Natural calamity

The advanced technology Internet of Things (IoT) visualizes a worldwide, that is, internally connected, networks of smart physical entities. IoT is a promising technology used in several applications including disaster management. In disaster management, the role of IoT is so important and ubiquitous and could be life-saving. This article describes the role of IoT in disaster management. More precisely, it presents IoT-based disaster management for different kind of disasters with a comparison between some solutions that are available in the market. It shows an implementation of some examples of the application of IoT such as early-warning system for fire detection and earthquake and represents some approaches talking about the application, IoT architecture, and focusing of the study on different disasters. This study could be a good guide to stakeholder about the use of IoT technology to secure their smart cities’ infrastructure and to manage disaster and reduce risks.

The importance of disaster management is evident by the increasing number of natural and manmade disasters such as Irma and Manchester attacks. The estimated cost of the recent Irma hurricane is believed to be more than 80 billion USD; more importantly, more than 40 lives have been lost and thousands were misplaced. Disaster management plays a key role in reducing the human and economic losses. In our earlier work, we have developed a disaster management system that uses VANET, cloud computing, and simulations to devise city evacuation strategies. In this paper, we extend our earlier work by using deep learning to predict urban traffic behavior. Moreover, we use GPUs to deal with compute intensive nature of deep learning algorithms. To the best of our knowledge, we are the first to apply deep learning approach in disaster management. We use real-world open road traffic within a city available through the UK Department for Transport. Our results demonstrate the effectiveness of deep learning approach in disaster management and correct prediction of traffic behavior in emergency situations.

The advanced technology Internet of Things (IoT) visualizes a worldwide, that is, internally connected, networks of smart physical entities. IoT is a promising technology used in several applications including disaster management. In disaster management, the role of IoT is so important and ubiquitous and could be life-saving. This article describes the role of IoT in disaster management. More precisely, it presents IoT-based disaster management for different kind of disasters with a comparison between some solutions that are available in the market. It shows an implementation of some examples of the application of IoT such as early-warning system for fire detection and earthquake and represents some approaches talking about the application, IoT architecture, and focusing of the study on different disasters. This study could be a good guide to stakeholder about the use of IoT technology to secure their smart cities’ infrastructure and to manage disaster and reduce risks.

The advanced technology Internet of Things (IoT) visualizes a worldwide, that is, internally connected, networks of smart physical entities. IoT is a promising technology used in several applications including disaster management. In disaster management, the role of IoT is so important and ubiquitous and could be life-saving. This article describes the role of IoT in disaster management. More precisely, it presents IoT-based disaster management for different kind of disasters with a comparison between some solutions that are available in the market. It shows an implementation of some examples of the application of IoT such as early-warning system for fire detection and earthquake and represents some approaches talking about the application, IoT architecture, and focusing of the study on different disasters. This study could be a good guide to stakeholder about the use of IoT technology to secure their smart cities’ infrastructure and to manage disaster and reduce risks.

The importance of disaster management is evident by the increasing number of natural and manmade disasters such as Irma and Manchester attacks. The estimated cost of the recent Irma hurricane is believed to be more than 80 billion USD; more importantly, more than 40 lives have been lost and thousands were misplaced. Disaster management plays a key role in reducing the human and economic losses. In our earlier work, we have developed a disaster management system that uses VANET, cloud computing, and simulations to devise city evacuation strategies. In this paper, we extend our earlier work by using deep learning to predict urban traffic behavior. Moreover, we use GPUs to deal with compute intensive nature of deep learning algorithms. To the best of our knowledge, we are the first to apply deep learning approach in disaster management. We use real-world open road traffic within a city available through the UK Department for Transport. Our results demonstrate the effectiveness of deep learning approach in disaster management and correct prediction of traffic behavior in emergency situations.

The advanced technology Internet of Things (IoT) visualizes a worldwide, that is, internally connected, networks of smart physical entities. IoT is a promising technology used in several applications including disaster management. In disaster management, the role of IoT is so important and ubiquitous and could be life-saving. This article describes the role of IoT in disaster management. More precisely, it presents IoT-based disaster management for different kind of disasters with a comparison between some solutions that are available in the market. It shows an implementation of some examples of the application of IoT such as early-warning system for fire detection and earthquake and represents some approaches talking about the application, IoT architecture, and focusing of the study on different disasters. This study could be a good guide to stakeholder about the use of IoT technology to secure their smart cities’ infrastructure and to manage disaster and reduce risks.

