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Multipath routing holds a great potential to provide sufficient bandwidth to a plethora of applications in wireless sensor networks. In this paper, we consider the problem of interference that can significantly affect the expected performances. We focus on the performance evaluation of the iterative paths discovery approach as opposed to the traditional concurrent multipath routing. Five different variants of multipath protocols are simulated and evaluated using different performance metrics. We mainly show that the iterative approach allows better performances when used jointly with an interference-aware metric or when an interference-zone marking strategy is employed. This latter appears to exhibit the best performances in terms of success ratio, achieved throughput, control messages overhead as well as energy consumption.

This paper aims to determine the network efficient topology for low power and lossy networks (LLNs) using routing protocol for LLN (RPL) with respect to the increase in network size and propose a novel approach to overcome the shortcomings of the existing models.

The authors have used Contiki OS/Cooja simulator to conduct experiments on primarily four topologies (star, bus/linear, ring/eclipse and random). They have implemented RPL protocol using Sky motes for each topology from 10, 20, 30 and up to 70 nodes. Consequently, after 24 h of experimentation, the readings have been noted and, alongside, a comprehensive comparative analysis has been performed based on the network density and metric parameters: packet delivery ratio (PDR), expected transmission (ETX) and power consumption. Further, a hybrid model is proposed where the additional factors of mobility, multiple sink and a combination of static and mobile nodes are introduced. The proposed model is then compared with the star model (all static nodes and star topology) and the dynamic model (all mobile nodes) to analyze the efficiency and network performance for different network sizes (28, 36, 38 and 44 nodes). The mobility is introduced using BonnMotion tool in Contiki OS.

Simulation results have shown that the star topology is most network efficient when compared with bus/linear, ring/eclipse and random topologies for low density and high scalable network. But when the same setup is compared with the proposed hybrid model, the proposed model shows a significant improvement and gives the best and efficient network performance with highest PDR (average improvement approximately 44.5%) and lowest ETX (average improvement approximately 49.5%) comparatively.

Also, these findings will benefit the deployment of smart devices used in advanced metering infrastructure, road side units and in various industrial applications such as traffic monitoring system, electronic toll collection and traffic analysis in the smart grid infrastructure.

The impact of topology is significant and detailed analysis is required to understand the impact of different topologies of the nodes in the network for the present and the future scenarios. As very few research studies have discussed this gap, this research paper is quintessential and shall open novel future potential direction. Also, the proposed approach of hybrid model with mobility has not been considered in the literature yet.

Routing protocol for low-power lossy network (RPL) being the de facto routing protocol used by low power lossy networks needs to provide adequate routing service to mobile nodes (MNs) in the network. As RPL is designed to work under constraint power requirements, its route updating frequency is not sufficient for MNs in the network. The purpose of this study is to ensure that MNs enjoy seamless connection throughout the network with minimal handover delay.

This study proposes a load balancing mobility aware secure hybrid – RPL in which static node (SN) identifies route using metrics like expected transmission count, and path delay and parent selection are further refined by working on remaining energy for identifying the primary route and queue availability for secondary route maintenance. MNs identify route with the help of smart timers and by using received signal strength indicator sampling of parent and neighbor nodes. In this work, MNs are also secured against rank attack in RPL.

This model produces favorable result in terms of packet delivery ratio, delay, energy consumption and number of living nodes in the network when compared with different RPL protocols with mobility support. The proposed model reduces packet retransmission in the network by a large margin by providing load balancing to SNs and seamless connection to MNs.

In this work, a novel algorithm was developed to provide seamless handover for MNs in network. Suitable technique was developed to provide load balancing to SNs in network by maintaining appropriate secondary route.

Wireless sensor network (WSN) and mobile crowd sensing (MCS) technologies face some challenges, especially when deployed in a large environment such as a smart city environment. WSN faces network latency, packets delivery and limited lifetime due to the nature of the used constrained internet of things small devices and low power network. On the other hand, most of the current applications that adapt MCS technology use 3G or long term evalution network to collect data and send them directly to the server. This leads to higher battery and bandwidth consumption and higher data cost.

This paper proposes a hybrid routing protocol based on the routing protocol (RPL) protocol that combines the two wireless sensing technologies (WSN and MCS) and allows the integration between them. The aim is to use MCS nodes in an opportunistic way to support static WSN nodes to enhance the performance.

