Search results for: laser line detection

Authors: Nur Ashida Salim, Muhammad Murtadha Othman, Ismail Musirin, Mohd Salleh Serwan

Abstract:

Uncertainty of system operating conditions is one of the causative reasons which may render to the instability of a transmission system. This will encumber the performance of transmission system to efficiently transmit the electrical power between areas. For that reason, accurate assessment of Transmission Reliability Margin (TRM) is essential in order to ensure effective power transfer between areas during the occurrence of system uncertainties. The power transfer is also called as the Available Transfer Capability (ATC) in which it is the information required by the utilities and marketers to instigate selling and buying the electric energy. This paper proposes a computationally effective approach to estimate TRM and ATC by considering the uncertainties of system cascading collapse and transmission line outages which is identified as the main reasons in power system instability. In accordance to the results that have been obtained, the proposed method is essential for the transmission providers which could help the power marketers and planning sectors in the operation and reserving transmission services based on the ATC calculated.

Keywords: system cascading collapse, transmission line outages, transmission reliability margin, available transfer capability

Procedia PDF Downloads 427

Authors: Alden Boby, Dane Brown, James Connan

Abstract:

Character recognition is a well-researched topic across disciplines. Regardless, creating a solution that can cater to multiple situations is still challenging. Vehicle licence plates lack an international standard, meaning that different countries and regions have their own licence plate format. A problem that arises from this is that the typefaces and designs from different regions make it difficult to create a solution that can cater to a wide range of licence plates. The main issue concerning detection is the character recognition stage. This paper aims to create an object detection-based character recognition model trained on a custom dataset that consists of typefaces of licence plates from various regions. Given that characters have featured consistently maintained across an array of fonts, YOLO can be trained to recognise characters based on these features, which may provide better performance than OCR methods such as Tesseract OCR.

Keywords: computer vision, character recognition, licence plate recognition, object detection

Procedia PDF Downloads 121

Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

Abstract:

With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

Procedia PDF Downloads 122

Authors: Jooyoung Park, Junkyeong Kim, Aoqi Zhang, Seunghee Park

Abstract:

Non-destructive testing on cable is in great demand due to safety accidents at sites where many equipments using cables are installed. In this paper, the quantitative change of the obtained signal was analyzed using a magnetic flux leakage (MFL) method. A two-dimensional simulation was conducted with a FEM model replicating real elevator cables. The simulation data were compared for three parameters (depth of defect, width of defect and inspection velocity). Then, an experiment on same conditions was carried out to verify the results of the simulation. Signals obtained from both the simulation and the experiment were transformed to characterize the properties of the damage. Throughout the results, a cable damage detection based on an MFL method was confirmed to be feasible. In further study, it is expected that the MFL signals of an entire specimen will be gained and visualized as well.

Keywords: magnetic flux leakage (mfl), cable damage detection, non-destructive testing, numerical simulation

Procedia PDF Downloads 383

Authors: Sunil Mittal, Sukhpreet Singh, Hardeep Kaur

Abstract:

The affinity of thiol group with heavy metals is a well-established phenomenon. The present investigation has been focused on electrochemical response of cysteine and thioredoxin against arsenite (As III) on indium tin oxide (ITO) electrodes. It was observed that both the compounds produce distinct response in free and immobilised form at the electrode. The SEM, FTIR, and impedance studies of the modified electrode were conducted for characterization. Various parameters were optimized to achieve As (III) effect on the reduction potential of the compounds. Cyclic voltammetry and linear sweep voltammetry were employed as the analysis techniques. The optimum response was observed at neutral pH in both the cases, at optimum concentration of 2 mM and 4.27 µM for cysteine and thioredoxin respectively. It was observed that presence of As (III) increases the reduction current of both the moieties. The linear range of detection for As (III) with cysteine was from 1 to 10 mg L⁻¹ with detection limit of 0.8 mg L⁻¹. The thioredoxin was found more sensitive to As (III) and displayed a linear range from 0.1 to 1 mg L⁻¹ with detection limit of 10 µg L⁻¹.

