The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; formerly named coronavirus virus or 2019-nCoV) disease (COVID-19) in China at the end of 2019 has caused a large global outbreak and is a major public health issue. As of February 20, 2021, data from the World Health Organization (WHO) have shown that more than 10,977,387 confirmed cases and 156,240 deaths have been identified in India. On January 30, 2020, the WHO declared COVID-19 as the sixth public health emergency of international concern. In India, there are 81,990 numbers of confirmed cases that have been identified as on May 15, 2020. In this regard, the Indian Council of Medical Research (ICMR) takes an initiative for providing intensive care to COVID-19 patients and to fulfill their needs. The percentage of patients infected with COVID-19 reported daily in India between April 1 and May 14, 2020 has been consistently between 20.64% and 30.81% of patients who are actively infected. Currently, India is sustaining in the pandemic situation. The number of patients infected since May 14 in India closely follows an exponential trend. If this trend continues for 1 more week, there will be 1-13 lakhs infected patients till mid-March and India will enter into a serious situation. Intensive care units are then at maximum capacity; up to 710,761 hospital isolation beds will be needed by mid-March, 2020. In this chapter, we discuss the preparations related to COVID-19 and its impact on the second highest populated country in the world. A prediction model is proposed to forecast the COVID-19 confirmed cases with high accuracy. The analysis might help political leaders and health authorities to allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks.

A significant international epidemic and serious public health concern have been brought on by the arrival of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; also known as the coronavirus virus or 2019-nCoV) illness (COVID-19) in China at the end of 2019. As of February 20, 2021, India had been home to more than 10,977,387 confirmed cases and 156,240 fatalities, according to the data from the World Health Organization (WHO). The WHO designated COVID-19 as the sixth public health emergency of global concern on January 30, 2020. On May 15, 2020, 81,990 cases have been verified in India. In this regard, the Indian Council of Medical Research takes action to fulfill the wishes of coronavirus patients by offering them intensive treatment. Between April 1 and May 14, 2020, the daily COVID-19 infection rate in India was regularly between 20.64% and 30.81% of patients who are actually sick. India is now coping with the epidemic issue. In India, the number of patients who have become infected since May 14 has roughly followed an exponential trajectory. If this pattern continues for another week, there will be between 1 lakh and 13 lakh infected persons by the middle of March, and India will face a grave situation. By mid-March 2020, there will be a demand for up to 710,761 hospital isolation beds since intensive care units will then be at capacity. In this chapter, we covered the COVID-19 preparations and their effects on the world's second-most populous nation. A prognostication model is suggested as a contribution to accurately predict COVID-19 corroborated instances. Our study could help political leading lights and health-conscious organizations to allocate the necessary employees, beds, and intensive care facilities in handling the issue over the coming days and weeks.

A man in his early 50s presented with small bowel obstruction, requiring emergency laparoscopic small bowel resection for the metastatic melanoma of the jejunum with no identifiable primary lesion. One week after his first treatment with ipilimumab and nivolumab, he presented with diffuse abdominal pain, constipation, and fatigue. A computerized tomography scan did not identify a cause for his symptoms. This was rapidly followed by thrombocytopenia on day 11 and then anemia. He commenced intravenous corticosteroids for a suspected diagnosis of immune-related thrombocytopenia. On day 15, a generalized onset motor seizure occurred, and despite plasmapheresis later that day, the patient died from fatal immune-related thrombotic thrombocytopenic purpura (TTP). This was confirmed with suppressed ADAMTS13 (<5%) testing on day 14. Immune-related TTP is a rare and, in this case, fatal immune- related adverse event. Further studies are required to identify additional immunosuppressive management for immune-related TTP.

