Towards Design of Context-Aware Sensor Grid Framework for Agriculture

This paper is to present context-aware sensor grid framework for agriculture and its design challenges. Use of sensor networks in the domain of agriculture is not new. However, due to the unavailability of any common framework, solutions that are developed in this domain are location, environment and problem dependent. Keeping the need of common framework for agriculture, Context-Aware Sensor Grid Framework is proposed. It will be helpful in developing solutions for majority of the problems related to irrigation, pesticides spray, use of fertilizers, regular monitoring of plot and yield etc. due to the capability of adjusting according to location and environment. The proposed framework is composed of three layer architecture including context-aware application layer, grid middleware layer and sensor network layer.

Processing the Medical Sensors Signals Using Fuzzy Inference System

Sensors possess several properties of physical measures. Whether devices that convert a sensed signal into an electrical signal, chemical sensors and biosensors, thus all these sensors can be considered as an interface between the physical and electrical equipment. The problem is the analysis of the multitudes of saved settings as input variables. However, they do not all have the same level of influence on the outputs. In order to identify the most sensitive parameters, those that can guide users in gathering information on the ground and in the process of model calibration and sensitivity analysis for the effect of each change made. Mathematical models used for processing become very complex. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available signals information from sensors. Moreover, the system allows the study of the influence of the various factors that take part in the decision system. Since its inception fuzzy set theory has been regarded as a formalism suitable to deal with the imprecision intrinsic to many problems. At the same time, fuzzy sets allow to use symbolic models. In this study an example was applied for resolving variety of physiological parameters that define human health state. The application system was done for medical diagnosis help. The inputs are the signals expressed the cardiovascular system parameters, blood pressure, Respiratory system paramsystem was done, it will be able to predict the state of patient according any input values.

On the Design of Shape Memory Alloy Locking Mechanism: A Novel Solution for Laparoscopic Ligation Process

The blood ducts must be occluded to avoid loss of blood from vessels in laparoscopic surgeries. This paper presents a locking mechanism to be used in a ligation laparoscopic procedure (LigLAP I), as an alternative solution for a stapling procedure. Currently, stapling devices are being used to occlude vessels. Using these devices may result in some problems, including injury of bile duct, taking up a great deal of space behind the vessel, and bile leak. In this new procedure, a two-layer suture occludes a vessel. A locking mechanism is also required to hold the suture. Since there is a limited space at the device tip, a Shape Memory Alloy (SMA) actuator is used in this mechanism. Suitability for cleanroom applications, small size, and silent performance are among the advantages of SMA actuators in biomedical applications. An experimental study is conducted to examine the function of the locking mechanism. To set up the experiment, a prototype of a locking mechanism is built using nitinol, which is a nickel-titanium shape memory alloy. The locking mechanism successfully locks a polymer suture for all runs of the experiment. In addition, the effects of various surface materials on the applied pulling forces are studied. Various materials are mounted at the mechanism tip to compare the maximum pulling forces applied to the suture for each material. The results show that the various surface materials on the device tip provide large differences in the applied pulling forces.

Sonochemically Prepared SnO2 Quantum Dots as a Selective and Low Temperature CO Sensor