Keywords: arsenite, cyclic voltammetry, cysteine, thioredoxin

Procedia PDF Downloads 212

Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

Procedia PDF Downloads 278

Authors: Yunbin Deng

Abstract:

Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

Procedia PDF Downloads 180

Authors: Akansha Tyagi, Mehar S. Sidhu, Ankur Mandal, Sanjay Kapoor, Sunil Dahiya, Jan M. Rost, Thomas Pfeifer, Kamal P. Singh

Abstract:

An all-reflective split and delay unit is designed for dispersion free measurement of broadband ultrashort pulses using a pair of reflective knife edge prism for splitting and recombining of the measuring pulse. It is based on symmetrical wavefront splitting of the measuring pulse having two separate arms to independently shape both split parts. We have validated our delay line with NIR –femtosecond pulse measurement centered at 800 nm using second harmonic-Interferometric frequency resolved optical gating (SH-IFROG). The delay line is compact, easy to align and provides attosecond stability and precision and thus make it more versatile for wide range of applications in ultrafast measurements. We envision that the present delay line will find applications in IR-IR controlling for high harmonic generation (HHG) and attosecond IR-XUV pump-probe measurements with solids and gases providing attosecond resolution and wide delay range.

Keywords: HHG, nonlinear optics, pump-probe spectroscopy, ultrafast metrology

Procedia PDF Downloads 201

Authors: Hamidullah Binol, Abdullah Bal

Abstract:

Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: food (ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods

Procedia PDF Downloads 433

Authors: My Ali El Khakani

Abstract:

Single-wall Carbon nanotubes (SWCNTs) possess an unprecedented combination of unique properties that make them highly promising for suitable for a new generation of photovoltaic (PV) devices. Prior to discussing the integration of SWCNTs films into effective PV devices, we will briefly highlight our work on the synthesis of SWCNTs by means of the KrF pulsed laser deposition technique, their purification and transfer onto n-silicon substrates to form p-n junctions. Some of the structural and optoelectronic properties of SWCNTs relevant to PV applications will be emphasized. By varying the SWCNTs film density (µg/cm2), we were able to point out the existence of an optimum value that yields the highest photoconversion efficiency (PCE) of ~10%. Further control of the doping of the p-SWCNTs films, through their exposure to nitric acid vapors, along with the insertion of an optimized hole-extraction-layer in the p-SWCNTs/n-Si hybrid devices permitted to achieve a PCE value as high as 14.2%. Such a high PCE value demonstrates the full potential of these p-SWCNTs/n-Si devices for sunlight photoconversion. On the other hand, by examining both the optical transmission and electrical conductance of the SWCNTs’ films, we established a figure of merit (FOM) that was shown to correlate well with the PCE performance. Such a direct relationship between the FOM and the PCE can be used as a guide for further PCE enhancement of these novel p-SWCNTs/n-Si PV devices.

Keywords: carbon nanotubes (CNTs), CNTs-silicon hybrid devices, photoconversion, photovoltaic devices, pulsed laser deposition

Procedia PDF Downloads 119

Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

Abstract:

Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

Procedia PDF Downloads 137

Authors: Irina Alexandra Paun, Mona Mihailescu, Marian Zamfirescu, Catalin Romeo Luculescu, Adriana Maria Acasandrei, Cosmin Catalin Mustaciosu, Roxana Cristina Popescu, Maria Dinescu

Abstract:

