VOLUME 7, ISSUE 12, DECEMBER 2019

Abstract: Cloud computing and resource provisioning is solution to different problems presented through starvation and shortage of resources. To this end, Intrusion detection plays a critical role by providing resources to clients as per requirements of clients. This paper presents study of techniques of Intrusion detection and suggests future enhancements as well. Intrusion detection categories including network, storage, data, desktop and server are discussed in detail with results and further improvement to minimize energy consumption is suggested. Optimization in Intrusion detection is achieved considering load balancing degree. Service in terms of storage is frequent since client storage requirements are in demand due to least cost. In addition, platform related requirements are also satisfied frequently. In case of failure of resources VM migration procedures are in place. This paper also put light on issues of VM migration to optimize migration time.

Parameters Considered: Migration time, degree of load balancing, cost, energy consumed

Techniques: Data, Storage, Server, network and desktop Intrusion detection, Pre-Copy, Post Copy and Hybrid approach under LIVE VM migration

Keywords: Intrusion detection, Migration, Migration time, Cost, degree of load balancing

Abstract: Haze is formed due to attenuation and air light processes which degrades the visibility of outdoor images. Haze removal from images provides applications in navigation, remote sensing, satellite image identification, object detection and many vision applications. Single image dehazing methods are based on statistical assumption and essence of the scene. This paper reviewed various single image haze removal algorithms used for dehazing operation in image processing applications.

Keywords: Dehazing, Image enhancement, Image Restoration, Single image

Abstract: Driving fatigue is one of the significant factors that cause road accidents and often result in a huge socio- economic loss to the country. The accurate and reliable driver fatigue state assessment system can reduce the accident rate. In this proposed work, Heart Rate Variability (HRV) derived from Electrocardiography (ECG) is used as input to measure driver fatigue state. Machine learning classifiers like Support Vector Machine (SVM) classifier, Decision Tree, K-Nearest Neighbour (KNN) algorithm, Ensemble bagged tree classifier, Quadratic discriminant method and Deep Auto encoder techniques are used to estimate the driver fatigue state and their performance is also analysed. These machine learning classification systems use HRV features measured in time domain, frequency domain and also nonlinear HRV features. This study was conducted on 10 healthy individuals in simulator driving environment. The results have shown that deep auto encoder technique achieves highest accuracy of 97% in determining the fatigue level of drivers.

Keywords: ECG, HRV, Fatigue, SVM, KNN, Deep Auto Encoder

Objectives of the proposed work are to show that:  Heart Rate Variability (HRV) is one of the strong parameter to indicate the Fatigue Level  To acquire the ECG data from the subject using wearable ECG electrode and to calculate the heart rate using RR-Interval  To make use of the machine learning classifiers for estimating the fatigue level and also make the performance analysis of the classifiers used in the test.

Abstract: To meet the increasing global demand for renewable energy such as wind energy, more and more new wind parks are installed worldwide. Most of the commercial turbines are designed for relatively high wind speeds, around 10m/s, produces insignificant amounts of power below wind speed of 5m/s. Taking a consideration of conventional axial flux, horizontal axis 3-blade wind turbine system this paper as discussed about design aspects of low wind speed turbines.

Keywords: HAWT, Small Turbines, TSR, Low Wind Speed

Abstract: In this paper, a new expression recognition approach is presented based on cognition and mapped binary patterns. At first, the approach is based on the LBP operator to extract the facial contours. Secondly, the establishment of pseudo 3D model is used to segment face area into six facial expression sub-regions. In this context, the sub-regions and the global facial expression images use the mapped LBP method for feature extraction, and then use two classifications which are the support vector machine and softmax with two kinds of emotion classification models the basic emotion model and the circumplex emotion model. At last, we perform a comparative experiment on the expansion of the Cohn-Kanade (CK +) facial expression data set and the test data sets collected from ten volunteers. The experimental results show that the method can effectively remove the confounding factors in the image. And the result of using the circumplex emotion model is obviously better than the traditional emotional model. By referring to relevant studies of human cognition, we verified that eyes and mouth express more emotion.

Facial expression analysis is a remarkable and demanding problem, and impacts significant applications in various fields like human-computer interaction and data-driven animation. Developing an efficient facial representation from the original face images is a crucial step for achieving facial expression recognition. Facial representation based on statistical local features, Local Binary Patterns (LBP) is practically assessed. Several machine learning techniques were thoroughly observed on various databases. LBP features- which are effectual and competent for facial expression recognition are generally used by researchers Cohn Kanade is the database for present work and the programming language used is MATLAB. Firstly, face area is divided in small regions, by which histograms, Local Binary Patterns (LBP) are extracted and then concatenated into single feature vector. This feature vector outlines a well-organized representation of face and is helpful in determining the resemblance among images.

Keywords: Binary pattern, Facial Expression, Gausian Filter, Recognization.

Abstract: Among the many applications of image processing, which are being investigated extensively by researchers at present, noise removal from digital images is one of the most interesting. The criticality of noise removal from digital images has increased in recent years with the advent of modern high-speed communication networks. Multimedia processing has emerged as a major thrust area due to the availability of high bandwidth for users. The current paper proposes an effective novel method for de-noising digital images. Types of noise commonly affecting digital images, and standard techniques used to de-noise digital images are discussed in brief, before demonstrating the superiority of the proposed median filtering method. The method is found to be more effective than many of the standard methods available.