This paper attempts to provide a minimal disaster management framework for the elderly who are living alone. Elderly people are generally vulnerable to hazards and emergency situations. The proposed framework aims at developing an IoT based intelligent, protective ecosystem for elderly that calls for help in emergencies like flood, earthquake, home fire, volcanic eruption, and storms. This disaster system makes use of a range of calamity sensors in conjunction with in house activities of the elderly subject. In the case of mishappening, the disaster relief authorities, community members, and other stakeholders will be instantly informed. All these sensors are powered through an uninterrupted electricity supply system which will continue to work even in case of power outages. The work carried out in this paper is deeply inspired by the need to have holistic platforms which ensure low-cost, robust, and responsive disaster alert system for the elderly (DASE) in place. Our objective is to overcome many of the shortcomings in the existing systems and offer a reactive disaster recovery technique. Additionally, this paper also incorporates the need to take care of numerous important factors, for instance, the elderly individual's limited physical and cognitive limitations, ergonomic requirements, spending capacity, etc.

"Doomsday" or "the End" is a favourite topic of Astrologers. In this article we analyse the factors leading up to the End of the Current Epoch and speculate on the circumstances leading to it. As part of this speculation we present a novel approach to calculation of Population at the end of an Epoch. Underlying these calculations is a correlation for Population based on Contemporary as well as Geological Timescale. The equation for Population of the World is quite similar on both timescales. The periods of history analysed are based on Hindu Scriptures. Speculation on how the End will come about and the countries likely to be impacted is also included. We are sure the article will be of interest to all readers. The idea is to inform not frighten the public on this favourite topic.

This paper attempts to provide a minimal disaster management framework for the elderly who are living alone. Elderly people are generally vulnerable to hazards and emergency situations. The proposed framework aims at developing an IoT based intelligent, protective ecosystem for elderly that calls for help in emergencies like flood, earthquake, home fire, volcanic eruption, and storms. This disaster system makes use of a range of calamity sensors in conjunction with in house activities of the elderly subject. In the case of mishappening, the disaster relief authorities, community members, and other stakeholders will be instantly informed. All these sensors are powered through an uninterrupted electricity supply system which will continue to work even in case of power outages. The work carried out in this paper is deeply inspired by the need to have holistic platforms which ensure low-cost, robust, and responsive disaster alert system for the elderly (DASE) in place. Our objective is to overcome many of the shortcomings in the existing systems and offer a reactive disaster recovery technique. Additionally, this paper also incorporates the need to take care of numerous important factors, for instance, the elderly individual's limited physical and cognitive limitations, ergonomic requirements, spending capacity, etc.

Today, natural calamity and accidents are a big problem in the world as a consequence of the rise in reckless driving. Incidents are blamed for a significant amount of crashes, fire, derailment incidents every year. The study explores dif erent techniquesfor disaster mitigation and management. At first, a survey is presented about the dif erent techniques used by the users with the purpose of mitigation and management. Afterwards a comparison is done based on the survey done to identify the preferred choice of users and the results indicated that around 90% of the users preferred a combination of IoT and cloud technologies. Even survey conducted by bain is presented which shows the Percentage of users giving positive response for deploying IoT in research.

Today, natural calamity and accidents are a big problem in the world as a consequence of the rise in reckless driving. Incidents are blamed for a significant amount of crashes, fire, derailment incidents every year. The study explores different techniquesfor disaster mitigation and management. At first, a survey is presented about the different techniques used by the users with the purpose of mitigation and management. Afterwards a comparison is done based on the survey done to identify the preferred choice of users and the results indicated that around 90% of the users preferred a combination of IoT and cloud technologies. Even survey conducted by bain is presented which shows the Percentage of users giving positive response for deploying IoT in research.

Today, natural calamity and accidents are a big problem in the world as a consequence of the rise in reckless driving. Incidents are blamed for a significant amount of crashes, fire, derailment incidents every year. The study explores different techniques for disaster mitigation and management. At first, a survey is presented about the different techniques used by the users with the purpose of mitigation and management. Afterwards a comparison is done based on the survey done to identify the preferred choice of users and the results indicated that around 90% of the users preferred a combination of IoT and cloud technologies. Even survey conducted by bain is presented which shows the Percentage of users giving positive response for deploying IoT in research.

The (IoT) is a narrative paradigm, which is contemplate to apply to a diversity of promising areas applications to access wireless communication system and artificial information technologies. Meanwhile, the emerging cellular network infrastructure of the fifth generation provides the opportunity to install big sensors in IOT & to procedure massive data that threatens communications technology and data mining. A novel model has been proposed for 5G Intelligent Internet of Things, for intelligent management of big data and maximizing channels of communication. First of all, author articulate the 5G and IOT concept and introduce three main 5G and IOT components. Then the author will explore the relationships between these elements and present the main methods & techniques depend on our  suggested model, including the big data mining. Furthermore, an experimental test assesses the efficiency of 5G and IOT and greatly improves the efficient use of channels and QoS. Eventually, there will be a discussion on different systems and transparent problems.