The evaluation of the proposed protocol was conducted in a static WSN to study the impact of the integration on the WSN performance. The results reveal a good enhancement on packet delivery ratio (17% more), end-to-end delay (50% less) and power consumption (25% less) compared with native RPL (without MCS integration).

The authors believe that the hybrid-RPL protocol can be useful for sensing and data collection purposes, especially in urban areas and smart city contexts.

Coronavirus disease 2019 is one of the novel diseases formed by a dreadful virus called Severe Acute Respiratory Syndrome Coronavirus 2. Various countries are affected by this viral disease, and many countries declare a lockdown with several rules and conditions. To prevent this rapid viral transmission, various researchers have introduced different mobile applications. This paper aims to study issues like viral transmission, mortality rates, vaccination rates, etc. and also provides suitable solutions based on the statistical analysis with the assistance of the Six-Sigma Define-Measure-Analyse-Improve-Control (DMAIC) concept.

Statistical analysis is done for different countries, and the required solutions are provided by using the DMAIC procedure. This application has the ability to represent the current risk status of the user and notify them to secure themselves.

The proposed work suggests the Aarogya Setu application to prevent large viral transmission by affording many preventive measures. This application also issues the current risk status of each individual user. Hence, it gives improved results in avoiding high viral transmission.

The proposed six-sigma DMAIC concept also affords the control measures to prevent viral transmission. Hence, the suggested application has the highest chance of avoiding the rapid viral transmission.

This study is a sequel of a paper by Fidelman in 1996, where it was argued that the idea of Hendrickson and Hendrickson in 1982, that high intelligence is related to a small probability of neural transmission‐errors, may be correct, in spite of the contradictory evidence. The relation between several biological theories of intelligence is discussed in this study. These theories are Haier’s and Schafer’s theories relating intelligence to the energy consumption of the brain, the Hendrickson paradigm, Eysenck’s extension of the Hendrickson paradigm according to which a neural message is sent repeatedly until it is received identically a certain number of times, Jensen’s theory relating intelligence to reaction‐time, and Haier’s theory of synaptic density. Discusses the proposition that the attentional theory of Bates and Eysenck may be considered as an extension of the paradigm of Schafer.

Inclusion of mobile nodes (MNs) in Internet of Things (IoT) further increases the challenges such as frequent network disconnection and intermittent connectivity because of high mobility rate of nodes. This paper aims to propose a proactive mobility and congestion aware route prediction mechanism (PMCAR) to find the congestion free route from leaf to destination oriented directed acyclic graph root (DODAG-ROOT) which considers number of MNs connected to a static node. This paper compares the proposed technique (PMCAR) with RPL (OF0) which considers the HOP-COUNT to determine the path from leaf to DODAG-ROOT. The authors performed a simulation with the proposed technique in MATLAB to present the benefits in terms of packet loss and energy consumption.

In this pandemic situation, mobile and IoT play major role in predicting and preventing the CoronaVirus Disease of 2019 (COVID-19). Huge amount of computations is happening with the data generated in this pandemic with the help of mobile devices. To route the data to remote locations through the network, it is necessary to have proper routing mechanism without congestion. In this paper, PMCAR mechanism is introduced to achieve the same. Internet of mobile Things (IoMT) is an extension of IoT that consists of static embedded devices and sensors. IoMT includes MNs which sense data and transfer it to the DODAG-ROOT. The nodes in the IoMT are characterised by low power, low memory, low computing power and low bandwidth support. Several challenges are encountered by routing protocols defined for IPV6 over low power wireless personal area networks to ensure reduced packet loss, less delay, less energy consumption and guaranteed quality of service.

The results obtained shows a significant improvement compared to the existing approach such as RPL (OF0). The proposed route prediction mechanism can be applied largely to medical applications which are delay sensitive, particularly in pandemic situations where the number of patients involved and the data gathered from them flows towards a central root for analysis. Support of data transmission from the patients to the doctors without much delay and packet loss will make the response or decisions available more quickly which is a vital part of medical applications.

The computational technologies in this COVID-19 pandemic situation needs timely data for computation without delay. IoMT is enabled with various devices such as mobile, sensors and wearable devices. These devices are dedicated for collecting the data from the patients or any objects from different geographical location based on the predetermined time intervals. Timely delivery of data is essential for accurate computation. So, it is necessary to have a routing mechanism without delay and congestion to handle this pandemic situation. The proposed PMCAR mechanism ensures the reliable delivery of data for immediate computation which can be used to make decisions in preventing and prediction.

