Search results for: automatic test system (ATS)

Authors: Ping Jiang, Yunyan Xing, Dian Zhang, Bo Guo

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The reliability qualification test (RQT) is widely used in product development to qualify whether the product meets predetermined reliability requirements, which are mainly described in terms of reliability indices, for example, MTBF (Mean Time Between Failures). It is widely exercised in product development. In engineering practices, RQT plans are mandatorily referred to standards, such as MIL-STD-781 or GJB899A-2009. But these conventional RQT plans in standards are not preferred, as the test plans often require long test times or have high risks for both producer and consumer due to the fact that the methods in the standards only use the test data of the product itself. And the standards usually assume that the product is exponentially distributed, which is not suitable for a complex product other than electronics. So it is desirable to develop an RQT plan derivation method that safely shortens test time while keeping the two risks under control. To meet this end, for the product whose lifetime follows Weibull distribution, an RQT plan derivation method is developed. The merit of the method is that expert judgment is taken into account. This is implemented by applying the Bayesian method, which translates the expert judgment into prior information on product reliability. Then producer’s risk and the consumer’s risk are calculated accordingly. The procedures to derive RQT plans are also proposed in this paper. As extra information and expert judgment are added to the derivation, the derived test plans have the potential to shorten the required test time and have satisfactory low risks for both producer and consumer, compared with conventional test plans. A case study is provided to prove that when using expert judgment in deriving product test plans, the proposed method is capable of finding ideal test plans that not only reduce the two risks but also shorten the required test time as well.

Keywords: expert judgment, reliability qualification test, test plan derivation, producer’s risk, consumer’s risk

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

Procedia PDF Downloads 343

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: control, fuzzy logic, sensitive system, technological proves

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Authors: Eric Yi-Hsiu Huang, Meng-Chun Kao, Wen-Chuan Kuo

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For every laparoscopic surgery, a safe pneumoperitoneumcreation (gaining access to the peritoneal cavity) is the first and essential step. However, closed pneumoperitoneum is usually obtained by blind insertion of a Veress needle into the peritoneal cavity, which may carry potential risks suchas bowel and vascular injury.Until now, there remains no definite measure to visually confirm the position of the needle tip inside the peritoneal cavity. Therefore, this study established an image-guided Veress needle method by combining a fiber probe with optical coherence tomography (OCT). An algorithm was also proposed for determining the exact location of the needle tip through the acquisition of OCT images. Our method not only generates a series of “live” two-dimensional (2D) images during the needle puncture toward the peritoneal cavity but also can eliminate operator variation in image judgment, thus improving peritoneal access safety. This study was approved by the Ethics Committee of Taipei Veterans General Hospital (Taipei VGH IACUC 2020-144). A total of 2400 in vivo OCT images, independent of each other, were acquired from experiments of forty peritoneal punctures on two piglets. Characteristic OCT image patterns could be observed during the puncturing process. The ROC curve demonstrates the discrimination capability of these quantitative image features of the classifier, showing the accuracy of the classifier for determining the inside vs. outside of the peritoneal was 98% (AUC=0.98). In summary, the present study demonstrates the ability of the combination of our proposed automatic identification method and OCT imaging for automatically and objectively identifying the location of the needle tip. OCT images translate the blind closed technique of peritoneal access into a visualized procedure, thus improving peritoneal access safety.

Keywords: pneumoperitoneum, optical coherence tomography, automatic identification, veress needle

