Network performance optimization using Odd and Even routing algorithm

The revolution on static wireless sensor network (WSN) had gained popularity in remote monitoring especially in oil and gas pipeline integrity. The use of WSN in oil and gas pipelines facilitates real time data transmission from sensors to the monitoring station located miles away. WSN for pipeline network are critical performance driven communication mechanism due to its unique linear geographical set up. The network performance of linear topology is compromised proportionally to the number of nodes. Such a drawback results in poor delivery ratio, throughput, latency and fairness due to its snowball effect towards the destination node. In this paper, we proposed a novel routing method, Odd-Even Linear Static Routing Path (OE-LSRP) to achieve significant improvements in overall network performance in TCP traffic. Various simulation experiments are tested with OE-LSRP in accordance to IEEE 802.11standard to achieve results in making it feasible for the pipeline network

TCP Timeout Mechanism for Optimization of Network Fairness and Performance in Multi-Hop Pipeline Network

In the recent years, wireless sensor network (WSN) has a huge impact in many remote based applications especially in oil and gas pipeline monitoring. Thus, the deployment of a multi-hop linear WSN will be a practical solution on pipelines. With a large multi-hop linear WSN, the overall network performance is badly affected especially due to node starvation. Inequality among source nodes is relatively an amplified factor of generated data rate and source node distances from the destination node. In this paper, we proposed a mathematical model for TCP Delayed Timeout Acknowledgement (DTO-ACK) mechanism for non-zero passive nodes. Optimum throughput fairness can be achieved by implementation of DTO-ACK with Dual Interleaving Linear Static Routing Protocol (DI-LSRP) for flat topology. Implementation of DTO-ACK and modification of TCP parameters reduces packet collision and ensures optimal throughput fairness in a multi-hop linear topology using TCP agent

Enhancing Pipeline Network Performance Using Dual Interleaving Cluster Head Routing Protocol

Remote monitoring of oil and gas pipelines has been the most prevalent application of static wireless sensor network (WSN). WSN has a great potential in facilitating real-time data transfer between sensor nodes and a centralise monitoring station. For pipeline WSN, network performance is critical among sensor nodes in a linear chain topology. Expanding the communication range by increasing number of nodes in a linear architecture compromises the performance of WSN. Thus, WSN results in a severe impact on low throughput, high latency, poor delivery ratio, high energy consumption and network inequality. In this paper, we proposed Dual Interleaving Cluster Head Linear Static Routing Protocol (DICH-LSRP), a routing protocol for cluster-based topology. DICH-LSRP in a pipeline simulation environment were evaluated with compliance to IEEE 802.11 standard on impending factors of WSN performance. The simulation results help to better understand some key areas of WSN performance metrics and the implementation of DICH-LSRP in a multi-hop linear topology

Inbuilt Tendency of the eIF2 Regulatory System to Counteract Uncertainties

Eukaryotic initiation factor 2 (eIF2) plays a fundamental role in the regulation of protein synthesis. Investigations have revealed that the regulation of eIF2 is robust against intrinsic uncertainties and is able to efficiently counteract them. The robustness properties of the eIF2 pathway against intrinsic disturbances is also well known. However the reasons for this ability to counteract stresses is less well understood. In this article, the robustness conferring properties of the eIF2 dependent regulatory system is explored with the help of a mathematical model. The novelty of the work presented in this article lies in articulating the possible reason behind the inbuilt robustness of the highly engineered eIF2 system against intrinsic perturbations. Our investigations reveal that the robust nature of the eIF2 pathway may originate from the existence of an attractive natural sliding surface within the system satisfying reaching and sliding conditions that are well established in the domain of control engineering

Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization

PURPOSE OF REVIEW: This article aims to discuss the current state of resources enabling the democratization of artificial intelligence (AI) in ophthalmology. RECENT FINDINGS: Open datasets, efficient labeling techniques, code-free automated machine learning (AutoML) and cloud-based platforms for deployment are resources that enable clinicians with scarce resources to drive their own AI projects. SUMMARY: Clinicians are the use-case experts who are best suited to drive AI projects tackling patient-relevant outcome measures. Taken together, open datasets, efficient labeling techniques, code-free AutoML and cloud platforms break the barriers for clinician-driven AI. As AI becomes increasingly democratized through such tools, clinicians and patients stand to benefit greatly

