Search results for: morphology detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4847

Search results for: morphology detection

4247 Probability-Based Damage Detection of Structures Using Model Updating with Enhanced Ideal Gas Molecular Movement Algorithm

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

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4246 Hyperspectral Imaging and Nonlinear Fukunaga-Koontz Transform Based Food Inspection

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

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4245 Enhancing French Vocabulary Acquisition: The Impact of Explicit Instruction on Productive Non-Cognate Suffixes for Beginner Learners

Authors: Deborah Idowu

Abstract:

This research delves into the effectiveness of explicitly teaching productive non-cognate French suffixes to English beginner learners of the French language. It is widely accepted that cognates, especially orthographic ones, can be inferred by learners from their first language (in this case, English). The same is the case for derived French words with cognate suffixes, provided the learner is familiar with the lemma, which can either be cognate or non-cognate. However, the same cannot be said for derived French words with non-cognate suffixes. These suffixes often pose challenges to learners, even when the base word is familiar to them. The primary goal of this research is to enhance the vocabulary comprehension and expansion of English-speaking beginners in French by focusing on the recognition of derived French words that may not align with their L1 knowledge. The methodology employed in this study of derivational morphology involves an experimental group receiving explicit instruction on productive non-cognate suffixes, while a control group does not. By utilizing confidence ratings and other analytical tools, the analysis aims to measure the impact of this targeted instruction on the learners' ability to understand and incorporate non-cognate suffixes into their French vocabulary. Through this experimental approach, the research seeks to provide valuable insights into how explicit instruction on non-cognate suffixes can benefit beginner French learners, ultimately aiding them in navigating the intricacies of French derivational morphology. The objectives of this research are as follows: i. to investigate the impact of explicitly teaching productive non-cognate suffixes on the vocabulary comprehension and expansion of beginner learners of the French language; ii. to assess the effectiveness of targeted instruction on non-cognate suffixes in aiding English-speaking learners in recognizing and understanding derived French words that may not align with their native language knowledge, iii. to compare the vocabulary acquisition and retention of beginner French learners who receive explicit instruction on non-cognate suffixes with those who do not to determine the effectiveness of this instructional approach, iv. to analyze the confidence ratings and other analytical methods to gauge the learners' ability to integrate non-cognate suffixes into their French vocabulary and comprehend the meaning of derived words more effectively, v. to contribute insights into how explicit instruction on non-cognate suffixes can enhance the overall language learning experience for beginner learners of French, particularly in the area of French derivational morphology.

Keywords: suffixes, derivational morphology, non-cognates, vocabulary acquisition, French language learners

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4244 Designing a Corpus Database to Enhance the Learning of Old English Language

Authors: Raquel Mateo Mendaza, Carmen Novo Urraca

Abstract:

The current paper presents the elaboration of a corpus database that aligns two different corpora in order to simplify the search of information both for researchers and students of Old English. This database comprises the information contained in two main reference corpora, namely the Dictionary of Old English Corpus (DOEC), compiled at the University of Toronto, and the York-Toronto-Helsinki Parsed Corpus of Old English (YCOE). The first one provides information on all surviving texts written in the Old English language. The latter offers the syntactical and morphological annotation of several texts included in the DOEC. Although both corpora are closely related, as the YCOE includes the DOE source text identifier, the main problem detected is that there is not an alignment of texts that allows for the search of whole fragments to be further analysed in terms of morphology and syntax. The database proposed in this paper gathers all this information and presents it in a simple, more accessible, visual, and educational way. The alignment of fragments has been done in an automatized way. However, some problems have emerged during the creating process particularly related to the lack of correspondence in the division of fragments. For this reason, it has been necessary to revise the whole entries manually to obtain a truthful high-quality product and to carefully indicate the gaps encountered in these corpora. All in all, this database contains more than 60,000 entries corresponding with the DOE fragments annotated by the YCOE. The main strength of the resulting product is its research and teaching implications in the study of Old English. The use of this database will help researchers and students in the study of different aspects of the language, such as inflectional morphology, syntactic behaviour of given words, or translation studies, among others. By means of the search of words or fragments, the annotated information on morphology and syntax will be automatically displayed, automatizing, and speeding up the search of data.

