The Effect of the Tool Geometry and Cutting Conditions on the Tool Deflection and Cutting Forces

In this paper by measuring the cutting forces the effect of the tool shape and qualifications (sharp and worn cutting tools of both vee and knife edge profile) and cutting conditions (depth of cut and cutting speed) in the turning operation on the tool deflection and cutting force is investigated. The workpiece material was mild steel and the cutting tool was made of high speed steel. Cutting forces were measured by a dynamometer (type P.E.I. serial No 154). The dynamometer essentially consisted of a cantilever structure which held the cutting tool. Deflection of the cantilever was measured by an L.V.D.T (Mercer 122) deflection indicator. No cutting fluid was used during the turning operations. A modern CNC lathe machine (Okuma LH35-N) was used for the tests. It was noted that worn vee profile tools tended to produce a greater increase in the vertical force component than the axial component, whereas knife tools tended to show a more pronounced increase in the axial component.

General Haemodynamics, Aerobic Potential and Strategy for Adaptation of Students to Team Sports

Differentiated impact of team sports (basketball, indoor soccer, handball) on general haemodynamics and aerobic potential of students who specialize in technical subjects is detected only on the fourth year of studies in the institute of higher education. Those who play basketball and indoor soccer have shown increase of stroke and minute volume of blood indices, pumping and contractile function of the heart, oxygenation of blood and oxygen delivery to tissues, aerobic energy supply and balance of sympathetic and parasympathetic activity of the nervous regulation mechanism of the circulatory system. Those who play handball have shown these indices statistically decreased. On the whole playing basketball and indoor soccer optimizes the strategy for adaptation of students to the studying process, but playing handball does the opposite thing. The leading factor for adaptation of students is: those who play basketball have increase of minute blood volume which stipulates velocity of the system blood circulation and well-timed oxygen delivery to tissues; those who play indoor soccer have increase of power and velocity of contractile function of the heart; those who play handball have increase of resistance of thorax to the system blood flow which minimizes contractile function of the heart, blood oxygen saturation and delivery of oxygen to tissues.

Hardware Stream Cipher Based On LFSR and Modular Division Circuit

Proposal for a secure stream cipher based on Linear Feedback Shift Registers (LFSR) is presented here. In this method, shift register structure used for polynomial modular division is combined with LFSR keystream generator to yield a new keystream generator with much higher periodicity. Security is brought into this structure by using the Boolean function to combine state bits of the LFSR keystream generator and taking the output through the Boolean function. This introduces non-linearity and security into the structure in a way similar to the Non-linear filter generator. The security and throughput of the suggested stream cipher is found to be much greater than the known LFSR based structures for the same key length.

Generator Capability Curve Constraint for PSO Based Optimal Power Flow

An optimal power flow (OPF) based on particle swarm optimization (PSO) was developed with more realistic generator security constraint using the capability curve instead of only Pmin/Pmax and Qmin/Qmax. Neural network (NN) was used in designing digital capability curve and the security check algorithm. The algorithm is very simple and flexible especially for representing non linear generation operation limit near steady state stability limit and under excitation operation area. In effort to avoid local optimal power flow solution, the particle swarm optimization was implemented with enough widespread initial population. The objective function used in the optimization process is electric production cost which is dominated by fuel cost. The proposed method was implemented at Java Bali 500 kV power systems contain of 7 generators and 20 buses. The simulation result shows that the combination of generator power output resulted from the proposed method was more economic compared with the result using conventional constraint but operated at more marginal operating point.

Artificial Neural Network with Steepest Descent Backpropagation Training Algorithm for Modeling Inverse Kinematics of Manipulator

Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.

Control of Vibrations in Flexible Smart Structures using Fast Output Sampling Feedback Technique

This paper features the modeling and design of a Fast Output Sampling (FOS) Feedback control technique for the Active Vibration Control (AVC) of a smart flexible aluminium cantilever beam for a Single Input Single Output (SISO) case. Controllers are designed for the beam by bonding patches of piezoelectric layer as sensor / actuator to the master structure at different locations along the length of the beam by retaining the first 2 dominant vibratory modes. The entire structure is modeled in state space form using the concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite Element Method (FEM) and the state space techniques by dividing the structure into 3, 4, 5 finite elements, thus giving rise to three types of systems, viz., system 1 (beam divided into 3 finite elements), system 2 (4 finite elements), system 3 (5 finite elements). The effect of placing the sensor / actuator at various locations along the length of the beam for all the 3 types of systems considered is observed and the conclusions are drawn for the best performance and for the smallest magnitude of the control input required to control the vibrations of the beam. Simulations are performed in MATLAB. The open loop responses, closed loop responses and the tip displacements with and without the controller are obtained and the performance of the proposed smart system is evaluated for vibration control.

