Search results for: land resources optimization.

Authors: T. Chaiechi, N. Stoeckl

Abstract:

Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.

Keywords: Cost, biodiversity conservation, Multi-output production systems, Empirical techniques.

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Authors: M. Sadeghzadeh, M. Teshnehlab

Abstract:

Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant colony optimization, Classification, Datamining, Feature selection.

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Authors: Hong-Ren Chen, Fang-Yu Yeh

Abstract:

In the past, there were more researches of recommendation system in applied electronic commerce. However, because all circles promote information technology integrative instruction actively, the quantity of instruction resources website is more and more increasing on the Internet. But there are less website including recommendation service, especially for teachers. This study established an instruction resource recommendation website that analyzed teaching style of teachers, then provided appropriate instruction resources for teachers immediately. We used the questionnaire survey to realize teacher-s suggestions and satisfactions with the instruction resource contents and recommendation results. The study shows: (1)The website used “Transactional Ability Inventory" that realized teacher-s style and provided appropriate instruction resources for teachers in a short time, it reduced the step of data filter. (2)According to the content satisfaction of questionnaire survey, four styles teachers were almost satisfied with the contents of the instruction resources that the website recommended, thus, the conception of developing instruction resources with different teaching style is accepted. (3) According to the recommendation satisfaction of questionnaire survey, four styles teachers were almost satisfied with the recommendation service of the website, thus, the recommendation strategy that provide different results for teachers in different teaching styles is accepted.

Keywords: Instruction resource, recommendation service, teaching style.

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Authors: Yi Xu, Zexiang Li

Abstract:

In inspection and workpiece localization, sampling point data is an important issue. Since the devices for sampling only sample discrete points, not the completely surface, sampling size and location of the points will be taken into consideration. In this paper a method is presented for determining the sampled points size and location for achieving efficient sampling. Firstly, uncertainty analysis of the localization parameters is investigated. A localization uncertainty model is developed to predict the uncertainty of the localization process. Using this model the minimum size of the sampled points is predicted. Secondly, based on the algebra theory an eigenvalue-optimal optimization is proposed. Then a freeform surface is used in the simulation. The proposed optimization is implemented. The simulation result shows its effectivity.

Keywords: eigenvalue-optimal optimization, freeform surface inspection, sampling size and location, sampled points.

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Authors: Ramin Javadzadeh., Zahra Afsahi, MohammadReza Meybodi

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The Artificial immune systems algorithms are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Artificial Immune System Algorithm is introduced for the first time to overcome its problems of artificial immune system. That use of the small size of a local search around the memory antibodies is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the standard artificial immune system algorithms

Keywords: Artificial immune system, Cellular Automata, Cellular learning automata, Cellular learning automata, , Local search, Optimization.

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Authors: Chuan Li, Ming Liang, Qibing Yu

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To improve the dynamics response of the vehicle passive suspension, a two-terminal mass is suggested to connect in parallel with the suspension strut. Three performance criteria, tire grip, ride comfort and suspension deflection, are taken into consideration to optimize the suspension parameters. However, the three criteria are conflicting and non-commensurable. For this reason, the Chebyshev goal programming method is applied to find the best tradeoff among the three objectives. A simulation case is presented to describe the multi-objective optimization procedure. For comparison, the Chebyshev method is also employed to optimize the design of a conventional passive suspension. The effectiveness of the proposed design method has been clearly demonstrated by the result. It is also shown that the suspension with a two-terminal mass in parallel has better performance in terms of the three objectives.

Keywords: Vehicle, passive suspension, two-terminal mass, optimization, Chebyshev goal programming

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Authors: Diana Gómez-Cano, J. C. Ochoa-Botero, Roberto Bernal Correa, Yhan Paul Arias

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To obtain high mechanical performance, the fresh conditions of a mortar are decisive. Measuring the absorption of aggregates used in mortar mixes is a fundamental requirement for proper design of the mixes prior to their placement in construction sites. In this sense, absorption is a determining factor in the design of a mix because it conditions the amount of water, which in turn affects the water/cement ratio and the final porosity of the mortar. Thus, this work focuses on the mechanical behavior of recycled mortars manufactured from moisture correction using the Thermogravimetric Balancing Halogen Light (TBHL) technique in comparison with the traditional ASTM C 128 International Standard method. The advantages of using the TBHL technique are favorable in terms of reduced consumption of resources such as materials, energy and time. The results show that in contrast to the ASTM C 128 method, the TBHL alternative technique allows obtaining a higher precision in the absorption values of recycled aggregates, which is reflected not only in a more efficient process in terms of sustainability in the characterization of construction materials, but also in an effect on the mechanical performance of recycled mortars.

