Presently a day the human life and the climate have often been jeopardized by the characteristic perils like seismic tremor, torrent, flood, twister and avalanches. As an outcome of which the human culture and the country's economy get hampered following the event of a catastrophic event. In agricultural nations like India, where the populace is huge and is expanding step by step, the social and financial components power individuals to live in weak territories, because of which the impacts of these cataclysmic events are disastrous. Among every one of these dangers, liquefaction of soil can be brought up as one of the most appalling seismic perils. Consequently assessment of liquefaction helplessness is a significant part of geotechnical designing. Soil-structure connection impact in the examination and plan of RC outline structures is progressively perceived yet not infiltrated to the grass root level attributable to different complexities included. It is settled reality that the dirt structure collaboration impact significantly impact the plan of multi-story structures exposed to parallel seismic burdens. In this examination we are performing seismic appraisal utilizing Analytical apparatus SAP2000 over a midrise building outline where we will give sidelong load to zone V (0.36) to decide soil structure communication for parallel burdens, for this investigation a midrise even structure of G+7 storey is considered.

Influence of wind load as a wonder on structures, especially tall structures can't be unnoticed. It's fundamental to consider the aftereffect of wind in style and examination of structures. The structure is investigated for the gravity loads and furthermore for the parallel burdens for example wind load in zone-ii (Bhopal), zone-iii (Nagpur), zone iv (Delhi), zone-v (Calcutta), zone-vi (Darbhanga).The structure is made on the product known as staad.pro v8i. This examination is the investigation of the Reinforced concrete cement multi-story building (G+10). The codes utilized for the estimations of Dead burden are IS:875(Part 1)- 1987 ,for live burden the code IS :875(Part 2)- 1987 and for the counts of wind power in various breeze zones are IS :875 ( section 3) - 1987.The aftereffect of these examination shows the adjustment in powers, removals responses and weight of steel the amount of auxiliary material expected to oppose parallel burdens will increment definitely.quantity of structural material needed to resist lateral loads will increase drastically.

In this paper a novel technique based on adaptive filtering is proposed for the control of three phase universal active power filter with solar photovoltaic array integrated at its DC bus. two adaptive filter along with a zero-crossing detection technique are used to extract the magnitude of fundamental active component of distorted load currents, which is then used in estimation of reference signal for the shunt active filter. This technique enables extraction of active component of all three phases with reduced mathematical computation. The series active filter control is based on synchronous reference frame theory and it regulates load voltage and maintains it in-phase with voltage at point of common coupling under conditions of voltage sag and swell. A universal active power filter is connected to a test system for harmonics mitigation generated by non-linear load connected to three phase grid. The universal active power filter has two VSCs connected in series and parallel to the grid PCC. The two VSCs are connected to common PVA along with DC link capacitor the harmonic distortion comparison is done on source current using FFT analysis with PI and fuzzy logic controller.

A Girder bridge is a bridge that utilizations braces as the methods for supporting the deck. A bridge comprises of three sections: The Foundation of projections and bearings and Substructure of projection and dock and The Superstructure (brace, bracket, or curve) and deck. A Girder bridge is likely the most usually fabricated and used bridge on the planet. Its fundamental plan, in the most improved frame, can be contrasted with a log extending from one side to alternate over a stream or river.The two sections must cooperate to make a solid, durable bridge. Prestressed Concrete is fundamentally concrete in which interior worry of reasonable extent and dispersion are presented pressure coming about because of outer load are concentrated to wanted degree. In this research work we are analyzing a girder bridge with the effect of prestressed concrete and compare it with general deck bridge. In terms of finite elemental analysis, forces and cost analysis. Here it is concluded that implementation of prestressed deck is resulting in economical, stable and load resisting member.

