Displacement monitoring technique using a smartphone based on the laser projection-sensing method

Infrastructure systems are tied closely to the function of human society in many aspects. Effective approaches to maintaining infrastructure are critical for public safety. The assessment of structural conditions, diagnosis of structural damage, and infrastructure safety protection may be achieved by monitoring and analyzing structural responses. Many approaches have been pursued to monitor different types of structural responses; displacement monitoring is one of the commonly used approaches. Various types of sensors have been developed to monitor structural displacement with a range of cost, ease-of-use, and effectiveness. Radar systems provide a family of high-accuracy displacement measurements. Specifically, continuous-wave (CW) radar is a promising technology for structural applications. CW radar transmits the microwave to the target continuously and captures the signal reflected. By analyzing the difference between the transmitted and reflected microwaves, the radar can measure the relative displacement between the target and the radar. Some specific types of CW radars have been developed to monitor structural displacement and have demonstrated promising performance. Radar-based structural monitoring applications are presented and specific types of CW radars developed for structural monitoring are introduced. The operating mechanism for conducting displacement measurement with CW radars is presented. The hardware designs of the CW radars and the signal processing from radar signals to final displacement information are described. The structural displacement monitoring using the CW radar is quantified in both laboratory and field validation experiments. Challenges associated with applying the CW radar to monitoring structural displacement are summarized, and future work to improve the performance of CW radar is suggested.

To decrease the cost of instrumentation for the strain and displacement monitoring method that uses sensors as well as considers the structural health monitoring challenges in sensor installation, it is necessary to develop a machine vision-based monitoring method. For this method, the most important step is the accurate extraction of the image feature. In this article, the edge detection operator based on multi-scale structure elements and the compound mathematical morphological operator is proposed to provide improved image feature extraction. The proposed method can not only achieve an improved filtering effect and anti-noise ability but can also detect the edge more accurately. Furthermore, the required image features (vertex of a square calibration board and centroid of a circular target) can be accurately extracted using the extracted image edge information. For validation, the monitoring tests for the structural local mean strain and in-plane displacement were designed accordingly. Through analysis of the error between the measured and calculated values of the structural strain and displacement, the feasibility and effectiveness of the proposed edge detection operator are verified.

Structural dynamic displacement is an important indicator of the health condition of long-span bridges. Monitoring of bridge dynamic displacement has been a critical task within the context of structural health monitoring (SHM). Traditionally, the structural displacement measurement methods are contact, wired and time-consuming. With the great progress of image processing technique and vision robot science, the visionbased monitoring systems have been developed rapidly and received a huge amount of attentions in the field of SHM. However, in the practical applications, the environmental factors will affect the operational performance of the vision-based system. In this study, a series of comparative experiments are conducted to explore the robustness of vision-based structural dynamic displacement monitoring under varying illumination conditions by use of various types of vision targets (quick response (QR) code and LED lamp). The experimental results indicate that the robustness of the vision-based system is weakened under poor illumination conditions when the QR code is used to be the vision target in comparison with the vision target of LED lamp.

An enhanced inverse finite element method for displacement and stress monitoring of multilayered composite and sandwich structures

A novel approach for displacement and stress monitoring of sandwich structures based on the inverse Finite Element Method

Structural displacement estimation by fusing vision camera and accelerometer using hybrid computer vision algorithm and adaptive multi-rate Kalman filter

This paper is aimed at increasing the demand of real-time access and application services. An Internet in vehicles system based on On-Board Diagnostics (OBD) technology and android platform was proposed. This system was composed of a data acquisition device, an android smartphone, network access and a remote service center. Through the OBD interface interacting with the vehicle, the vehicle identification number (VIN), mileage, and condition information can be obtained, which could be used for vehicle identification and effective vehicle condition monitoring and control. The intelligent navigation services using GPS, AGPS, and INS based on an android smartphone was provided so the corresponding manmachine voice interaction and network data switching could be achieved. The results of the experiment indicated that the system can effectively provide data sharing, intelligent navigation, and remote fault diagnosis services, which can meet needs of the real-time capability and applicability of the Internet in vehicles system.

In this work, we demonstrate that wireless surface acoustic wave devices can be used to monitor millimetre displacements in crack opening during the cyclic and static loading of reinforced concrete structures. Sensors were packaged to extend their gauge length and to protect them against brittle fracture, before being surface-mounted onto the tensioned surface of a concrete beam. The accuracy of measurements was verified using computational methods and optical-fibre strain sensors. After packaging, the displacement and temperature resolutions of the surface acoustic wave sensors were 10 and 2 °C respectively. With some further work, these devices could be retrofitted to existing concrete structures to facilitate wireless structural health monitoring.