Nowadays, the Internet of things (IoT) provides various services to drivers by equipped with smart devices. In this regard, the next generation of vehicles collaborates with the features of IoT to provide safety and security on the roads. To achieve this, it is equipped with short-range communication advances and establishes Vehicle-to-Vehicle (V2V) connectivity. The standardized V2V connectivity and communication are termed in IEEE 802.11p. Later, an alternative named (LTE-V2V) has been introduced. However, both technologies are only concerned with the continuous broadcast of information and cooperative awareness. It only takes information from one vehicle in a text way and sends it to another. In this regard, efficient and satisfactory safety is not provided by these technologies for the analysis of real-time road traffic monitoring. Therefore in this paper, we proposed a solution by providing real-time information on road conditions and traffic scenarios to the drivers. We utilized the capturing of images of road conditions by the positioned cameras and Global Positioning System (GPS) to extract the information regarding vehicle and camera position. The proposed work provides better security rather than a message-passing system in V2V communication. The drivers in our anticipated scenarios can extract and see a clear view of road conditions by the use of captured videos/images. Our proposed solution copes well with moderate traffic conditions and provides a high satisfaction score. The simulation results show that our proposed work can achieve high performance in the provision of providing safety compared to other schemes introduced in this field.

COVID 19 is a corona virus-related ailment. A global pandemic has commenced over the fatality of the virus. The gravity of the situation is taken into account by medical professionals across the globe. Along with the Covid protocols being implemented, detection at the onset of the illness allows patients to isolate themselves, reducing the risk of infection. Lately, Chest X ray scans are invaluable when it comes to COVID 19 detection. On account of their quicker imaging time, extensive availability, budget-friendly, and portability have reaped a great deal of attention and become very promising. COVID 19, owing to its tortuous mutation, is an enigma and, hence a timely and automatic diagnosis would be instrumental in helping professionals. Virtual assistants allow users to communicate in natural language, they are used to supplement health service capacity and lower exposure. Therefore, to predict Covid-19 disease we employed the chest X-ray image data-set and implemented the CNN model of Deep Learning along with the Alexa Speech recognition skill set.

Nowadays, Internet-of-things (IoT) provides various services to the users by equipped with the smart devices. In this regard, the next generation of vehicles collaborates with the features of IoT to provide the safety and security on the roads. To achieve this, it equipped with short-range communication advances and establishes Vehicle-to-Vehicle (V2V) connectivity. The standardized V2V connectivity and communication are termed as IEEE 802.11p. Later, an alternative named as (LTE-V2V) has been introduced. However, both the technologies are only concerned with the continuous broadcast of information and cooperative awareness. It only takes information from one vehicle in the format of text message and sends to another. In this regard, an efficient and satisfactory safety is not provided by these technologies for analysis of real-time road traffic monitoring. A clear observation of road conditions and awareness of event triggering is a necessary task rather than broadcasting of information provided by the vehicles. Therefore in this paper, we proposed a solution by providing the real-time information about road conditions and traffic scenarios to the users. We utilized the capturing images of road conditions by the positioned cameras and Global Positioning System in order to extract the information regarding vehicle and camera position. The proposed work provides a better security rather than message passing system in V2V communication. The users in our anticipated scenarios can extract and see a clear view of road conditions by use of captured videos/images. We offered an approach named as Smart Road Monitoring for IoT based smart cities to provide an effective solution for the real-time analysis of traffic road conditions. The proposed approach gives a clear view of conditions of the road to the users such that they can make a decision according to their suitability Our proposed solution well copes with the moderate traffic conditions and provides high satisfaction score. The performance analysis is done in a comparison of V2V and LTE-V2V in terms of various metrics. The simulation results show that our proposed work can achieve high performance in the provision of providing safety compared to other scheme introduced in this field.

Content-centric networking (CCN) is gradually becoming the alternative approach to the traditional Internet architecture through enlightening information (content) distribution on the Internet with content names. The growing rate of Internet traffic has adapted a content-centric architecture to better serve the user requirement of accessing a content. For enhancing content delivery, ubiquitous in-network caching is utilized to store a content in each and every router by the side of the content delivery path. From the study, it is evaluated that a better performance can be achieved when caching is done by a subset of CRs instead of all CRs in a content delivery path. Motivated by this, we proposed an adaptive neuro-fuzzy inference system-based caching (ANFIS-BC) scheme for CCN to improve the cache performance. The proposed ANFIS-BC scheme utilizes the feature of centrality-measures for selection of a router for caching in a network. Our results demonstrated that the ANFIS-BC scheme consistently achieves better caching gain across the multiple network topologies.