This paper manages the trial Investigation on concrete by partial replacement of fine aggregate with copper slag to improve the quality strength parameters, for example compressive strength, split tensile strength, and flexural strength of the M-25and M-30 grade of concrete. Here the fine aggregate partially replaced with copper slag in concrete with 5%, 10%, 15% & 20% by weight of fine aggregates and cement Mix design was prepared for M-25 and M-30 grade of concrete by replacement of copper slag as fine aggregate and cement. We can reduce the digging of river sand which effects the hydraulic structure stability and as well as we can reduce the open land fill and environmental pollution with copper slag usage it in concrete. Test outcomes shows that the strength performances of concrete has enhanced having copper slag as a partial substitution of Sand and cement (0-20%) in concrete however in conditions of stability the concrete establish to be low resistant to acid attack and high resistance against sulphate attack. At that point investigate variation between values of results with conventional concrete. Graphs are drawn strength vs. replacement with fine aggregate results are compared with normal concrete.

The study of present day, the spectrum usage reveals that nearly 70% of available spectrum is underutilized which is a serious concern as the available spectrum is the most precious resource for radio communication. The concept of cognitive radio emerged as a very strong solution that employs Dynamic Spectrum Access (DSA) in contrast to the present day situation employing Fixed Spectrum Allocation (FSA). To combat the difficulties of hidden user node problem, SNR degradation and issues related to difficulties in non-cooperative spectrum sensing, the cognitive radio networks were upgraded to the cooperative spectrum sensing. Cooperative sensing acquires information from multiple secondary users for primary user detection. By analyzing the conclusions drawn from this research, it is reconfirmed that the adopted enhanced energy detection provides a better sensing performance than the traditional energy detection described in literature and provides an enhancement of 20.25% in detection probability for the simulation done in this dissertation. The simulation done in this dissertation establishes that if the enhanced energy detection scheme is employed for local sensing instead of the traditional method, the performance of the traditional centralized combining hybrid spectrum sensing (employing Hard Combination at the Fusion Center) is improved for all the three rules viz. AND, OR, Majority rule. The increase in mean probability of detection is most significant for the Majority rule (which is 71.48%) and least significant for AND rule (which is 0.00256%), whereas it is 0.02% for OR rule, as concluded from the simulation proposed in this dissertation. Thus a centralized cooperative spectrum sensing network employing Hard Combination at the Fusion Center, can be optimized by using the Enhanced Energy Detection for local sensing.

Cross-site scripting (XSS) is a scripting attack on web pages and accounted as one of the most dangerous vulnerability found in web applications. Security researchers investigated several issues and found XSS vulnerability in most of the popular websites. Once the vulnerability is exploited, an attacker gains a voluntary access of the legitimate user’s web-browser and may perform cookie-stealing, malware-spreading, session-hijacking, and malicious redirection. As a preventive measure against such attacks, it is imperative to adopt security measures that inevitably block the third party interference. The most recent attack on existing websites is DOM based Cross Site Scripting attack, it is much harder to detect and therefore it must be prevented. This attack can harm millions of people in a few seconds. Vulnerabilities of websites are mostly exploited through HTTP GET submission method and HTTP POST submission method. To prevent the existing websites from the XSS attacks, a methodology of two way detector & filter is developed.

The present study aims to identify the most suitable way to utilize the waste materials produced from industries as the replacement of cement for highway construction purposes. Several studies have been conducted across the world which identified the adverse effects of different waste materials on environment as well as on human health also. The basis of different studies, it was revealed that the production of cement on large scale is also responsible for causing several diseases to the human and the water pollution. Therefore, it is the need of the situation to utilize the different waste material as an alternative of cement. For the same purpose several studies were conducted across the world. Consequently, different waste materials were found to be appropriate ranging from 5% to 50% for the highway construction purposes. But, still there is a need to replace the cement completely by introducing another material by considering the chemical composition of cement. In the present study, an attempt has been made to aware the researchers and engineers to manufacture inexperienced concrete in order to attain the balance between environment, economical and technical aspects by highlighting different methods of utilizing the discarded materials.