In this study, a low temperature sensor highly selective to CO in presence of methane is fabricated by using 4 nm SnO2 quantum dots (QDs) prepared by sonication assisted precipitation. SnCl4 aqueous solution was precipitated by ammonia under sonication, which continued for 2 h. A part of the sample was then dried and calcined at 400°C for 1.5 h and characterized by XRD and BET. The average particle size and the specific surface area of the SnO2 QDs as well as their sensing properties were compared with the SnO2 nano-particles which were prepared by conventional sol-gel method. The BET surface area of sonochemically as-prepared product and the one calcined at 400°C after 1.5 hr are 257 m2/gr and 212 m2/gr respectively while the specific surface area for SnO2 nanoparticles prepared by conventional sol-gel method is about 80m2/gr. XRD spectra revealed pure crystalline phase of SnO2 is formed for both as-prepared and calcined samples of SnO2 QDs. However, for the sample prepared by sol-gel method and calcined at 400°C SnO crystals are detected along with those of SnO2. Quantum dots of SnO2 show exceedingly high sensitivity to CO with different concentrations of 100, 300 and 1000 ppm in whole range of temperature (25- 350°C). At 50°C a sensitivity of 27 was obtained for 1000 ppm CO, which increases to a maximum of 147 when the temperature rises to 225°C and then drops off while the maximum sensitivity for the SnO2 sample prepared by the sol-gel method was obtained at 300°C with the amount of 47.2. At the same time no sensitivity to methane is observed in whole range of temperatures for SnO2 QDs. The response and recovery times of the sensor sharply decreases with temperature, while the high selectivity to CO does not deteriorate.

Study of MHD Oblique Stagnation Point Assisting Flow on Vertical Plate with Uniform Surface Heat Flux

The aim of this paper is to study the oblique stagnation point flow on vertical plate with uniform surface heat flux in presence of magnetic field. Using Stream function, partial differential equations corresponding to the momentum and energy equations are converted into non-linear ordinary differential equations. Numerical solutions of these equations are obtained using Runge-Kutta Fehlberg method with the help of shooting technique. In the present work the effects of striking angle, magnetic field parameter, Grashoff number, the Prandtl number on velocity and heat transfer characteristics have been discussed. Effect of above mentioned parameter on the position of stagnation point are also studied.

DCGA Based-Transmission Network Expansion Planning Considering Network Adequacy

Transmission network expansion planning (TNEP) is an important component of power system planning that its task is to minimize the network construction and operational cost while satisfying the demand increasing, imposed technical and economic conditions. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, the lines adequacy rate has not been studied after the planning horizon, i.e. when the expanded network misses its adequacy and needs to be expanded again. In this paper, in order to take transmission lines condition after expansion in to account from the line loading view point, the adequacy of transmission network is considered for solution of STNEP problem. To obtain optimal network arrangement, a decimal codification genetic algorithm (DCGA) is being used for minimizing the network construction and operational cost. The effectiveness of the proposed idea is tested on the Garver's six-bus network. The results evaluation reveals that the annual worth of network adequacy has a considerable effect on the network arrangement. In addition, the obtained network, based on the DCGA, has lower investment cost and higher adequacy rate. Thus, the network satisfies the requirements of delivering electric power more safely and reliably to load centers.

Adoption of Appropriate and Cost Effective Technologies in Housing: Indian Experience

Construction cost in India is increasing at around 50 per cent over the average inflation levels. It have registered increase of up to 15 per cent every year, primarily due to cost of basic building materials such as steel, cement, bricks, timber and other inputs as well as cost of labour. As a result, the cost of construction using conventional building materials and construction is becoming beyond the affordable limits particularly for low-income groups of population as well as a large cross section of the middle - income groups. Therefore, there is a need to adopt cost-effective construction methods either by up-gradation of traditional technologies using local resources or applying modern construction materials and techniques with efficient inputs leading to economic solutions. This has become the most relevant aspect in the context of the large volume of housing to be constructed in both rural and urban areas and the consideration of limitations in the availability of resources such as building materials and finance. This paper makes an overview of the housing status in India and adoption of appropriate and cost effective technologies in the country.

Artificial Neural Network based Web Application Firewall for SQL Injection

In recent years with the rapid development of Internet and the Web, more and more web applications have been deployed in many fields and organizations such as finance, military, and government. Together with that, hackers have found more subtle ways to attack web applications. According to international statistics, SQL Injection is one of the most popular vulnerabilities of web applications. The consequences of this type of attacks are quite dangerous, such as sensitive information could be stolen or authentication systems might be by-passed. To mitigate the situation, several techniques have been adopted. In this research, a security solution is proposed using Artificial Neural Network to protect web applications against this type of attacks. The solution has been experimented on sample datasets and has given promising result. The solution has also been developed in a prototypic web application firewall called ANNbWAF.

