with the global-local problem. The paper also identifies future avenues of research for the employer branding field.

Keywords: Authenticity, Counter-signals, Employer Branding, Global-Local Problem, Signaling Theory.

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Authors: M.H.Ghaffari

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A theoretical study is conducted to design and explore the effect of different parameters such as heat loads, the tube size of piping system, wick thickness, porosity and hole size on the performance and capability of a Loop Heat Pipe(LHP). This paper presents a steady state model that describes the different phenomena inside a LHP. Loop Heat Pipes(LHPs) are two-phase heat transfer devices with capillary pumping of a working fluid. By their original design comparing with heat pipes and special properties of the capillary structure, they-re capable of transferring heat efficiency for distances up to several meters at any orientation in the gravity field, or to several meters in a horizontal position. This theoretical model is described by different relations to satisfy important limits such as capillary and nucleate boiling. An algorithm is developed to predict the size of the LHP satisfying the limitations mentioned above for a wide range of applied loads. Finally, to assess and evaluate the algorithm and all the relations considered, we have used to design a new kind of LHP to recover the heat from the exhaust of an actual Gas Turbine. By finding the results, it showed that we can use the LHP as a very high efficient device to recover the heat even in high amount of loads(exhaust of a gas turbine). The sizes of all parts of the LHP were obtained using the developed algorithm.

Keywords: Loop Heat Pipe, Head Load, Liquid-Vapor Interface, Heat Transfer, Design Algorithm

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Authors: Muhammad Rehan Khalid, Ahmed Farhan Hanif, Adnan Ahmed Khan

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This paper investigates the performance of Multiple- Input Multiple-Output (MIMO) feedback system combined with Orthogonal Frequency Division Multiplexing (OFDM). Two types of codebook based channel feedback techniques are used in this work. The first feedback technique uses a combination of both the long-term and short-term channel state information (CSI) at the transmitter, whereas the second technique uses only the short term CSI. The long-term and short-term CSI at the transmitter is used for efficient channel utilization. OFDM is a powerful technique employed in communication systems suffering from frequency selectivity. Combined with multiple antennas at the transmitter and receiver, OFDM proves to be robust against delay spread. Moreover, it leads to significant data rates with improved bit error performance over links having only a single antenna at both the transmitter and receiver. The effectiveness of these techniques has been demonstrated through the simulation of a MIMO-OFDM feedback system. The results have been evaluated for 4x4 MIMO channels. Simulation results indicate the benefits of the MIMO-OFDM channel feedback system over the one without incorporating OFDM. Performance gain of about 3 dB is observed for MIMO-OFDM feedback system as compared to the one without employing OFDM. Hence MIMO-OFDM becomes an attractive approach for future high speed wireless communication systems.

Keywords: MIMO systems, OFDM, Codebooks, Channel Feedback

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Authors: Zeitoun D. G., Thierry Dana-Picard

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The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.

Keywords: Function singularities, mesh generation, point allocation, visualization, collocation least squares method, Augmented Lagrangian method, Uzawa's Algorithm, Preconditioned Conjugate Gradien

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Authors: Umar Ubandawaki

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Political participation involves voluntary and deliberate efforts by the members of a political system to determine the kinds of political institution and individuals that will govern them and equally influence the mobilization and allocation of the available societal resources. Over the years, youths in Nigeria participate actively in political party rallies and voting to elect their leaders and representatives in governance. This paper examines categories and nature of participation in politics as well as factors that drive youths into politics in Sokoto State. A survey conducted, through focus group discussions, interviews and questionnaire, in the six sampled Local Government of Sokoto State identifies three category of political participation; namely, active, moderate and apathetic participation. The findings reveal that 63.57% of respondents are apathetic to politics in the State and unemployed youth constitutes 34.74% of the entire responses. The paper establishes that lack of attainment of need (63.22%) is one of the reasons that make youths engage into participatory activities that encourage political thuggery and manipulation of electoral outcomes. The paper recommends that youths should be engaged into positive rational participatory activities that ensure inclusiveness and promotion of good governance in Nigeria. It is hoped that this will enlighten youths and policy implementers on the constructive strategies in controlling youths’ negative participation in politics in Nigeria.