Information-centric networking (ICN) is gradually becoming an alternative approach to the conventional Internet architecture through the distribution of enlightening information (named as content) on the Internet. Given the growing Internet traffic, the adapted information-centric architecture is expected to more favourably serve the user’s need of accessing data. In this paper, we proposed a novel framework for cache management in ICN that jointly considers the caching strategy and network coding. For the proposed cache management framework, we first evaluated a new Centrality-measures to assess the variation in the behaviour of each node in the network and to identify such behaviour. Subsequently, we developed an efficient random network coding-based cache management algorithm to obtain a support for caching and multicasting in the ICN paradigm. Extensive simulations were made, and related results showed that our proposed scheme has better performance in terms of cache hit ratio, average download time, server hit reduction ratio, and traffic overhead compared with other schemes in our simulated scenarios.

Nowadays, Information centric networking has tremendous importance in accessing internet based applications. The increasing rate of Internet traffic has encouraged to adapt content centric architectures to better serve content provider needs and user demand of internet based applications which is based on receiver driven data retrieval. These architectures have built-in network Caches and these properties improves efficiency of content delivery with high speed and efficiency and they are very efficient in comparison with traditional caching of internet access methodologies. By using Information centric architectures, users need not download content from content server despite they can easily access data from nearby caches. User requested content is independent of the location of that data by use of caching approaches and does not rely on storage and transmission methodologies of that content. There has been many researches going to base on caching approaches in the Content centric network. Efficient caching is essential to reduce delay and to enhance performance of the network. Efficient caching is essential to reduce delay and to enhance performance of the network. So, in this paper, we presented a survey on caching approaches and related issues like cache content, availability, and cache router localization and so on. The main focus to present a state-of-art research paper for researchers who are interested in the area of Information centric network so that they can get an idea about what work and issues have been developed and arises in this particular caching field.

To provide broadband access services to customers, which resides residential and enterprise field, Worldwide Interoperability for Microwave Access (WiMAX) is one of the famous wireless technologies. WiMAX can provide high-speed data rate with large-scale coverage such that it contains a high transmission range as well as it supports high mobility with a large number of nodes. It requires scheduling algorithm in the MAC layer of its protocol stack because the number of users that want service is high in number. One of the most used scheduling algorithms is the Earliest Deadline First (EDF) but it contains certain performance limitations. As well as there is a need for security before allocation of bandwidth to the users because WiMAX is a wireless technology and may be vulnerable to lots of security attacks and if once the bandwidth is allocated to any malicious user, then the system of WiMAX communication will be under dangerous attacks. In this paper, we proposed a secure heuristic earliest deadline first uplink scheduler in the MAC layer of the WiMAX with some authorization procedures. The proposed scheme protects the allocation of bandwidth to any malicious node such that the system will be prevented from security attacks like Denial of Service (DoS), flooding attack, etc., as well as it will use heuristic approach for scheduling. Therefore, it can efficiently schedule user’s request and provide fairness to the WiMAX system and we called as Secure Heuristic EDF Uplink Scheduler (SH-EDF). The performance of SH-EDF uplink scheduler will be evaluated in the provisions of various performance metrics.

Content-centric Networking（CCN） is progressively flattering the substitutable approach to the Internet architecture through illuminating information（content） dissemination on the Internet with content forenames.The emergent proportion of Internet circulation has expectant adjusting Content-centric architecture to enhance serve the user prerequisites of accessing content.In recent years,one of the key aspects of CCN is ubiquitous in-network caching,which has been widely received great attention in research interest.One foremost shortcoming of in-network caching is that content producers have no awareness about where their content is put in storage.Because routers in CCN have caching capabilities,therefore,each and every content router can cache the content item in its storage capacity.This is problematic in the case in which a producer wishes to update or make the changes in its content item.In this paper,we present an approach regarding how to address this issue with a scheme called efficient content update（ECU）.Our proposed ECU scheme achieves content update via trifling packets that resemble contemporary CCN communication messages with the use of additional table.We measure the performance of ECU scheme by means of simulations and make available a comprehensive exploration of its results.