Rarefactive and Compressive Solitons in Warm Dusty Plasma with Electrons and Nonthermal Ions

Dust acoustic solitary waves are studied in warm dusty plasma containing negatively charged dusts, nonthermal ions and Boltzmann distributed electrons. Sagdeev pseudopotential method is used in order to investigate solitary wave solutions in the plasmas. The existence of compressive and rarefractive solitons is studied.

Autonomous Robots- Visual Perception in Underground Terrains Using Statistical Region Merging

Robots- visual perception is a field that is gaining increasing attention from researchers. This is partly due to emerging trends in the commercial availability of 3D scanning systems or devices that produce a high information accuracy level for a variety of applications. In the history of mining, the mortality rate of mine workers has been alarming and robots exhibit a great deal of potentials to tackle safety issues in mines. However, an effective vision system is crucial to safe autonomous navigation in underground terrains. This work investigates robots- perception in underground terrains (mines and tunnels) using statistical region merging (SRM) model. SRM reconstructs the main structural components of an imagery by a simple but effective statistical analysis. An investigation is conducted on different regions of the mine, such as the shaft, stope and gallery, using publicly available mine frames, with a stream of locally captured mine images. An investigation is also conducted on a stream of underground tunnel image frames, using the XBOX Kinect 3D sensors. The Kinect sensors produce streams of red, green and blue (RGB) and depth images of 640 x 480 resolution at 30 frames per second. Integrating the depth information to drivability gives a strong cue to the analysis, which detects 3D results augmenting drivable and non-drivable regions in 2D. The results of the 2D and 3D experiment with different terrains, mines and tunnels, together with the qualitative and quantitative evaluation, reveal that a good drivable region can be detected in dynamic underground terrains.

Empowering Communications Challenged users using Development Kits

The rapid pace of technological advancement and its consequential widening digital divide has resulted in the marginalization of the disabled especially the communication challenged. The dearth of suitable technologies for the development of assistive technologies has served to further marginalize the communications challenged user population and widen this chasm even further. Given the varying levels of disability there and its associated requirement for customized solution based. This paper explains the use of a Software Development Kits (SDK) for the bridging of this communications divide through the use of industry poplar communications SDKs towards identification of requirements for communications challenged users as well as identification of appropriate frameworks for future development initiatives.

Multiscale Analysis and Change Detection Based on a Contrario Approach

Automatic methods of detecting changes through satellite imaging are the object of growing interest, especially beca²use of numerous applications linked to analysis of the Earth’s surface or the environment (monitoring vegetation, updating maps, risk management, etc...). This work implemented spatial analysis techniques by using images with different spatial and spectral resolutions on different dates. The work was based on the principle of control charts in order to set the upper and lower limits beyond which a change would be noted. Later, the a contrario approach was used. This was done by testing different thresholds for which the difference calculated between two pixels was significant. Finally, labeled images were considered, giving a particularly low difference which meant that the number of “false changes” could be estimated according to a given limit.

Removal of Arsenic (III) from Contaminated Waterby Synthetic Nano Size Zerovalent Iron

The present work was conducted for Arsenic (III) removal, which one of the most poisonous groundwater pollutants, by synthetic nano size zerovalent iron (nZVI). Batch experiments were performed to investigate the influence of As (III), nZVI concentration, pH of solution and contact time on the efficiency of As (III) removal. nZVI was synthesized by reduction of ferric chloride by sodium borohydrid. SEM and XRD were used to determine particle size and characterization of produced nanoparticles. Up to 99.9% removal efficiency for arsenic (III) was obtained by nZVI dosage of 1 g/L at time equal to 10 min. and pH=7. It could be concluded that the removal efficiency were enhanced with increasing of ZVI dosage and reaction time, but decreased with increasing of arsenic concentration and pH for nano sized ZVI. nZVI presented an outstanding ability to remove As (III) due to not only a high surface area and low particle size but also to high inherent activity.