Today, natural calamity and accidents are a big problem in the world as a consequence of the rise in reckless driving. Incidents are blamed for a significant amount of crashes, fire, derailment incidents every year. The study explores dif erent techniquesfor disaster mitigation and management. At first, a survey is presented about the dif erent techniques used by the users with the purpose of mitigation and management. Afterwards a comparison is done based on the survey done to identify the preferred choice of users and the results indicated that around 90% of the users preferred a combination of IoT and cloud technologies. Even survey conducted by bain is presented which shows the Percentage of users giving positive response for deploying IoT in research

Today, natural calamity and accidents are a big problem in the world as a consequence of the rise in reckless driving. Incidents are blamed for a significant amount of crashes, fire, derailment incidents every year. The study explores dif erent techniquesfor disaster mitigation and management. At first, a survey is presented about the dif erent techniques used by the users with the purpose of mitigation and management. Afterwards a comparison is done based on the survey done to identify the preferred choice of users and the results indicated that around 90% of the users preferred a combination of IoT and cloud technologies. Even survey conducted by bain is presented which shows the Percentage of users giving positive response for deploying IoT in research.

Today, natural calamity and accidents are a big problem in the world as a consequence of the rise in reckless driving. Incidents are blamed for a significant amount of crashes, fire, derailment incidents every year. The study explores different techniques for disaster mitigation and management. At first, a survey is presented about the different techniques used by the users with the purpose of mitigation and management. Afterwards a comparison is done based on the survey done to identify the preferred choice of users and the results indicated that around 90% of the users preferred a combination of IoT and cloud technologies. Even survey conducted by bain is presented which shows the Percentage of users giving positive response for deploying IoT in research.

This paper talks about the prediction of types of landslides. It employs Random Forest Classifier technique, the ensemble version of Decision Trees. The results of the experiment show that ensemble techniques provide a better result compared to other algorithms. The dataset used here, in this paper, is Landslides After Rainfall dataset from NASA. This model achieves 59% accuracy without feature selection and 84% accuracy with feature selection.

"Doomsday" or "the End" is a favourite topic of Astrologers. In this article we analyse the factors leading up to the End of the Current Epoch and speculate on the circumstances leading to it. As part of this speculation we present a novel approach to calculation of Population at the end of an Epoch. Underlying these calculations is a correlation for Population based on Contemporary as well as Geological Timescale. The equation for Population of the World is quite similar on both timescales. The periods of history analysed are based on Hindu Scriptures. Speculation on how the End will come about and the countries likely to be impacted is also included. We are sure the article will be of interest to all readers. The idea is to inform not frighten the public on this favourite topic.

Following is Adiyen's humble attempt to analyse past history of World Population and take a shot at when we are likely to exceed a population of 10 billion. Historically (based on Hindu beliefs) change of Eon or YUGAM has taken place when population increases by a factor of 10 and reduces average age by a factor of 10. Based on this one-tenth rule we expect a YUGA PARIVARTHANAM (Change of Eon) by as near as year 2022. Let us all brace to welcome the new YUGAM and take steps for Survival.

The web is full of the content which is either in complete or semi unstructured form and retrieving the essential data out of this unstructured form is very difficult so the concept of the information extraction (IE) keeping in view the necessary parameters becomes highly essential. This paper presents a comparative study for how the problem of information extraction can be handled for a dataset by taking the first step towards IE of named entity recognition (NER) into consideration. Various classifiers/techniques and impact of pipeline on some of them is discussed in this paper for NER and based on the results with keeping the due response time into consideration the classifier/technique of conditional random fields for NER serves out to be the best with an average recall and precision of 0.97 each helping in predicting efficiently of whether a given word is a part of the named entity or not. The automation in the field of medical science for search of the patient for clinical trials from the clinical databases serves to be the most important area of concern at the present time & this paper provides an approach for choosing the technique according to parameters, also discussing the results of the novel algorithmic approach.

ABSTRACT:
The Back propagation Algorithm is a multilayered, feed forward neural network and is one of the most popular and efficient techniques used. This can be used for dataset classification with suitable combination of training, learning and transfer functions. However, there are some problems associated with this Algorithm like Step-size Problem and Local Minima. In this paper we will discuss about the working of the algorithm and efficient ways to perform learning by overcoming the problems in it. We use three common classification problems to illustrate the ways of efficient learning. All the methods and algorithms were implemented using the features of Java.

Keywords: Back Propagation Algorithm, Neural Network, Programming Neural Networks