CONTRIBUTION OF AI TO THE CONSTRUCTION WORLD

Artificial intelligence is a department of computer science and information technological know-how, involved in the research, layout, and application of intelligent computer. Conventional techniques for modeling and optimizing complicated structure systems require big amounts of computing assets, and artificial-intelligence-primarily based solutions can frequently provide treasured alternatives for successfully solving problems inside the civil engineering. This paper summarizes currently evolved methods and theories within the growing path for programs of synthetic intelligence in civil engineering, such as evolutionary computation, neural networks, fuzzy systems, professional machine, reasoning, type, and learning, in addition to others like chaos theory, cuckoo seek, firefly algorithm, know-how-based engineering, and simulated annealing. The primary studies tendencies are also talked about in the end. The paper presents an overview of the advances of synthetic intelligence carried out in civil engineering.

SIGNIFICANT ROLE OF AI & ML TECHNIQUES USED IN IMPROVEMENT OF CYBER SECURITY

Cyber Security has become an arising challenge for business information system in current era. AI (Artificial Intelligence) is broadly utilized in various field, however it is still generally new in cyber security. Nonetheless, the applications in network protection are significant for everybody`s day by day life. In this paper, we present the current status of AI in cyber security field, and afterward portray a few contextual investigations and uses of AI to help the community including engineering managers, teachers, educators, business people, and understudies to more readily comprehend this field, for example, the difficulties and uncertain issues of AI in online protection. According to the new challenges, the expert community has two main approaches: to adopt the philosophy and methods of Military Intelligence, and to use Artificial Intelligence methods for counteraction of Cyber Attacks. Cyber security is a vital danger for any business as the quantity of attacks is expanding. Developing of attacks on cyber security is undermining our reality. AI (Artificial Intelligence) and ML (Machine Leaning) can help identify dangers and give proposals to cyber Analyst. Advancement of appropriation of AI/ML applied to cyber security requires banding together of industry, the scholarly community, and government on a worldwide scale. We also discuss future research opportunities associated with the development of AI techniques in the cyber security ?eld across a scope of utilization areas.

HYBRID RECOMMENDATION SYSTEM FOR BETTER MINING RULES GENERATION OF USER AND CONSUMER DATA

In today’s world Data and information playing an important role in each field including online and software data. However, it is very difficult task to abstract & sorted consumer data for use. To solve this data overloading and sorting of useful data a Hybrid Recommendation System (HRS) comes into existence. The focus of HRS is to suggest the best applicable and useful items to the related customers or user. The recommendations can be applied to decision-making processes, like which types of things to get, which new videos to watch to, which online latest games and software to search, or which is the best product among all. The benefits of Hybrid Recommendation System persist on quality efficiency of the system. The efficient things can be calculated in the forms of easy to use, reliable accurate and expandable. The main goal of this proposed HRS is to better mining rules based on user and consumer data to improve the accuracy of Hybrid Recommendation System.

AN IMPLEMENTATION OF EFFICIENT PATH SELECTION METHOD FOR SUCCESSFUL DATA TRANSMISSION IN MOBILE AD HOC NETWORKS

Routing is a process of forwarding the data from a known source to the destination. In this procedure, the data might travel during some in-between paths, and there exist a required to select the best probable best possible nodes to forward the data. This best selection of nodes will permit to achieve a high presentation in the network. Big amount of worked has been carried out to find the best pathway in the network routing to progress its effectiveness and to eliminate overcrowding problems. A good routing algorithm should be able to find an optimal path and it must be simple. It also must have low overhead, and be robust and stable, converging rapidly, and must remain flexible. Routing in MANET by means of the direct pathway metric is not a sufficient situation to construct high quality pathway, since minimum hop count routing frequently chooses routes that have considerably less capacity than the best pathway that live in the network. In this article, we suggest a mechanism to prefer the routing protocol based on manifold measure like Throughput, PDR, energy expenditure etc. These paths are quite resourceful. Network presentation will be raise by using these paths. The efficiency of our mechanism is illustrated by simulations conducted using network simulator ns-2.

GOVT_EXAM ONTOLOGY IN SEMANTIC WEB FOR QUERY RETRIEVAL

The World wide web is growing day by day exponentially and it becomes difficult to find the relevant information even using efficient search engines. Search results always give lots of irrelevant data which often misled to actual needed information. One solution of this problem is semantic web which was proposed by Sir Tim Berner’s Lee. Semantic web is an extended version of World Wide Web that has opened the new doors for efficient information retrieval process. Ontology is one of the methodologies to implement the semantic web. In this paper govt exam ontology is created with the help of protégé ontology creation tool. In the given ontology various relationship between different govt exams of central and state level is provided and also the general information about these exams like exam type, subject level of exam and institutes for coaching is given. This domain specific ontology can help the potential information seeker to get the accurate information which can help to crack the exam.