To accommodate increasing levels of device integration at the chip level, circuit line densities in electronic packages are continually increasing. Greater circuit line density, in turn, necessitates a corresponding increase in package‐to‐board interconnection density, with I/O counts expected to reach over 600 by 1995. In conjunction with the upward trend in I/O counts are a complementary upward trend in clock speed and an opposing downward trend in package sizes driven by the need to provide more functionality in less space, particularly in notebooks and PCMCIA cards. To satisfy the requirements of increased I/O counts and clock speed, and reduced package sizes, various package‐to‐board interconnection technologies are being developed, such as flip chip attach (FCA) using C4 joints. However, FCA interconnections have a disadvantage of being very difficult, if not impossible, to visually inspect. Though automatic test equipment (ATE) can determine whether the package is functional, it cannot determine the quality and reliability of FCA interconnections. Of the possible inspection techniques available to assess the quality of FCA interconnections — differential laser thermal analysis, acoustic microscopy and cross‐sectional X‐ray radiography — only cross‐sectional X‐ray radiography is capable of accurate, automated inspection of production volumes. This paper will first examine the requirements for inspecting FCA joints and will then describe the various inspection alternatives, outlining their advantages and disadvantages. Having described the potential advantage of one particular cross‐sectional X‐ray technique, digital tomosynthesis, the paper will conclude with some cross‐sectional images of FCA and SMT joints taken by a digital tomosynthesis system being developed for the inspection of FCA joints.

The main purpose of this study is to examine the role of the coronavirus disease 2019 (COVID-19) test on transmission data globally to reveal the fact that the actual picture of transmission history cannot be exposed if the countries do not perform the test adequately.

Using Our World in Data for 212 countries and areas and 162 time periods daily from December 31, 2019, to June 09, 2020, on an unbalanced panel framework, we have developed a panel-based path analysis model to explore the interdependence of various actors of COVID-19 cases of transmission across the globe. After controlling for per capita gross domestic product (GDP), age structure and government stringency, we explore the proposition that COVID-19 tests affect transmission positively. As an anecdote, we also explore the direct, indirect and total effects of different potential determinants of transmission cases worldwide and gather an idea about each factor's relative role in a structural equation framework.

Using the panel path model, we find that a 1 standard deviation change in the number of tests results in a 0.70 standard deviation change in total cases per million after controlling for several variables like per capita GDP, government stringency and age population (above 65).

It is not possible to get balanced data of COVID-19 for all the countries for all the periods. Similarly, the socioeconomic, political and demographic variables used in the model are not observed daily, and they are only available on an annual basis.

Countries which cannot afford to carry out more tests are also the countries where transmission rates are suppressed downward and negatively manipulated.

Cross country collaboration in terms of COVID-19 test instruments, vaccination and technology transfer are urgently required. This collaboration may be sought as an alternative to foreign development assistance.

This article provides an alternative approach to modeling COVID-19 transmission through the panel path model where the test is considered as an endogenous determinant of transmission, and the endogeneity has been channeled through per capita GDP, government stringency and age structure without using any regression-based modeling like pooled ordinary least squares (OLS), fixed-effects, two-stage least squares or generalized method of moments (GMM). Endogeneity has been handled without using any instruments.

The aim of the study is to better understand how lesson study (LS) contributes to challenging teachers' views of mathematics teaching and learning.

This study is part of a wider ongoing project aiming at improving primary mathematics teaching in Malawi through professional development (PD) of teachers using a LS model. The units being analyzed are teachers' written reflections and lesson plans. The analytical approach is qualitative content analysis.

Initially, the participating Malawian primary teachers report traditional views of mathematics teaching and learning. After having participated in a LS cycle, they reported on the need to work on how to involve and create space for learners' participation in mathematic lessons and highlight the importance for learners to discover mathematics on their own.

This is a small-scale study due to LS being quite new in the Malawian context and the need to test before possible upscaling.

The paper includes a description on how LS might contribute to challenging Malawian teachers' views of mathematics teaching and learning; this can be valuable information for others who are attempting to use LS in a similar context.

This paper fulfills an identified need to learn more about how LS might contribute to challenging teachers' views of mathematics teaching and learning worldwide.