Framework of damage detection in vehicle-bridge coupled system and application to bridge scour monitoring

Most vibration-based damage identification methods make use of measurements directly from bridge structures with attached sensors. However, the vehicle moving on the bridge can serve as both an active actuator and a response receiver. This dissertation aimed to develop new methodologies to eventually detect bridge damages such as scour using the dynamic response of the vehicle. To reach the final objective, a framework of damage identification was developed first, which gave a guideline on the three crucial steps for damage detection. An optimization method was proposed that combines the Genetic Algorithm (GA) and the First Order (FO) method. It has the advantages of the global and local algorithms and converges faster than the traditional method using any initial values. Secondly, a new methodology using the transmissibility of vehicle and bridge responses was developed to detect bridge damages. The transmissibility of a simplified vehicle-bridge coupled (VBC) system was analyzed theoretically and numerically to study the feasibility of this method. To obtain the transmissibility, two methods were proposed using two “static” vehicles on the bridge. Then, a tractor-trailer test system was designed to obtain reliable responses and extract bridge modal properties from the dynamic response of moving vehicles. The test vehicle consists of a tractor and two following trailers. The residual responses of the two trailers were used, which successfully eliminated the roughness and vehicle driving effect and extracted the bridge modal properties. This methodology was applied on a field bridge and revealed a good performance. Most previous studies of bridge scour focus on the scour causes instead of its consequences. Finally, in this dissertation the developed methodologies were applied to detect scour damage from the response of bridge and/or vehicles. The scour effect on a single pile was studied and methods of scour damage detections were proposed. A monitoring system using fiber optic sensors was designed and tested in the laboratory and is being applied to a field bridge. Finally, the scour effect on the response of the entire bridge and the traveling vehicle was also investigated under the bridge-vehicle-wave interaction, which in turn was used to detect the bridge scour

Researchers who lead the trends

Xuan-Hung Doan, Phuong-Tram T. Nguyen, Viet-Phuong La, Hong-Kong T. Nguyen (2019). Chapter 5. Researchers who lead the trends. In Quan-Hoang Vuong, Trung Tran (Eds.), The Vietnamese Social Sciences at a Fork in the Road (pp. 98–120). Warsaw, Poland: De Gruyter. DOI:10.2478/9783110686081-010 Online ISBN: 9783110686081 © 2019 Sciend

Repeatability of nerve conduction measurements derived entirely by computer methods

<p>Abstract</p> <p>Background</p> <p>Nerve conduction studies are an objective, quantitative, and reproducible measure of peripheral nerve function and are widely used in the diagnosis of neuropathies. The purpose of this study is to determine the reliability of nerve conduction parameters derived entirely from computer based data acquisition and waveform cursor assignments and to quantify the relative contributions of test variability sources.</p> <p>Methods</p> <p>Thirty volunteers, some with symptoms suggestive of neuropathies; of these, 29 completed the study. The median, ulnar, deep peroneal, posterior tibial, and sural nerves were evaluated bilaterally at two test sessions 3-7 days apart. Within each session, nerves were tested twice within 10 minutes. The analyzed nerve conduction parameters include motor latencies, motor conduction velocity (CV), compound muscle action potential (CMAP) amplitude, F-wave latencies (minimum, mean and maximum), sensory peak latency (DSL), sensory CV, and sensory nerve action potential (SNAP) amplitude. The primary outcome measure is variance component analysis and the corresponding coefficient of variation (CoV). The between-session-test variance is the sum of within-session variance and between-session variance, quantifying the total variation between test sessions. Additional statistical measures include the intraclass correlation coefficient (ICC) and relative interval variation (RIV).</p> <p>Results</p> <p>Motor and sensory latencies, CV and F-wave latency parameters have low between-session-test CoVs, ranging from 4.2% to 9.8%. Amplitude parameters have a higher between-session-test CoVs in the range of 15.6--19.8%. Between-test CoVs are about 30--80% lower than between-session CoVs with the exception of F-wave latency parameters. Between-test ICC values are 0.96 or above for all parameters. Between-session ICC ranges from 0.98 for F-wave latency to 0.77 for sural sensory CV. All latency-related between-session ICCs have a value 0.83 or above. The RIVs are the tightest for F-wave latency parameters and widest for CMAP amplitude parameters. Repeatability in a sub-group of subjects with more severe symptom grades follows the same trend as the overall study population without substantial quantitative differences.</p> <p>Conclusion</p> <p>The study demonstrates the high repeatability of nerve conduction parameters acquired by modern electrodiagnostic instruments using computer based waveform cursor assignment. The reliability is comparable to benchmark studies in which the nerve conduction measurements were performed manually in controlled multi-center clinical trials. Furthermore, the ranking of reliability, whereby F-wave latencies have the best reproducibility and amplitudes the worst, is also consistent with the benchmark studies.</p