Keywords: Democracy, Governance, Inclusiveness, Participation and Politics.

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Authors: Ali Sarosh, Dong Yun-Feng, Muhammad Umer

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Fully reusable spaceplanes do not exist as yet. This implies that design-qualification for optimized highly-integrated forebody-inlet configuration of booster-stage vehicle cannot be based on archival data of other spaceplanes. Therefore, this paper proposes a novel TIPSO-SVM expert system methodology. A non-trivial problem related to optimization and classification of hypersonic forebody-inlet configuration in conjunction with mass-model of the two-stage-to-orbit (TSTO) vehicle is solved. The hybrid-heuristic machine learning methodology is based on two-step improved particle swarm optimizer (TIPSO) algorithm and two-step support vector machine (SVM) data classification method. The efficacy of method is tested by first evolving an optimal configuration for hypersonic compression system using TIPSO algorithm; thereafter, classifying the results using two-step SVM method. In the first step extensive but non-classified mass-model training data for multiple optimized configurations is segregated and pre-classified for learning of SVM algorithm. In second step the TIPSO optimized mass-model data is classified using the SVM classification. Results showed remarkable improvement in configuration and mass-model along with sizing parameters.

Keywords: TIPSO-SVM expert system, TIPSO algorithm, two-step SVM method, aerothermodynamics, mass-modeling, TSTO vehicle.

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Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: Data grid, data replication, simulation, replica selection, replica placement.

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Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

Abstract:

Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: Combustion Duration, crank angle, mass fraction burnt, producer gas, wiebe combustion model, wide open throttle.

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Authors: H. Chaker, T. Slama, N. Elyétim

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This paper analyzes the effects of gender, affiliation, prior work experience, social work, and vicarious learning through family role models on entrepreneurial skills development by students when they followed the teaching through the entrepreneurship method in Tunisia. We suggest that these variables enhance the development of students’ entrepreneurial skills when combined with teaching through entrepreneurship. The article assesses the impact of these combinations by comparing their effects on the development of thirteen students’ entrepreneurial competencies, namely entrepreneurial mindset, core self-evaluation, entrepreneurial attitude, entrepreneurial knowledge, creativity, financial literacy, managing ambiguity, marshaling of resources, planning, teaching methods, entrepreneurial teachers, innovative employee, and entrepreneurial intention. We use a two-sample independent t-test to make the comparison, and the results indicate that, when combined with teaching through the entrepreneurship method, students with prior work experience developed better six entrepreneurial skills; students with social work developed better three entrepreneurial skills, men developed better four entrepreneurial skills than women. However, all students developed their entrepreneurial skills through this practical method regardless of their affiliation and their vicarious learning through family role models.

Keywords: Affiliation, entrepreneurial skills, gender, role models, social work, teaching through entrepreneurship, vicarious learning, work experience.

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Authors: A. Sharma, R. Tewari, S. K. Soni

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Biofuels production has come forth as a future technology to combat the problem of depleting fossil fuels. Bio-based ethanol production from enzymatic lignocellulosic biomass degradation serves an efficient method and catching the eye of scientific community. High cost of the enzyme is the major obstacle in preventing the commercialization of this process. Thus main objective of the present study was to optimize composition of medium components for enhancing cellulase production by newly isolated strain of Bacillus tequilensis. Nineteen factors were taken into account using statistical Plackett-Burman Design. The significant variables influencing the cellulose production were further employed in statistical Response Surface Methodology using Central Composite Design for maximizing cellulase production. The optimum medium composition for cellulase production was: peptone (4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L), Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride (0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at 37oC. Analysis of variance (ANOVA) revealed high coefficient of determination (R2) of 0.99. Maximum cellulase productivity of 11.5 IU/ml was observed against the model predicted value of 13 IU/ml. This was found to be optimally active at 60oC and pH 5.5.

Keywords: Bacillus tequilensis, CMCase, Submerged Fermentation, Optimization, Plackett-Burman Design, Response Surface Methodology.