Procedia PDF Downloads 126

Authors: Ahmet Yetik, Seyit Ali Kara, Cevat Özarpa

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Load changes occur on natural gas and oil pipelines due to natural disasters. The displacement of the soil around the natural gas and oil pipes due to situations that may cause erosion, such as earthquakes, landslides, and floods, is the source of this load change. The exposure of natural gas and oil pipes to variable loads causes deformation, cracks, and breaks in these pipes. Cracks and breaks on the pipes cause damage to people and the environment due to reasons such as explosions. Especially with the examinations made after natural disasters, it can be easily understood which of the pipes has more damage in the regions followed. It has been determined that the earthquakes in Turkey caused permanent damage to the pipelines. This project was designed and realized because it was determined that there were cracks and gas leaks in the insulation gaskets placed in the pipelines, especially at the junction points. In this study, A new SCADA (Supervisory Control and Data Acquisition) application has been developed to monitor load changes caused by natural disasters. The newly developed SCADA application monitors the changes in the x, y, and z axes of the stresses occurring in the pipes with the help of strain gauge sensors placed on the pipes. For the developed SCADA system, test setups in accordance with the standards were created during the fieldwork. The test setups created were integrated into the SCADA system, and the system was followed up. Thanks to the SCADA system developed with the field application, the load changes that will occur on the natural gas and oil pipes are instantly monitored, and the accumulations that may create a load on the pipes and their surroundings are immediately intervened, and new risks that may arise are prevented. It has contributed to energy supply security, asset management, pipeline holistic management, and sustainability.

Keywords: earthquake, natural gas pipes, oil pipes, strain measurement, stress measurement, landslide

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Authors: Chairul Fajar, Muhammad Nur Hidayat, Muksalmina

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The issue of Over Dimension Over Loading (ODOL) in Indonesia remains a significant challenge, causing traffic accidents, disrupting traffic flow, accelerating road damage, and potentially leading to bridge collapses. Klaten Regency, located on the slopes of Mount Merapi along the Woro River in Kemalang District, has potential Class C excavation materials such as sand and stone. Data from the Klaten Regency Transportation Department indicates that ODOL violations account for 72%, while non-violating vehicles make up only 28%. ODOL involves modifying factory-standard vehicles beyond the limits specified in the Type Test Registration Certificate (SRUT) to save costs and travel time. This study aims to develop a prototype ‘Sabrang’ monitoring system based on Arduino Mega to control and monitor ODOL freight transportation in the mining of Class C excavation materials in Klaten Regency. The prototype is designed to automatically measure the dimensions and weight of objects using a microcontroller. The data analysis techniques used in this study include the Normality Test and Paired T-Test, comparing sensor measurement results on scaled objects. The study results indicate differences in measurement validation under room temperature and ambient temperature conditions. Measurements at room temperature showed that the majority of H0 was accepted, meaning there was no significant difference in measurements when the prototype tool was used. Conversely, measurements at ambient temperature showed that the majority of H0 was rejected, indicating a significant difference in measurements when the prototype tool was used. In conclusion, the ‘Sabrang’ monitoring system prototype is effective for controlling ODOL, although measurement results are influenced by temperature conditions. This study is expected to assist in the monitoring and control of ODOL, thereby enhancing traffic safety and road infrastructure.

Keywords: over dimension over loading, prototype, microcontroller, Arduino, normality test, paired t-test

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Authors: S. K. Gupta, Richa Bansal

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In a deregulated power system structure, power producers, and customers share a common transmission network for wheeling power from the point of generation to the point of consumption. All parties in this open access environment may try to purchase the energy from the cheaper source for greater profit margins, which may lead to overloading and congestion of certain corridors of the transmission network. This may result in violation of line flow, voltage and stability limits and thereby undermine the system security. Utilities therefore need to determine adequately their Available Transfer Capability (ATC) to ensure that system reliability is maintained while serving a wide range of bilateral and multilateral transactions. This paper presents power transfer distribution factor based on AC load flow for the determination and enhancement of ATC. The study has been carried out for IEEE 24 bus Reliability Test System.

Keywords: available transfer capability, FACTS devices, power transfer distribution factors, electric

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Authors: Bin Li, Mei Liu

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Arrival time information is a crucial component of advanced public transport system (APTS). The advertisement of arrival time at stops can help reduce the waiting time and anxiety of passengers, and improve the quality of service. In this research, an experiment was conducted to compare the performance on prediction accuracy and precision between the link-based and the path-based historical travel time based model with the automatic vehicle location (AVL) data collected from an actual bus route. The research results show that the path-based model is superior to the link-based model, and achieves the best improvement on peak hours.