Keywords: Alternative raw materials, halogen light, recycled mortar, resources optimization, water absorption.

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Authors: S. Kavitha, Nirmala P. Ratchagar

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This paper presents the novel deterministic dynamic programming approach for solving optimization problem with quadratic objective function with linear equality and inequality constraints. The proposed method employs backward recursion in which computations proceeds from last stage to first stage in a multi-stage decision problem. A generalized recursive equation which gives the exact solution of an optimization problem is derived in this paper. The method is purely analytical and avoids the usage of initial solution. The feasibility of the proposed method is demonstrated with a practical example. The numerical results show that the proposed method provides global optimum solution with negligible computation time.

Keywords: Backward recursion, Dynamic programming, Multi-stage decision problem, Quadratic objective function.

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Authors: M. Massour El Aoud, M. Franceschi, M. Maher

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The approach proposed here is oriented in the direction of fuzzy system for the analysis and the synthesis of intelligent climate controllers, the simulation of the internal climate of the greenhouse is achieved by a linear model whose coefficients are obtained by identification. The use of fuzzy logic controllers for the regulation of climate variables represents a powerful way to minimize the energy cost. Strategies of reduction and optimization are adopted to facilitate the tuning and to reduce the complexity of the controller.

Keywords: Greenhouse, fuzzy logic, optimization, gradient descent.

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Authors: Janaína F. Guidolini, Jean P. H. B. Ometto, Angélica Giarolla, Peter M. Toledo, Carlos A. Valera

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The water crisis, a major problem of the 21^st century, occurs mainly due to poor management. The central issue that should govern the management is the integration of the various aspects that interfere with the use of water resources and their protection, supported by legal basis. A watershed is a unit of water interacting with the physical, biotic, social, economic and cultural variables. The Brazilian law recognized river basin as the territorial management unit. Based on the diagnosis of the current situation of the water resources of the Rio Grande Basin, a discussion informed in the Brazilian legal basis was made to propose measures to fight or mitigate damages and environmental degradation in the Basin. To manage water resources more efficiently, conserve water and optimize their multiple uses, the integration of acquired scientific knowledge and management is essential. Moreover, it is necessary to monitor compliance with environmental legislation.

Keywords: Conservation of soil and water, river basin, sustainability, water governance.

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Authors: Kehinde K. Agbele, Kehinde Daniel Aruleba, Eniafe F. Ayetiran

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When using Information Retrieval Systems (IRS), users often present search queries made of ad-hoc keywords. It is then up to the IRS to obtain a precise representation of the user’s information need and the context of the information. This paper investigates optimization of IRS to individual information needs in order of relevance. The study addressed development of algorithms that optimize the ranking of documents retrieved from IRS. This study discusses and describes a Document Ranking Optimization (DROPT) algorithm for information retrieval (IR) in an Internet-based or designated databases environment. Conversely, as the volume of information available online and in designated databases is growing continuously, ranking algorithms can play a major role in the context of search results. In this paper, a DROPT technique for documents retrieved from a corpus is developed with respect to document index keywords and the query vectors. This is based on calculating the weight (

Keywords: Internet ranking,

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Authors: Wan-Yu Liu, Jiunn-Cheng Lin, Chun-Cheng Lin

Abstract:

Green Forestation Plan (GFP) was expected to promote the reforestation of plains totaling 60,000 has within the first 8 years. Annual subsidies were budgeted at $120,000 per ha, and $2.4 million for 20 years. In this research we have surveyed landlords- opinions toward the GFP in an attempt to understand landlords- incentives for participating in the GFP and their levels of concern and agreement toward the policy design. Based our analysis of landlords- opinions on the policy design, we expect to derive appropriate complementary measures, establish effective promotional schemes, and raise the policy effectiveness of the GFP. According to the results of this research, there was still a relatively high proportion of population who were not aware of GFP; more than 50% of landlords were neutral or willing to participate given high reforestation subsidies; approximately 30% of landlords were unwilling to participate. In terms of the designs of GFP, more than 50% of respondents were concerned and agreed with the policy design. In terms of the period of this policy, 52.7% of respondents indicated that it should be shortened to 15 years or lower. In terms of the amount of the subsidy, 41.7% of respondents showed that it should be raised to approximately $250,000/ha. In terms of land area restrictions, 88.0% of respondents believed that the minimum should be lowered to 0.4 ha. More than 70% of respondents owned less than 0.4 has of land, and since they do not own enough land to be eligible for the program, more than 80% of landlords wished to lower the minimum requirements of land area. In addition, 59.3% of respondents were reluctant to participate in reforestation because their lands were too small to be eligible; 15.0% of respondents were reluctant because the duration was too long. Responses to the question about “how the policy can be adjusted to provide incentives for landlords- participation" revealed that almost 40% of respondents desired higher subsidies. Some policy suggestions are provided as follows: (1) many landlords are still unaware of the GFP so the government should enhance the promotion of the policy; (2) many landlords are unwilling to participate in GFP mainly because they do not own enough lands to be eligible, hence the government should consider adjusting its requirements for minimum agricultural land area; (3) for subsequent promotions on GFP, the government may consider targeting on the landlords with high income and high level of education; (4) because the subsidy of this policy alone provides limited help to landlords, the government should help the landlords to explore other revenue possibilities from afforestation in addition to the existing subsidies and raise the participation incentives.

Keywords: Green Forestation Plan (GFP), Landlord, Willingness to Participate.

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Authors: Barbara Vojvodikova, Katerina Jupova, Iva Ticha

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Cities in their historical evolution have always adapted their internal structure to the needs of society (for example protective city walls during classicism era lost their defense function, became unnecessary, were demolished and gave space for new features such as roads, museums or parks). Today it is necessary to modify the internal structure of the city in order to minimize the impact of climate changes on the environment of the population. This article discusses the results of the Urban Climate model owned by VITO, which was carried out as part of a project from the European Union's Horizon grant agreement No 730004 Pan-European Urban Climate Services Climate-Fit city. The use of the model was aimed at changes in land use and land cover in cities related to urban heat islands (UHI). The task of the application was to evaluate possible land use change scenarios in connection with city requirements and ideas. Two pilot areas in the Czech Republic were selected. One is Ostrava and the other Hodonín. The paper provides a demonstration of the application of the model for various possible future development scenarios. It contains an assessment of the suitability or inappropriateness of scenarios of future development depending on the temperature increase. Cities that are preparing to reconstruct the public space are interested in eliminating proposals that would lead to an increase in temperature stress as early as in the assignment phase. If they have evaluation on the unsuitability of some type of design, they can limit it into the proposal phases. Therefore, especially in the application of models on Local level - in 1 m spatial resolution, it was necessary to show which type of proposals would create a significant temperature island in its implementation. Such a type of proposal is considered unsuitable. The model shows that the building itself can create a shady place and thus contribute to the reduction of the UHI. If it sensitively approaches the protection of existing greenery, this new construction may not pose a significant problem. More massive interventions leading to the reduction of existing greenery create a new heat island space.

Keywords: Heat islands, land use, urban climate model.

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Authors: R. Santhosh, T. Ravichandran

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This paper evaluates the accrual based scheduling for cloud in single and multi-resource system. Numerous organizations benefit from Cloud computing by hosting their applications. The cloud model provides needed access to computing with potentially unlimited resources. Scheduling is tasks and resources mapping to a certain optimal goal principle. Scheduling, schedules tasks to virtual machines in accordance with adaptable time, in sequence under transaction logic constraints. A good scheduling algorithm improves CPU use, turnaround time, and throughput. In this paper, three realtime cloud services scheduling algorithm for single resources and multiple resources are investigated. Experimental results show Resource matching algorithm performance to be superior for both single and multi-resource scheduling when compared to benefit first scheduling, Migration, Checkpoint algorithms.