In a conventional cognitive radio (CR) network, only when the primary user's (PU) frequency bands are sensed to be free, secondary users (SUs) can utilize these frequency band resources. Therefore, spectrum sensing (SS) can improve spectrum utilization. Spectrum sharing means that the SUs are allowed to utilize the licensed spectrum bands belonging to the PU to transmit information with PU simultaneously. Energy harvesting (EH) and cognitive radio (CR) are expected to provide a new solution to deal with the shortage of energy and spectrum, respectively. However, the efficiency of EH is low and the wireless terminals are growing exponentially, which make the research on increasing energy efficiency (EE) and spectrum efficiency (SE) crucial. In this paper we present survey for the energy harvesting techniques in wireless communication.

Wireless technology enables many services and applications and will play a key role for enabling the smart and autonomous systems of the future. Wireless networks also provide mission critical infrastructure for public safety, national security, and military communications. This popularity of wireless technology can be attributed to its ease of access and high availability; however, these very same features contribute too many of its vulnerabilities Attacks such as jamming, spoofing, and eavesdropping. With the rapid development of the information age, the hidden dangers of radio order and spectrum security are becoming more and more serious. In this paper we present the survey for the anomaly based detection in wireless networks.

The According the 2010 global burden of disease study, Chronic Kidney Diseases (CKD) was ranked 18th in the list of causes of total no. of deaths worldwide. 10% of the population worldwide is affected by CKD. The prediction of CKD can become a boon for the population to predict the health. Various method and techniques are undergoing the research phase for developing the most accurate CKD prediction system. Using Machine Learning techniques is the most promising one in this area due to its computing function and Machine Learning rules. Existing Systems are working well in predicting the accurate result but still more attributes of data and complicity of health parameter make the root layer for the innovation of new approaches. This study focuses on a novel approach for improving the prediction of CKD. In recent time Neural network system has discovered its use in disease diagnoses, which is depended upon prediction from symptoms data set. Chronic kidney disease detection system using neural network is shown here. This system of neural network accepts disease-symptoms as input and it is trained according to various training algorithms. After neural network is trained using back propagation algorithms, this trained neural network system is used for detection of kidney disease in the human body.

In this paper a landsman PFC converter is modelled with control on the output voltage through voltage-oriented control. The output from the landsman PFC converter is fed to isolated DC-DC converter for charging the battery. The output voltage of the PFC converter is controlled using PI controller to generate specific required DC voltage given as a reference by the user. The isolated DC-DC converter is controlled by current-oriented control with feedback from the battery terminal voltage and current. Even in the isolated DC-DC converter a PI controller is used to control the charging current of the battery. The PI controller is further replaced with fuzzy interface system for better response and settling of the output voltage of the PFC converter. A comparative analysis of the PFC converter characteristics with PI and fuzzy controller are modelled in MATLAB Simulink environment.

A single-phase grid connected transformer less photo voltaic (PV) inverter which can operate either in buck or in boost mode, and can extract maximum power simultaneously from two serially connected sub arrays while each of the sub array is facing different environmental conditions, is presented in this paper. As the inverter can operate in buck as well as in boost mode depending on the requirement, the constraint on the minimum number of serially connected solar PV modules that is required to form a subarray is greatly reduced. As a result, power yield from each of the sub array increases when they are exposed to different environmental conditions. In this paper fuzzy logic-controlled buck –boost dc to dc converter for multi PVA system are developed. When the PI controller is replaced by fuzzy logic controller, then the output dc link voltage of buck boost will get improved. General design of a fuzzy logic controller (FLC), based on Matlab/Simulink is performed. This design compared with Proportional Integrated (PI) controller. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail for different study conditions.

In this real-world, BC (Breast Cancer) is the second most common cause of death in developed and undeveloped countries. Among 8 percent of women diagnosed with Breast Cancer (BC) are marked by gene mutation, chronic pain, size change, color (redness), and breast skin texture. Breast cancer classification leads pathologists to a systemic and rational prognosis, usually with binary (benign cancer/cancer) classified more commonly. Machine Learning techniques (ML) are now widely used in the issue of breast cancer classification. They offer high accuracy in classification and efficient diagnostic ability. This paper introduces two layers Deep Neural Network for the classification of breast cancer followed by gradient approach and back propagation method. The findings indicate that two layer deep neural network is the most accurate (99.91%) with the lowest error rate relative to the NB classifier (96.19%).