Barriers to green supply chain management: An emerging economy context

© 2019 Elsevier Ltd Green supply chain management is attracting increasing attention as a way to decrease the adverse environmental effects of industries worldwide. However, considering the context of an emerging economy like Bangladesh, green supply chain management is still in its inception and has not been widely embraced in the textile industry, and therefore barriers hindering its adoption in emerging economy context demand a comprehensive investigation. This research reviews the viewpoints and hurdles in adopting green supply chain management practices in the context of the Bangladeshi textile industry. A questionnaire survey of Bangladeshi textile practitioners of operations and supply chain management division, having a sample size of thirty, was undertaken to identify the barriers, and a hierarchical cluster analysis technique was used in the detailed analysis of this data. Opinions were sought from experts on the significance of the resulting clusters, considering the relative importance of the barriers. Fifteen barriers to the adoption of green supply chain management were identified in the review of the literature, with these barriers then analyzed by using the data collected from Bangladeshi textile industry practitioners. The research indicates that the most important barrier is that there is low demand from customers and financial constraint resulting from short term little financial benefit to businesses, with lack of government regulations also a commonly faced barrier in adopting green supply chain initiatives. This study will provide valuables insights to practitioners and relevant policy makers about the barriers prevailing in the emerging economies towards the adoption of green supply chain management practices, which, in turn, can guide to undertake appropriate steps for alleviating those barriers

Restoration of Liquid Effluent from Oil Palm Agroindustry in Malaysia using UV/TiO2 and UV/ZnO Photocatalytic Systems: A Comparative Study

In this study, we have employed a photocatalytic method to restore the liquid effluent from a palm oil mill in Malaysia. Specifically, the performance of both TiO2 and ZnO was compared for the photocatalytic polishing of palm oil mill effluent (POME). The ZnO photocatalyst has irregular shape, bigger in particle size but smaller BET specific surface area (9.71 m2/g) compared to the spherical TiO2 photocatalysts (11.34 m2/g). Both scavenging study and post-reaction FTIR analysis suggest that the degradation of organic pollutant in the TiO2 system has occurred in the bulk solution. In contrast, it is necessary for organic pollutant to adsorb onto the surface of ZnO photocatalyst, before the degradation took place. In addition, the reactivity of both photocatalysts differed in terms of mechanisms, photocatalyst loading and also the density of photocatalysts. From the stability test, TiO2 was found to offer higher stability, as no significant deterioration in activity was observed after three consecutive cycles. On the other hand, ZnO lost around 30% of its activity after the 1st-cycle of photoreaction. The pH studies showed that acidic environment did not improve the photocatalytic degradation of the POME, whilst in the basic environment, the reaction media became cloudy. In addition, longevity study also showed that the TiO2 was a better photocatalyst compared to the ZnO (74.12%), with more than 80.0% organic removal after 22 h of UV irradiation

Exploring the factors contributing to increase in facility child births in Bangladesh between 2004 and 2017-2018

Although Bangladesh has gained rapid improvement in births at health facilities, yet far behind to achieve the SDG target. Assessing the contribution of factors in increased use of delivery at facilities are important to demonstrate. To explore the determinants and their contribution in explaining increased use of facility child births in Bangladesh. Reproductive-aged women (15-49 years) of Bangladesh. We used the latest five rounds (2004, 2007, 2011, 2014, 2017-2018) of Bangladesh Demographic and Health Surveys (BDHSs). The regression based classical decomposition approach has been used to explore the determinants and their contribution in explaining the increased use of facility child birth. A sample of 26,686 reproductive-aged women were included in the analysis, 32.90% (8780) from the urban and 67.10% (17,906) from the rural area. We observed a 2.4-fold increase in delivery at facilities from 2004 to 2017-2018, in rural areas it is more than three times higher than the urban areas. The change in mean delivery at facilities is about 1.8 whereas, the predicted change is 1.4. In our full sample model antenatal care visits contribute the largest predicted change of 22.3%, wealth and education contributes 17.3% and 15.3% respectively. For the rural area health indicator (prenatal doctor visit) is the largest drivers contributing 42.7% of the predicted change, hereafter education, demography and wealth. However, in urban area education and health contributed equally 32.0% of the change followed by demography (26.3%) and wealth (9.7%). Demographic variables (maternal BMI, birth order, age at marriage) contributing more than two-thirds (41.2%) of the predicted change in the model without the health variables. All models showed more than 60.0% predictive power. Health sector interventions should focus both coverage and quality of maternal health care services to sustain steady improvements in child birth facilities. [Abstract copyright: © 2023 The Authors. Published by Elsevier Ltd.