BackgroundThe results of cardiac troponin I (cTnI) methods used in the diagnosis of acute myocardial infarction (AMI) are highly variable. In this study, it was aimed to compare the analytical performance of the Mindray CL-series TnI method with the Beckman Coulter-Access II AccuTnI+3 method.MethodsAnalytical performance and method comparison experiments for cTnI measurement with Mindray CL-1000i and Beckman Coulter-Access II instruments were with the Clinical and Laboratory Standards Institute (CLSI) documents EP15-A3 and EP9-A3. Precision studies were performed with commercially available third-party quality control (QC) materials. Method comparison experiments were performed by using patient samples. Furthermore, the limit of quantification (LoQ), total analytical error (TAE), and sigma metrics of both methods was determined.ResultsThe repeatability CV% for the three levels of Mindray CL-series TnI were 1.86, 1.75, and 1.08, while within the laboratory, CV% values were 3.36, 5.27, and 5.82. The quantification limits for Mindray CL-series and Beckman AccuTnI+3 were found to be 0.0085 and 0.0366 ng/mL with a CV level of less than 10%, respectively. The Mindray CL-series TnI results in the method comparison study were higher compared to the Beckman Coulter Access II AccuTnI+3 method.ConclusionsWith low repeatability, low bias, and low LoQ, The Mindray CL-series cTnI method shows it may be used safely in its category. The significant difference between the two methods in the method comparison study reveals cTnI methods in the market should be standardized to ensure global traceability.

ObjectivesCeftazidime/avibactam is used for severe infections caused by carbapenemase-producing Klebsiella pneumoniae. Combination therapy with older antibiotics is frequently used, but the supporting data are limited. This study aimed to evaluate ceftazidime/avibactam in combination with colistin against KPC-2-producing K. pneumoniae.Material and methodsFive clinical KPC-2-producing K. pneumoniae strains were characterized by phenotypic antibiotic susceptibility testing and whole-genome sequencing. Single antibiotics and combinations were evaluated in 24-h static time-kill experiments with ceftazidime/avibactam concentrations of 0.5× MICratio and colistin at 0.5× and 1× MIC. One strain was subjected to 32-h dynamic time-kill experiments with ceftazidime/avibactam at concentrations mimicking patient pharmacokinetics in plasma and colistin added to 1 mg/L, i.e. the average free steady-state concentration. Population analysis was performed at 0, 16, and 32 h by plating at 4× and 8× MICratio (ceftazidime/avibactam) or MIC (colistin) to assess resistance development.ResultsAll strains were susceptible to ceftazidime/avibactam and colistin, had mutations in ompK35 and ompK36, and carried multiple β-lactamase genes. Ceftazidime/avibactam combined with colistin demonstrated 24-h synergy in static time-kill experiments against 3 of 5 strains. Although ceftazidime/avibactam and colistin alone showed rapid initial killing in the dynamic experiments, regrowth occurred after 4–8 h. The three-drug combination displayed a bactericidal effect and synergy at 14–32 h. Resistance development resulting in 64-fold MIC increases was observed in experiments with colistin alone.ConclusionsThis study showed synergy with ceftazidime/avibactam and colistin against KPC-2-producing K. pneumoniae at clinically relevant concentrations. More studies are warranted to investigate the clinical potential of this combination.

Nowadays some universities have been using e-learning in the teaching-learning process. Generally e-learning available in the form of web based application, but does not exist in the form of mobile application yet. Problem that arise when using a mobile device is the screen size is too small, so that the user need to zoom and scroll to get comfortable viewing. Another problem is the user using varying operating system such as android, blackberry and iOS. To overcome those problems, this research is conducted to assist in the teaching-learning process by developing a model of mobile e-learning application that can run on cross-platform, which is on Android and BlackBerry platform. The application is created using PhoneGap that uses HTML5, CSS3, and JavaScript based on Hybrid Mobile Application. The system on the application follows Lentera e-learning system based on Moodle. Lentera is a web based e-learning system used in Petra Charistian University. On the server side, it takes a modified Moodle's source code based on PHP so the application can be run in accordance with the system. The application has a different interface from the website version. The interface is designed to be suitable on smartphone which is has limited screen space. The result shows that the application can run on cross-platform, those are Blackberry and Android smartphone. The application also runs online together with the Lentera website. The basic features of Lentera have been successfully implemented on this application. Assessment of the application as a whole is more than 50% of respondents answered very good.

As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; understanding of images. For mobile computer vision, Smartphone must be faster and real time. In this study two applications have been developed on Android platform using OpenCV and core library called as CamTest with own implemented algorithms. Efficiency of two Android applications have been compared and found that OpenCV performs faster than CamTest. The results of examining the best object detection algorithm with reverence to efficiency shows that FAST algorithm has the finest blend of speed and object detection performance. Next projected object recognition system using FAST algorithm, which uses SVM, BPNN for training and validation of object in real time. The application detects the object perfectly with recognition time around 2 ms using SVM and 1 ms using BPNN.

