Performance evaluation of LoRaWAN for Green Internet of Things

LoRa is a long-range, low power and single-hop wireless technology that has been envisioned for Internet of Things (IoT) applications having battery driven nodes. Nevertheless, increase in number of end devices and varying throughput requirements impair the performance of pure Aloha in LoRaWAN. Considering these limitations, we evaluate the performance of slotted Aloha in LoRaWAN using extensive simulations. We employed packet error rate (PER), throughput, delay, and energy consumption of devices under different payload sizes and varying number of end devices as benchmarks. Moreover, an analytical analysis of backlogged and non-backlogged under slotted Aloha LoRaWAN environment is also performed. The simulation shows promising results in terms of PER and throughput compared to the pure Aloha. However, increase in delay has been observed during experimental evaluation.Finally, we endorse slotted aloha LoRaWAN for Green IoT Environment

The response of sugarcane (Saccharum officinarum L) genotypes to callus induction, regeneration and different concentrations of the selective agent (geneticin -418)

Two commercial cultivars (CPF-245 and CPF-237) and three advanced lines (CSSG-668, S-2003US633, S-2003US114) of sugarcane (Saccharum officinarium) grown in Punjab, Pakistan were evaluated for their potential to induce callus, embryogenic callus and regeneration. Cultivar CSSG-668 was found to be the best genotype yielding maximum embryogenic callus and regeneration whereas cultivar CPF- 245 exhibited lowest callus induction frequency. Five different concentrations (0, 20, 40, 60, and 80mg/L) of the selective agent (geneticin-418) were used to optimize selection conditions with nontransformed embryogenic calli. The geneticin concentration 60 mg/L was found to be the optimal dose to select the embryogenic calli of genotypes CSSG-668, CPF-245 and S-2003US63, while 35 mg/L geneticin was found to be the best concentration for S-2003US-114. Similarly, 60 mg/L geneticin was optimum dose to select regenerated plantlets of the cultivars CSSG-668 and CPF-245 while it was 40, 25 mg/L for the cultivars S-2003US-114 and S-2003US-633, respectively. It is concluded from the present study that geneticin concentration in the range of 25 to 60 mg/L can be effectively used for the selection of transformed embryogenic calli and regenerants of different sugarcane cultivars.Keywords: Callus induction, embryogenic callus, regeneration, Saccharum officinarum L., selection, geneticin

Social commerce in e-business of Pakistan: opportunities, challenges and solutions

social media make ultimate building blocks in the development of novel approaches in e-business of Pakistan with the conjuncture of Web 2.0 social media has a variety of application domain including social commerce. S-commerce is redesigning modern e-business with promising economic technological and social outcrop. Customers keep their expectations higher always, so precisely all business are trying to exceed the customers' expectations with pre and post-sale interaction on social networking sites like face book or Twitter accounts. Customers can interact, look and compare company products, reviews and feedback in their social circle friends of friends of friends. This paper proposes a survey about prospects of social commerce in e-business of Pakistan. In addition, this paper would proposes research framework for foster future e-business opportunities, challenges and provide a solution to build up buyers trust as well as to enhance the interactive online buying process in local e-business of Pakistan using social media

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

In this paper, we investigate the wireless power transfer and energy-efficiency (EE) optimization problem for nano-centric vehicular networks operating over the terahertz band. The inbody nano-sensors harvest energy from a power station via radio-frequency signal and then use the harvested energy to transmit data to the sink node. By considering the properties of terahertz band (i.e., sensitivity to distance and frequency over the communication path), we adopt the Brownian motion model to develop a time-variant terahertz channel model and to describe the mobility of the nano-sensors. Thus, based on the channel model and energy resources, we further develop a long-term EE optimization problem. The EE optimization is further converted into a series of energy-efficient resource allocation problems over the time slots via equivalent transformation method. The resource allocation problem for each timeslot, which is formulated as a mixed integer nonlinear programming (MINLP), is solved based on the particle swarm optimization (PSO) method. In addition, a dynamic PSO-based EE optimization (DPEEO) algorithm is developed to obtain the sub-optimal solution for the EE optimization problem. By exploiting the special structure of the reformulated problem, an improved DPEEO algorithm, is presented which can handle the problem’s constraints quite well, decreases the research space, and greatly reduces the length of the convergence time. Simulation results validate the theoretical analysis of our system

