The PASCAL Visual Object Classes Challenge

Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning models used in the general application of energy consumption. Through a novel search and taxonomy the most relevant literature in the field are classified according to the ML modeling technique, energy type, perdition type, and the application area. A comprehensive review of the literature identifies the major ML methods, their application and a discussion on the evaluation of their effectiveness in energy consumption prediction. This paper further makes a conclusion on the trend and the effectiveness of the ML models. As the result, this research reports an outstanding rise in the accuracy and an ever increasing performance of the prediction technologies using the novel hybrid and ensemble prediction models.

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Energy consumption prediction using machine learning: A review

This paper presents a hierarchical self organizing neural network model and its application in the learning of the trajectory distribution patterns for event recognition. By linking the side neurons, some lines are formed. Each line becomes an internal net of the hierarchical self organizing neural network. Corresponding to the hierarchical self organizing neural network model, the authors define two neighborhoods, namely the neuron neighborhood and the internal net neighborhood. The neurons in both neighborhoods will update their weights to different extent. In this way, the trajectory distribution patterns can be learned. Using the learned patterns, the authors consider both local and global anomaly detection as well as object behavior prediction. Experimental results demonstrate the effectiveness of the approach to trajectory analysis.

A Hierarchical Self-Organizing Approach for Learning the Patterns of Motion Trajectories

We present results of measurements of fluorescence spectra due to the in- teraction of a Ti:sapphire laser pulse with N2 molecules at different gas pressures and pulse energies. The analysis of the data together with the results of numerical simu- lations, using a propagation model, reveal signatures of the phenomena of intensity clamping and of re-focusing of the laser pulse at high gas pressure. The laser pulse energy for intensity clamping as a function of the gas pressure is determined.

http://rd.springer.com/content/pdf/10.1007%2Fs003400100637.pdf

Intensity clamping and re-focusing of intense femtosecond laser pulses in nitrogen molecular gas

Named Data Networking (NDN) is a future Internet architecture, which locates the requested content using unique content names for effective content distribution. The very nature of Vehicular Adhoc Networks (VANETs), where the nodes are constantly mobile, has a high influence on the process of connection establishment, making it a challenging task. Hence, the attributes of NDN have been adapted into VANETs and is termed as Vehicular Named Data Networks (VNDN). VNDN locates the requested content within the vehicular network domain using the content name instead of its locale. Every node that requires a specific content sends out an Interest packet as a means of request and keeps waiting for the corresponding Data packet. A Time To Live (TTL) field is maintained in every Interest packet to restrict its broadcast scope. A record of each incoming Interest that is yet to be fulfilled is maintained as a Pending Interest Table (PIT). Each PIT record is kept for a specific period of time, termed as PIT Entry Lifetime (PEL). The PIT entry is removed when the Data packet arrives at the node or if the lifetime of an entry expires. The loss of Interest and Data packets are frequent due to the dynamic topology of VANETs causing an increase in PIT size depending on the PEL. A fixed PEL value of 4 seconds in Vanilla NDN does not seem to reduce the PIT size, thereby leading to packet drops, which in turn would affect the overall efficiency of VNDN. In this work, a hop limit based PEL estimation mechanism is proposed, where each vehicle that forwards the Interest estimates the PEL and reduces the PIT size.

Pending Interest Lifetime Mechanism for Vehicular Named Data Networks

Wireless networking technology is becoming increasingly popular but, at the same time, has introduced many security issues WEP standards are followed in WLANs for providing security But WEP is fatally crippled by the fact that WEP keys are the same for all users, all sessions and never changes and its poor implementation of the RC4 encryption scheme The authentication mechanism is based on a  simple challenge-response protocol The main problem with the previously used method was same key was used for both encryption and authentication But the proposed authentication is by means of certificates using Extensible Authentication Protocol and a session key is transferred after successful authentication between mobile node and server This session key is then used for encrypting messages using Advanced Encryption Standard between mobile node and server

https://innovareacademics.in/journals/index.php/ajpcr/article/viewFile/19987/11379.pdf

Advanced encryption and extended authentication for wireless lan

The objective of this study is to develop the design of a generic infrastructure for on-demand applications for intelligent transport systems (ITS) in an urban area. The main idea of the study is to allow seamless service composition and consumption, but also to allow rapid deployment of new services through the pooling of different devices and access networks that may be owned and operated by different actors such as telecom operators, transportation service operators, governmental organizations, etc. This research serves the solution for the problem of interoperability between different devices, on the fly device reconfiguration and service discovery.

/pdf/universal-infrastructure-of-m2m-enabled-inter-cloud-services-4shkfr66uc.pdf

Universal infrastructure of m2m enabled inter-cloud services for intelligent transportation system

Despite the wide adoption of distributed computing with several webs standards and cloud technologies; building of city wide health management system for smart city platform is a daunting task. Owing to the limitations in sparse learning of disease outbreak and its dynamic nature. As it would require development of a scalable, distributed and evolving architecture on the web; where a sparse machine learning based algorithm will enable authorities collaborate in preventing, controlling and responding to a specific disease outbreak and its time factor analysis.  In this work, a mathematical system model is presented for sparse learning in Geographic Information System (GIS) based architecture to support continuity of microservices in health management setting. The model is able to continually cope with the transformation in architecture to match with the system goals of microservices and anticipate the evolutionary aspects of the architecture configuration.

/pdf/mathematical-architecture-of-microservices-for-geographic-21y629ncjl.pdf

Mathematical architecture of microservices for geographic information system based health management system

This study presents a modeling method for control system of multi-coupled non-linear cyber physical system with the help of second-order dynamics of communicating membrane system of neuronal popula...

Consensus-based decision making in non-linearly multi-coupled IoT networked SLAM operations:

. In this article we consider the geometrical iterative process deﬁned by the Kasner triangles with a ﬁxed real weight. The main results about the convergence of this process are given in Section 2. The proofs are elementary and use the general theory of the second order linear recurrences. In the remark after the proof a higher level approach is presented.

Jagadeesh Kannan R

Papers

Advanced encryption and extended authentication for wireless lan

Universal infrastructure of m2m enabled inter-cloud services for intelligent transportation system

Mathematical architecture of microservices for geographic information system based health management system

Consensus-based decision making in non-linearly multi-coupled IoT networked SLAM operations:

Dynamic geometry of kasner triangles with a fixed weight