Research on the Layout of Ground Control Points in Plain area 1:10000 DLG Production Using POS Technique

POS (also been called DGPS/IMU) technique can obtain the Exterior Orientation Elements of aerial photo, so the triangulation and DLG production using POS can save large numbers of ground control points (GCP), and this will improve the produce efficiency of DLG and reduce the cost of collecting GCP. This paper mainly research on POS technique in production of 1:10 000 scale DLG on GCP distribution. We designed 23 kinds of ground control points distribution schemes, using integrated sensor direction method to do the triangulation experiments, based on the results of triangulation, we produce a map with the scale of 1:10 000 and test its accuracy. This paper put forward appropriate GCP distributing schemes by experiments and research above, and made preparations for the application of POS technique on photogrammetry 4D data production.

Advantages of Composite Materials in Aircraft Structures

In the competitive environment of aircraft industries it becomes absolutely necessary to improve the efficiency, performance of the aircrafts to reduce the development and operating costs considerably, in order to capitalize the market. An important contribution to improve the efficiency and performance can be achieved by decreasing the aircraft weight through considerable usage of composite materials in primary aircraft structures. In this study, a type of composite material called Carbon Fiber Reinforced Plastic (CFRP) is explored for the usage is aircraft skin panels. Even though there were plenty of studies and research has been already carried out, here a practical example of an aircraft skin panel is taken and substantiated the benefits of composites material usage over the metallic skin panel. A crown skin panel of a commercial aircraft is designed using both metal and composite materials. Stress analysis has been carried out for both and margin of safety is estimated for the critical load cases. The skin panels are compared for manufacturing, tooling, assembly and cost parameters. Detail step by step comparison between metal and composite constructions are studied and results are tabulated for better understanding.

Dynamic Routing to Multiple Destinations in IP Networks using Hybrid Genetic Algorithm (DRHGA)

In this paper we have proposed a novel dynamic least cost multicast routing protocol using hybrid genetic algorithm for IP networks. Our protocol finds the multicast tree with minimum cost subject to delay, degree, and bandwidth constraints. The proposed protocol has the following features: i. Heuristic local search function has been devised and embedded with normal genetic operation to increase the speed and to get the optimized tree, ii. It is efficient to handle the dynamic situation arises due to either change in the multicast group membership or node / link failure, iii. Two different crossover and mutation probabilities have been used for maintaining the diversity of solution and quick convergence. The simulation results have shown that our proposed protocol generates dynamic multicast tree with lower cost. Results have also shown that the proposed algorithm has better convergence rate, better dynamic request success rate and less execution time than other existing algorithms. Effects of degree and delay constraints have also been analyzed for the multicast tree interns of search success rate.

Measuring Process Component Design on Achieving Managerial Goals

Process-oriented software development is a new software development paradigm in which software design is modeled by a business process which is in turn translated into a process execution language for execution. The building blocks of this paradigm are software units that are composed together to work according to the flow of the business process. This new paradigm still exhibits the characteristic of the applications built with the traditional software component technology. This paper discusses an approach to apply a traditional technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses, and these process components can be reused to design the business processes of other application domains. The decomposition considers five managerial goals, namely cost effectiveness, ease of assembly, customization, reusability, and maintainability. The paper presents how to design or decompose process components from a business process model and measure some technical features of the design that would affect the managerial goals. A comparison between the measurement values from different designs can tell which process component design is more appropriate for the managerial goals that have been set. The proposed approach can be applied in Web Services environment which accommodates process-oriented software development.

Corporate Social Responsibility Practices of the Textile Firms Quoted in Istanbul Stock Exchange

Corporate social responsibility (CSR) can be defined as the management of social, environmental, economical and ethical concepts and firms sensivities to the expectations of the social stakeholders. CSR is seen as an important competitive advantage in the textile sector because this sector has an important impact on the environment and it is labor extensive. Textile sector has a strong advantage when compared with other sectors in Turkey due to its low labor costs and abundancy of raw materials. Turkey was a producer and an exporter of cotton, and an importer of fiber, clothes and dresses until 1950s. After 1950s, Turkey has begun to export fiber, ready-made clothes and become one of the most important textile producers in the world recently. CSR practices of the textile firms that are quoted in Istanbul Stock Exchange and these firms sensivities to their internal and external stakeholders and environment will be presented in this study.