Keywords: alignment, corpus database, morphosyntactic analysis, Old English

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4243 Analyze and Visualize Eye-Tracking Data

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

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4242 Characterization of Biodegradable Polycaprolactone Containing Titanium Dioxide Micro and Nanoparticles

Authors: Emi Govorčin Bajsića, Vesna Ocelić Bulatović, Miroslav Slouf, Ana Šitum

Abstract:

Composites based on a biodegradable polycaprolactone (PCL) containing 0.5, 1.0 and 2.0 wt % of titanium dioxide (TiO2) micro and nanoparticles were prepared by melt mixing and the effect of filler type and contents on the thermal properties, dynamic-mechanical behaviour and morphology were investigated. Measurements of storage modulus and loss modulus by dynamic mechanical analysis (DMA) showed better results for microfilled PCL/TiO2 composites than nanofilled composites, with the same filler content. DSC analysis showed that the Tg and Tc of micro and nanocomposites were slightly lower than those of neat PCL. The crystallinity of the PCL increased with the addition of TiO2 micro and nanoparticles; however, the c for the PCL was unchanged with micro TiO2 content. The thermal stability of PCL/TiO2 composites were characterized using thermogravimetric analysis (TGA). The initial weight loss (5 wt %) occurs at slightly higher temperature with micro and nano TiO2 addition and with increasing TiO2 content.

Keywords: polycaprolactone, titanium dioxide, thermal properties, morphology

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4241 Detection of Elephant Endotheliotropic Herpes Virus in a Wild Asian Elephant Calf in Thailand by Using Real-Time PCR

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

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4240 Ultra-Sensitive Point-Of-Care Detection of PSA Using an Enzyme- and Equipment-Free Microfluidic Platform

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

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4239 Smoker Recognition from Lung X-Ray Images Using Convolutional Neural Network

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

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4238 Computer Aided Diagnosis Bringing Changes in Breast Cancer Detection

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)

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4237 Fabrication of Modified Chitosan-Gold Nanoshell with Mercaptopropionic Acid(MPA) for γ-Aminobutyric Acid Detection as a Surface-Enhanced Raman Scattering Substrate

Authors: Bi Wa, Su-Yeon Kwon, Ik-Joong Kang

Abstract:

Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. In this case, the Mercaptopropionic Acid (MPA) is used to modified chitosan –gold nanoshell, which enhances the absorption between GABA and Chitosan-gold nanoshell. The sulfur end of the MPA is linked to gold which is the surface of the chitosan nanoparticles via the very strong S–Au bond, while a functional group (carboxyl group) attached to GABA. The controlling of particles’ size and the surface morphology are also the important factors during the whole experiment. The particle around 100nm is using to link to MPA, and the range of GABA from 1mM to 30mM was detected by the Raman Scattering to obtain the calibrate curve. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced raman scattering

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4236 Impedance Based Biosensor for Agricultural Pathogen Detection

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

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4235 Energy Detection Based Sensing and Primary User Traffic Classification for Cognitive Radio

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)

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4234 Fabrication of Highly-Ordered Interconnected Porous Polymeric Particles and Structures

Authors: Mohammad Alroaithi

Abstract:

Porous polymeric materials have attracted a great attention due to their distinctive porous structure within a polymer matrix. They are characterised by the presence of external pores on the surface as well as inner interconnected windows. Conventional techniques to produce porous polymeric materials encounters major challenge in controlling the properties of the resultant structures including morphology, pores, cavities size, and porosity. Herein, we present a facile and versatile microfluidics technique for the fabrication of uniform porous polymeric structures with highly ordered and well-defined interconnected windows. The shapes of the porous structures can either be a microparticles or foam. Both shapes used microfluidics platform to first produce monodisperse emulsion. The uniform emulsions, were then consolidated into porous structures through UV photopolymerisation. The morphology, pores, cavities size, and porosity of the structures can be precisely manipulated by the flowrate. The proposed strategy might provide a key advantage for fabrication of uniform porous materials over many existing technologies.