Keywords: bus transit, arrival time prediction, link-based, path-based

Procedia PDF Downloads 357

Authors: Pham Van Hung, Nguyen Trong Hieu, Le Quoc Dinh, Nguyen Kiem Chien, Le Dinh Hieu

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The article focuses on the study of automatic flight control on missiles during operation. The quality standards and characteristics of missile operations are very strict, requiring high stability and accurate response to commands within a relatively wide range of work. The study analyzes the linear transfer function model of the Missile Roll channel to facilitate the development of control systems. A two-loop control structure for the Missile Roll channel is proposed, with the inner loop controlling the Missile Roll rate and the outer loop controlling the Missile Roll angle. To determine the optimal control parameters, a genetic algorithm is applied. The study uses MATLAB simulation software to implement the genetic algorithm and evaluate the quality of the closed-loop system. The results show that the system achieves better quality than the original structure and is simple, reliable, and ready for implementation in practical experiments.

Keywords: genetic algorithm, roll chanel, two-loop control structure, missile

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Juan Ignacio Arango, Andres Diaz, Giacomo Barbieri

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In soilless culture, the definition of efficient fertigation strategies is fundamental for the growth of crops. Flexible test-benches able to independently manage groups of crops are key for investigating efficient fertigation practices through experimentation. These test-benches must be able to provide nutrient solution (NS) in a precise, uniform and repeatable way in order to effectively implement and compare different fertigation strategies. This article describes a distribution module for investigating fertigation practices able to control the fertigation dose and frequency. The proposed solution is characterized in terms of precision, uniformity and repeatability since these parameters are fundamental in the implementation of effective experiments for the investigation of fertigation practices. After a calibration process, the implemented system reaches a precision of 1mL, a uniformity of 98.5% at a total cost of 735USD.

Keywords: recision horticulture, test-bench, fertigation strategy, automation, flexibility

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Authors: Mohammed S. Assiri

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In EFL programs, rating scales used in writing assessment are often constructed by intuition. Intuition-based scales tend to provide inaccurate and divisive ratings of learners’ writing performance. Hence, following an empirical approach, this study attempted to develop a rating scale for elementary-level writing at an EFL program in Saudi Arabia. Towards this goal, 98 students’ essays were scored and then coded using comprehensive taxonomy of writing constructs and their measures. An automatic linear modeling was run to find out which measures would best predict essay scores. A nonparametric ANOVA, the Kruskal-Wallis test, was then used to determine which measures could best differentiate among scoring levels. Findings indicated that there were certain measures that could serve as either good predictors of essay scores or differentiators among scoring levels, or both. The main conclusion was that a rating scale can be empirically developed using predictive and discriminative statistical tests.

Keywords: analytic scoring, rating scales, writing assessment, writing constructs, writing performance

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Authors: Kamna Solanki, Yudhvir Singh, Sandeep Dalal

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Software testing is a time and cost intensive process. A scrutiny of the code and rigorous testing is required to identify and rectify the putative bugs. The process of bug identification and its consequent correction is continuous in nature and often some of the bugs are removed after the software has been launched in the market. This process of code validation of the altered software during the maintenance phase is termed as Regression testing. Regression testing ubiquitously considers resource constraints; therefore, the deduction of an appropriate set of test cases, from the ensemble of the entire gamut of test cases, is a critical issue for regression test planning. This paper presents a novel method for designing a suitable prioritization process to optimize fault detection rate and performance of regression test on predefined constraints. The proposed method for test case prioritization m-ACO alters the food source selection criteria of natural ants and is basically a modified version of Ant Colony Optimization (ACO). The proposed m-ACO approach has been coded in 'Perl' language and results are validated using three examples by computation of Average Percentage of Faults Detected (APFD) metric.