A Novel SVM-Based OOK Detector in Low SNR Infrared Channels

Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

Simulation of Robotic Arm using Genetic Algorithm and AHP

In this paper, we have proposed a low cost optimized solution for the movement of a three-arm manipulator using Genetic Algorithm (GA) and Analytical Hierarchy Process (AHP). A scheme is given for optimizing the movement of robotic arm with the help of Genetic Algorithm so that the minimum energy consumption criteria can be achieved. As compared to Direct Kinematics, Inverse Kinematics evolved two solutions out of which the best-fit solution is selected with the help of Genetic Algorithm and is kept in search space for future use. The Inverse Kinematics, Fitness Value evaluation and Binary Encoding like tasks are simulated and tested. Although, three factors viz. Movement, Friction and Least Settling Time (or Min. Vibration) are used for finding the Fitness Function / Fitness Values, however some more factors can also be considered.

A Goal Programming Approach for Plastic Recycling System in Thailand

Plastic waste is a big issue in Thailand, but the amount of recycled plastic in Thailand is still low due to the high investment and operating cost. Hence, the rest of plastic waste are burnt to destroy or sent to the landfills. In order to be financial viable, an effective reverse logistics infrastructure is required to support the product recovery activities. However, there is a conflict between reducing the cost and raising environmental protection level. The purpose of this study is to build a goal programming (GP) so that it can be used to help analyze the proper planning of the Thailand-s plastic recycling system that involves multiple objectives. This study considers three objectives; reducing total cost, increasing the amount of plastic recovery, and raising the desired plastic materials in recycling process. The results from two priority structures show that it is necessary to raise the total cost budget in order to achieve targets on amount of recycled plastic and desired plastic materials.

Hydrogen Sulphide Removal Using a Novel Biofilter Media

Air emissions from waste treatment plants often consist of a combination of Volatile Organic Compounds (VOCs) and odors. Hydrogen sulfide is one of the major odorous gases present in the waste emissions coming from municipal wastewater treatment facilities. Hydrogen sulfide (H2S) is odorous, highly toxic and flammable. Exposure to lower concentrations can result in eye irritation, a sore throat and cough, shortness of breath, and fluid in the lungs. Biofiltration has become a widely accepted technology for treating air streams containing H2S. When compared with other nonbiological technologies, biofilter is more cost-effective for treating large volumes of air containing low concentrations of biodegradable compounds. Optimization of biofilter media is essential for many reasons such as: providing a higher surface area for biofilm growth, low pressure drop, physical stability, and good moisture retention. In this work, a novel biofilter media is developed and tested at a pumping station of a municipality located in the United Arab Emirates (UAE). The media is found to be very effective (>99%) in removing H2S concentrations that are expected in pumping stations under steady state and shock loading conditions.

ISTER (Immune System - Tumor Efficiency Rate): An Important Key for Planning in Radiotherapic Facilities

The use of the oncologic index ISTER allows for a more effective planning of the radiotherapic facilities in the hospitals. Any change in the radiotherapy treatment, due to unexpected stops, may be adapted by recalculating the doses to the new treatment duration while keeping the optimal prognosis. The results obtained in a simulation model on millions of patients allow the definition of optimal success probability algorithms.

Reducing Power Consumption in Cloud Platforms using an Effective Mechanism

In recent years there has been renewal of interest in the relation between Green IT and Cloud Computing. The growing use of computers in cloud platform has caused marked energy consumption, putting negative pressure on electricity cost of cloud data center. This paper proposes an effective mechanism to reduce energy utilization in cloud computing environments. We present initial work on the integration of resource and power management that aims at reducing power consumption. Our mechanism relies on recalling virtualization services dynamically according to user-s virtualization request and temporarily shutting down the physical machines after finish in order to conserve energy. Given the estimated energy consumption, this proposed effort has the potential to positively impact power consumption. The results from the experiment concluded that energy indeed can be saved by powering off the idling physical machines in cloud platforms.