Tibia fractures managed with minimally invasive internal fixation: a case series of 20 cases

Distal tibia fractures are frequently associated with an extensive soft tissue injury, leading to a higher risk of complications such as skin complications, infection, non-union, and eventually poor overall outcome. This study aims to measure the outcome of open/closed distal tibia fractures treated with minimally invasive internal fixation. We aim to propose an algorithm for the management of distal tibia fractures by evaluating the treatment options, outcomes, and risk factors present. This study is a case series study of all distal tibia fractures treated surgically in Kamineni Academy of Medical Sciences, LB Nagar from 2018 to 2022. Patient records were reviewed to analyze the outcomes of surgical treatment and the risk factors associated with it

Key Features of SARS-CoV-2 and Available Therapies for COVID-19

The disease caused by severe acute respiratory syndrome (SARS-CoV2) is highly pathogenic and communicable infection, progressed in Wuhan city of China and then goes viral around the globe. The Genomic investigations exposed that Phylogenetically SARS-CoV2 resembles the other SARS-like bat viruses, therefore bats were also considered as the possible potential reservoir for SARS-CoV2. There are 2 prevalent types of SARS-CoV2, L type (~70%) and S type (~30%).The L strains are considered more infectious and virulent than the ancestral S strain. The positive sense single-stranded RNA genetic material contains 29891 nucleotides which codes for 9860 amino acids. The ORF1a/b is involved in carrying the translation of two (2) polyproteins, pp1a and pp1ab as well as the encoding of 16 NSPs (Non-structural proteins), and the leftover ORFS can bring about the encoding of non-essential and structural proteins. The origination source and transmission to humankinds is still not clear, but the intermediate hosts are supposed to have a significant role in the transfer and emergence of SARS-CoV2 from bats to humans. There is still no approved drug or vaccine available for Covid-19. In the current review, we condense and fairly evaluate the emergence and pathogenicity of SARS-CoV2, SARS-CoV and MERS-CoV. Moreover, we also discuss the treatment and vaccine developments strategies for Covid-19

An Internet of Things based bed-egress alerting paradigm using wearable sensors in elderly care environment

The lack of healthcare staff and increasing proportions of elderly population is alarming. The traditional means to look after elderly has resulted in 255,000 reported falls (only within UK). This not only resulted in extensive aftercare needs and surgeries (summing up to £4.4 billion) but also in added suffering and increased mortality. In such circumstances, the technology can greatly assist by offering automated solutions for the problem at hand. The proposed work offers an Internet of things (IoT) based patient bed-exit monitoring system in clinical settings, capable of generating a timely response to alert the healthcare workers and elderly by analyzing the wireless data streams, acquired through wearable sensors. This work analyzes two different datasets obtained from divergent families of sensing technologies, i.e., smartphone-based accelerometer and radio frequency identification (RFID) based accelerometer. The findings of the proposed system show good efficacy in monitoring the bed-exit and discriminate other ambulating activities. Furthermore, the proposed work manages to keep the average end-to-end system delay (i.e., communications of sensed data to Data Sink (DS)/Control Center (CC) + machine-based feature extraction and class identification + feedback communications to a relevant healthcare worker/elderly) below 1 10 th of a second

Heuristic edge server placement in Industrial Internet of Things and cellular networks