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Authors: Chiang Tzu-Chiang, Chang Jia-Lin, Tsai Yue-Fu, Li Sha-Pai

Abstract:

With the advantage of wireless network technology, there are a variety of mobile applications which make the issue of wireless sensor networks as a popular research area in recent years. As the wireless sensor network nodes move arbitrarily with the topology fast change feature, mobile nodes are often confronted with the void issue which will initiate packet losing, retransmitting, rerouting, additional transmission cost and power consumption. When transmitting packets, we would not predict void problem occurring in advance. Thus, how to improve geographic routing with void avoidance in wireless networks becomes an important issue. In this paper, we proposed a greedy geographical void routing algorithm to solve the void problem for wireless sensor networks. We use the information of source node and void area to draw two tangents to form a fan range of the existence void which can announce voidavoiding message. Then we use source and destination nodes to draw a line with an angle of the fan range to select the next forwarding neighbor node for routing. In a dynamic wireless sensor network environment, the proposed greedy void avoiding algorithm can be more time-saving and more efficient to forward packets, and improve current geographical void problem of wireless sensor networks.

Keywords: Wireless sensor network, internet routing, wireless network, greedy void avoiding algorithm, bypassing void.

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Authors: A. Sindhuja, V. Sadasivam

Abstract:

Breast Cancer is the most common malignancy in women and the second leading cause of death for women all over the world. Earlier the detection of cancer, better the treatment. The diagnosis and treatment of the cancer rely on segmentation of Sonoelastographic images. Texture features has not considered for Sonoelastographic segmentation. Sonoelastographic images of 15 patients containing both benign and malignant tumorsare considered for experimentation.The images are enhanced to remove noise in order to improve contrast and emphasize tumor boundary. It is then decomposed into sub-bands using single level Daubechies wavelets varying from single co-efficient to six coefficients. The Grey Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) features are extracted and then selected by ranking it using Sequential Floating Forward Selection (SFFS) technique from each sub-band. The resultant images undergo K-Means clustering and then few post-processing steps to remove the false spots. The tumor boundary is detected from the segmented image. It is proposed that Local Binary Pattern (LBP) from the vertical coefficients of Daubechies wavelet with two coefficients is best suited for segmentation of Sonoelastographic breast images among the wavelet members using one to six coefficients for decomposition. The results are also quantified with the help of an expert radiologist. The proposed work can be used for further diagnostic process to decide if the segmented tumor is benign or malignant.

Keywords: Breast Cancer, Segmentation, Sonoelastography, Tumor Detection.

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

Abstract:

Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: Beam structures, layerwise, optimization, variable angle tow, neural network

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Authors: M. Farahnakian, M.R. Razfar, S. Elhami-Joosheghan

Abstract:

This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.

Keywords: cutting parameters, face milling, surface roughness, artificial neural network, Electromagnetism-like algorithm,

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.

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Authors: Suzan M. Shahin, Mohammed A. Salem

Abstract:

Essential oils are expensive phytochemicals produced and extracted from specific species belonging to particular families in the plant kingdom. In the United Arab Emirates country (UAE), is located in the arid region of the world, nine species, from the Lamiaceae family, having the capability to produce therapeutic grade essential oils. These species include; Mentha spicata, Ocimum forskolei, Salvia macrosiphon, Salvia aegyptiaca, Salvia macilenta, Salvia spinosa, Teucrium polium, Teucrium stocksianum and Zataria multiflora. Although, such potential species are indigenous to the UAE, however, there are almost no studies available to investigate the chemical composition and the quality of the extracted essential oils under the UAE climatological conditions. Therefore, great attention has to be given to such valuable natural resources, through conducting highly supported research projects, tailored to the UAE conditions, and investigating different extraction techniques, including the application of the latest available technologies, such as superficial fluid CO2. This is crucially needed; in order to accomplish the greatest possibilities in the medicinal field, specifically in the discovery of new therapeutic chemotypes, as well as, to achieve the sustainability of this natural resource in the country.

Keywords: Essential oils, extraction techniques, Lamiaceae, traditional medicine, United Arab Emirates (UAE).

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