A Novel, Cost-effective Design to Harness Ocean Energy in the Developing Countries

The world's population continues to grow at a quarter of a million people per day, increasing the consumption of energy. This has made the world to face the problem of energy crisis now days. In response to the energy crisis, the principles of renewable energy gained popularity. There are much advancement made in developing the wind and solar energy farms across the world. These energy farms are not enough to meet the energy requirement of world. This has attracted investors to procure new sources of energy to be substituted. Among these sources, extraction of energy from the waves is considered as best option. The world oceans contain enough energy to meet the requirement of world. Significant advancements in design and technology are being made to make waves as a continuous source of energy. One major hurdle in launching wave energy devices in a developing country like Pakistan is the initial cost. A simple, reliable and cost effective wave energy converter (WEC) is required to meet the nation-s energy need. This paper will present a novel design proposed by team SAS for harnessing wave energy. This paper has three major sections. The first section will give a brief and concise view of ocean wave creation, propagation and the energy carried by them. The second section will explain the designing of SAS-2. A gear chain mechanism is used for transferring the energy from the buoy to a rotary generator. The third section will explain the manufacturing of scaled down model for SAS-2 .Many modifications are made in the trouble shooting stage. The design of SAS-2 is simple and very less maintenance is required. SAS-2 is producing electricity at Clifton. The initial cost of SAS-2 is very low. This has proved SAS- 2 as one of the cost effective and reliable source of harnessing wave energy for developing countries.

Financing - Scheduling Optimization for Construction Projects by using Genetic Algorithms

Investment in a constructed facility represents a cost in the short term that returns benefits only over the long term use of the facility. Thus, the costs occur earlier than the benefits, and the owners of facilities must obtain the capital resources to finance the costs of construction. A project cannot proceed without an adequate financing, and the cost of providing an adequate financing can be quite large. For these reasons, the attention to the project finance is an important aspect of project management. Finance is also a concern to the other organizations involved in a project such as the general contractor and material suppliers. Unless an owner immediately and completely covers the costs incurred by each participant, these organizations face financing problems of their own. At a more general level, the project finance is the only one aspect of the general problem of corporate finance. If numerous projects are considered and financed together, then the net cash flow requirements constitute the corporate financing problem for capital investment. Whether project finance is performed at the project or at the corporate level does not alter the basic financing problem .In this paper, we will first consider facility financing from the owner's perspective, with due consideration for its interaction with other organizations involved in a project. Later, we discuss the problems of construction financing which are crucial to the profitability and solvency of construction contractors. The objective of this paper is to present the steps utilized to determine the best combination of minimum project financing. The proposed model considers financing; schedule and maximum net area .The proposed model is called Project Financing and Schedule Integration using Genetic Algorithms "PFSIGA". This model intended to determine more steps (maximum net area) for any project with a subproject. An illustrative example will demonstrate the feature of this technique. The model verification and testing are put into consideration.

Water Demand Prediction for Touristic Mecca City in Saudi Arabia using Neural Networks

Saudi Arabia is an arid country which depends on costly desalination plants to satisfy the growing residential water demand. Prediction of water demand is usually a challenging task because the forecast model should consider variations in economic progress, climate conditions and population growth. The task is further complicated knowing that Mecca city is visited regularly by large numbers during specific months in the year due to religious occasions. In this paper, a neural networks model is proposed to handle the prediction of the monthly and yearly water demand for Mecca city, Saudi Arabia. The proposed model will be developed based on historic records of water production and estimated visitors- distribution. The driving variables for the model include annuallyvarying variables such as household income, household density, and city population, and monthly-varying variables such as expected number of visitors each month and maximum monthly temperature.

Emergency Health Management and Student Hygiene at a South African University

Risk of infectious disease outbreaks is related to the hygiene among the population. To assess the actual risks and modify the relevant emergency procedures if necessary, a hygiene survey was conducted among undergraduate students on the Rhodes University campus. Soap was available to 10.5% and only 26.8% of the study participants followed proper hygiene in relation to food consumption. This combination increases the risk of infectious disease outbreaks at the campus. Around 83.6% were willing to wash their hands if soap was provided. Procurement and availability of soap in undergraduate residences on campus should be improved, as the total cost is estimated at only 2000 USD per annum. Awareness campaigns about food-related hygiene and the need for regular handwashing with soap should be run among Rhodes University students. If successful, rates of respiratory and hygiene-related diseases will be decreased and emergency health management simplified.