Design and Economical Performance of Gray Water Treatment Plant in Rural Region

In India, the quarrel between the budding human populace and the planet-s unchanging supply of freshwater and falling water tables has strained attention the reuse of gray water as an alternative water resource in rural development. This paper present the finest design of laboratory scale gray water treatment plant, which is a combination of natural and physical operations such as primary settling with cascaded water flow, aeration, agitation and filtration, hence called as hybrid treatment process. The economical performance of the plant for treatment of bathrooms, basins and laundries gray water showed in terms of deduction competency of water pollutants such as COD (83%), TDS (70%), TSS (83%), total hardness (50%), oil and grease (97%), anions (46%) and cations (49%). Hence, this technology could be a good alternative to treat gray water in residential rural area.

Fuzzy Join Dependency in Fuzzy Relational Databases

The join dependency provides the basis for obtaining lossless join decomposition in a classical relational schema. The existence of Join dependency shows that that the tables always represent the correct data after being joined. Since the classical relational databases cannot handle imprecise data, they were extended to fuzzy relational databases so that uncertain, ambiguous, imprecise and partially known information can also be stored in databases in a formal way. However like classical databases, the fuzzy relational databases also undergoes decomposition during normalization, the issue of joining the decomposed fuzzy relations remains intact. Our effort in the present paper is to emphasize on this issue. In this paper we define fuzzy join dependency in the framework of type-1 fuzzy relational databases & type-2 fuzzy relational databases using the concept of fuzzy equality which is defined using fuzzy functions. We use the fuzzy equi-join operator for computing the fuzzy equality of two attribute values. We also discuss the dependency preservation property on execution of this fuzzy equi- join and derive the necessary condition for the fuzzy functional dependencies to be preserved on joining the decomposed fuzzy relations. We also derive the conditions for fuzzy join dependency to exist in context of both type-1 and type-2 fuzzy relational databases. We find that unlike the classical relational databases even the existence of a trivial join dependency does not ensure lossless join decomposition in type-2 fuzzy relational databases. Finally we derive the conditions for the fuzzy equality to be non zero and the qualification of an attribute for fuzzy key.

Gasifier System Identification for Biomass Power Plants using Neural Network

The use of renewable energy sources becomes more necessary and interesting. As wider applications of renewable energy devices at domestic, commercial and industrial levels has not only resulted in greater awareness, but also significantly installed capacities. In addition, biomass principally is in the form of woods, which is a form of energy by humans for a long time. Gasification is a process of conversion of solid carbonaceous fuel into combustible gas by partial combustion. Many gasifier models have various operating conditions; the parameters kept in each model are different. This study applied experimental data, which has three inputs, which are; biomass consumption, temperature at combustion zone and ash discharge rate. One output is gas flow rate. For this paper, neural network was used to identify the gasifier system suitable for the experimental data. In the result,neural networkis usable to attain the answer.

Effect of Boric Acid on a-Hydroxy Acids Compounds in Thin Layer Chromatography

In this investigation Salicylic acid, Sulfosalicylic acid and Acetyl salicylic acid were chosen as a sample for thin layer chromatography (TLC) on silica gel plates. Bicarbonate buffer at different pH containing different amounts of boric acid was applied as mobile phase. Specific interaction of these substances with boric acid has effect on Rf in thin layer chromatography. Regular and similar trend was observed in variations of Rf for mentioned compounds in TLC by altering of percentages of boric acid in mobile phase in pH range of 8-10. Also effect of organic solvent, mixture of water/ organic solvent and organic solvent containing boric acid as mobile phase was studied.

Investigation of Artificial Neural Networks Performance to Predict Net Heating Value of Crude Oil by Its Properties

The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.

