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

Static pipeline network performance optimisation using dual interleave routing algorithm

Copyright © 2022 The Author(s). In the recent years, there is an increasing demand on multi-hop wireless sensor networks (WSN) especially for remote condition and integrity monitoring of oil and gas pipelines. The sensing points are connected through WSN points, known as a wireless communication medium, between the remotely measured locations on a pipeline and a centralised monitoring station, located some distance away. Generally, WSN deployment on a multi-hop linear topology has critical factors that contribute towards overall degrading of network performance proportional to the number of nodes. This is especially true in highly dense networks. In general, such a drawback contributes towards poor network reliability, low network capacity, high latency, and inequality with snowballing effect, increasing in the direction of the destination node. This paper introduces the Dual Interleaving Linear Static Routing (DI-LSR) for a multi-hop linear network with high reliability and efficiency to significantly enhance the overall network performance of a pipeline network. The DI-LSR was tested and analysed according to IEEE 802.11 standard in a various simulation environment for future real-time deployment in a pipeline network.ABSTRAK: Sejak beberapa tahun kebelakangan ini, terdapat permintaan yang drastik pada rangkaian multi-hop sensor wayarles (WSN) terutamanya bagi pemantauan jarak jauh dan integriti saluran paip minyak dan gas. Kesemua unit pengesan antara lokasi disambung melalui satu saluran WSN yang dikenali sebagai medium komunikasi wayarles dan diukur ke stesen pemantauan berpusat. Penempatan WSN pada topologi linear multi-hop mempunyai faktor-faktor penyumbang kepada penurunan prestasi keseluruhan rangkaian yang berkadar dengan jumlah bilangan nod dalam rangkaian yang padat. Secara umum, kelemahan ini adalah penyumbang kepada kebolehpercayaan rangkaian, kapasiti rangkaian rendah, respon rangkaian tinggi dan faktor pendorong kesan ketidaksamaan terhadap nod destinasi. Kajian ini memperkenalkan Dual interleaving Linear Static Routing (DI-LSR) iaitu algoritma jalinan komunikasi cekap bagi mencapai peningkatan ketara keseluruhan prestasi dalam saluran paip rangkaian. DI-LSR telah diuji dan dianalisa dalam pelbagai persekitaran simulasi mengikut piawaian IEEE 802.11 bagi mengatur kedudukan pada masa depan saluran paip rangkaian.This work is part of a research project entitled Analysis and implementation of an IoT based remote monitoring of oil and gas pipelines, grant no. PJP/2018/FKEKK (5B)/S01618 funded by Universiti Teknikal Malaysia Melaka

A critical look at studies applying over-sampling on the TPEHGDB dataset

Preterm birth is the leading cause of death among young children and has a large prevalence globally. Machine learning models, based on features extracted from clinical sources such as electronic patient files, yield promising results. In this study, we review similar studies that constructed predictive models based on a publicly available dataset, called the Term-Preterm EHG Database (TPEHGDB), which contains electrohysterogram signals on top of clinical data. These studies often report near-perfect prediction results, by applying over-sampling as a means of data augmentation. We reconstruct these results to show that they can only be achieved when data augmentation is applied on the entire dataset prior to partitioning into training and testing set. This results in (i) samples that are highly correlated to data points from the test set are introduced and added to the training set, and (ii) artificial samples that are highly correlated to points from the training set being added to the test set. Many previously reported results therefore carry little meaning in terms of the actual effectiveness of the model in making predictions on unseen data in a real-world setting. After focusing on the danger of applying over-sampling strategies before data partitioning, we present a realistic baseline for the TPEHGDB dataset and show how the predictive performance and clinical use can be improved by incorporating features from electrohysterogram sensors and by applying over-sampling on the training set

Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease

We present the first application of the hypothesis-rich mathematical theory to genome-wide association data. The Hamza et al. late-onset sporadic Parkinson's disease genome-wide association study dataset was analyzed. We found a rare, coding, non-synonymous SNP variant in the gene DZIP1 that confers increased susceptibility to Parkinson's disease. The association of DZIP1 with Parkinson's disease is consistent with a Parkinson's disease stem-cell ageing theory.Comment: 14 page

Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression

Trials of large group teaching in Malaysian private universities: a cross sectional study of teaching medicine and other disciplines

<p>Abstract</p> <p>Background</p> <p>This is a pilot cross sectional study using both quantitative and qualitative approach towards tutors teaching large classes in private universities in the Klang Valley (comprising Kuala Lumpur, its suburbs, adjoining towns in the State of Selangor) and the State of Negeri Sembilan, Malaysia. The general aim of this study is to determine the difficulties faced by tutors when teaching large group of students and to outline appropriate recommendations in overcoming them.</p> <p>Findings</p> <p>Thirty-two academics from six private universities from different faculties such as Medical Sciences, Business, Information Technology, and Engineering disciplines participated in this study. SPSS software was used to analyse the data. The results in general indicate that the conventional instructor-student approach has its shortcoming and requires changes. Interestingly, tutors from Medicine and IT less often faced difficulties and had positive experience in teaching large group of students.</p> <p>Conclusion</p> <p>However several suggestions were proposed to overcome these difficulties ranging from breaking into smaller classes, adopting innovative teaching, use of interactive learning methods incorporating interactive assessment and creative technology which enhanced students learning. Furthermore the study provides insights on the trials of large group teaching which are clearly identified to help tutors realise its impact on teaching. The suggestions to overcome these difficulties and to maximize student learning can serve as a guideline for tutors who face these challenges.</p

RNA Binding Protein CUGBP2/CELF2 Mediates Curcumin-Induced Mitotic Catastrophe of Pancreatic Cancer Cells

Curcumin inhibits the growth of pancreatic cancer tumor xenografts in nude mice; however, the mechanism of action is not well understood. It is becoming increasingly clear that RNA binding proteins regulate posttranscriptional gene expression and play a critical role in RNA stability and translation. Here, we have determined that curcumin modulates the expression of RNA binding protein CUGBP2 to inhibit pancreatic cancer growth.In this study, we show that curcumin treated tumor xenografts have a significant reduction in tumor volume and angiogenesis. Curcumin inhibited the proliferation, while inducing G2-M arrest and apoptosis resulting in mitotic catastrophe of various pancreatic cancer cells. This was further confirmed by increased phosphorylation of checkpoint kinase 2 (Chk2) protein coupled with higher levels of nuclear cyclin B1 and Cdc-2. Curcumin increased the expression of cyclooxygenase-2 (COX-2) and vascular endothelial growth factor (VEGF) mRNA, but protein levels were lower. Furthermore, curcumin increased the expression of RNA binding proteins CUGBP2/CELF2 and TIA-1. CUGBP2 binding to COX-2 and VEGF mRNA was also enhanced, thereby increasing mRNA stability, the half-life changing from 30 min to 8 h. On the other hand, silencer-mediated knockdown of CUGBP2 partially restored the expression of COX-2 and VEGF even with curcumin treatment. COX-2 and VEGF mRNA levels were reduced to control levels, while proteins levels were higher.Curcumin inhibits pancreatic tumor growth through mitotic catastrophe by increasing the expression of RNA binding protein CUGBP2, thereby inhibiting the translation of COX-2 and VEGF mRNA. These data suggest that translation inhibition is a novel mechanism of action for curcumin during the therapeutic intervention of pancreatic cancers