PERFORMANCE ANALYSIS OF NOISE REMOVAL TECHNIQUES FOR FACIAL IMAGES- A COMPARATIVE STUDY

Image de-noising has been a challenging issue in the field of digital image processing. It involves the manipulation of image data to produce a visually high quality image. While maintaining the desired information in the quality of an image, elimination of noise is an essential task. Various domain applications such as medical science, forensic science, text extraction, optical character recognition, face recognition, face detection etc. deal with noise removal techniques. There exist a variety of noises that may corrupt the images in different ways. Here, we explore filtering techniques viz. Mean filter, Median filter and Wiener filter to remove noises existing in facial images. The noises of our interest are namely; Gaussian noise, Salt & Pepper noise, Poisson noise and Speckle noise in our study. Further, we perform a comparative study based on the parameters such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structure Similarity Index Method (SSIM). For this research work, MATLAB R2013a on Labeled faces in Wild (lfw) database containing 120 facial images is used. Based upon the aforementioned parameters, we have attempted to analyze the performance of noise removal techniques with different types of noises. It has been observed that MSE, PSNR and SSIM for Mean filter are 44.19 with Poisson noise, 35.88 with Poisson noise and 0.197 with Gaussian noise respectively whereas for that of Median filter, these are 44.12 with Poisson noise, 46.56 with Salt & Pepper noise and 0.132 with Gaussian noise respectively. Wiener filter when contaminated with Poisson, Salt & Pepper and Gaussian noise, these parametric values are 44.52, 44.33 and 0.245 respectively. Based on these observations, we claim that the Median filtering technique works the best when contaminated with Poisson noise while the error strategy is dominant. On the other hand, Median filter also works the best with Salt & Pepper noise when Peak Signal to Noise Ratio is important. It is interesting to note that Median filter performs effectively with Gaussian noise using SSIM.

ENHANCED APPROACH FOR SOIL CLASSIFICATION USING BOOSTED C5.0 DECISION TREE ALGORITHM

Data mining includes the utilization of erudite data analysis tools to discover previously unidentified, suitable patterns and relationships in enormous data sets. Data mining tools can incorporate statistical models, machine learning methods such as neural networks or decision trees, and mathematical algorithms. As a result data mining comprises of more process. This performs analysis and prediction than collecting and managing data. The main objective of data mining is to identify valid, potentially useful, novel and understandable correlations and patterns in existing data. Finding and analyzing useful patterns in data is known by different names (e.g., knowledge extraction, information discovery, information harvesting, data archaeology, and data pattern processing). The term data mining is basically utilized by statisticians, database researchers, and the business communities.

IMPACT OF BLOCK CHAIN IN COMMUNICATION AND NETWORK

A block chain network is a technical infrastructure that provides ledger and smart contract (chain code) services to applications. Primarily, smart contracts are used to generate transactions which are subsequently distributed to every peer node in the network where they are immutably recorded on their copy of the ledger. The users of applications might be end users using client applications or block chain network administrators. First and foremost, block chain is a public electronic ledger built around a P2P system that can be openly shared among disparate users to create an unchangeable record of transactions, each time-stamped and linked to the previous one. Every time a set of transactions is added, that data becomes another block in the chain.

AN ANALYTICAL STUDY ON CLOUD COMPUTING

This paper is about the An Analytical Study on Cloud Computing. Cloud computing is the development of parallel computing, grid computing, distributed computing, and virtualization technologies which define the shape of a new area. In contrast to a variety of benefits related with cloud computing, there are certain challenges as well. These challenges include security, privacy and reliability of data, high costs of data transfers, and regularity in the availability of services, and bugs in large-scale distributed systems. Cloud computing is a method of computing in a place that provides users with the ability of information technology as a service and allows them to have access to these services on the Internet without having limited information. Cloud computing can help businesses transform their closing server infrastructures into dynamic environments, expanding and reducing server capacity depending on their demand. Cloud is a image to describe web as a space where computing has been pre-installed and close as a service; data, operating systems, applications, storage and processing power close on the web ready to be shared. In cloud computing data owners expand their complex data management systems from community sites to the public cloud for great pliability and cost-effective. The searching of this study that highlight there are five main issues related with cloud computing execution which are Mobility and Cloud Government Application security issues, Cloud Security data, cloud security platform, Cloud Security Services and Application, cloud network security issues and infrastructure issues.

IMPACT OF CLOUD COMPUTING ON BUSINESS

Cloud computing is very helpful for a business just because cloud computing helps the small and large business to start a digital business. Due to the rapid growth of computing resources over the past years, cloud computing has been treated as a prominent research field and this technology appeared as a new solution in the IT field. Many businesses including small, medium, and enterprise are migrating to this technology for so many reasons such as availability of computing resources, reduced total cost of ownership, on- demand services, increased revenue, and many more. Cloud Computing offers a number of advantages of cloud migration that motivated business enterprises to adopt this change. Our Prime Minister Mr. Narendra Modi Ji dreams to make a digital India and the cloud could help to make India digital.