Keywords: Cloud computing, Scheduling, Migration, Checkpoint, Resource Matching.

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Authors: M. Pandi, K. Premalatha

Abstract:

The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.

Keywords: Spread out, simplex, multi-minima, fitness function, optimization, search area, monocyte, solution, genomes.

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Authors: A. K. Abdel-Fattah, A. B. El-Tawil, N. A. Harraz

Abstract:

This paper focuses on the operational and strategic planning decisions related to the quayside of container terminals. We introduce an integrated operational research (OR) and system dynamics (SD) approach to solve the Berth Allocation Problem (BAP) and the Quay Crane Assignment Problem (QCAP). A BAP-QCAP optimization modeling approach which considers practical aspects not studied before in the integration of BAP and QCAP is discussed. A conceptual SD model is developed to determine the long-term effect of optimization on the system behavior factors like resource utilization, attractiveness to port, number of incoming vessels to port and port profits. The framework can be used for improving the operational efficiency of container terminals and providing a strategic view after applying optimization.

Keywords: Operational research, system dynamics, container terminal, quayside operational problems, strategic planning decisions.

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Authors: M. Schulze, P. Crespo Del Granado

Abstract:

This paper considers the influence of promotion instruments for renewable energy sources (RES) on a multi-energy modeling framework. In Europe, so called Feed-in Tariffs are successfully used as incentive structures to increase the amount of energy produced by RES. Because of the stochastic nature of large scale integration of distributed generation, many problems have occurred regarding the quality and stability of supply. Hence, a macroscopic model was developed in order to optimize the power supply of the local energy infrastructure, which includes electricity, natural gas, fuel oil and district heating as energy carriers. Unique features of the model are the integration of RES and the adoption of Feed-in Tariffs into one optimization stage. Sensitivity studies are carried out to examine the system behavior under changing profits for the feed-in of RES. With a setup of three energy exchanging regions and a multi-period optimization, the impact of costs and profits are determined.

Keywords: Distributed generation, optimization methods, power system modeling, renewable energy.

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Keywords: Particle swarm optimization, Phillips-Heffron model, power system stability, PSS, TCSC.

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Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, S. S. Rajiv Sushanth

Abstract:

Supply chain consists of all stages involved, directly or indirectly, includes all functions involved in fulfilling a customer demand. In two stage transportation supply chain problem, transportation costs are of a significant proportion of final product costs. It is often crucial for successful decisions making approaches in two stage supply chain to explicit account for non-linear transportation costs. In this paper, deterministic demand and finite supply of products was considered. The optimized distribution level and the routing structure from the manufacturing plants to the distribution centres and to the end customers is determined using developed mathematical model and solved by proposed particle swarm optimization based genetic algorithm. Numerical analysis of the case study is carried out to validate the model.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing

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Authors: F. Djeffal, N. Lakhdar, T. Bendib

Abstract:

The study of the transport coefficients in electronic devices is currently carried out by analytical and empirical models. This study requires several simplifying assumptions, generally necessary to lead to analytical expressions in order to study the different characteristics of the electronic silicon-based devices. Further progress in the development, design and optimization of Silicon-based devices necessarily requires new theory and modeling tools. In our study, we use the PSO (Particle Swarm Optimization) technique as a computational tool to develop analytical approaches in order to study the transport phenomenon of the electron in crystalline silicon as function of temperature and doping concentration. Good agreement between our results and measured data has been found. The optimized analytical models can also be incorporated into the circuits simulators to study Si-based devices without impact on the computational time and data storage.

Keywords: Particle Swarm, electron mobility, Si-based devices, Optimization.

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Authors: A. K. Al-Othman, K. M. EL-Nagger

Abstract:

Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: Security Constrained Economic Dispatch, Direct Search method, optimization.