Keywords: polymer, porous particles, microfluidics, porous structures

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4233 e-Learning Security: A Distributed Incident Response Generator

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

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4232 Early Stage Suicide Ideation Detection Using Supervised Machine Learning and Neural Network Classifier

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 90
4231 Fault Tolerant Control of the Dynamical Systems Based on Internal Structure Systems

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

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4230 Cepstrum Analysis of Human Walking Signal

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

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4229 The Effect of Calcining Temperature on Photocatalytic Activity of Porous ZnO Architecture

Authors: M. Masar, P. Janota, J. Sedlak, M. Machovsky, I. Kuritka

Abstract:

Zinc oxide (ZnO) nano crystals assembled porous architecture was prepared by thermal decomposition of zinc oxalate precursor at various temperatures ranging from 400-900°C. The effect of calcining temperature on structure and morphology was examined by scanning electron microscopy (SEM), X-ray diffractometry, thermogravimetry, and BET adsorption analysis. The porous nano crystalline ZnO morphology was developed due to the release of volatile precursor products, while the overall shape of ZnO micro crystals was retained as a legacy of the precursor. The average crystallite size increased with increasing temperature of calcination from approximately 21 nm to 79 nm, while the specific surface area decreased from 30 to 1.7 m2g-1. The photo catalytic performance of prepared ZnO powders was evaluated by degradation of methyl violet 2B, a model compound. The significantly highest photo catalytic activity was achieved with powder calcined at 500°C. This may be attributed to the sufficiently well-developed crystalline arrangement, while the specific surface area is still high enough.

Keywords: ZnO, porous structure, photodegradation, methyl violet

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4228 Redundancy in Malay Morphology: School Grammar versus Corpus Grammar

Authors: Zaharani Ahmad, Nor Hashimah Jalaluddin

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The aim of this paper is to examine and identify the issue of linguistic redundancy in two competing grammars of Malay, namely the school grammar and the corpus grammar. The former is a normative grammar which is formally and prescriptively taught in the classroom, whereas the latter is a descriptive grammar that is informally acquired and mastered by the students as native speakers of the language outside the classroom. Corpus grammar is depicted based on its actual used in natural occurring texts, as attested in the corpus. It is observed that the grammar taught in schools is incompatible with the grammar used in the corpus. For instance, a noun phrase containing nominal reduplicated form which denotes plurality (i.e. murid-murid ‘students’ which is derived from murid ‘student’) and a modifier categorized as quantifiers (i.e. semua ‘all’, seluruh ‘entire’, and kebanyakan ‘most’) is not acceptable in the school grammar because the formation (i.e. semua murid-murid ‘all the students’ kebanyakan pelajar-pelajar ‘most of the students’) is claimed to be redundant, and redundancy is prohibited in the grammar. Redundancy is generally construed as the property of speech and language by which more information is provided than is precisely required for the message to be understood, so that, if some information is omitted, the remaining information will still be sufficient for the message to be comprehended. Thus, the correct construction to be used is strictly the reduplicated form (i.e. murid-murid ‘students’) or the quantifier plus the root (i.e. semua murid ‘all the students’) with the intention that the grammatical meaning of plural is not repeated. Nevertheless, the so-called redundant form (i.e. kebanyakan pelajar-pelajar ‘most of the students’) is frequently used in the corpus grammar. This study shows that there are a number of redundant forms occur in the morphology of the language, particularly in affixation, reduplication and combination of both. Apparently, the so-called redundancy has grammatical and socio-cultural functions in communication that is to give emphasis and to stress the importance of the information delivered by the speakers or writers.

Keywords: corpus grammar, morphology, redundancy, school grammar

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4227 Cell Elevator: A Novel Technique for Cell Sorting and Circulating Tumor Cell Detection and Discrimination

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

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4226 An MrPPG Method for Face Anti-Spoofing

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

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4225 Single Pole-To-Earth Fault Detection and Location on the Tehran Railway System Using ICA and PSO Trained Neural Network

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

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4224 Microfluidic Paper-Based Electrochemical Biosensor

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 (R² > 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

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4223 Detection of Nutrients Using Honeybee-Mimic Bioelectronic Tongue Systems

Authors: Soo Ho Lim, Minju Lee, Dong In Kim, Gi Youn Han, Seunghun Hong, Hyung Wook Kwon