Keywords: regression testing, software testing, test case prioritization, test suite optimization

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Authors: Dede Basturk, Metin Kaya, Halil Taskin, Nurtekin Erkmen

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In total, 29 students studying in Selçuk University Physical Training and Sports School who are recreationally active participated voluntarilyin this study which was carried out in order to examine effects of Vertimax trainings on agility, quickness and acceleration. 3 groups took their parts in this study as Vertimax training group (N=10), Ordinary training group (N=10) and Control group (N=9). Measurements were carried out in performance laboratory of Selçuk University Physical Training and Sports School. A training program for quickness and agility was followed up for subjects 3 days a week (Monday, Wednesday, Friday) for 8 weeks. Subjects taking their parts in vertimax training group and ordinary training group participated in the training program for quickness and agility. Measurements were applied as pre-test and post-test. Subjects of vertimax training group followed the training program with vertimax device and subjects of ordinary training group followed the training program without vertimax device. As to control group who are recreationally active, they did not participate in any program. 4 gate photocells were used for measuring and measurement of distances was carried out in m. Furthermore, single gate photocell and honi were used for agility test. Measurements started with 15 minutes of warm-up. Acceleration, quickness and agility tests were applied on subjects. 3 measurements were made for each subject at 3 minutes resting intervals. The best rating of three measurements was recorded. 5 m quickness pre-test value of vertimax training groups has been determined as 1,11±0,06 s and post-test value has been determined as 1,06 ± 0,08 s (P<0,05). 5 m quickness pre-test value of ordinary training group has been determined as 1,11±0,06 s and post-test value has been determined as 1,07±0,07 s (P<0,05).5 m quickness pre-test value of control group has been determined as 1,13±0,08 s and post-test value has been determined as 1,10 ± 0,07 s (P>0,05). Upon examination of 10 m acceleration value before and after the training, 10 m acceleration pre-test value of vertimax training group has been determined as 1,82 ± 0,07 s and post-test value has been determined as 1,76±0,83 s (P>0,05). 10 m acceleration pre-test value of ordinary training group has been determined as 1,83±0,05 s and post-test value has been determined as 1,78 ± 0,08 s (P>0,05).10 m acceleration pre-test value of control group has been determined as 1,87±0,11 s and post-test value has been determined as 1,83 ± 0,09 s (P>0,05). Upon examination of 15 m acceleration value before and after the training, 15 m acceleration pre-test value of vertimax training group has been determined as 2,52±0,10 s and post-test value has been determined as 2,46 ± 0,11 s (P>0,05).15 m acceleration pre-test value of ordinary training group has been determined as 2,52±0,05 s and post-test value has been determined as 2,48 ± 0,06 s (P>0,05). 15 m acceleration pre-test value of control group has been determined as 2,55 ± 0,11 s and post-test value has been determined as 2,54 ± 0,08 s (P>0,05).Upon examination of agility performance before and after the training, agility pre-test value of vertimax training group has been determined as 9,50±0,47 s and post-test value has been determined as 9,66 ± 0,47 s (P>0,05). Agility pre-test value of ordinary training group has been determined as 9,99 ± 0,05 s and post-test value has been determined as 9,86 ± 0,40 s (P>0,05). Agility pre-test value of control group has been determined as 9,74 ± 0,45 s and post-test value has been determined as 9,92 ± 0,49 s (P>0,05). Consequently, it has been observed that quickness and acceleration features were developed significantly following 8 weeks of vertimax training program and agility features were not developed significantly. It is suggested that training practices used for the study may be used for situations which may require sudden moves and in order to attain the maximum speed in a short time. Nevertheless, it is also suggested that this training practice does not make contribution in development of moves which may require sudden direction changes. It is suggested that productiveness and innovation may come off in terms of training by using various practices of vertimax trainings.

Keywords: vertimax, training, quickness, agility, acceleration

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Authors: Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii

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Today dairy farm experts and farmers have well recognized the importance of dairy cow Body Condition Score (BCS) since these scores can be used to optimize milk production, managing feeding system and as an indicator for abnormality in health even can be utilized to manage for having healthy calving times and process. In tradition, BCS measures are done by animal experts or trained technicians based on visual observations focusing on pin bones, pin, thurl and hook area, tail heads shapes, hook angles and short and long ribs. Since the traditional technique is very manual and subjective, the results can lead to different scores as well as not cost effective. Thus this paper proposes an algebraic geometric imaging approach for an automatic dairy cow BCS system. The proposed system consists of three functional modules. In the first module, significant landmarks or anatomical points from the cow image region are automatically extracted by using image processing techniques. To be specific, there are 23 anatomical points in the regions of ribs, hook bones, pin bone, thurl and tail head. These points are extracted by using block region based vertical and horizontal histogram methods. According to animal experts, the body condition scores depend mainly on the shape structure these regions. Therefore the second module will investigate some algebraic and geometric properties of the extracted anatomical points. Specifically, the second order polynomial regression is employed to a subset of anatomical points to produce the regression coefficients which are to be utilized as a part of feature vector in scoring process. In addition, the angles at thurl, pin, tail head and hook bone area are computed to extend the feature vector. Finally, in the third module, the extracted feature vectors are trained by using Markov Classification process to assign BCS for individual cows. Then the assigned BCS are revised by using multiple regression method to produce the final BCS score for dairy cows. In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.

Keywords: algebraic geometric imaging approach, body condition score, Markov classification, polynomial regression

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Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

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The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

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Authors: Sara Mahesar, Saleem M. Chandio, Hira Soomro

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Nonlinear system of equations in two variables is a system which contains variables of degree greater or equal to two or that comprises of the transcendental functions. Mathematical modeling of numerous physical problems occurs as a system of nonlinear equations. In applied and pure mathematics it is the main dispute to solve a system of nonlinear equations. Numerical techniques mainly used for finding the solution to problems where analytical methods are failed, which leads to the inexact solutions. To find the exact roots or solutions in case of the system of non-linear equations there does not exist any analytical technique. Various methods have been proposed to solve such systems with an improved rate of convergence and accuracy. In this paper, a new scheme is developed for solving system of non-linear equation in two variables. The iterative scheme proposed here is modified form of the conventional Newton’s Method (CN) whose order of convergence is two whereas the order of convergence of the devised technique is three. Furthermore, the detailed error and convergence analysis of the proposed method is also examined. Additionally, various numerical test problems are compared with the results of its counterpart conventional Newton’s Method (CN) which confirms the theoretic consequences of the proposed method.

Keywords: conventional Newton’s method, modified Newton’s method, order of convergence, system of nonlinear equations

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

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Authors: A. R. Bagirzade, A. Sh. Najafova, S. M. Yessirkepova, E. S. Albert

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This article describes a text recognition method based on Optical Character Recognition (OCR). The features of the OCR method were examined using the ABBYY FineReader program. It describes automatic text recognition in images. OCR is necessary because optical input devices can only transmit raster graphics as a result. Text recognition describes the task of recognizing letters shown as such, to identify and assign them an assigned numerical value in accordance with the usual text encoding (ASCII, Unicode). The peculiarity of this study conducted by the authors using the example of the ABBYY FineReader, was confirmed and shown in practice, the improvement of digital text recognition platforms developed by Electronic Publication.

Keywords: ABBYY FineReader system, algorithm symbol recognition, OCR/ICR techniques, recognition technologies

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Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

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New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

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Authors: Norbert Szulc, Cezary Wieczorkowski, Igor Baranowski

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In this paper, a control system that bridges the gap in support for Unmanned Surface Vessels in the PX4 Opensource Autopilot was developed. The system is designed for an omnidirectional water craft with four motors. A modular autopilot architecture design centred around publish-subscribe interprocess communication was used. The paper presents the implementation and integration process of a generic surface vehicle controller capable of driving any configuration of motors through the recently introduced in control allocator in PX4 autopilot. The proposed approach was successfully tested in a case study through implementation on the ASV Perkoz.

