A mathematical model that makes use of data mining and soft computing techniques is proposed to estimate the software development effort. The proposed model works as follows: The parameters that have impact on the development effort are divided into groups based on the distribution of their values in the available dataset. The linguistic terms are identified for the divided groups using fuzzy functions, and the parameters are fuzzified. The fuzzified parameters then adopt associative classification for generating association rules. The association rules depict the parameters influencing the software development effort. As the number of parameters that influence the effort is more, a large number of rules get generated and can reduce the complexity, the generated rules are filtered with respect to the metrics, support and confidence, which measures the strength of the rule. Genetic algorithm is then employed for selecting set of rules with high quality to improve the accuracy of the model. The datasets such as Nasa93, Cocomo81, Desharnais, Maxwell, and Finnish-v2 are used for evaluating the proposed model, and various evaluation metrics such as Mean Magnitude of Relative Error, Mean Absolute Residuals, Shepperd and MacDonell’s Standardized Accuracy, Enhanced Standardized Accuracy and Effect Size are adopted to substantiate the effectiveness of the proposed methods. The results infer that the accuracy of the model is influenced by the metrics support, confidence, and the number of association rules considered for effort prediction.

Due to environmental conditions, the wind power generation is fluctuating in nature. This affects the electrical network interconnected with these systems. When the wind power generators are connected to the nonlinear loads, there is distortion in the waveform. These distortions should be within limits according to national and international guidelines framed for power quality. This paper presents a mitigation technique with a shunt active filter, which reduces harmonic distortion to the permitted limit. Sine pulse width modulation (SPWM) control scheme is used to control shunt active filter. This technique eliminates harmonic distortion and maintains unity power factor. The simulation for proposed method is carried out using MATLAB/SIMULINK and results are validated.

An Intelligent Transportation System (ITS) is a new system developed for the betterment of user in traffic and transport management domain area for smart and safe driving. ITS subsystems are Emergency vehicle notification systems, Automatic road enforcement, Collision avoidance systems, Automatic parking, Map database management, etc. Advance Driver Assists System (ADAS) belongs to ITS which provides alert or warning or information to the user during driving. The proposed method uses Gaussian filtering and Median filtering to remove noise in the image. Subsequently image subtraction is achieved by subtracting Median filtered image from Gaussian filtered image. The resultant image is converted to binary image and the regions are analyzed using connected component approach. The prior work on speed bump detection is achieved using sensors which are failed to detect speed bumps that are constructed with small height and the detection rate is affected due to erroneous identification. And the smartphone and accelerometer methodologies are not perfectly suitable for real time scenario due to GPS error, network overload, real-time delay, accuracy and battery running out. The proposed system goes very well for the roads which are constructed with proper painting irrespective of their dimension.

Embedded systems used in real-time applications require low power, less area and high computation speed. For digital signal processing, image processing and communication applications, data are often received at a continuously high rate. The type of necessary arithmetic functions and matrix operations may vary greatly among different applications. The RTL-based design and verification of one or more of these functions could be time-consuming. Some High Level Synthesis tools reduce this design and verification time but may not be optimal or suitable for low power applications. The design tool proposed in this paper can improve the design time and reduce the verification process. The design tool offers a fast design and verification platform for important matrix operations. These operations range from simple addition to more complex matrix operations such as LU and QR factorizations. The proposed platform can improve design time by reducing verification cycle. This tool generates Verilog code and its testbench that can be realized in FPGA and VLSI systems. The designed system uses MATLAB-based verification and reporting.

The electromagnetic torque and speed in Switched Reluctance Motor (SRM) greatly depend on the excitation parametersi.e. turn-on angle, turn-off angle, dwell angle and magnitude of the phase currents of its phases. At lower speeds, a change in the current contributes the torque requirement which can be achieved either by voltage control (pulse width modulation) or instantaneous current control techniques. At high speeds, due to high back EMF, the regulation of current is crucial and achieved with the control of switching angles of phases. This type of control is referred as average torque control, where the torque is averaged over one stroke (2π/Nr). With constant dwell angle, advancing the phase angle influences the current into the phase winding at minimum inductance position. It has more time to get the current out of the phase winding before the rotor reaches the negative inductance slope. To maintain the speed of the motor at different load conditions, the turn-on and turn-off angles are adaptively varied. The change in dwell angle may be required where the turn-on and turn-off angle may not be sufficient to reach the required speed. In this paper, a new algorithm is proposed for self tuning of switching parameters of SRM. The proposed algorithm is simulated in MATLAB-Simulink and experimentally validated with Field Programmable Gated Array (FPGA) using MATLAB- system generator environment.