A major concern in bone tissue engineering is to develop complex 3D architectures that mimic the natural cells environment, facilitate the cells growth in a defined manner and allow the flow transport of nutrients and metabolic waste. In particular, porous structures of controlled pore size and positioning are indispensable for growing human-like bone structures. Another concern is to monitor both the structures and the seeded cells with high spatial resolution and without interfering with the cells natural environment. The present approach relies on laser-based technologies employed for fabricating porous biomimetic structures that support the growth of osteoblast-like cells and for their non-invasive 3D imaging. Specifically, the porous structures were built by two photon polymerization –direct writing (2PP_DW) of the commercially available photoresists IL-L780, using the Photonic Professional 3D lithography system. The structures consist of vertical tubes with micrometer-sized heights and diameters, in a honeycomb-like spatial arrangement. These were fabricated by irradiating the IP-L780 photoresist with focused laser pulses with wavelength centered at 780 nm, 120 fs pulse duration and 80 MHz repetition rate. The samples were precisely scanned in 3D by piezo stages. The coarse positioning was done by XY motorized stages. The scanning path was programmed through a writing language (GWL) script developed by Nanoscribe. Following laser irradiation, the unexposed regions of the photoresist were washed out by immersing the samples in the Propylene Glycol Monomethyl Ether Acetate (PGMEA). The porous structures were seeded with osteoblast like MG-63 cells and their osteogenic potential was tested in vitro. The cell-seeded structures were analyzed in 3D using the digital holographic microscopy technique (DHM). DHM is a marker free and high spatial resolution imaging tool, where the hologram acquisition is performed non-invasively i.e. without interfering with the cells natural environment. Following hologram recording, a digital algorithm provided a 3D image of the sample, as well as information about its refractive index, which is correlated with the intracellular content. The axial resolution of the images went down to the nanoscale, while the temporal scales ranged from milliseconds up to hours. The hologram did not involve sample scanning and the whole image was available in one frame recorded going over 200μm field of view. The digital holograms processing provided 3D quantitative information on the porous structures and allowed a quantitative analysis of the cellular response in respect to the porous architectures. The cellular shape and dimensions were found to be influenced by the underlying micro relief. Furthermore, the intracellular content gave evidence on the beneficial role of the porous structures in promoting osteoblast differentiation. In all, the proposed laser-based protocol emerges as a promising tool for the fabrication and non-invasive imaging of porous constructs for bone tissue engineering. Acknowledgments: This work was supported by a grant of the Romanian Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project PN-II-RU-TE-2014-4-2534 (contract 97 from 01/10/2015) and by UEFISCDI PN-II-PT-PCCA no. 6/2012. A part of this work was performed in the CETAL laser facility, supported by the National Program PN 16 47 - LAPLAS IV.

Keywords: biomimetic, holography, laser, osteoblast, two photon polymerization

Procedia PDF Downloads 273

Authors: Bopit Puyati, Anchittha Kaewchana, Nuntita Ruksachat

Abstract:

In January 2018, a male wild elephant, approximately 2 years old, was found dead in Phu Luang Wildlife Sanctuary, Loei province. The elephant was likely to die around 2 weeks earlier. The carcass was decayed without any signs of attack or bullet. No organs were removed. A deadly viral disease was suspected. Different organs including lung, liver, intestine and tongue were collected and submitted to the veterinary research and development center, Surin province for viral detection. The samples were then examined with real-time PCR for detecting U41 Major DNA binding protein (MDBP) gene and with conventional PCR for the presence of specific polymerase gene. We used tumor necrosis factor (TNF) gene as the internal control. In our real-time PCR, elephant endotheliotropic herpesvirus (EEHV) was recovered from lung, liver, and tongue whereas only tongue provided a positive result in the conventional PCR. All samples were positive with TNF gene detection. To our knowledge, this is the first report of EEHV detection in wild elephant in Thailand. EEHV surveillance in this wild population is strongly suggested. Linkage between EEHV in wild and domestic elephants should be further explored.

Keywords: elephant endotheliotropic herpes virus, PCR, Thailand, wild Asian elephant

Procedia PDF Downloads 144

Authors: Ying Li, Rui Hu, Shizhen Chen, Xin Zhou, Yunhuang Yang

Abstract:

Prostate cancer is one of the leading causes of cancer-related death among men. Prostate-specific antigen (PSA), a specific product of prostatic epithelial cells, is an important indicator of prostate cancer. Though PSA is not a specific serum biomarker for the screening of prostate cancer, it is recognized as an indicator for prostate cancer recurrence and response to therapy for patient’s post-prostatectomy. Since radical prostatectomy eliminates the source of PSA production, serum PSA levels fall below 50 pg/mL, and may be below the detection limit of clinical immunoassays (current clinical immunoassay lower limit of detection is around 10 pg/mL). Many clinical studies have shown that intervention at low PSA levels was able to improve patient outcomes significantly. Therefore, ultra-sensitive and precise assays that can accurately quantify extremely low levels of PSA (below 1-10 pg/mL) will facilitate the assessment of patients for the possibility of early adjuvant or salvage treatment. Currently, the commercially available ultra-sensitive ELISA kit (not used clinically) can only reach a detection limit of 3-10 pg/mL. Other platforms developed by different research groups could achieve a detection limit as low as 0.33 pg/mL, but they relied on sophisticated instruments to get the final readout. Herein we report a microfluidic platform for point-of-care (POC) detection of PSA with a detection limit of 0.5 pg/mL and without the assistance of any equipment. This platform is based on a previously reported volumetric-bar-chart chip (V-Chip), which applies platinum nanoparticles (PtNPs) as the ELISA probe to convert the biomarker concentration to the volume of oxygen gas that further pushes the red ink to form a visualized bar-chart. The length of each bar is used to quantify the biomarker concentration of each sample. We devised a long reading channel V-Chip (LV-Chip) in this work to achieve a wide detection window. In addition, LV-Chip employed a unique enzyme-free ELISA probe that enriched PtNPs significantly and owned 500-fold enhanced catalytic ability over that of previous V-Chip, resulting in a significantly improved detection limit. LV-Chip is able to complete a PSA assay for five samples in 20 min. The device was applied to detect PSA in 50 patient serum samples, and the on-chip results demonstrated good correlation with conventional immunoassay. In addition, the PSA levels in finger-prick whole blood samples from healthy volunteers were successfully measured on the device. This completely stand-alone LV-Chip platform enables convenient POC testing for patient follow-up in the physician’s office and is also useful in resource-constrained settings.

Keywords: point-of-care detection, microfluidics, PSA, ultra-sensitive

Procedia PDF Downloads 111

Authors: Moumita Chanda, Md. Fazlul Karim Patwary

Abstract:

Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

Procedia PDF Downloads 85

Authors: Hamed Karimian, Noraziah Nordin, Mohamad Ibrahim Noordin, Syam Mohan, Mahboubeh Razavi, Najihah Mohd Hashim, Happipah Mohd Ali

Abstract:

Satureja bachtiarica Bunge is a perennial medicinal plant belonging to the Lamiaceae family and endemic species in Iran. Satureja bachtiarica Bunge with the local name of Marzeh koohi is edible vegetable use as flavoring agent, anti-bacterial and to relieve cough and indigestion. In this study, the anti-cancer effect of Satureja bachtiarica Bunge on the MDA-MB-231 cell line as an Breast cancer cell model has been analyzed for the first time. Satureja bachtiarica Bunge was extracted using different solvents in the order of increasing polarity. Cytotoxicity activity of hexane extract of Satureja bachtiarica Bunge (SBHE) was observed using MTT assay. Acridine orange/Propidium iodide staining was used to detect early apoptosis; Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS), with Annexin-Vserving as a marker for apoptotic cells. Caspase 3/7, 8 and-9 assays showed significantly activation of caspase-9 where lead intrinsic mitochondrial pathway. Bcl-2/Bax expressions and cell cycle arrest were also investigated. SBHE had exhibited significantly higher cytotoxicity against MDA-MB-231 Cell line compare to other cell lines. A significant increase in chromatin condensation in the cell nucleus was observed by fluorescence analysis. Treatment of MDA-MB-231 cells with SBHE encouraged apoptosis, by down-regulating Bcl-2 and up-regulating Bax, which lead the activation of caspase 9. Moreover, SBHE treatment significantly arrested MDA-MB-231 cells in the G1 phase. Together, the results presented in this study demonstrated that SBHE inhibited the proliferation of MDA-MB-231 cells, leading cell cycle arrest and programmed cell death, which was confirmed to be through the mitochondrial pathway.

