Search results for: automatic test system

Authors: Buse T. Aydin, Enver Ozdemir

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An automatic dependent surveillance-broadcast (ADS-B) system has serious security problems. In this study, a double layer authentication scheme between the aircraft and ground station, aircraft to aircraft, ground station to ATC tower is designed to prevent any unauthorized aircrafts from introducing themselves as friends. This method can be used as a solution to the problem of authentication. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or unknown according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as friend. As a result, the ADS-B messages coming from this authenticated friendly aircraft will be processed. In this method, even if the embedded key is captured by the unknown aircraft, without the information of the second layer, the unknown aircraft can easily be determined. Overall, in this work, we present a reliable system by adding physical layer in the authentication process.

Keywords: ADS-B, authentication, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 179

Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

Procedia PDF Downloads 149

Authors: H. J. Liu, Y. A. Chan, C. K. Pai, K. C. Tseng, Y. H. Chen, Y. L. Chan, T. C. Kuo

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To satisfy the mission requirement of the FORMOSAT-7 project, NSPO has initialized a self-reliant development on satellite propulsion technology. A trade-off study on different types of on-board propulsion system has been done. A green propellant, high-concentration hydrogen peroxide (H2O2 hereafter), is chosen in this research because it is ITAR-free, nontoxic and easy to produce. As the components designed for either cold gas or hydrazine propulsion system are not suitable for H2O2 propulsion system, the primary objective of the research is to develop the components compatible with H2O2. By cooperating with domestic research institutes and manufacturing vendors, several prototype components, including a diaphragm-type tank, pressure transducer, ball latching valve, and one-Newton thruster with catalyst bed, were manufactured, and the functional tests were performed successfully according to the mission requirements. The requisite environmental tests, including hot firing test, thermal vaccum test, vibration test and compatibility test, are prepared and will be to completed in the near future. To demonstrate the subsystem function, an Air-Bearing Thrust Stand (ABTS) and a real-time Data Acquisition & Control System (DACS) were implemented to assess the performance of the proposed H2O2 propulsion system. By measuring the distance that the thrust stand has traveled in a given time, the thrust force can be derived from the kinematics equation. To validate the feasibility of the approach, it is scheduled to assess the performance of a cold gas (N2) propulsion system prior to the H2O2 propulsion system.

Keywords: FORMOSAT-7, green propellant, Hydrogen peroxide, thruster

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Authors: Tao Feng, Wei-Wei Zhang, Chang-Ming Ding

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Cross-site scripting (XSS) is one of the most popular WEB Attacking methods at present, and also one of the most risky web attacks. Because of the population of JavaScript, the scene of the cross site scripting attack is also gradually expanded. However, since the web application developers tend to only focus on functional testing and lack the awareness of the XSS, which has made the on-line web projects exist many XSS vulnerabilities. In this paper, different various techniques of XSS attack are analyzed, and a method automatically to detect it is proposed. It is easy to check the results of vulnerability detection when running it as a plug-in.

Keywords: XSS, no target attack platform, automatic detection，XSS detection

Procedia PDF Downloads 403

Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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Authors: Reyhaneh Soltanshah, Hamid R. Zarandi

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In order to be more efficient in industries that are related to computer systems, software testing is necessary despite spending time and money. In the embedded system software test, complete knowledge of the embedded system architecture is necessary to avoid significant costs and damages. Software tests increase the price of the final product. The aim of this article is to provide a method to reduce time and cost in tests based on program structure. First, a complete review of eleven white box test methods based on ISO/IEC/IEEE 29119 2015 and 2021 versions has been done. The proposed algorithm is designed using two versions of the 29119 standards, and some white-box testing methods that are expensive or have little coverage have been removed. On each of the functions, white box test methods were applied according to the 29119 standard and then the proposed algorithm was implemented on the functions. To speed up the implementation of the proposed method, the Unity framework has been used with some changes. Unity framework can be used in embedded software testing due to its open source and ability to implement white box test methods. The test items obtained from these two approaches were evaluated using a mathematical ratio, which in various software mining reduced between 50% and 80% of the test cost and reached the desired result with the minimum number of test items.

