Efficient compression and network adaptive video coding for distributed video surveillance

The availability of cheap network based video cameras and the prevalence of wireless networks has lead to a major thrust towards deployment of large scale Distributed Video Surveillance (DVS) systems. This has opened up an important area of research to deal with the issues involved in DVS system for efficient collection and transmission of large scale video streams from the cameras at the guarded sites, to the end users in possibly constrained network conditions. In this paper, we propose a framework based on content-based video classification and scalable compression scheme to provide a robust bandwidth efficient video transmission for DVS. The scheme builds on a Discrete Wavelet Transform (DWT) based Color-Set Partitioning for Hierarchical Trees (CSPIHT) coding to obtain a scalable bitstream. Wavelet domain segmentation and compression assists in development of a DVS architecture. The architecture includes a novel module for dynamic allocation of Network bandwidth based on the current available resources and constraints. Different frame constituents are optimally coded based on their relative significance, perceptual quality, and available estimate of network bandwidth. Experimental result over different video sequences and simulations for Network conditions demonstrate the efficient performance of the approach.     

OS-Guard: on-site signature based framework for multimedia surveillance data management

This paper presents OS-Guard(On-Site Guard), a novel on-site signature based framework for multimedia surveillance data management. One of the major concerns in widespread deployment of multimedia surveillance systems is the enormous amount of data collected from multiple media streams that need to be communicated, observed and stored for crime alerts and forensic analysis. This necessitates investigating efficient data management techniques to solve this problem. This work aims to tackle this problem, motivated by the following observation, more data does not mean more information. OS-Guard is a novel framework that attempts to collect informative data and filter out non-informative data on-site, thus taking a step towards solving the data management problem. In the framework, both audio and video cues are utilized by extracting features from the incoming data stream and the resultant real valued feature data is binarized for efficient storage and processing. A feature selection process based on association rule mining selects discriminant features. A short representative sample of the whole database is generated using a novel reservoir sampling algorithm that is stored onsite and used with an support vector machine to classify an important event. Initial experiments for a Bank ATM monitoring scenario demonstrates promising results.     

Windows in the workplace: examining issues of environmental sustainability and occupant comfort in the selection of multi-glazed windows

Windows are important in the workplace for both environmental and psychological reasons. Good glazing design can reduce energy outputs by lowering the requirements for heating or cooling; frame design can utilise more sustainable materials and those with lower embodied energy, such as timber and aluminium-clad timber. Windows are also important for the provision of daylight and a view, both of which have known psychological benefits, although glare and passive solar gain can be problematic.Three studies were undertaken to look at sustainability and comfort issues for a number of different types of multi-glazed windows. Focus groups and interviews with professionals were used to examine issues of sustainability and productivity. Four case study buildings were surveyed to examine the level of energy use for different glazing specifications. A post-occupancy survey was then used to examine the level of comfort in these buildings. Results showed that architects consider comfort and productivity in their designs, but consider sustainability less often. Surveys of energy usage showed that building design can influence the efficiency of multi-glazed windows; this result was mirrored in the post-occupancy survey where design factors influenced occupant comfort. The research concludes that comfort and productivity in the workplace is related more to design factors than to sustainability factors.     

A machine learning based IoT for providing an intrusion detection system for security

Digital communication is provided with an effective communication platform to share and transfer information. The emergence of the Cyber-Physical System (CPS) is a platform incorporated with electronic devices that enables the services through a digital platform. The considerable challenges of this system are security issues, abnormality, and service failure. Hence, the requirement of providing an effective system, which should be overcome these issues. This paper analyzes these problems and providing the paradigm in terms of enhanced communication paradigm, specifically propose Energy Aware Smart Home (EASH) framework. With this work, the problem in communication failures and types of network attacks are analyzed in EASH. With the utilization of the machine learning technique, the abnormality sources of the communication paradigm are differentiated. To evaluate the performance, we analyze the proposed work based on its accuracy, performance, and efficiency. Hence, we obtain better results especially the result shows an 85% accuracy rate. In the future, we try to enhance a high accuracy rate for further development.     