Rapid developments in industry 4.0, machine learning, and digital twins have introduced new latency, reliability, and processing restrictions in Industrial Internet of Things (IIoT) and mobile devices. However, using current Information and Communications Technology (ICT), it is difficult to optimally provide services that require high computing power and low latency. To meet these requirements, mobile edge computing is emerging as a ubiquitous computing paradigm that enables the use of network infrastructure components such as cluster heads/sink nodes in IIoT and cellular network base stations to provide local data storage and computation servers at the edge of the network. However, optimal location selection for edge servers within a network out of a very large number of possibilities, such as to balance workload and minimize access delay is a challenging problem. In this paper, the edge server placement problem is addressed within an existing network infrastructure obtained from Shanghai Telecom’s base station the dataset that includes a significant amount of call data records and locations of actual base stations. The problem of edge server placement is formulated as a multi-objective constraint optimization problem that places edge servers strategically to the balance between the workloads of edge servers and reduce access delay between the industrial control center/cellular base-stations and edge servers. To search randomly through a large number of possible solutions and selecting those that are most descriptive of optimal solution can be a very time-consuming process, therefore, we apply the genetic algorithm and local search algorithms (hillclimbing and simulated annealing) to find the best solution in the least number of solution space explorations. Experimental results are obtained to compare the performance of the genetic algorithm against the above-mentioned local search algorithms. The results show that the genetic algorithm can quickly search through the large solution space as compared to local search optimization algorithms to find an edge placement strategy that minimizes the cost functio

Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival.

As data-rich medical datasets are becoming routinely collected, there is a growing demand for regression methodology that facilitates variable selection over a large number of predictors. Bayesian variable selection algorithms offer an attractive solution, whereby a sparsity inducing prior allows inclusion of sets of predictors simultaneously, leading to adjusted effect estimates and inference of which covariates are most important. We present a new implementation of Bayesian variable selection, based on a Reversible Jump MCMC algorithm, for survival analysis under the Weibull regression model. A realistic simulation study is presented comparing against an alternative LASSO-based variable selection strategy in datasets of up to 20,000 covariates. Across half the scenarios, our new method achieved identical sensitivity and specificity to the LASSO strategy, and a marginal improvement otherwise. Runtimes were comparable for both approaches, taking approximately a day for 20,000 covariates. Subsequently, we present a real data application in which 119 protein-based markers are explored for association with breast cancer survival in a case cohort of 2287 patients with oestrogen receptor-positive disease. Evidence was found for three independent prognostic tumour markers of survival, one of which is novel. Our new approach demonstrated the best specificity.PJN and SR were funded by the Medical Research Council. PJN also acknowledges partial support from the NIHR Cambridge Biomedical Research Centre.This is the accepted manuscript. The final version is available from SAGE at http://dx.doi.org/10.1177/096228021454874

An Efficient Channel Access Scheme for Vehicular Ad-hoc Networks

Vehicular Ad-hoc Networks (VANETs) are getting more popularity due to the potential Intelligent Transport Systems (ITS) technology. It provides many efficient network services such as safety warnings (collision warning), entertainment (video and voice), maps based guidance, emergency information, etc. VANETs most commonly use Road Side Units (RSUs) and Vehicle-to-Vehicle (V2V) referred as Vehicle-to-Infrastructure (V2I) mode for data accessing. IEEE 802.11p standard which was originally designed for Wireless Local Area Networks (WLANs) is modified to address such type of communication. However, IEEE 802.11p uses Distributed Coordination Function (DCF) for communication between wireless nodes. Therefore, it does not perform well for high mobility networks such as VANETs. Moreover, in RSU mode timely provision of data/services under high density of vehicles is challenging. In this paper, we propose a RSU-based efficient channel access scheme for VANETs under high traffic and mobility. In the proposed scheme, the contention window is dynamically varied according to the times (deadlines) the vehicles are going to leave the RSU range. The vehicles with shorter time deadlines are served first and vice versa. Simulation are performed by using the Network Simulator (NS-3) v. 3.6. The simulation results show that the proposed scheme performs better in terms of throughput, backoff rate, RSU response time, and fairness