Nowadays, Wireless Sensor Network (WSN) achieves substantial attention in the research as well as the industrial area. WSN integrates with various protocols to give the variety of application-based services related to healthcare, habitat monitoring, smart city, military usage and disaster management etc. By providing different applications and services, it composites with the terms Internet-of-the things (IoT). However, when these measures are collaborated with the industrial revolution, it becomes Industrial Internet-of-the things (IIoT). In this way, it provides high scalability by the support of the large number of Internet users with the usage of IPv6 instead of IPv4. It is essential that the working modules and protocol to be energy efficient. The reason is, a lifetime of a deployed sensor is directly related to its draining short-term battery. By following, these point into account, various protocols are utilized and tested by IIoT based WSN. Although, these all do not give satisfactory performance in terms of the appropriate data rate to provide the high speed to run the various categories of applications and services in IIoT. Therefore in this paper, we select G.9959 protocol instead of IEEE 802.15.4 and compared the IPv6 packet delivery rate with respect to energy and latency. Furthermore, an analysis is performed to see the effect on energy when the bandwidth moderates. Further, extensive simulations were made, and related results showed that our proposed scheme has better performance compared with other schemes in our simulated scenarios.

People waste a lot of time in searching for a roadside parking space, especially in busy areas like the marketplace. In addition to wastage of time, it causes extra congestion on the road as vehicles which were supposed to be parked are still roaming on the roads, consequently extra pollution, and most importantly stress and inconvenience to the driver. To address these issues, a framework is proposed to provide assistance to drivers in searching for a roadside parking place. Instead of providing direction to one parking area, which is not feasible as roadside parking areas do not have reservation facilities, this framework will suggest a series of options (basically routes) for the driver to follow. The approach uses ant colony optimization to tackle the computationally challenging task. The algorithm tries to suggest a route which is not only close to the drivers location but also avoids areas of congestion if possible. The proposed approach is simulated using SUMO simulator suite. The proposed routing approach has been compared with the random routing approach using different metrics and the results show that the proposed approach performs significantly better than the random approach.

To give the complete description of an environment or to take a robust decision, a number of observations are collected and combined from the multiple sensor nodes. The process of combining and analyzing the observations is called multisensor data fusion. The fusion is used to produce more consistent, accurate, and useful information than that provided by any individual sensor node. For efficiency, data fusion is performed on the sensed sample collected by sensor nodes. However, fusion on the network path parameters is also essential to select an appropriate forwarding route for sending the data. In addition, to increase the lifetime of a network, an efficient strategy is needed in order to select a cluster head node. Therefore, in this paper, we propose a multisensor data fusion (MDF) strategy which performs fusion on collected network parameters for the selection of an appropriate path with collaboration of Fuzzy-based cluster head selection (FBCHS). Jointly, we named the strategy as the MDF-FBCHS strategy for IoT-oriented WSN. Extensive simulations were made, and related results showed that our proposed scheme has better performance compared with other schemes in our simulated scenarios.

To give the complete description of an environment or to take a robust decision, a number of observations are collected and combined from multiple sensor nodes. The process of combining and analyzing the observations is called multisensor data fusion. The fusion is used to produce more consistent, accurate, and useful information rather than provided by any individual sensor node. Data fusion finds wide application in many areas of such as object recognition, wireless sensor network, image processing, environment mapping, and localization. Nowadays, the Internet of Things (IoT) utilizes wireless sensor network (WSN) as a necessary platform for data sensing and communication. For efficiency, data fusion is performed on the sensed sample collected by the sensor nodes. However, fusion of the network parameters is also essential to select an appropriate sensor node for the forwarding of data. Therefore, in this paper, we propose a multisensor data fusion (MDF) strategy that performs fusion of the collected network parameters like bandwidth and centrality for the selection of an appropriate path. Extensive simulations were made, and related results showed that our proposed scheme has a better performance compared with other schemes in our simulated scenarios.