Experimental optimization of dry sliding wear behavior of in situ AlB2/Al composite based on Taguchi’s method

A wear rate prediction model for aluminum based composites reinforced with 10 and 30 wt.% in situ aluminum diboride (AlB₂) flakes was developed using Taguchi’s method by considering the parameters of sliding velocity, normal load, sliding distance and reinforcement ratio. Having produced the in situ reinforced bulk of composite, the final shape of the test samples was given through squeeze casting method. The wear behavior of the specimen was investigated using pin-on-disk rig where the samples sliding against a steel disk under different conditions. The orthogonal array, signal-to-noise ratio (S/N) and analysis of variance (ANOVA) were employed to study the optimal testing parameters on composite samples. The experimental results demonstrate that the normal load and reinforcement ratio were the major parameters influencing the specific wear rate for all samples, followed by sliding velocity. The sliding distance, however, was found to have a negligible effect on the specific wear rate. Moreover, the optimal combination of the testing parameters has been predicted. The predicted specific wear rates for all the test samples were found to lie close to that of the experimentally observed ones.     

Reliability-based design recommendations for composite corrugated-web beams

Developments and advances in fabrication technology have led to a new generation of structural shapes in the composite construction market, among them, the composite sinusoidal-web girder. A sinusoidal-web girder is a built-up I-girder with a thin-walled corrugated web (with a sinusoidal profile) and flat plate flanges. The corrugated web considerably increases the rigidity and the resistance to shear forces and local effects, thus reducing the occurrence of local and shear buckling. In spite of the advantages this type of composite construction may offer, there are no standards addressing the design of such girders. In this paper, the development of reliability-based design recommendations for both composite sinusoidal beams and their connections to adjacent elements is reported. To this end: (i) finite-element models for connections and composite girders are developed and validated, (ii) theoretical models are proposed, (iii) reliability analyses are performed, and (iv) implicit reliability levels are checked against current practice. It is shown that the proposed theoretical models, despite all the complexities involved, are in good agreement with both experimental and numerical analyses. It is found that the safety levels resulting from the proposed design recommendations are consistent with current trends in structural engineering practice.     

Microstructure study and constitutive modeling of Ti–6Al–4V alloy at elevated temperatures

A reliable and accurate prediction of flow behavior of metals in industrial forming process considering the coupled effects of strain, strain rate and temperature is crucial in understanding the workability of the metal and optimizing parameters for hot forming process. In this study, the tensile fracture behavior of the Ti–6Al–4V alloy is examined with scanning electron microscope (SEM) over the range of magnifications. SEM study revealed that microvoids and shallow dimples are observed at the fracture surface which indicates the fracture is predominately ductile in nature. Also, an investigation on flow behavior of Ti–6Al–4V alloy is done using constitutive models. Four constitutive models; modified Johnson-Cook (m-JC), modified Arrhenius type equations (m-Arr), modified Zerilli–Armstrong (m-ZA) and Rusinek–Klepaczko (RK) models are developed to predict the flow stress. The predictions of these constitutive models are compared with each other using statistical measures like correlation coefficient, average absolute error and its standard deviation. Comparing the statistical measures, m-Arr model is a better model for predicting the flow stress, but considering the fact that m-ZA model is a physical based model, m-ZA model is preferred over the m-Arr model.     

Wear properties of friction stir processed AISI D2 tool steel

Influences of microstructural and textural properties of friction stir processing (FSP) on dry reciprocating wear properties of AISI D2 tool steel are investigated in this study. The mechanical improvement is attributed not only to the homogenous distribution of very small carbides in a refined matrix, but also to significant development of textures during FSP. The excellent wear resistance is ascribed to nanohardness enhancement of the FSPed steel. Dominant shear components of {111} 〈110〉 and {112} 〈111〉 with the lowest Taylor׳s factor and the high density of close-packed planes formation significantly enhance the wear resistance of FSPed sample at 500 rpm.