Advances in Communication, Cloud, and Big Data

Wireless Sensor Networks (WSNs) are made up of small low-power nodes that are used in different areas like environment monitoring and several military and civilian applications. But due to its small size and limited energy source, energy efficiency is its main area of concern, and many methods have been developed to improve its network lifetime. Game Theory is being used in WSNs to improve the energy efficiency of a network and its lifetime. Game Theory is suitable for such problems as it can be used in node or network level to encourage the decision-making capabilities of WSNs. This survey paper focuses on different types of clustering protocols designed in WSNs using Game Theory to combat the problem of energy efficiency. In particular, we address the approaches by which Game Theory has been used in WSNs to improve its network lifetime including the games used in each protocol.

This paper investigates the design of power and spectrally efficient coded modulations based on amplitude phase shift keying (APSK) modulation with application to satellite broadband communications. This paper presents the error rate analysis of circular APSK modulation with additive white Gaussian noise (AWGN) channel, and an approach to design optimum APSK configuration is being discussed. A circular APSK constellation can have a large number of configurations based on the number of points present in each ring and a total number of rings, which have variable bit error rate based on the configuration. The approach tries to find the optimum APSK configuration and analyzes their performance in Rician and AWGN channels.

The twenty-first century can be said as the era of engulfing data. From social networking sites to politics, from businesses to education, all sectors of the modern world are flooded with voluminous data. As Alan Kay quotes “this is the century in which you can be proactive about the future; you don’t have to be reactive”, big data analytics can be the tool and the need of the future to predict the trends, detect the challenges, and leverage the opportunities. Among various sectors like business, social networks, entertainment, politics, educational institutions are seen and expected socially to be more transparent and accountable. With these growing concern and hunger for the academic excellence both to individuals and institutions as well, it becomes inevitable to implement big data analytics in the educational institutions. Its proper implementation can bring the revolutionary development on the education sector. Instead of some inherent challenges, big data analytics can represent customized learning environments to the learners, can reduce potential dropouts, lower the academic risks, complexity could be reduced and can enhance the quality of education system as a whole. The main objective of this paper is to highlight on the emergent need and scope of big data analytics in the educational sector.

Land capability classification for agriculture assesses the land based on various land capability factors and variables to produce thematic land capability mapping for economical and sustainable agriculture. The main objective of this paper is to survey the important available GIS and remote sensing-based methods proposed for land capability classification. The influence of different capability factors and their sources is also discussed. Furthermore, the scopes of present-day GIS and remote sensing technology for land characterization with important terminologies used are also reviewed.

The paper is a survey of vehicular radar for road safety. Vehicular radar is also called automotive radar. It is introduced for avoiding collision and for reducing human and economic losses in road accidents. Automotive radar functions to detect objects and obstacles in its surrounding area and to prevent collision. Its other applications include speed sensing, predictive crash sensing, collision mitigation, and automatic braking which are addressed in this survey. This paper presents recent approaches done in automotive radar and trend and requirements of autonomous driving.

Cloud robotics is one of the important and upcoming technologies of the twenty-first century. It is in actual fact a computing system which is distributed in nature, and the processing is performed over the cloud, for computation of huge amount of tasks. Cloud services help robots to find its application, both in the indoor or outdoor environment for various purposes in our everyday life. Before the advent of cloud, the robots were mostly independent and performed computation and storage in the onboard computer or microchip. This led to huge overhead on the processing power of the robot. Therefore, the survey is organized around two major aspects of robot navigation, i.e. robotics with onboard information and robotics with cloud infrastructure. This paper highlights the change in the technologies for robot navigation and the benefits of cloud infrastructure.

Image segmentation is a complex and essential task used in many computer vision applications. The problem of image segmentation can essentially be formulated as a grouping problem which in its simplest form tries to group the pixels of image into distinguished regions of interest so that further processing of the extracted regions can be achieved. This work proposes an image segmentation model which is inspired by the findings in cognitive psychology theories to divide the image into separate coherent regions. The proposed work tries to correlate between human and machine cognition by studying the segmentation process under the light of psychology of human vision.

The computer vision field deals with the problem of understanding the scene or features in images of real world with the help of image processing and pattern recognition techniques. The main complication in this task is that the objects present in the images may have different appearances to the camera due to illumination effects, camera position, shadows, types of camera, etc. Nevertheless, with the advancement of technologies, today computer vision has provided reliable methods for various tasks like object classification, action recognition, autonomous driving, scene analysis, highlights extraction in videos and many more. But the problem of automatic qualifying is that how well people perform these actions has been largely unexplored. Human visual system and cognition can outperform the performance of computer vision algorithms. The objective of this paper is to highlight the state of the art of various psychological views of human visual perception in computer vision methods that have been found to operate well and that led up to the above-mentioned capabilities.

This paper analyzes the main models of collaboration in a particular existing Web site and develops a Web Content Management System (CMS). This development can help Web developers by giving overview of building and maintaining Web sites. It is faster and user friendly. It also provides easy maintenance and further updating and better facility to upload documents instantly and better appearance as well. Corporate information can be created and managed using this CMS. This management system and back-end databases allows easy updating a Web site. Content authors and marketers need the ability to change content quickly and easily. It is accessible from any computer that is connected to Internet. CMS can be used for page updating on the fly, change or upload images, and add dynamic contents to different files. It provides the developers with ready to use themes, and thus, it is a time-saving and easy operation as there is the requirement of less coding work. Here need for a CMS and system requirements to support a large content management system is described. Feedback from technical personnel also provided. It covers the complete lifecycle of the pages on site. It provides simple tools to create the content and to publish and finally to archive.