Keywords: embedded software, reduce costs, software testing, white-box testing

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Authors: Sonay Ödemiş

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Movement Staff Notation System (MSNS) is a movement transcription, analyzing method, and it's been constantly improved since it was first developed in 2005. This method is based on human anatomy, is being used and applied in the lessons at The Department of Turkish Folk Dances in Istanbul Technical University, nowadays. In this research, it is aimed to discover, how MSNS can help to participants about learning the basic movements of lower extremity. This experiment has six volunteers who were randomly selected. Each volunteer has been graded for their dance backgrounds and all the volunteers have been studied for six weeks. Each week has included different topic and examples such as contacts on foot, jumps, timing, directions and basic symbols of MSNS. Examples have changed from easy to hard. On conclusion, 6 volunteer subjects were tested in final test. The tests were recorded with the camera. In this presentation, it will be explained and detailed the results of the reading test on MSNS. Some of important video records will be watched and interpreted after the test. As a conclusion, all the scores will be interpreted and assessed from different perspectives.

Keywords: dance notation, Turkish dances, reading test, Education

Procedia PDF Downloads 233

Authors: Minh-Thuan Nguyen, Phuong-Thai Nguyen, Van-Vinh Nguyen, Quang-Minh Nguyen

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Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the qualify of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.

Keywords: GPT-2, product description, transformer, task-adaptive, language model, pretraining

Procedia PDF Downloads 197

Authors: Pengzhou Lu, Liming Xin, Payam Tavakoli, Zhonghua Lin, Roberto V. P. Ribeiro, Mitesh V. Badiwala

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Ex vivo Heart Perfusion (EVHP) has been developed as an alternative strategy to expand cardiac donation by enabling resuscitation and functional assessment of hearts donated from marginal donors, which were previously not accepted. EVHP parameters, such as perfusion flow (PF) and perfusion pressure (PP) are crucial for optimal organ preservation. However, with the heart’s constant physiological changes during EVHP, such as coronary vascular resistance, manual control of these parameters is rendered imprecise and cumbersome for the operator. Additionally, low control precision and the long adjusting time may lead to irreversible damage to the myocardial tissue. To solve this problem, an automatic heart perfusion system was developed by applying a Human-Machine Interface (HMI) and a Programmable-Logic-Controller (PLC)-based circuit to control PF and PP. The PLC-based control system collects the data of PF and PP through flow probes and pressure transducers. It has two control modes: the RPM-flow mode and the pressure mode. The RPM-flow control mode is an open-loop system. It influences PF through providing and maintaining the desired speed inputted through the HMI to the centrifugal pump with a maximum error of 20 rpm. The pressure control mode is a closed-loop system where the operator selects a target Mean Arterial Pressure (MAP) to control PP. The inputs of the pressure control mode are the target MAP, received through the HMI, and the real MAP, received from the pressure transducer. A PID algorithm is applied to maintain the real MAP at the target value with a maximum error of 1mmHg. The precision and control speed of the RPM-flow control mode were examined by comparing the PLC-based system to an experienced operator (EO) across seven RPM adjustment ranges (500, 1000, 2000 and random RPM changes; 8 trials per range) tested in a random order. System’s PID algorithm performance in pressure control was assessed during 10 EVHP experiments using porcine hearts. Precision was examined through monitoring the steady-state pressure error throughout perfusion period, and stabilizing speed was tested by performing two MAP adjustment changes (4 trials per change) of 15 and 20mmHg. A total of 56 trials were performed to validate the RPM-flow control mode. Overall, the PLC-based system demonstrated the significantly faster speed than the EO in all trials (PLC 1.21±0.03, EO 3.69±0.23 seconds; p < 0.001) and greater precision to reach the desired RPM (PLC 10±0.7, EO 33±2.7 mean RPM error; p < 0.001). Regarding pressure control, the PLC-based system has the median precision of ±1mmHg error and the median stabilizing times in changing 15 and 20mmHg of MAP are 15 and 19.5 seconds respectively. The novel PLC-based control system was 3 times faster with 60% less error than the EO for RPM-flow control. In pressure control mode, it demonstrates a high precision and fast stabilizing speed. In summary, this novel system successfully controlled perfusion flow and pressure with high precision, stability and a fast response time through a user-friendly interface. This design may provide a viable technique for future development of novel heart preservation and assessment strategies during EVHP.