The Impact of Cybercrime in Modern Generation Based on Systematic Literature Review Analysis

Cybercrime is a term for any illegal activity that uses a computer as its primary means of commission. Due to the pervasive presence of the internet, the modern generation faces unprecedented challenges posed by cybercrime. Cybercrime has brought a lot of impacts to individuals, societies, and institutions in contemporary times. Sadly, it has become one of the most worrying issues in the current world. This study was done to determine the impact of cybercrime in modern generation. This research employs a qualitative approach by conducting a systematic literature review utilizing the PRISMA method. Moreover, it incorporates the outcomes of prior studies by employing a screening process to identify and critically access each one, thereby reestablishing their significance with the current study. The results of the study found impacts of cybercrime in modern generation which are financial consequences, expanding security budget, social implications, information security concern, and psychological and emotional toll

Optimal Control Strategies in an Alcoholism Model

This paper presents a deterministic SATQ-type mathematical model (including susceptible, alcoholism, treating, and quitting compartments) for the spread of alcoholism with two control strategies to gain insights into this increasingly concerned about health and social phenomenon. Some properties of the solutions to the model including positivity, existence and stability are analyzed. The optimal control strategies are derived by proposing an objective functional and using Pontryagin’s Maximum Principle. Numerical simulations are also conducted in the analytic results

Using Fine-grained Emotion Computing Model to Analyze the Interactions between Netizens’ Sentiments and Stock Returns

From the perspective of behavioural finance, this paper combines the fine-grained sentiment calculation with the stock market econometric model to explore the interactions between netizens’ sentiments and stock returns, analyze the differences in the influences of various emotions expressed by netizens on the stock market. First, it constructs a sentiment dictionary for the financial field; then, it calculates the emotion values contained in the text corpus, and constructs a textual sentiment classifier based on the recurrent neural network, calculates the emotion value and establishes the daily netizen sentiment index; and finally, it builds an econometric model to study the interactions between the netizen sentiment index and the stock returns. The results show that this model improves the accuracy of sentiment classification, reduces the number of iterations and saves computing resources; and that the netizen sentiment index, especially, “disgust” and “like”, has significant effects on the stock price changes and transaction volumes, while on the other hand, the listed company’s stock returns data has no reverse effect on the netizen sentiment index

Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study

With the fast advances in nextgen sequencing technology, high-throughput RNA sequencing has emerged as a powerful and cost-effective way for transcriptome study. De novo assembly of transcripts provides an important solution to transcriptome analysis for organisms with no reference genome. However, there lacked understanding on how the different variables affected assembly outcomes, and there was no consensus on how to approach an optimal solution by selecting software tool and suitable strategy based on the properties of RNA-Seq data. To reveal the performance of different programs for transcriptome assembly, this work analyzed some important factors, including k-mer values, genome complexity, coverage depth, directional reads, etc. Seven program conditions, four single k-mer assemblers (SK: SOAPdenovo, ABySS, Oases and Trinity) and three multiple k-mer methods (MK: SOAPdenovo-MK, trans-ABySS and Oases-MK) were tested. While small and large k-mer values performed better for reconstructing lowly and highly expressed transcripts, respectively, MK strategy worked well for almost all ranges of expression quintiles. Among SK tools, Trinity performed well across various conditions but took the longest running time. Oases consumed the most memory whereas SOAPdenovo required the shortest runtime but worked poorly to reconstruct full-length CDS. ABySS showed some good balance between resource usage and quality of assemblies. Our work compared the performance of publicly available transcriptome assemblers, and analyzed important factors affecting de novo assembly. Some practical guidelines for transcript reconstruction from short-read RNA-Seq data were proposed. De novo assembly of C. sinensis transcriptome was greatly improved using some optimized methods