Vehicular ad hoc network (VANET) is a category of mobile ad hoc network (MANET). VANET provides wireless communication among vehicle-to-vehicle (V2V) and vehicle to a computing device located on roadside infrastructure called Road Side Unit (RSU). The communication between vehicles can be used for safety provisioning and emergency awareness by exchanging information among traffic participants to realize a cooperative and more efficient transportation system. An important issue associated with V2V communications used for traffic safety and emergency awareness applications (TSEAAs) is better routing with the Quality of Service (QoS) support. This paper reviews the existing QoS routing protocols based on the two important parameters: link efficiency and link stability.

A compact multiband diamond-shaped fractal bow-tie terahertz antenna is designed on FR4_epoxy substrate with permittivity 4.4. The dimension of substrate is 4 × 6 × 1.5 mm³. Multi-bands are obtained in S₁₁ versus frequency plots. The effects of creating defects in the ground plane of the antenna were studied and analyzed to get the optimized performance of antenna in the frequency bands at 0.500, 0.560, and 0.594 THz, respectively.

Mobile ad hoc networks (MANETs) represent a class of networking that is quite essential and different from the traditional systems. Though the use of MANETs is gaining popularity in academic and commercial domains, MANETs have been initially designed to be deployed in areas such as emergency search and rescue operations, military battlefields, and other hostile or challenging environments. Because of the demanding environments that they have to operate in, MANETs do not have well-defined infrastructure unlike wired networks. All the participating nodes in a MANET work via cooperation and hence central coordination is absent. This places an inherent trust among the nodes forming the network in a MANET. Another major consideration regarding MANETs is that they have to often deal with limited resources such as power and bandwidth. These characteristic properties of MANETs make them susceptible to different kinds of attacks which aim to find vulnerabilities in the MANET protocols or target the limited resources. Hence, it becomes essential to recognize these threats and find ways to mitigate and tackle them. This paper will emphasize in understanding threats in ad hoc networks and the approaches to deal with these threats.

Human–computer interaction (HCI) has become one of the important aspects in human life. Signals generated from human body are biosignals and have huge potential to be used as an interface for human–computer devices. Multiple devices are present that recognize these biosignals which are generated during muscle contraction and converting those signals into some command to be used as an input to the HCI devices. However, the task can be acquired through biosignals which forms a neural linkage with the computer techniques like electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG). In past, there have been lots of studies wherein many researchers have used biosignals to control other device. EMG is hence one of the least explored mechanism form of biosignal to be deployed in HCI, and its studies are useful for neuromuscular system as certain diseases may slow down muscle contraction and muscle firing leading to paralysis of muscle.

Medium Access Control (MAC) protocol will play a very critical role in achieving the desired Quality of Service (QoS). The other crucial factor a MAC control is the total amount of energy spent by the network, which is very essential in determining the lifetime of the network. This paper argues that IEEE 802.15.4 can act as a suitable MAC protocol for application such as Internet of Things. The paper presents an overview on IEEE 802.15.4 protocol’s working mechanism. Further, the paper also discusses certain issues need to be overcome for successful deployment of IEEE 802.15.4 in Internet of Things (IoT) to get the desired performance.

Speech, the act of speaking, is the most natural way of exchanging information between homo sapiens. Speech primarily conveys the message via words, spoken by the speaker. Speech also conveys the emotion with which the speaker speaks, speaker’s health condition, gender of the speaker, and also the language in which the speaker is speaking. Systems which aim to recognize the speaker-related information in speech signals through an extraction and characterization process are called speaker recognition systems. Speaker recognition applications are becoming common and useful nowadays as many of the modern devices are designed and produced for the convenience of the general public. Speaker recognition systems are developed for many indigenous languages. Application of hidden Markov models (HMMs) to speaker recognition has seen considerable success and gained much popularity. This paper presents an attempt made toward developing a speaker gender recognition system. A model built using Hidden Markov Model Toolkit (HTK 3.4.1) has been trained and tested on sample speech of either gender in Bodo language, and results show good recognition.

The extraction of the drainage hydrographical network is very important for various types of study such as hydrological analysis, geomorphology, environmental science, terrain analysis and still a research topic in the field of GIS. Drainage network is extracted through satellite image (e.g., digital elevation model) processing, contour map processing, and raster map processing. A raster map of an area contains many layers such as road network, building, forest area, waterbody, river pattern, text, and drainage pattern extracted from raster map is part of document image analysis. A toposheet or contour map contains the linear feature, namely elevation contour, waterbody, river network, text, and the extraction process of drainage line is time-consuming and traditional process. Due to the advances in satellite imagery, high-resolution digital elevation model (DEM) is captured by many satellites recently. The DEMs are advantageous over toposheet because it provides seamless provision of data with global coverage. Accurate drainage extraction from DEMs is used for morphometric analysis, hydrological analysis, terrain analysis, and many other areas in recent year across the world as DEM provides the fastest way to extract feature in various ways. This paper provides the evolution of satellite imagery and the accurate extraction of drainage network for various applications, namely geomorphometric analysis, hydrologic analysis, terrain analysis, and also describes the steps involved to extract drainage pattern from DEM, an up-to-date process.

Mobile ad hoc network is an infrastructure-less network where the nodes are mobile and each node behaves as a router. There are many routing protocols in MANET which are used to govern the path from the source node to destination node. Many problems are associated with the MANET due to its wireless nature and the dynamic topologies, so this survey paper focuses on behavior of Transmission Control Protocol in reactive and proactive routing protocols of MANET which are DSDV, AODV, and DSR.