Annual Power Load Forecasting Using Support Vector Regression Machines: A Study on Guangdong Province of China 1985-2008

Load forecasting has always been the essential part of an efficient power system operation and planning. A novel approach based on support vector machines is proposed in this paper for annual power load forecasting. Different kernel functions are selected to construct a combinatorial algorithm. The performance of the new model is evaluated with a real-world dataset, and compared with two neural networks and some traditional forecasting techniques. The results show that the proposed method exhibits superior performance.

The Intuitionistic Fuzzy Ordered Weighted Averaging-Weighted Average Operator and its Application in Financial Decision Making

We present a new intuitionistic fuzzy aggregation operator called the intuitionistic fuzzy ordered weighted averaging-weighted average (IFOWAWA) operator. The main advantage of the IFOWAWA operator is that it unifies the OWA operator with the WA in the same formulation considering the degree of importance that each concept has in the aggregation. Moreover, it is able to deal with an uncertain environment that can be assessed with intuitionistic fuzzy numbers. We study some of its main properties and we see that it has a lot of particular cases such as the intuitionistic fuzzy weighted average (IFWA) and the intuitionistic fuzzy OWA (IFOWA) operator. Finally, we study the applicability of the new approach on a financial decision making problem concerning the selection of financial strategies.

Comparison between Solar Simulation and Infrared Technique for Thermal Balance Test

The precision of heat flux simulation influences the temperature field and test aberration for TB test and also reflects the test level for spacecraft development. This paper describes TB tests for a small satellite using solar simulator, electric heaters, calrod heaters to evaluate the difference of the three methods. Under the same boundary condition, calrod heaters cases were about 6oC higher than solar simulator cases and electric heaters cases for non-external-heat-flux cases (extreme low temperature cases). While calrod heaters cases and electric heaters cases were 5~7oC and 2~3oC lower than solar simulator cases respectively for high temperature cases. The results show that the solar simulator is better than calrod heaters for its better collimation, non-homogeneity and stability.

Tobephobia: Teachers- Ineptitude to Manage Curriculum Change

In this paper, Tobephobia (TBP) alludes to the fear of failure experienced by teachers to manage curriculum change. TBP is an emerging concept and it extends the boundaries of research in terms of how we view achievement and failure in education. Outcomes-based education (OBE) was introduced fifteen years ago in South African schools without simultaneously upgrading teachers- professional competencies. This exploratory research, therefore examines a simple question: What is the impact of TBP and OBE on teachers? Teacher ineptitude to cope with the OBE curriculum in the classroom is a serious problem affecting large numbers of South African teachers. This exploratory study sought to determine the perceived negative impact of OBE and TBP on teachers. A survey was conducted amongst 311 teachers in Port Elizabeth and Durban, South Africa. The results confirm the very negative impact of TBP and OBE on teachers. This exploratory study authenticates the existence of TBP.

Intelligent Video-Based Monitoring of Freeway Traffic

Freeways are originally designed to provide high mobility to road users. However, the increase in population and vehicle numbers has led to increasing congestions around the world. Daily recurrent congestion substantially reduces the freeway capacity when it is most needed. Building new highways and expanding the existing ones is an expensive solution and impractical in many situations. Intelligent and vision-based techniques can, however, be efficient tools in monitoring highways and increasing the capacity of the existing infrastructures. The crucial step for highway monitoring is vehicle detection. In this paper, we propose one of such techniques. The approach is based on artificial neural networks (ANN) for vehicles detection and counting. The detection process uses the freeway video images and starts by automatically extracting the image background from the successive video frames. Once the background is identified, subsequent frames are used to detect moving objects through image subtraction. The result is segmented using Sobel operator for edge detection. The ANN is, then, used in the detection and counting phase. Applying this technique to the busiest freeway in Riyadh (King Fahd Road) achieved higher than 98% detection accuracy despite the light intensity changes, the occlusion situations, and shadows.