Keywords: Image Processing, Digital Images, De-Noising, Median Filtering

Abstract: The objective of Digital Subscriber Line (DSL) is to propagate signal from the transmitter to the receiver over telephone lines. In communication industry Asymmetric Digital Subscriber Line (ADSL) is widely used because it can handle both phone services and internet access services at same time. As the communication industry develops, its main concern is to maximize the user handling capacity of communication systems. For this purpose, ADSL uses Discrete Multitone (DMT) modulator with QAM bank. But as the number of users increases the system complexity and interference also increases. The communication channel is not free from the effects of channel impairments such as noise, interference and fading. These channel impairments caused signal distortion and Signal to Ratio (SNR) degradation. One method that can be implemented to overcome this problem is by introducing channel coding. Channel encoding is applied by adding redundant bits to the transmitted data. The redundant bits increase raw data used in the link and therefore, increase the bandwidth requirement. So, if noise or fading occurred in the channel, some data may still be recovered at the receiver. While at the receiver, channel decoding is used to detect or correct errors that are introduced to the channel. So first design an Asymmetric Digital Subscriber Line (ADSL) with Discrete Multitone (DMT) modulator having 16-QAM banks. Then analyze this ADSL system with different interleaving schemes to reduce the interference and improve the performance of system

Keywords: DSL, ADSL, DMT, BER

Abstract: The rapid emergence of transport network companies was one of the great surprises in planning and policy in the late 2010s. Many see these private operators disrupting the rigid institutional structures of the past by providing for out of mode transport immediately. Transport network companies (TNCs) have sought to build a range of transport options for consumers across the car transport system, ostensibly by coordinating a multitude of small operators and expanding their services into other forms of transport like bicycles and larger vehicles. Through these smart platforms, it is claimed, consumers can now access the entire car transport system with a single click. The technology revolution has embraced the transport sector, and planners and government agencies have been left scrambling.

Yet like the ride sharing start-ups of the late 1990s and early 2000s, this apparent revolution has occurred on an internal basis, with little nor no thought to how these transformative forces might be integrated with the wider public transport ecosystem. Without the need for any regulatory referent, profitability would appear to be paramount in the delivery of these services. Indeed, the postcode blackspot that was central Los Angeles prior to ex-ante regulation could well be a precursor to some of the more peripheral areas of other developed, α+ city regions. In addition, TNCs and taxi networks now control a substantial proportion of the business decisions of the participating operators.
Still, cities have been slow to learn, and several of these challenges remain unaddressed. As a result, many of the challenges of the past that need addressing in the future now appear to have been replicated on an even larger scale with private operators overtaking the traditional one-mode networks. Much of this is a consequence of the original formulation which assumed that transport equivalence would lead to an equal operating environment on both sides of the transport divide, despite clear evidence across research programs that there were service quality differentials between modes this assumption might benefit the private provider.

Keywords: Connected Mobility,Urban Transport Systems,Mobility-as-a-Service (MaaS),Smart City Infrastructure,IoT in Transportation,Autonomous Vehicles,Real-Time Traffic Management,Urban Mobility Analytics,Shared Mobility Solutions,Electric Vehicle (EV) Integration,Data-Driven Transport Planning,Sustainable Urban Mobility,Mobility Data Platforms,Multimodal Transportation,Dynamic Service Optimization.

Abstract: DevOps is an important concept in the world of software development and deployment that aims at marrying development (Dev) with operations (Ops). Its application throughout organizations has yielded great results. Not only has it bypassed the problems of rigid software processes, but it has increased product velocity, thereby increasing customer satisfaction. Operating with DevOps principles leads to high performing technology organizations. Over the years, technology has advanced. Businesses now desire to act at DevOps speed. Inside the realm of enterprise technology, however, several long-standing problems still exist. Dealing with those problems is often a painful uphill battle. In this paper, we explore DevOps enablement in a legacy insurance enterprise with a multi-decade on-premises primary claim processing infrastructure and address subjects like culture, legacy transition, and individual forms of legacy enablement that allowed a large enterprise to embrace larger transformations while modernizing their infrastructure in a secure, risk-mitigated way. All of this while giving business units, stakeholders to the transformation, the ability to deploy policy or claim changes frequently, thereby providing continual business value. As noted earlier, applying DevOps at the enterprise level has been considered difficult and not something that has been widely practiced. Lessons learned, best practices established, and caveats across several industry verticals of secure DevOps enablement across legacy infrastructure are detailed in this paper. Embracing these practices will provide a seamless but secure DevOps capability for many enterprises running legacy infrastructure inside their firewalls.

Keywords: DevOps, enablement, legacy systems, insurance, infrastructure, Agile, policy deployment, claims deployment, modernization, continuous integration, continuous delivery, CI/CD, automation, digital transformation, system integration, scalability, microservices, containers, cloud adoption, orchestration, API integration, legacy modernization, deployment pipelines, version control, configuration management, monitoring, testing automation, security, compliance, DevSecOps, collaboration, agile workflows.