Abstract:

We report a floating electrode-based bioelectronic tongue mimicking honeybee taste systems for the detection and discrimination of various nutrients. Here, carbon nanotube field effect transistors with floating electrodes (CNT-FET) were hybridized with nanovesicles containing honeybee nutrient receptors, gustatory receptors of Apis mellifera. This strategy enables us to detect nutrient substance with a high sensitivity and selectivity. It could also be utilized for the detection of nutrients in liquid food. This floating electrode-based bioelectronic tongue mimicking insect taste systems can be a simple, but highly effective strategy in many different basic research areas about sensory systems. Moreover, our research provides opportunities to develop various applications such as food screening, and it also can provide valuable insights on insect taste systems.

Keywords: taste system, CNT-FET, insect gustatory receptor, biolelectronic tongue

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4222 Hydrogel Based on Cellulose Acetate Used as Scaffold for Cell Growth

Authors: A. Maria G. Melero, A. M. Senna, J. A. Domingues, M. A. Hausen, E. Aparecida R. Duek, V. R. Botaro

Abstract:

A hydrogel from cellulose acetate cross linked with ethylenediaminetetraacetic dianhydride (HAC-EDTA) was synthesized by our research group, and submitted to characterization and biological tests. Cytocompatibility analysis was performed by confocal microscopy using human adipocyte derived stem cells (ASCs). The FTIR analysis showed characteristic bands of cellulose acetate and hydroxyl groups and the tensile tests evidence that HAC-EDTA present a Young’s modulus of 643.7 MPa. The confocal analysis revealed that there was cell growth at the surface of HAC-EDTA. After one day of culture the cells presented spherical morphology, which may be caused by stress of the sequestration of Ca2+ and Mg2+ ions at the cell medium by HAC-EDTA, as demonstrated by ICP-MS. However, after seven days and 14 days of culture, the cells present fibroblastoid morphology, phenotype expected by this cellular type. The results give efforts to indicate this new material as a potential biomaterial for tissue engineering, in the future in vivo approach.

Keywords: cellulose acetate, hydrogel, biomaterial, cellular growth

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4221 Evaluation of Four Different DNA Targets in Polymerase Chain Reaction for Detection and Genotyping of Helicobacter pylori

Authors: Abu Salim Mustafa

Abstract:

Polymerase chain reaction (PCR) assays targeting genomic DNA segments have been established for the detection of Helicobacter pylori in clinical specimens. However, the data on comparative evaluations of various targets in detection of H. pylori are limited. Furthermore, the frequencies of vacA (s1 and s2) and cagA genotypes, which are suggested to be involved in the pathogenesis of H. pylori in other parts of the world, are not well studied in Kuwait. The aim of this study was to evaluate PCR assays for the detection and genotyping of H. pylori by targeting the amplification of DNA targets from four genomic segments. The genomic DNA were isolated from 72 clinical isolates of H. pylori and tested in PCR with four pairs of oligonucleotides primers, i.e. ECH-U/ECH-L, ET-5U/ET-5L, CagAF/CagAR and Vac1F/Vac1XR, which were expected to amplify targets of various sizes (471 bp, 230 bp, 183 bp and 176/203 bp, respectively) from the genomic DNA of H. pylori. The PCR-amplified DNA were analyzed by agarose gel electrophoresis. PCR products of expected size were obtained with all primer pairs by using genomic DNA isolated from H. pylori. DNA dilution experiments showed that the most sensitive PCR target was 471 bp DNA amplified by the primers ECH-U/ECH-L, followed by the targets of Vac1F/Vac1XR (176 bp/203 DNA), CagAF/CagAR (183 bp DNA) and ET-5U/ET-5L (230 bp DNA). However, when tested with undiluted genomic DNA isolated from single colonies of all isolates, the Vac1F/Vac1XR target provided the maximum positive results (71/72 (99% positives)), followed by ECH-U/ECH-L (69/72 (93% positives)), ET-5U/ET-5L (51/72 (71% positives)) and CagAF/CagAR (26/72 (46% positives)). The results of genotyping experiments showed that vacA s1 (46% positive) and vacA s2 (54% positive) genotypes were almost equally associated with VaCA+/CagA- isolates (P > 0.05), but with VacA+/CagA+ isolates, S1 genotype (92% positive) was more frequently detected than S2 genotype (8% positive) (P< 0.0001). In conclusion, among the primer pairs tested, Vac1F/Vac1XR provided the best results for detection of H. pylori. The genotyping experiments showed that vacA s1 and vacA s2 genotypes were almost equally associated with vaCA+/cagA- isolates, but vacA s1 genotype had a significantly increased association with vacA+/cagA+ isolates.