The solar air heater has an important place among solar heat collectors. It can be used as sub-systems in many systems meant for the utilization of solar energy. Possible applications of solar air heaters are drying or curing of agricultural products, space heating for comfort regeneration of dehumidifying agents, seasoning of timber, curing of industrial products such as plastics. When air at high temperature is required the design of a heater becomes complicated and very costly. As far as the ultimate application for heating air to maintain a comfortable environment is concerned, the solar air heater is the most logical choice. In general solar heaters are quite suitable for low and moderate temperatures application as their design is simple. These solar air heaters have low heat transfer efficiency which can be improved using geometrical modifications like optimizing duct geometry or adding artificial roughness. Artificial roughness element with gap used to enhance the performance of solar air heater. Compared to the traditional smooth absorber plate and absorber plate with artificial roughness element without gap, the thermo-hydraulic performance (THP) of discrete artificial roughened solar air heater was found more. An experimental study of the heat transfer and fluid flow properties of the solar air heater was carried out using artificial roughness with an area in the absorbent plate. The use of artificial roughness on the underside of the absorber plate is an effective and economic way to improve the thermal performance of a solar air heater. Several experimental investigations, involving different types of roughness elements, have been carried out to improve the heat transfer from the absorber plate to air flowing in solar air heaters. In this paper the CFD analysis on heat transfer and friction in rectangular ducts roughened with broken ‘S’ shaped ribs has been presented. The relative gap width (g/e) is 1.0 and relative gap position (d/W) varied from 0.30 to 0.60 and other parameter are constant. The effects of relative gap position (d/W) on Nusselt number, friction factor and thermo-hydraulic performance parameter have been discussed and results compared with smooth duct under similar conditions. It is found that the maximum heat transfer and friction characteristic at a relative gap position of 0.50.

In recent years, the heterogeneous wireless network, which can support high-density and high-rate traffic, has attracted much research interest from both academic and industry sectors. The cooperation between the macro base stations (BSs) and the femto BSs can greatly improve the quality of service (QoS) of the user equipment, as well as the spectrum efficiency and the energy efficiency. The demand for bandwidth-critical applications has stimulated the research community not only to develop new ways of communication, but also to use the existing spectrum efficiently. In this paper, we aim to provide an in-depth survey on the most recent advances in spectrum sensing techniques in cognitive radio network.

This paper proposes a standalone two stage solar photovoltaic (PV) water pumping system. This system utilizes a solar PV array, boost dc-dc converter, Utility grid, three-phase voltage source converter; three phase VSI (Voltage Source Inverter), PMSM (Permanent Magnet Synchronous Motor). The boost converter used between PV array and VSI, serves the purpose of MPP (Maximum Power Point) tracking by adjusting the duty ratio using an INC (Incremental Conductance) method in order to extract optimum power from the PV array. In this way, the purpose of effective and efficient water pumping is achieved. The proposed system is modelled using MATLAB/ Simulink environment and its performance is simulated to study its behavior under varying insolation level.

This paper deals with the design and stability analysis of a DC microgrid employing battery-super capacitor based hybrid energy storage system. Standalone photovoltaic-based microgrid with energy storage system could be a promising solution for powering up off-grid communities. One of the major issues that hinder the development of standalone microgrid is the poor service life of the batteries. A standalone DC micro grid system is introduced with photo voltaic array feeding the load. A supportive source using battery energy storage system is connected in parallel for power injection during no irradiation or low irradiation conditions. The power from the PVA and battery are shared by the load during all irradiation levels. For sudden load change conditions, a super capacitor is also connected to ensure maintenance of DC voltage amplitude.