In Wireless Sensor Networks (WSN), the lifetime of sensors is the crucial issue. Numerous schemes are proposed to augment the life time of sensors based on the wide range of parameters. In majority of the cases, the center of attraction will be the nodes’ lifetime enhancement and routing. In the scenario of cluster based WSN, multi-hop mode of communication reduces the communication cast by increasing average delay and also increases the routing overhead. In this proposed scheme, two ideas are introduced to overcome the delay and routing overhead. To achieve the higher degree in the lifetime of the nodes, the residual energy (remaining energy) of the nodes for multi-hop node choice is taken into consideration first. Then the modification in the routing protocol is evolved (Multi-Hop Dynamic Path-Selection Algorithm—MHDP). A dynamic path updating is initiated in frequent interval based on nodes residual energy to avoid the data loss due to path extrication and also to avoid the early dying of nodes due to elevation of data forwarding. The proposed method improves network’s lifetime significantly. The diminution in the average delay and increment in the lifetime of network are also accomplished. The MHDP offers 50% delay lesser than clustering. The average residual energy is 20% higher than clustering and 10% higher than multi-hop clustering. The proposed method improves network lifetime by 40% than clustering and 30% than multi-hop clustering which is considerably much better than the preceding methods.

Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.

The efficient use of energy is an important performance metric to extend the lifetime of wireless sensor networks. Since major energy consumption of node is due to its transceiver, the design of MAC protocol plays a vital role in sensor network design. In cluster based sensor networks, due to the different functions of member node and cluster head node, the usage of common MAC protocol results increased energy consumption. To overcome this problem, a novel energy efficient hybrid MAC protocol (EEHMAC) for cluster based wireless sensor networks is proposed in this paper. The proposed EEHMAC protocol uses E-TDMA (Energy efficient TDMA) for intra-cluster communication and FDMA (Frequency Division Multiple Access) for inter-cluster communication. IDS (Iterative Deepening Search) based Scheduling algorithm is used for assigning time slot and frequency slot to nodes. Nodes in EEHMAC follow the periodic duty cycle, which reduces the idle listening, and overhearing problems. Simulation results reveal that an average of 18% energy saving is achieved compared to LEACH (Low Energy Adaptive Clustered Hierarchy) protocol and 10% energy is saved in comparison with GH-MAC (Graph theory based Hybrid MAC) protocol. It is evident that delay of EEHMAC is reduced by 17% and throughput is increased by 15% under all traffic conditions. These results demonstrate that EEHMAC performs better than existing MAC protocols in terms of energy efficiency, delay and throughput.

The world is heading towards renewable energy, but the two key disputes that stop its well-known adoption are the power production level and the price of the production. Distributed generation (DG), and hybrid systems with battery backup are the solution for uninterrupted power supply. It is obtained using the Multi-Objective Genetic Algorithm (NSGA II). Techno-economic methodology is used in this proposed system for the size optimization. The result is based on the system cost, in order to meet the load requirements. The effect of temporal sampling is optimized using low-rate temporal data. It is compared with hybrid DC microgrid, which has been optimized using high temporal resolution data.

This paper proposes a novel price based load frequency control scheme for a two area system, using an Unscheduled Interchange (UI) price signal, which is ideal and suitable for electricity market. The Government of India has introduced Availability Based Tariff (ABT) structure with an intention of ensuring grid security and to regulate grid indiscipline through Central Electricity Regulatory Commission Regulation. After the introduction of this regulation, the over or under injection by the generating companies (GENCOs) during off peak or peak hours are demoralized and the frequency is maintained at the nominal value. In this paper, the GENCOs instead of reacting to this price signal manually, an automated mode of frequency control is deployed in each area using UI price signal to achieve fast response to load change. The Distribution Company (DISCO) Participation Matrix (DPM) has also been employed in this work to relate the scenario under deregulation of electricity market. The proposed scheme has been verified for different cases by simulating it on a two area system, each having four GENCOs and one DISCO in MATLAB/SIMULINK environment. From the results, it is clearly observed that if the proposed method is employed by all GENCOs, it will certainly enhance the control of system frequency and at the same time throw down the UI liability of market participants. It also ensures that the GENCOs and DISCOs strictly adhere to the bilateral contract following the DISCO participation matrix.