In this paper, the authors propose a smart home-care system built on an Android smartphone. The database and application programming interface (API) are set up on the server side. The database collects information from various sensors and stores it, and the API acts as a bridge between the mobile phone and the database. The API prevents the leakage of private data. In the associated Android smartphone app, two functions are provided: instant monitoring based on in-home sensor data and fall detection using the three-axis accelerometer, gyroscope, and orientation sensor inbuilt into the smartphone. When the sensor data are abnormal, the remote controller is notified immediately. Moreover, the remote controller can view real-time images by using an IP camera to guarantee home safety. As for fall detection, given that falls cause severe injuries in elder people and children, the proposed app can detect a fall event, send a help message, and indicate the user’s location by using the global positioning system and Google Maps API. According to the simulation results obtained in this study, the proposed system exhibited a fall-detection sensitivity of 92.5% and specificity of 97.6%, thus proving that the system can be effectively used for home care.

Objectives We evaluated analytical performance, functionality, reliability, and comparability of cobas® pure integrated solutions (Roche Diagnostics) under routine-like conditions. Methods The study was conducted in Europe and Asia (five sites). Seventy-six applications covering ion selective electrolytes (ISE), clinical chemistry (CC), and immunochemistry (IC) analytes were assessed using Elecsys® immunochemistry assays (Roche Diagnostics). Samples included control material and pseudonymized residual samples (plasma/serum/urine). Analytical performance, functionality, and system reliability were evaluated. An inter-laboratory survey, routine simulation imprecision (RSI) and method comparison experiments, and dedicated workflow runs were conducted. Results Most coefficients of variation (CVs) for repeatability were <1 % for ISE, ≤2 % for CC, and <2.5 % for IC assays; for intermediate precision were ≤2 % for ISE and CC, and <2.5 % for IC assays; and for reproducibility were ≤3 % for ISE and CC, and <2.5 % for IC assays. Most RSI reference (94 %) and random part (93 %) CVs were ≤2 %; 99 % of runs completed without system-related interruption. 218 method comparisons generated median Passing–Bablok slope of 1.00, median bias at the medical decision point of −0.1 %, and median Pearson’s r of 0.998. Conclusions cobas pure integrated solutions demonstrated precise and accurate results under routine-like conditions and comparable results vs. commercial analyzers, supporting implementation into routine practice.

In squamous cell carcinoma, squamous cell carcinoma antigen levels are often elevated. This multi-center study evaluated the technical performance of a new Elecsys® squamous cell carcinoma assay, which measures serum squamous cell carcinoma antigen 1 and 2 levels in an equimolar manner, and investigated the potential of squamous cell carcinoma antigen for differential diagnosis of cervical, lung, and head and neck squamous cell carcinoma.Assay precision and method comparison experiments were performed across three European sites. Reference ranges for reportedly healthy individuals were determined using samples from banked European and Chinese populations. Differential diagnosis experiments determined whether cervical, lung, or head and neck cancer could be differentiated from apparently healthy, benign, or other malignant cohorts using squamous cell carcinoma antigen levels alone. Squamous cell carcinoma antigen cut-off levels were calculated based on squamous cell carcinoma antigen levels at 95% specificity. Repeatability coefficients of variation across nine analyte concentrations were ≤5.3%, and intermediate precision coefficients of variation were ≤10.3%. Method comparisons showed good correlations with Architect and Kryptor systems (slopes of 1.1 and 1.5, respectively). Reference ranges for 95th percentiles for apparently healthy individuals were 2.3 ng/mL (95% confidence interval: 1.9-3.8; European cohort, n = 153) and 2.7 ng/mL (95% confidence interval: 2.2-3.3; Chinese cohort, n = 146). Strongest differential diagnosis results were observed for cervical squamous cell carcinoma: receiver operating characteristic analysis showed that squamous cell carcinoma antigen levels (2.9 ng/mL cut-off) differentiate cervical squamous cell carcinoma (n = 127) from apparently healthy females (n = 286; area under the curve: 86.2%; 95% confidence interval: 81.8-90.6; sensitivity: 61.4%; specificity: 95.6%), benign diseases (n = 187; area under the curve: 86.3%; 95% confidence interval: 81.2-91.3; sensitivity: 61.4%; specificity: 95.0%), and other cervical cancers (n = 157; area under the curve: 78.9%; 95% confidence interval: 70.8-87.1; sensitivity: 61.4%; specificity: 86.7%). Squamous cell carcinoma may also aid in the differential diagnosis of lung cancer. The Elecsys squamous cell carcinoma assay exhibited good technical performance and is suitable for differential diagnosis of cervical squamous cell carcinoma in clinical practice.