Investigation of Inert Gas Injection in Steam Reforming of Methane: Energy

Synthesis gas manufacturing by steam reforming of hydrocarbons is an important industrial process. High endothermic nature of the process makes it one of the most cost and heat intensive processes. In the present work, composite effect of different inert gases on synthesis gas yield, feed gas conversion and temperature distribution along the reactor length has been studied using a heterogeneous model. Mathematical model was developed as a first stage and validated against the existing process models. With the addition of inert gases, a higher yield of synthesis gas is observed. Simultaneously the rector outlet temperature drops to as low as 810 K. It was found that Xenon gives the highest yield and conversion while Helium gives the lowest temperature. Using Xenon inert gas 20 percent reduction in outlet temperature was observed compared to traditional case.

Characterization of Catalagzi Fly Ash for Heavy Metal Adsorption

Fly ash is a significant waste that is released of thermal power plants and defined as very fine particles that are drifted upward with up taken by the flue gases due to the burning of used coal [1]. The fly-ash is capable of removing organic contaminants in consequence of high carbon content, a large surface area per unit volume and contained heavy metals. Therefore, fly ash is used as an effective coagulant and adsorbent by pelletization [2, 3]. In this study, the possibility of use of fly ash taken from Turkey like low-cost adsorbent for adsorption of zinc ions found in waste water was investigated. The fly ash taken from Turkey was pelletized with bentonite and molass to evaluate the adsorption capaticity. For this purpose; analyses such as sieve analysis, XRD, XRF, FTIR and SEM were performed. As a result, it was seen that pellets prepared from fly ash, bentonite and molass would be used for zinc adsorption.

Study on Ultrasonic Vibration Effects on Grinding Process of Alumina Ceramic (Al2O3)

Nowadays, engineering ceramics have significant applications in different industries such as; automotive, aerospace, electrical, electronics and even martial industries due to their attractive physical and mechanical properties like very high hardness and strength at elevated temperatures, chemical stability, low friction and high wear resistance. However, these interesting properties plus low heat conductivity make their machining processes too hard, costly and time consuming. Many attempts have been made in order to make the grinding process of engineering ceramics easier and many scientists have tried to find proper techniques to economize ceramics' machining processes. This paper proposes a new diamond plunge grinding technique using ultrasonic vibration for grinding Alumina ceramic (Al2O3). For this purpose, a set of laboratory equipments have been designed and simulated using Finite Element Method (FEM) and constructed in order to be used in various measurements. The results obtained have been compared with the conventional plunge grinding process without ultrasonic vibration and indicated that the surface roughness and fracture strength improved and the grinding forces decreased.

Losses Analysis in TEP Considering Uncertainity in Demand by DPSO

This paper presents a mathematical model and a methodology to analyze the losses in transmission expansion planning (TEP) under uncertainty in demand. The methodology is based on discrete particle swarm optimization (DPSO). DPSO is a useful and powerful stochastic evolutionary algorithm to solve the large-scale, discrete and nonlinear optimization problems like TEP. The effectiveness of the proposed idea is tested on an actual transmission network of the Azerbaijan regional electric company, Iran. The simulation results show that considering the losses even for transmission expansion planning of a network with low load growth is caused that operational costs decreases considerably and the network satisfies the requirement of delivering electric power more reliable to load centers.

Social and Economic Effects of Mining Industry Restructuring in Romania -Case Studies

As in other countries from Central and Eastern Europe, the economic restructuring occurred in the last decade of the twentieth century affected the mining industry in Romania, an oversize and heavily subsidized sector before 1989. After more than a decade since the beginning of mining restructuring, an evaluation of current social implications of the process it is required, together with an efficiency analysis of the adaptation mechanisms developed at governmental level. This article aims to provide an insight into these issues through case studies conducted in the most important coal basin of Romania, Petroşani Depression.