Keywords: H. pylori, PCR, detection, genotyping

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4220 Morphometrics Study of Apis florea and Apis mellifera from Different Locations in Sudan

Authors: Mohammed M. Ibrahim, A. A. Yusuf, Manuel Du, Fiona Mumoki

Abstract:

The traditional honey bee species of Sudan is Apis mellifera, but in 1985, the dwarf bee Apis florea was introduced to the country, so now there are two species present. However, there are conflicting assessments regarding the subspecies of Apis mellifera colonies in Sudan. Likewise, it is unclear if, in the 40 years since its introduction, Apis florea has already developed regional differences or ecotypes. To shed light on these questions, we performed a morphology study on Sudanese honeybees. Samples of 10 to 20 honeybee workers per colony of the two species were collected from 16 locations, spanning different climatic zones in Sudan during 2021. Measurements were taken from 16 morphometric characteristics using a stereo-microscope equipped with an Image Analysis System (Moticam Image Plus 5.0 Digital Microscope Camera) to study their variability. The results indicate that in both species, the general means of various characters showed significant differences (p < 0.05) within a species between different locations, indicating that there might indeed be regional differences. However, more taxonomic investigation and, ideally also, molecular studies are needed in order to confirm the proper identification of subspecies and their ecotypes.

Keywords: Apis, subspecies, morphology, Sudan

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4219 Synthesis of Flower-Like Silver Nanoarchitectures in Special Shapes and Their Applications in Surface-Enhanced Raman Scattering

Authors: Radka Králová, Libor Kvítek, Václav Ranc, Aleš Panáček, Radek Zbořil

Abstract:

Surface–Enhanced Raman Scattering (SERS) is an optical spectroscopic technique with very good potential for sensitive detection of substances. In this research, active substrates with high enhancement were provided. Novel silver particles (nanostructures) with high roughened, flower–like morphology were prepared by reduction of cation complex [Ag(NH3)2]+ in presence of sodium borohydride as reducing agent and stabilized polyacrylic acid. The products were characterized by UV/VIS absorption spectrophotometry. Special shapes of silver particles were determined by scanning electron microscopy (SEM) and transmission electron spectroscopy (TEM). Dispersions of this particle were put on fixed substrate to producing suitable layer for SERS. Adenine was applied as basic substance whose effect of enhancement on the layer of silver nanostructures was studied. By comparison with our work, the important influence of stabilizers, polyacrylic acid with various molecular weight and concentration, on the transfer of particles and formation of new structure was confirmed.

Keywords: metals, nanostructures, chemical reduction, Raman spectroscopy, optical properties

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4218 Location Detection of Vehicular Accident Using Global Navigation Satellite Systems/Inertial Measurement Units Navigator

Authors: Neda Navidi, Rene Jr. Landry

Abstract:

Vehicle tracking and accident recognizing are considered by many industries like insurance and vehicle rental companies. The main goal of this paper is to detect the location of a car accident by combining different methods. The methods, which are considered in this paper, are Global Navigation Satellite Systems/Inertial Measurement Units (GNSS/IMU)-based navigation and vehicle accident detection algorithms. They are expressed by a set of raw measurements, which are obtained from a designed integrator black box using GNSS and inertial sensors. Another concern of this paper is the definition of accident detection algorithm based on its jerk to identify the position of that accident. In fact, the results convinced us that, even in GNSS blockage areas, the position of the accident could be detected by GNSS/INS integration with 50% improvement compared to GNSS stand alone.

Keywords: driver behavior monitoring, integration, IMU, GNSS, monitoring, tracking

Procedia PDF Downloads 234