Medical diagnosis is considered an art regardless of all standardization efforts made, which is greatly due to the fact that medical diagnosis necessitates an expertise in coping with uncertainty simply not found in today's computing machinery. The researchers are encouraged by the advancement in computer technology and machine learning techniques to develop software to assist doctors in making decision without necessitating the direct consultation with the specialists. In this paper, application of data mining such as classification techniques in typical heart disease and diabetes diseases diagnosis has been investigated. The support vector machine with sequential minimal optimization algorithm is applied to India based patients’ data set. Results obtained show that support vector machine can be successfully used for diagnosing heart disease and diabetes diseases. The role of effective diagnosis and the advantages of data training on machine learning based automatic medical diagnosis system are suggested by the outcomes.

With data becoming increasingly available in recent years, black-box algorithms like boosting methods or neural networks play more important roles in the real world. However, interpretability is a severe need for several areas of applications, like health care or business. Doctors or managers often need to understand how models make predictions, in order to make their final decisions. The deployment of ML systems in complex, real world settings has led to increasing interest in systems optimized not only for expected task performance but also other important criteria such as safety, nondiscrimination, avoiding technical debt or satisfying the right to explanation.

In this a novel technique based on adaptive filtering is proposed for the control of three phase universal active power filter with solar photovoltaic array integrated at its DC bus. two adaptive filter along with a zero-crossing detection technique are used to extract the magnitude of fundamental active component of distorted load currents, which is then used in estimation of reference signal for the shunt active filter. This technique enables extraction of active component of all three phases with reduced mathematical computation. The series active filter control is based on synchronous reference frame theory and it regulates load voltage and maintains it in-phase with voltage at point of common coupling under conditions of voltage sag and swell.

Shunt active power filters (SAPFs) implemented without harmonic detection schemes are susceptible to sudden load variations. This paper proposes a robust control strategy to reduce this drawback. In this strategy, the dc-link voltage is regulated by a hybrid control technique combining a standard proportional–integral PI and a sliding-mode (SM) controllers. The SM scheme continuously determines the gains of the PI controller based on the control loop error and its derivative. The chattering due to the SM scheme is reduced by a transition rule that fixes the controller gains when steady-state condition is reached. This controller is termed as dual-sliding-mode-proportional–integral. The phase currents of the power grid are indirectly regulated by double-sequence controllers with two degrees of freedom, where the internal model principle is employed to avoid reference frame transformation.

The intrusion detection framework assumes a significant job in organization security. The Intrusion detection model is a prescient model used to foresee the organization's information traffic as regular or Attack. Machine Learning (ML) methods are utilized to assemble precise models for clustering, classification, and estimate. Intrusion detection systems (IDS) still have a few limitations and problems which opens new directions of research. As the era of the internet grows tremendously which results in more large data for which it needs to develop a better intrusion detection system that can work proactively. In this paper classification and prescient models for Intrusion detection are worked by utilizing ML based methods in particular BayesNet, NaiveBayes, J48, and Random Forest. These ML based methods are evaluated with KDDCUP 99 Dataset. Experiment results show that Random Forest Classifier beats different strategies in recognizing whether the information traffic is ordinary or an assault. We compute the results on various parameters like Accuracy, Precision, recall, F- Measures, and RoC area.

Few years have witnessed a significant increase in the use of portable computing devices such as smart phones, tablets and laptops. The popularity of these devices and the emergence of a range of innovative mobile applications and online services are driving the demand for more reliable wireless communication connectivity. Despite the maturity of mobile radio technologies such as 3G and 4G, Wi-Fi still represents a cheaper, faster, and more reliable communication alternative for many wireless users. Fast advance in the design of 5G cellular networks has motivated many research works in the recent years. The main research challenges are given by the explosive growth of traffic burden, the rise of energy consumption constraints, the unprecedentedly high demand for broadband mobile connectivity and Quality of Service (QoS). Therefore the appearance of new technologies and system designs is vital to bear such high demand in networks infrastructures, In this work present the review for IEEE 802.11 wireless local area networks and their importance in wireless communication.