Keywords: control system, PX4, drones, rovers, surface vessels, omnidirectional

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Authors: Yanhui Jia, Ning Guo, Juan Li, Yunkui Sun, Wei Yang, Tianping Zhang, Lin Ma, Wei Meng, Hai Geng

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The current statuses of lifetime test of LaB6 hollow cathode at the Lanzhou institute of physics (LIP), China, was described. 5A LaB6 hollow cathode was designed for LIPS-200 40mN Xenon ion thruster and it could be used for LHT-100 80 mN Hall thruster, too. Life test of the discharge and neutralizer modes of LHC-5 hollow cathode were stared in October 2011, and cumulative operation time reached 17,300 and 16,100 hours in April 2015, respectively. The life of cathode was designed more than 11,000 hours. Parameters of discharge and key structure dimensions were monitored in different stage of life test indicated that cathodes were health enough. The test will continue until the cathode cannot work or operation parameter is not in normally. The result of the endurance test of cathode demonstrated that the LaB6 hollow cathode is satisfied for the required of thruster in life and performance.

Keywords: LaB6, hollow cathode, thruster, lifetime test, electric propulsion

Procedia PDF Downloads 602

Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Mahawish Masud, Muhammad Iqbal, M. U. Khan, Farooque Azam

Abstract:

Manual writing of test cases from functional requirements is a time-consuming task. Such test cases are not only difficult to write but are also challenging to maintain. Test cases can be drawn from the functional requirements that are expressed in natural language. However, manual test case generation is inefficient and subject to errors.  In this paper, we have presented a systematic procedure that could automatically derive test cases from user stories. The user stories are specified in a restricted natural language using a well-defined template.  We have also presented a detailed methodology for writing our test ready user stories. Our tool “Test-o-Matic” automatically generates the test cases by processing the restricted user stories. The generated test cases are executed by using open source Selenium IDE.  We evaluate our approach on a case study, which is an open source web based application. Effectiveness of our approach is evaluated by seeding faults in the open source case study using known mutation operators.  Results show that the test case generation from restricted user stories is a viable approach for automated testing of web applications.

Keywords: automated testing, natural language, restricted user story modeling, software engineering, software testing, test case specification, transformation and automation, user story, web application testing

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Authors: A. Nazeri, R. Ziaie Moayed, H. Ghiasinejad

Abstract:

The present research has been performed to investigate the effect of base course application on load-settlement characteristics of sandy subgrade using plate load test. The main parameter investigated in this study was the subgrade reaction coefficient. The model tests were conducted in a 1.35 m long, 1 m wide, and 1 m deep steel test box of Imam Khomeini International University (IKIU Calibration Chamber). The base courses used in this research were in three different thicknesses of 15 cm, 20 cm, and 30 cm. The test results indicated that in the case of using base course over loose sandy subgrade, the values of subgrade reaction coefficient can be increased from 7  to 132 , 224 , and 396  in presence of 15 cm, 20 cm, and 30 cm base course, respectively.

Keywords: modulus of subgrade reaction, plate load test, base course, sandy subgrade

Procedia PDF Downloads 246

Authors: Ricardo Chaves, Carlos Vasconcelos

Abstract:

Candidates to join the Naval Academy have to take a set of physical tests, which is crucial for a high level of physical fitness. Thus, the planning of physical exercises for candidates to the Naval School must take into account the improvement of their physical fitness. The aim of this study was to investigate the impact of a 6-month exercise program to improve the physical fitness of an individual who will apply for the Naval Academy. This was a non-experimental pre-post-evaluation study. The patient was male, had 18 years old, and a body mass index of 21.1 kg.m². The patient participated in a 6-month aerobic and strength exercise program (3 sessions per week, 75 minutes duration each session). Physical fitness tests were performed according to the physical fitness requirements for entry into the Naval academy (muscle strength [maximum number of lifts and maximum number of sit-ups for 1 minute]; aerobic fitness [2.4 km run and 200 m swimming test]) before (baseline) and after the exercise intervention (6 months). Regarding muscle strength, in the abdominal test, the improvements between the pre-test (39 abdominals.) and post-test (61 abdominals) were 56.4%. For elevations, there was an increase in its number by 150% between the pre-test (4 elevations) and post-test (10 elevations). With regard to aerobic fitness, in the 2.4 km race, there was an evolution of 32.0% between the pre-test (16.46 min.) and the post-test (12.42 min.). For the 200-meter swimming test, there was a negative variation of 2% between the pre-test (2.25 min.) and post-test (2.28 min). A 6-month aerobic and strength exercise program leads to a positive evolution in the muscular strength of the patient. Regarding aerobic fitness, opposite results were found, with a positive evolution in the 2.4 km running test and a negative evolution in the swimming test. In future exercise programs for the improvement of the physical fitness of candidates for the Naval Academy, more emphasis has to be done on specific swimming training.