Keywords: automatic control system, biomedical engineering, ex-vivo heart perfusion, human-machine interface, programmable logic controller

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Authors: Saule Mussabekova, Samal Abzhanova

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The Kazakh Language Fluency Test, based on the IELTS exam, was implemented in 2012 at Nazarbayev University in Astana, Kazakhstan. We would like to share our experience in developing this exam and some exam results with other language instructors. In this paper, we will cover all these peculiarities and their related issues. The Kazakh Language Fluency Test is a young exam. During its development, we faced many difficulties. One of the goals of the university and the country is to encourage fluency in the Kazakh language for all citizens of the Republic. Nazarbayev University has introduced a Kazakh language program to assist in achieving this goal. This policy is one-step in ensuring that NU students have a thorough understanding of the Kazakh language through a fluency test based on the International English Language Testing System (IELTS). The Kazakh Language Fluency Test exam aims to determine student’s knowledge of Kazakh language. The fact is that there are three types of students at Nazarbayev University: Kazakh-speaking heritage learners, Russian-speaking and English-speaking students. Unfortunately, we have Kazakh students who do not speak Kazakh. All students who finished school with Russian language instruction are given Kazakh Language Fluency Test in order to determine their Kazakh level. After the test exam, all students can choose appropriate Kazakh course: Basic Kazakh, Intermediate Kazakh and Upper-Intermediate Kazakh. The Kazakh Language Fluency Test consists of four parts: Listening, Reading, Writing and Speaking. They are taken on the same day in the abovementioned order.

Keywords: diagnostic test, kazakh language, placement test, test result

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Authors: Pratibha Srivastava, Chithra V. J., Sudhakar S., Nitin K. D.

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A closed-loop system comprises of a controller, a response system, and an actuating system. The controller, which is the system under test for us, excites the actuators based on feedback from the sensors in a periodic manner. The sensors should provide the feedback to the System Under Test (SUT) within a deterministic time post excitation of the actuators. Any delay or miss in the generation of response or acquisition of excitation pulses may lead to control loop controller computation errors, which can be catastrophic in certain cases. Such systems categorised as hard real-time systems that need special strategies. The real-time operating systems available in the market may be the best solutions for such kind of simulations, but they pose limitations like the availability of the X Windows system, graphical interfaces, other user tools. In this paper, we present strategies that can be used on a general purpose operating system (Bare Linux Kernel) to achieve a deterministic deadline and hence have the added advantages of a GPOS with real-time features. Techniques shall be discussed how to make the time-critical application run with the highest priority in an uninterrupted manner, reduced network latency for distributed architecture, real-time data acquisition, data storage, and retrieval, user interactions, etc.

Keywords: real time data acquisition, real time kernel preemption, scheduling, network latency

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Authors: Naime Boudemagh, Zoheir Hammoudi

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The parameters estimation of the K-distribution is an essential part in radar detection. In fact, presence of interfering targets in reference cells causes a decrease in detection performances. In such situation, the estimate of the shape and the scale parameters are far from the actual values. In the order to avoid interfering targets, we propose an Automatic Censoring (AC) algorithm of radar interfering targets in K-distribution. The censoring technique used in this work offers a good discrimination between homogeneous and non-homogeneous environments. The homogeneous population is then used to estimate the unknown parameters by the classical Method of Moment (MOM). The AC algorithm does not need any prior information about the clutter parameters nor does it require both the number and the position of interfering targets. The accuracy of the estimation parameters obtained by this algorithm are validated and compared to various actual values of the shape parameter, using Monte Carlo simulations, this latter show that the probability of censing in multiple target situations are in good agreement.