Keywords: Satureja bachtiarica Bunge, MDA-MB-231, apoptosis, annexin-V, cell cycle

Procedia PDF Downloads 338

Authors: Devadrita Dey Sarkar

Abstract:

Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

Procedia PDF Downloads 456

Authors: Rhea Patel, Madhuri Vinchurkar, Rajul Patkar, Gopal Pranjale, Maryam Shojaei Baghini

Abstract:

One of the major limitations on food resources worldwide is the deterioration of plant products due to pathogenic infections. Early screening of plants for pathogenic infections can serve as a boon in the Agricultural sector. The standard microbiology techniques has not kept pace with the rapid enumeration and automated methods for bacteria detection. Electrochemical Impedance Spectroscopy (EIS) serves as a label free bio sensing technique to monitor pathogens in real time. The changes in the electrical impedance of a growing bacterial culture can be monitored to detect activity of microorganisms. In this study, we demonstrate development of a gold interdigitated electrode (gold IDE) based impedance biosensor to detect bacterial cells in real on-field crop samples. To calibrate our impedance measurement system, nutrient broth suspended Escherichia coli cells were used. We extended this calibrated protocol to identify the agricultural pathogens in real potato tuber samples. Distinct difference was seen in the impedance recorded for the healthy and infected potato samples. Our results support the potential application of this Impedance based biosensor in Agricultural pathogen detection.

Keywords: agriculture, biosensor, electrochemical impedance spectroscopy, microelectrode, pathogen detection

Procedia PDF Downloads 156

Authors: Huang Wei-Chi, Li Wei, Yu Tien-Chieh

Abstract:

Medication adherence is crucial for treatment success. Adherence problem is common in patients with polypharmacy, especially in the geriatric population who are vulnerable to multiple chronic conditions but averagely less knowledgeable about diseases and medications. In order to help patients take medications appropriately and enhance the understanding of diseases or medications, a Line official account named e-Pharmacist was designed. The line is a popular freeware app with the highest penetration rate (95.7%) in Taiwan. The interface of e-Pharmacist is user-friendly for easy-to-read and convenient operating. Differ from other medication adherence apps, users just added e-Pharmacist as a LINE friend without installing any more apps and the drug lists were automatically downloaded from the personal electronic medical records with security permission. Over and above medication reminder, several additional capabilities were set up and engaged in the platform of e-Pharmacist including prescription refill reservation, laboratory examination consultation, medical appointment registration, and “Daily Health Log” where patients can record and track data of blood pressure/blood sugar and daily meals for self-health management as well as can share the important information to clinical professionals when seeking medical help. Additionally, a Line chatbot was utilized to provide tailored medicine information for the individual user. From July 2020 to March 2022, around 3000 patients added e-pharmacist as Line friends. Every day more than 1500 patients receive messages from e-pharmacist to notify them to take medicine. Thanks to the e-pharmacist alert system and Chatbot, the low-compliance patients (defined by Program on Adherence to Medication, PAM) significantly dropped from 36% to 6%, whereas the high-compliance patients dramatically increased from 13% to 77%. The user satisfaction is 98%. In brief, an e-pharmacist is not only a medication reminder but also a tailored personal assistant with value-added service for health management.

Keywords: e-pharmacist, self-health management, medication reminder, value-added service

Procedia PDF Downloads 161

Authors: Urvee B. Trivedi, U. D. Dalal

Abstract:

As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

Procedia PDF Downloads 345

Authors: Bel G Raggad

Abstract:

An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.

Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection

Procedia PDF Downloads 438

Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

Abstract:

In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

Procedia PDF Downloads 91

Authors: Seyed Mohammad Hashemi, Shahrokh Barati

Abstract:

The problem of fault-tolerant control (FTC) by accommodation method has been studied in this paper. The fault occurs in any system components such as actuators, sensors or internal structure of the system and leads to loss of performance and instability of the system. When a fault occurs, the purpose of the fault-tolerant control is designate strategy that can keep the control loop stable and system performance as much as possible perform it without shutting down the system. Here, the section of fault detection and isolation (FDI) system has been evaluated with regard to actuator's fault. Designing a fault detection and isolation system for a multi input-multi output (MIMO) is done by an unknown input observer, so the system is divided to several subsystems as the effect of other inputs such as disturbing given system state equations. In this observer design method, the effect of these disturbances will weaken and the only fault is detected on specific input. The results of this approach simulation can confirm the ability of the fault detection and isolation system design. After fault detection and isolation, it is necessary to redesign controller based on a suitable modification. In this regard after the use of unknown input observer theory and obtain residual signal and evaluate it, PID controller parameters redesigned for iterative. Stability of the closed loop system has proved in the presence of this method. Also, In order to soften the volatility caused by Annie variations of the PID controller parameters, modifying Sigma as a way acceptable solution used. Finally, the simulation results of three tank popular example confirm the accuracy of performance.

Keywords: fault tolerant control, fault detection and isolation, actuator fault, unknown input observer

Procedia PDF Downloads 456

Authors: Koichi Kurita

Abstract:

In this study, we propose a real-time data collection technique for the detection of human walking motion from the charge generated on the human body. This technique is based on the detection of a sub-picoampere electrostatic induction current, generated by the motion, flowing through the electrode of a wireless portable sensor attached to the subject. An FFT analysis of the wave-forms of the electrostatic induction currents generated by the walking motions showed that the currents generated under normal and restricted walking conditions were different. Moreover, we carried out a cepstrum analysis to detect any differences in the walking style. Results suggest that a slight difference in motion, either due to the individual’s gait or a splinted leg, is directly reflected in the electrostatic induction current generated by the walking motion. The proposed wireless portable sensor enables the detection of even subtle differences in walking motion.

Keywords: human walking motion, motion measurement, current measurement, electrostatic induction

Procedia PDF Downloads 344

Authors: Kamta P. Namdeo

Abstract:

Novel thiazolidino-(3,2-b)-1, 2,4-triazole-5(6H)-one derivatives were synthesized, and anticancer activity was studied on human breast cancer cell line MFC7. It showed a significant decrease in cell viability with reference to the standard. The findings suggest that nitro-substituted compound showed best anticancer activity and activity was due to the triazole and thiazolidinone hetero nucleus present in the structure.

Keywords: anti-cancer, adriamycine, thiazolidinone, 1, 2, 4-triazole, thiazolidino-triazolone

Procedia PDF Downloads 376

Authors: Kevin Zhao, Norman J. Horing

Abstract:

A methodology for cells sorting and circulating tumor cell detection and discrimination is presented in this paper. The technique is based on Dielectrophoresis and microfluidic device theory. Specifically, the sorting of the cells is realized by adjusting the relation among the sedimentation forces, the drag force provided by the fluid, and the Dielectrophortic force that is relevant to the bias voltage applied on the device. The relation leads to manipulation of the elevation of the cells of the same kind to a height by controlling the bias voltage. Once the cells have been lifted to a position next to the bottom of the cell collection channel, the buffer fluid flashes them into the cell collection channel. Repeated elevation of the cells leads to a complete sorting of the cells in the sample chamber. A proof-of-principle example is presented which verifies the feasibility of the methodology.

Keywords: cell sorter, CTC cell, detection and discrimination, dielectrophoresisords, simulation

Procedia PDF Downloads 433

Authors: Lan Zhang, Cailing Zhang

Abstract:

In recent years, many face anti-spoofing algorithms have high detection accuracy when detecting 2D face anti-spoofing or 3D mask face anti-spoofing alone in the field of face anti-spoofing, but their detection performance is greatly reduced in multidimensional and cross-datasets tests. The rPPG method used for face anti-spoofing uses the unique vital information of real face to judge real faces and face anti-spoofing, so rPPG method has strong stability compared with other methods, but its detection rate of 2D face anti-spoofing needs to be improved. Therefore, in this paper, we improve an rPPG(Remote Photoplethysmography) method(MrPPG) for face anti-spoofing which through color space fusion, using the correlation of pulse signals between real face regions and background regions, and introducing the cyclic neural network (LSTM) method to improve accuracy in 2D face anti-spoofing. Meanwhile, the MrPPG also has high accuracy and good stability in face anti-spoofing of multi-dimensional and cross-data datasets. The improved method was validated on Replay-Attack, CASIA-FASD, Siw and HKBU_MARs_V2 datasets, the experimental results show that the performance and stability of the improved algorithm proposed in this paper is superior to many advanced algorithms.