Comparative Study on Production of Fructooligosaccharides by p. Simplicissimum Using Immobilized Cells and Conventional Reactor System

Fructooligosaccharides derived from microbial enzyme especially from fungal sources has been received particular attention due to its beneficial effects as prebiotics and mass production. However, fungal fermentation is always cumbersome due to its broth rheology problem that will eventually affect the production of FOS. This study investigated the efficiency of immobilized cell system using rotating fibrous bed bioreactor (RFBB) in producing fructooligosaccharides (FOS). A comparative picture with respect to conventional stirred tank bioreactor (CSTB) and RFBB has been presented. To demonstrate the effect of agitation intensity and aeration rate, a laboratory-scale bioreactor 2.5 L was operated in three phases (high, medium, low) for 48 hours. Agitation speed has a great influence on P. simplicissimum fermentation for FOS production, where the volumetric FOS productivity using RFBB is increased with almost 4 fold compared to the FOS productivity in CSTB that only 0.319 g/L/h. Rate of FOS production increased up to 1.2 fold when immobilized cells system was employed at aeration rate similar to the freely suspended cells at 2.0 vvm.

Evaluating the Effect of Domestic Price on Rice Production in an African Setting: A Typical Evidence of the Sierra Leone Case

Rice, which is the staple food in Sierra Leone, is consumed on a daily basis. It is the most imperative food crop extensively grown by farmers across all ecologies in the country. Though much attention is now given to rice grain production through the small holder commercialization programme (SHCP), however, no attention has been given in investigating the limitations faced by rice producers. This paper will contribute to attempts to overcome the development challenges caused by food insecurity. The objective of this paper is thus, to analysis the relationship between rice production and the domestic retail price of rice. The study employed a log linear model in which, the quantity of rice produced is the dependent variable, quantity of rice imported, price of imported rice and price of domestic rice as explanatory variables. Findings showed that, locally produced rice is even more expensive than the imported rice per ton, and almost all the inhabitants in the capital city which hosts about 65% of the entire population of the country favor imported rice, as it is free from stones with other impurities. On the other hand, to control price and simultaneously increase rice production, the government should purchase the rice from the farmers and then sell to private retailers.

Effects of Ultrasonic Treatment on Germination of Synthetic Sunflower Seeds

One problem of synthetic sunflower cultivation is an erratic germination of the seeds. To improve the germination, presowing seed treatment with an ultrasound was tested. All treatments were carried out at 40 kHz frequency with the intensities of 40, 60, 80 and 100% of the ultrasonic generator total power (250 W) for the durations of 5, 10, 15 and 20 minutes. Data on seed germination percentage, seed vigor index (SVI), root and shoot lengths of seedlings were collected. The results showed that germination, SVI, root and shoot lengths of ultrasonic treated seedlings were different from the control, depending on intensity of the ultrasound. The effects of ultrasonic treatment were significant on germination, resulting in a maximum increase of 43% at 40 and 60% intensities compared to that of the control seeds. In addition, seedlings of these 2 treatments had higher SVI and longer root and shoot lengths than that of the control seedlings. All treatment durations resulted in higher germination and SVI, longer root and higher shoot lenghts of seedlings than the control. Among the duration treatments, only SVI and seedling root length were significantly different.

A Dynamic Composition of an Adaptive Course

The number of framework conceived for e-learning constantly increase, unfortunately the creators of learning materials and educational institutions engaged in e-formation adopt a “proprietor" approach, where the developed products (courses, activities, exercises, etc.) can be exploited only in the framework where they were conceived, their uses in the other learning environments requires a greedy adaptation in terms of time and effort. Each one proposes courses whose organization, contents, modes of interaction and presentations are unique for all learners, unfortunately the latter are heterogeneous and are not interested by the same information, but only by services or documents adapted to their needs. Currently the new tendency for the framework conceived for e-learning, is the interoperability of learning materials, several standards exist (DCMI (Dublin Core Metadata Initiative)[2], LOM (Learning Objects Meta data)[1], SCORM (Shareable Content Object Reference Model)[6][7][8], ARIADNE (Alliance of Remote Instructional Authoring and Distribution Networks for Europe)[9], CANCORE (Canadian Core Learning Resource Metadata Application Profiles)[3]), they converge all to the idea of learning objects. They are also interested in the adaptation of the learning materials according to the learners- profile. This article proposes an approach for the composition of courses adapted to the various profiles (knowledge, preferences, objectives) of learners, based on two ontologies (domain to teach and educational) and the learning objects.