Keywords: parameters estimation, method of moments, automatic censoring, K distribution

Procedia PDF Downloads 373

Authors: Dar-Bin Shieh, Gwo-Bin Lee, Chen-Ming Chang, Chen Sheng Yeh, Chih-Chia Huang, Tsung-Ju Li

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Mitochondrial defects have a significant impact in many human diseases and aging associated phenotypes. The pathogenic mitochondrial DNA (mtDNA) mutations are diverse and usually present as heteroplasmic. mtDNA 4977bps deletion is one of the common mtDNA defects, and the ratio of mutated versus normal copy is significantly associated with clinical symptoms thus their quantitative detection has become an important unmet needs for advanced disease diagnosis and therapeutic guidelines. This study revealed a Micro-electro-mechanical-system (MEMS) enabled automatic microfluidic chip that only required minimal sample. The system integrated multiple laboratory operation steps into a Lab-on-a-Chip for high-sensitive and prompt measurement. The entire process including magnetic nanoparticle based mtDNA extraction in chip, mutation selective photonic DNA cleavage, and nanoparticle accelerated photonic quantitative polymerase chain reaction (qPCR). All subsystems were packed inside a miniature three-dimensional micro structured system and operated in an automatic manner. Integration of magnetic beads with microfluidic transportation could promptly extract and enrich the specific mtDNA. The near infrared responsive magnetic nanoparticles enabled micro-PCR to be operated by pulse-width-modulation controlled laser pulsing to amplify the desired mtDNA while quantified by fluorescence intensity captured by a complementary metal oxide system array detector. The proportions of pathogenic mtDNA in total DNA were thus obtained. Micro capillary electrophoresis module was used to analyze the amplicone products. In conclusion, this study demonstrated a new magnetophotonic based qPCR MEMS system that successfully detects and quantify specific disease related DNA mutations thus provides a promising future for rapid diagnosis of mitochondria diseases.

Keywords: mitochondrial DNA, micro-electro-mechanical-system, magnetophotonics, PCR

Procedia PDF Downloads 218

Authors: Xi Wang, Xiaoming Tao, Raymond C. H. So

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As one of the convenient and noninvasive sensing approaches, the automatic limb girth measurement has been applied to detect intention behind human motion from muscle deformation. The sensing validity has been elaborated by preliminary researches but still need more fundamental study, especially on kinetic contraction modes. Based on the novel fabric strain sensors, a soft and smart limb girth measurement system was developed by the authors’ group, which can measure the limb girth in-motion. Experiments were carried out on elbow isometric flexion and elbow isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and 120°/s for 10 subjects (2 canoeists and 8 ordinary people). After removal of natural circumferential increments due to elbow position, the joint torque is found not uniformly sensitive to the limb circumferential strains, but declining as elbow joint angle rises, regardless of the angular speed. Moreover, the maximum joint torque was found as an exponential function of the joint’s angular speed. This research highly contributes to the application of the automatic limb girth measuring during kinetic contractions, and it is useful to predict the contraction level of voluntary skeletal muscles.

Keywords: fabric strain sensor, muscle deformation, isokinetic contraction, joint torque, limb girth strain

Procedia PDF Downloads 337

Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Othmane Bouferroum, Malika Boudraa

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In this study, a dual exponential model for CV formant transition is derived from locus theory of speech perception. Then, an algorithm for automatic vowel and consonant’s target formant frequency detection is developed and tested on real speech. The results show that vowels and consonants are detected through transitions rather than their small stable portions. Also, vowel reduction is clearly observed in our data. These results are confirmed by the observations made in perceptual experiments in the literature.