Keywords: face anti-spoofing, face presentation attack detection, remote photoplethysmography, MrPPG

Procedia PDF Downloads 179

Authors: Masoud Safarishaal

Abstract:

Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

Procedia PDF Downloads 125

Authors: Ahmad Manbohi, Seyyed Hamid Ahmadi

Abstract:

A low-cost paper-based microfluidic device (PAD) for the multiplex electrochemical determination of glucose, uric acid, and dopamine in biological fluids was developed. Using wax printing, PAD containing a central zone, six channels, and six detection zones was fabricated, and the electrodes were printed on detection zones using pre-made electrodes template. For each analyte, two detection zones were used. The carbon working electrode was coated with chitosan-BSA (and enzymes for glucose and uric acid). To detect glucose and uric acid, enzymatic reactions were employed. These reactions involve enzyme-catalyzed redox reactions of the analytes and produce free electrons for electrochemical measurement. Calibration curves were linear (R^² > 0.980) in the range of 0-80 mM for glucose, 0.09–0.9 mM for dopamine, and 0–50 mM for uric acid, respectively. Blood samples were successfully analyzed by the proposed method.

Keywords: biological fluids, biomarkers, microfluidic paper-based electrochemical biosensors, Multiplex

Procedia PDF Downloads 283

Authors: Durri Andriani, Irsan Tahar, Lilian Sarah Hiariey

Abstract:

Every institution has to develop, implement, and control its policies to ensure the effectiveness of the institution. In doing so, all related stakeholders have to be involved to maximize the benefit of the policies and minimize the potential constraints and resistances. Open and distance education (ODE) institution is no different. As an education institution, ODE institution has to focus their attention to fulfilling academic needs of their students through open and distance measures. One of them is quality learning support system. Significant stakeholders in learning support system are tutors since they are the ones who directly communicate with students. Tutors are commonly seen as objects whose main responsibility is limited to implementing policies decided by management in ODE institutions. Nonetheless, tutors’ perceptions of tutorials are believed to influence tutors’ performances in facilitating learning support. It is therefore important to analyze tutors’ perception on various aspects of learning support. This paper presents analysis of tutors’ perceptions on policies of tutoriala in ODE institution using Policy Analysis Framework (PAF) modified by King, Nugent, Russell, and Lacy. Focus of this paper is on on-line tutors, those who provide tutorials via Internet. On-line tutors were chosen to stress the increasingly important used of Internet in ODE system. The research was conducted in Universitas Terbuka (UT), Indonesia. UT is purposely selected because of its large number (1,234) of courses offered and large area coverage (6000 inhabited islands). These posed UT in a unique position where learning support system has, to some extent, to be standardized while at the same time it has to be able to cater the needs of different courses in different places for students with different backgrounds. All 598 listed on-line tutors were sent the research questionnaires. Around 20% of the email addresses could not be reached. Tutors were asked to fill out open-ended questionnaires on their perceptions on definition of on-line tutorial, roles of tutors and students in on-line tutorials, requirement for on-line tutors, learning materials, and student evaluation in on-line tutorial. Data analyzed was gathered from 40 on-line tutors who sent back filled-out questionnaires. Data were analyzed qualitatively using content analysis from all 40 tutors. The results showed that using PAF as entry point in choosing learning support services as area of policy with delivery learning materials as the issue at UT has been able to provide new insights of aspects need to be consider in formulating policies in online tutorial and in learning support services. Involving tutors as source of information could be proven to be productive. In general, tutors had clear understanding about definition of online tutorial, roles of tutors and roles of students, and requirement of tutor. Tutors just need to be more involved in the policy formulation since they could provide data on students and problem faced in online tutorial. However, tutors need an adjustment in student evaluation which according tutors too focus on administrative aspects and subjective.

Keywords: distance education, on-line tutorial, tutorial policy, tutors’ perspectives

Procedia PDF Downloads 254