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Authors: S.P.Gautam, P.S.Bundela, R.K. Jain, V. N. Tripathi

Abstract:

The manufacturing transmission line tower parts has being generated hazardous waste which is required proper disposal of waste for protection of land pollution. Manufacturing Process in the manufacturing of steel angle, plates, pipes, channels are passes through conventional, semi automatic and CNC machines for cutting, marking, punching, drilling, notching, bending operations. All fabricated material Coated with thin layer of Zinc in Galvanizing plant where molten zinc is used for coating. Prior to Galvanizing, chemical like 33% concentrated HCl Acid, ammonium chloride and d-oil being used for pretreatment of iron. The bath of water with sodium dichromate is used for cooling and protection of the galvanized steel. For the heating purpose the furnace oil burners are used. These above process the Zinc dross, Zinc ash, ETP sludge and waste pickled acid generated as hazardous waste. The RPG has made captive secured land fill site, since 1997 since then it was using for disposal of hazardous waste after completion of SLF (Secured land fill) site. The RPG has raised height from ground level then now it is being used for disposal of waste as he designed the SLF after in creasing height of from GL it is functional without leach ate or adverse impacts in the environment.

Keywords: Disposal, Drilling, Fabricated. Hazardous waste, Punching.

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Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

Abstract:

In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller. 

Keywords: The Bouc-Wen hysteresis model, Particle swarm optimization, Prandtl-Ishlinskii model.

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Authors: Saijal K. K., K. Prabhakaran Nair

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This study aims to determine change in optimal locations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multiobjective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization result shows that the inboard flap location at low Ct /σ ratio move farther from the baseline value and at high Ct /σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: Helicopter rotor, Trailing-edge flap, Thrust coefficient to solidity (Ct /σ) ratio, Optimization.

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Authors: L. Basha, E. Gjika

Abstract:

This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.

Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.

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Authors: O. A. Rahmeh, P. Johnson, S. Lehmann

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Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.

Keywords: Complex networks, grid networks, load-balancing, random sampling.

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Authors: S. Divya Gnanarathinam, S. Sundaramurthy

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The tremendous increase in the population of the world creates the immediate need for the energy resources. All the people in the world need the sustainable energy resources which have low costs. Solar energy is appraised as one of the main energy resources in warm countries. The areas in the west of India like Rajasthan, Gujarat, etc. are immensely rich in solar energy resources. This paper deals with the development of dual axis solar tracker using Arduino board. Depending on the astronomical estimates of the sun from the GPS and sensor image processing outcomes, a methodology is proposed to locate the position of the sun to obtain the maximum solar energy. Based on the outcomes, the solar tracking system figures out whether to use image processing outcomes or astronomical estimates to attain the maximum efficiency of the solar panel. Finally, the experimental values obtained from the solar tracker for both the sunny and the rainy days are being tabulated.

Keywords: Dual axis solar tracker, Arduino board, LDR sensors, global positioning system.

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Authors: Jan Ceselsky

Abstract:

Construction and reconstruction of settlements and individual municipalities, environmental management and the creation, deployment of the forces of production and building transport and technical equipment requires a large expenditure of material and human resources. That is why the economic aspects of the majority decision in these planes built in the foreground and are often decisive. Thereby but more serious is that the economic aspects of the settlement, the creation and function remain in their whole, unprocessed, and cannot speak of a set of individual techniques and methods traditional indicators and experiments with new approaches. This is true both at the level of the national economy, and in their own urban designs. Still a few remain identified specific economic shaping patterns of settlement and the less it is possible to speak of their control. Also practical assessing economics of specific solutions are often used non-apt indicators in addition to economics usually identifies with the lowest acquisition cost or high-intensity land use with little regard for functional efficiency and little studied much higher operating and maintenance costs".

Keywords: Investment, municipal engineering, value for money.

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Authors: Kittipob Kondee, Chutima Prommak

Abstract:

In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: Indoor positioning System, Optimization System design, Multi-Floor Building, Wireless Sensor Networks.

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Authors: Tarek M. Mahmoud

Abstract:

Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.

Keywords: Genetic Algorithms, Flow Assignment, Routing, Computer network, Simulated Annealing.

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