Keywords: acoustic invariance, coarticulation, formant transition, locus equation

Procedia PDF Downloads 270

Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

Procedia PDF Downloads 397

Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

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Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

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Authors: A. Sopharak, B. Uyyanonvara, S. Barman

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Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.

Keywords: diabetic retinopathy, microaneurysm, naive Bayes classifier, SVM classifier

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Authors: Andrei Contan, Richard Torkar

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Aim: The process of test automation and its practices in industry have to be better understood, both for the industry itself and for the research community. Method: We conducted a quantitative industry survey by asking IT professionals to answer questions related to the area of test automation. Results: Test automation needs and practices vary greatly between organizations at different stages of the software development life cycle. Conclusions: Most of the findings are general test automation challenges and are specific to small- to medium-sized companies, developing software applications in the web, desktop or mobile domain.

Keywords: survey, testing, test automation, status of test automation

Procedia PDF Downloads 659

Authors: B. G. Ayantunji, B. Musa, H. Mai-Unguwa, L. A. Sunmonu, A. S. Adewumi, L. Sa'ad, A. Kado

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For achieving reliable and efficient communication system, both terrestrial and satellite communication, surface refractivity is critical in planning and design of radio links. This study analyzed the impact of atmospheric parameters on Ultra High Frequency (UHF) signal strength over Gusau, North West, Nigeria. The analysis exploited meteorological data measured simultaneously with UHF signal strength for the month of June 2017 using a Davis Vantage Pro2 automatic weather station and UHF signal strength measuring devices respectively. The instruments were situated at the premise of Federal University, Gusau (6° 78' N, 12° 13' E). The refractivity values were computed using ITU-R model. The result shows that the refractivity value attained the highest value of 366.28 at 2200hr and a minimum value of 350.66 at 2100hr local time. The correlation between signal strength and refractivity is 0.350; Humidity is 0.532 and a negative correlation of -0.515 for temperature.

Keywords: refractivity, UHF (ultra high frequency) signal strength, free space, automatic weather station

Procedia PDF Downloads 197

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Oyenike M. Olanrewaju, Faith O. Echobu, Aderemi G. Adesoji, Emmy Danny Ajik, Joseph Nda Ndabula, Stephen Lucas

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Nutrients are required for any soil with which plants thrive to improve efficient growth and productivity. Amongst these nutrients required for proper plant productivity are nitrogen, phosphorus and potassium (NPK). Due to factors like leaching, nutrients uptake by plants, soil erosion and evaporation, these elements tend to be in low quantity and the need to replenish them arises. But these replenishment of soil nutrients cannot be done without a timely soil test to enable farmers to know the amount of each element in short quantity and evaluate the amount required to be added. Though wet soil analysis is good but it comes with a lot of challenges ranging from soil test gargets availability to the technical knowledge of how to conduct such soil test by the common farmer. Internet of things test kit was developed to fill in the gaps created by wet soil analysis, as it can test for N, P, K, soil temperature and soil moisture in a given soil at the time of test. In this implementation, sample test was carried out within 0.2 hectares of land divided into smaller plots. The kits perform adequately well as the range of values obtained across the segments were within a very close range.

Keywords: Internet of Things, soil nutrients, test kit, soil temperature

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

Abstract:

Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

Procedia PDF Downloads 178

Authors: Haziyah Hussin

Abstract:

Hazi Attire software is purposely designed to be used for pattern drafting of the Malay Traditional Women Apparel. It is software created using LISP Program that works under AutoCAD engine and able to draft various patterns for Malay women apparels from fitted, semi-fitted and loose silhouettes. It is fully automatic and the user can select styles from the menu on the screen and enter the measurements. Within five seconds patterns are ready to be printed and sewn. Hazi Attire is different from other programmes available in the market since it is fully automatic, user-friendly and able to print selected pattern chosen quickly and accurately. With this software (Hazi Attire), the selected styles can be generated the pattern according to made-to-measure or standard sizes. It would benefit the apparel industries by reducing manufacturing lead time and cycle time.