Keywords: case study, exercise program, Naval Academy, physical fitness

Procedia PDF Downloads 88

Authors: Jawad Ul Haq, Evan Mazur, Ahmed Qureshi, Mohamed Al-Hussein

Abstract:

The uses of wood in furniture, building, bridges and aluminum in transportation and construction, make aluminum and forest economy a prominent matter in North America. Machines available to date to cut the aforementioned materials are mostly industry oriented with complex structure and operations which require special training and skill. Furthermore, requirements such as pneumatics, 3-phase supply are associated with cost, maintenance, and safety hazards. Power saws are very useful tools used to cut and shape materials; however, they can cause serious hand injuries. Operator’s hands in table saw are vulnerable as they are used to guide pieces into the saw. Apart from hands, saw operator is also prone to material being kicked back out of the saw or sustain eye or respiratory injuries due to rapidly flying sawdust and other debris. In this paper, design of an automatic saw cutting machine has been proposed to ensure safety, portability, usage at domestic level and capability to cut both aluminum and wood. This paper demonstrates detailed Mechanical design in SOLIDWORKS and Control Systems using Programmable Logic Controller (PLC), based on the aforementioned design objectives.

Keywords: programmable logic controller, saw cutting, control, automation

Procedia PDF Downloads 270

Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Arthur Ricardo Deps Miguel Ferreira, John Buchanan, Amarnath Banerjee

Abstract:

This paper describes the development of a virtual-reality system ARWED, which will be used in physical rehabilitation of patients with reduced upper extremity mobility to increase limb Active Range of Motion (AROM). The ARWED system performs a symmetric reflection and real-time mapping of the patient’s healthy limb on to their most affected limb, tapping into the mirror neuron system and facilitating the initial learning phase. Using the ARWED, future experiments will test the extension of the action-observation priming effect linked to the mirror-neuron system on healthy subjects and then stroke patients.

Keywords: physical rehabilitation, mirror neuron, virtual reality, stroke therapy

Procedia PDF Downloads 427

Authors: Elena V. Lysenko

Abstract:

Motivating as the leading function of a modern Human Resources Management involves issues of increasing the effectiveness of the organization in a broader context. During the formation of motivational systems, the top-management of organization should pay equal attention to both external motivation (incentive system) and internal (self-motivation). The balance of internal and external motivation harmonizes the relations between employers and employees, increases the level of job satisfaction by the organization staff, which in turn leads the organization to success and ensures the organization`s profitability and competitiveness in the market environment. The article is devoted to the study of personnel motivation system in the small metal trade company, which is located in Yekaterinburg, Russian Federation. The study took place during November-December, 2016 ordered by the Company Director to analyze the motivational potential of work (managerial aspect of motivation) and motivation of personnel (personnel aspect of motivation) with the purpose to construct a system of employees’ motivation. The research tools included 6 specially selected tests of motivation, which are: “Motivation profile of your job”, “Constructive motivational attitudes”, Tests about Motivation of achievements (1st variant: Test by А.Mehrabian by the theory of D.С.McClelland and 2nd variant: Test about leading needs according with the theory of D.С.MacClelland), Tests by T.Elers (1st variant: “Determination of the motivation towards success or to avoid failure” and 2nd variant: “Trends to achieve results or to avoid failure”). The results of the study showed only one, but fundamental problem of the whole organization: high level of both motivational potential in work and self-motivation, especially in terms of achievement motivation, but serious lack of productivity. According the results which study showed this problem is derived from insufficient staff competence. The research suggests basic guidelines in order to build the new personnel motivation system for this Company, which is planned to be developed in the nearest future.

Keywords: incentive system, motivation of achievements, motivation system, self-motivation

Procedia PDF Downloads 309