In order to give a complete description of an environment or to make a robust decision, a number of observations must be collected and combined from multiple sensor nodes. In these large collections of data, only some are useful, whereas others are redundant. This redundancy decreases performance in terms of computing overhead, excessive transmission, and covering a large space. The process of selecting and analyzing the useful information from the collection of sensed data is called mining. Mining is used to produce more consistent, accurate, and useful information than that provided by any individual sensor node. Data mining has been widely applied in many areas, such as object recognition, wireless sensor networks (WSNs), image processing, environment mapping, and localization. Nowadays, Internet of Things utilizes WSN as a necessary platform for sensing and communication of the data. For efficiency, mining of spatial and temporal data is performed on the sensed sample collected by sensor nodes. Therefore, in this paper, a redundancy removal strategy is proposed, which performs mining on collected data to select the appropriate information before forwarding to a base station or a cluster head in the WSN. Extensive simulations were conducted, and the related results showed that the proposed scheme had better performance compared to other schemes in our simulated scenarios.

Software-defined network is one of the best methodologies of computer network that countenances to an administrator to succeed the computer network amenities through the perception of subordinate side by side functionality. Software-defined network (SDN) is alienated into two fragments: one is Control plane and former is Data plane. In control plane are the actually deployed devices. This control plane is located at a fundamental controller. The controller is responsible for building the forwarding base and figuring out how a packet should be forwarded through a network. The SDN controller takes the information of packages and places it in a forwarding table or flow table of devices, the controller verifies the protocol made by the administrator and forward the packet to the router. In this paper, the performance analysis of SDN is done with the help of one, two and three controllers and will see how much the transfer time is affected with increasing number of controllers.

Primary Objective• To compare investigator-assessed progression free survival (PFS) between Tamoxifen and placebo versus Tamoxifen in combination with Taselisib at the RPTD.

The current standard of care for recurrent or metastatic cervical cancer (CA) includes treatment using multi-agent chemotherapy plus bevacizumab. This combination has been shown to improve overall survival and has potential for long term control in up to 15% of patients (pts). Bevacizumab (bev) is a VEGF inhibitor, and VEGF is known to be involved in normal tissue repair following high dose radiation. The risk for severe bowel injuries following bev administration is thought to be low. However, not much data exists regarding its true safety when used in the immediate period following high dose rate brachytherapy (HDR brachy). We present some cautionary data identifying the possibility of higher than expected risks for severe toxicity in pts treated using bev after curative therapy including pelvicRT and brachytherapy. A retrospective review of pts treated for recurrent, persistent or metastatic cervical CA with a regimen including bev after completing definitive pelvicRT with weekly cisplatin and HDR brachy was performed from 6/2009 to 1/2017. Bev was most commonly delivered 15mg/kg every 3 weeks. Median dose of RT was 4500cGy whole pelvis concurrent with cisplatin. Most common HDR brachy dose was 5Gy x 5Fx and a median of 75.5 Gy equivalent dose at 2 Gy per fraction (EQD2). Toxicities were scored using RTOG criteria. Analysis was performed using chi-square and independent t-test. Twenty-one pts were identified with a median age of 47 years (range 27-69). Primary tumor stages were FIGO IB2(N)= 1, IIA = 5, IIB = 4, IIIA = 0, IIIB = 10, IVA = 1. Ten (48%) pts presented with node positive disease. Bev was administered for a median of 5 cycles (range 1 - 10) and started on average 9.5 months after completion of RT. After a mean follow-up of 17.1 months since initiating bev, a total of 9 pts have been observed to develop a severe (grade 3+) toxicity: 6 (29%) bowel perforations and 3 (14%) fistula formations. These occurred at a mean of 2.3 and 4.7 months after initiation of bev, respectively. All fistulas appeared to be due to treatment related toxicity and none of the 6 perforations occurred in the setting of recurrent disease. Two bowel perforations were fatal. In pts with and without complications, mean time from RT to bev was 6.0 (range 1-12) and 12.4 months (range 2 to 27), respectively (P=0.044). Mean EQD2 in pts with complications vs. without was 74.7Gy and 75.37Gy, respectively (p=0.796). Two pts (20%) with FIGO I/II disease and 7 pts (63.6%) with FIGO III/IV disease had complications (p=0.044). In this limited series of pts, a significantly higher rate of severe bowel toxicity was observed. It is hypothesized that this may be due to the use of bev within the immediate recovery period of HDR brachytherapy for cervical CA. Upon analysis, correlations for development of toxicity included timing of bev administration and tumor stage. Additional caution and safety testing might be warranted in pts receiving angiogenesis inhibitors in the immediate period post definitive therapy.