Keywords: basic pattern, pattern drafting, toile, Malay traditional women apparel, the measurement parameters, fitted, semi-fitted and loose silhouette

Procedia PDF Downloads 269

Authors: Chinlun Lai, Yu-Mei Chang

Abstract:

In this paper, an augmented reality learning support system is proposed to replace the traditional teaching tool thus to help students improve their learning motivation, effectiveness, and efficiency. The system can not only reduce the exhaust of educational hardware and realistic material, but also provide an eco-friendly and self-learning practical environment in any time and anywhere with immediate practical experiences feedback. To achieve this, an interactive self-training methodology which containing step by step operation directions is designed using virtual 3D scenario and wearable device platforms. The course of nasogastric tube care of nursing skills is selected as the test example for self-learning and online test. From the experimental results, it is observed that the support system can not only increase the student’s learning interest but also improve the learning performance than the traditional teaching methods. Thus, it fulfills the strategy of learning by practice while reducing the related cost and effort significantly and is practical in various fields.

Keywords: augmented reality technology, learning support system, self-learning, simulation learning method

Procedia PDF Downloads 167

Authors: Gyoutae Park, Woosuk Kim, Sangguk Ahn, Seungmo Kim, Minjun Kim, Jinhan Lee, Youngdo Jo, Jongsam Moon, Hiesik Kim

Abstract:

In this research, we designed a remote system to test parameters of gas detectors such as gas concentration and initial response time. This testing system is available to measure two gas instruments simultaneously. First of all, we assembled an experimental jig with a square structure. Those parts are included with a glass flask, two high-quality cameras, and two Ethernet modems for transmitting data. This remote gas detector testing system extracts numerals from videos with continually various gas concentrations while LCDs show photographs from cameras. Extracted numeral data are received to a laptop computer through Ethernet modem. And then, the numerical data with gas concentrations and the measured initial response speeds are recorded and graphed. Our remote testing system will be diversely applied on gas detector’s test and will be certificated in domestic and international countries.

Keywords: gas leak detector, inspection instrument, extracting numerals, concentration

Procedia PDF Downloads 374

Authors: Pandega Gama Mahardika, Muhammad Rifki Al Iksan, Datuk Fachrul Razy

Abstract:

Oil And Gas Tanker Driver is a high-risk jobdesc. drivers drive with sleep circadian rhythm disturbances. Therefore, FAMOUS (Fatigue Management Online Ultimate System) conducted a diagnostic test on the effectiveness and accuracy of the Psychomotor vigilance test (PVT) in the field to capture the fatigue level of Oil And Gas Tanker Driver. Fatigue examination with the PVP method for 3 minutes using the Pertamina FAMOUS system (Fatigue Management Online Ultimate System). The research sample was Oil And Gas Tanker Driver Elnusa petrofin drivers as many as 2205 people. PVT is categorical data that states a driver has a low or high fatigue level. The quality of sleep at home was recorded by filling in a score of 1 = not well, 2 = not well, 3 = well, per person. A total of 1852 (84%) driver had a low fatigue level, while 353 (16%) driver had a high fatigue level. Poor sleep quality was experienced by 68 (79%) driver who had a high fatigue level. Oil And Gas Tanker Driver who slept soundly at home as many as 1804 (87%) had a low fatigue level. The correlation coefficient of sleep quality home and fatigue level is significant because it shows a probability value of 0.00 (p <5%). Fatigue level can be diagnosed through examining sleep quality, using FAMOUS Program for occupational medicine, particularly in the oil and gas sector.

Keywords: psychomotor vigilance test, fatigue, sleep, oil and gas tanker driver drivers, pertamina FAMOUS

Procedia PDF Downloads 90

Authors: Chinlun Lai, Lunjyh Jiang

Abstract:

Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

Procedia PDF Downloads 224