Exact Solution of the Ising Model on the 15 X 15 Square Lattice with Free Boundary Conditions

The square-lattice Ising model is the simplest system showing phase transitions (the transition between the paramagnetic phase and the ferromagnetic phase and the transition between the paramagnetic phase and the antiferromagnetic phase) and critical phenomena at finite temperatures. The exact solution of the squarelattice Ising model with free boundary conditions is not known for systems of arbitrary size. For the first time, the exact solution of the Ising model on the square lattice with free boundary conditions is obtained after classifying all ) spin configurations with the microcanonical transfer matrix. Also, the phase transitions and critical phenomena of the square-lattice Ising model are discussed using the exact solution on the square lattice with free boundary conditions.

Low Power Bus Binding Based on Dynamic Bit Reordering

In this paper, the problem of reducing switching activity in on-chip buses at the stage of high-level synthesis is considered, and a high-level low power bus binding based on dynamic bit reordering is proposed. Whereas conventional methods use a fixed bit ordering between variables within a bus, the proposed method switches a bit ordering dynamically to obtain a switching activity reduction. As a result, the proposed method finds a binding solution with a smaller value of total switching activity (TSA). Experimental result shows that the proposed method obtains a binding solution having 12.0-34.9% smaller TSA compared with the conventional methods.

Smith Predictor Design by CDM for Temperature Control System

Smith Predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system and very sensitive to uncertain system with variable time-delay. In this paper is concerned with a design method of smith predictor for temperature control system by Coefficient Diagram Method (CDM). The simulation results show that the control system with smith predictor design by CDM is stable and robust whilst giving the desired time domain system performance.

Wrap-around View Equipped on Mobile Robot

This paper presents a wrap-around view system with 4 smart cameras module and remote motion mobile robot control equipped with smart camera module system. The two-level scheme for remote motion control with smart-pad(IPAD) is introduced on this paper. In the low-level, the wrap-around view system is controlled or operated to keep the reference points lying around top view image plane. On the higher level, a robot image based motion controller is utilized to drive the mobile platform to reach the desired position or track the desired motion planning through image feature feedback. The design wrap-around view system equipped on presents such advantages as follows: 1) a satisfactory solution for the FOV and affine problem; 2) free of any complex and constraint with robot pose. The performance of the wrap-around view equipped on mobile robot remote control is proven by experimental results.

DEMO Based Optimal Power Purchase Planning Under Electricity Price Uncertainty

Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

A C1-Conforming Finite Element Method for Nonlinear Fourth-Order Hyperbolic Equation

In this paper, the C1-conforming finite element method is analyzed for a class of nonlinear fourth-order hyperbolic partial differential equation. Some a priori bounds are derived using Lyapunov functional, and existence, uniqueness and regularity for the weak solutions are proved. Optimal error estimates are derived for both semidiscrete and fully discrete schemes.

Effects of Environmental Factors on Polychaete Assemblage in Penang National Park, Malaysia

Macrobenthos distribution along the coastal waters of Penang National Park was studid to estimate the effect of different environmental parameters at three stations, during six sampling months, from June 2010 to April 2011. The aim of this survey was to investigate different environment stress over soft bottom polychaete community along Teluk Ketapang and Pantai Acheh (Penang National Park) over a year period. Variations in the polychaete community were evaluated using univariate and multivariate methods. A total of 604 individuals were examined which was grouped into 23 families. Family Nereidae was the most abundant (22.68%), followed by Spionidae (22.02%), Hesionidae (12.58%), Nephtylidae (9.27%) and Orbiniidae (8.61%). It is noticeable that good results can only be obtained on the basis of good taxonomic resolution. The maximum Shannon-Wiener diversity (H'=2.16) was recorded at distance 200m and 1200m (August 2010) in Teluk Ketapang and lowest value of diversity was found at distance 1200m (December 2010) in Teluk Ketapang.