Search results for: space detection to first responders
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6936

Search results for: space detection to first responders

5766 A Handheld Light Meter Device for Methamphetamine Detection in Oral Fluid

Authors: Anindita Sen

Abstract:

Oral fluid is a promising diagnostic matrix for drugs of abuse compared to urine and serum. Detection of methamphetamine in oral fluid would pave way for the easy evaluation of impairment in drivers during roadside drug testing as well as ensure safe working environments by facilitating evaluation of impairment in employees at workplaces. A membrane-based point-of-care (POC) friendly pre-treatment technique has been developed which aided elimination of interferences caused by salivary proteins and facilitated the demonstration of methamphetamine detection in saliva using a gold nanoparticle based colorimetric aptasensor platform. It was found that the colorimetric response in saliva was always suppressed owing to the matrix effects. By navigating the challenging interfering issues in saliva, we were successfully able to detect methamphetamine at nanomolar levels in saliva offering immense promise for the translation of these platforms for on-site diagnostic systems. This subsequently motivated the development of a handheld portable light meter device that can reliably transduce the aptasensors colorimetric response into absorbance, facilitating quantitative detection of analyte concentrations on-site. This is crucial due to the prevalent unreliability and sensitivity problems of the conventional drug testing kits. The fabricated light meter device response was validated against a standard UV-Vis spectrometer to confirm reliability. The portable and cost-effective handheld detector device features sensitivity comparable to the well-established UV-Vis benchtop instrument and the easy-to-use device could potentially serve as a prototype for a commercial device in the future.

Keywords: aptasensors, colorimetric gold nanoparticle assay, point-of-care, oral fluid

Procedia PDF Downloads 39
5765 Shape Management Method of Large Structure Based on Octree Space Partitioning

Authors: Gichun Cha, Changgil Lee, Seunghee Park

Abstract:

The objective of the study is to construct the shape management method contributing to the safety of the large structure. In Korea, the research of the shape management is lack because of the new attempted technology. Terrestrial Laser Scanning (TLS) is used for measurements of large structures. TLS provides an efficient way to actively acquire accurate the point clouds of object surfaces or environments. The point clouds provide a basis for rapid modeling in the industrial automation, architecture, construction or maintenance of the civil infrastructures. TLS produce a huge amount of point clouds. Registration, Extraction and Visualization of data require the processing of a massive amount of scan data. The octree can be applied to the shape management of the large structure because the scan data is reduced in the size but, the data attributes are maintained. The octree space partitioning generates the voxel of 3D space, and the voxel is recursively subdivided into eight sub-voxels. The point cloud of scan data was converted to voxel and sampled. The experimental site is located at Sungkyunkwan University. The scanned structure is the steel-frame bridge. The used TLS is Leica ScanStation C10/C5. The scan data was condensed 92%, and the octree model was constructed with 2 millimeter in resolution. This study presents octree space partitioning for handling the point clouds. The basis is created by shape management of the large structures such as double-deck tunnel, building and bridge. The research will be expected to improve the efficiency of structural health monitoring and maintenance. "This work is financially supported by 'U-City Master and Doctor Course Grant Program' and the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIP) (NRF- 2015R1D1A1A01059291)."

Keywords: 3D scan data, octree space partitioning, shape management, structural health monitoring, terrestrial laser scanning

Procedia PDF Downloads 292
5764 A Structure-Switching Electrochemical Aptasensor for Rapid, Reagentless and Single-Step, Nanomolar Detection of C-Reactive Protein

Authors: William L. Whitehouse, Louisa H. Y. Lo, Andrew B. Kinghorn, Simon C. C. Shiu, Julian. A. Tanner

Abstract:

C-reactive protein (CRP) is an acute-phase reactant and sensitive indicator for sepsis and other life-threatening pathologies, including systemic inflammatory response syndrome (SIRS). Currently, clinical turn-around times for established CRP detection methods take between 30 minutes to hours or even days from centralized laboratories. Here, we report the development of an electrochemical biosensor using redox probe-tagged DNA aptamers functionalized onto cheap, commercially available screen-printed electrodes. Binding-induced conformational switching of the CRP-targeting aptamer induces a specific and selective signal-ON event, which enables single-step and reagentless detection of CRP in as little as 1 minute. The aptasensor dynamic range spans 5-1000nM (R=0.97) or 5-500nM (R=0.99) in 50% diluted human serum, with a LOD of 3nM, corresponding to 2-orders of magnitude sensitivity under the clinically relevant cut-off for CRP. The sensor is stable for up to one week and can be reused numerous times, as judged from repeated real-time dosing and dose-response assays. By decoupling binding events from the signal induction mechanism, structure-switching electrochemical aptamer-based sensors (SS-EABs) provide considerable advantages over their adsorption-based counterparts. Our work expands on the retinue of such sensors reported in the literature and is the first instance of an SS-EAB for reagentless CRP detection. We hope this study can inspire further investigations into the suitability of SS-EABs for diagnostics, which will aid translational R&D toward fully realized devices aimed at point-of-care applications or for use more broadly by the public.

Keywords: structure-switching, C-reactive protein, electrochemical, biosensor, aptasensor.

Procedia PDF Downloads 53
5763 Evaluation of Japanese Kyoto Park in Terms of User Satisfaction

Authors: Ruhugül Özge Gemici

Abstract:

The need for open space, which is an important problem especially since the 19th century, has become more important in today's conditions. The most important factor in increasing the livability of cities is the open and green areas. Parks are the most important of the urban open and green space elements that provide the most benefit to users. In this context, the user satisfaction of the Japanese Kyoto Park, which is the subject of the research, was evaluated in the light of the questionnaires. With this analysis, the satisfaction level of the user using the park was determined. Suggestions have been developed for the park to be handled and regulated according to the user requests and requirements changing over time.

Keywords: landscape, landscape design, open and green spaces, sculpture

Procedia PDF Downloads 216
5762 Integrated Free Space Optical Communication and Optical Sensor Network System with Artificial Intelligence Techniques

Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

Abstract:

5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

Procedia PDF Downloads 50
5761 Impact of Capture Effect on Receiver Initiated Collision Detection with Sequential Resolution in WLAN

Authors: Sethu Lekshmi, Shahanas, Prettha P.

Abstract:

All existing protocols in wireless networks are mainly based on Carrier Sense Multiple Access with Collision avoidance. By applying collision detection in wireless networks, the time spent on collision can be reduced and thus improves system throughput. However in a real WLAN scenario due to the use of nonlinear modulation techniques only receiver can decided whether a packet loss take place, even there are multiple transmissions. In this proposed method, the receiver or Access Point detects the collision when multiple data packets are transmitted from different wireless stations. Whenever the receiver detects a collision, it transmits a jamming signal to all the transmitting stations so that they can immediately stop their on-going transmissions. We also provide preferential access to all collided packet to reduce unfairness and to increase system throughput by reducing contention. However, this preferential access will not block the channel for the long time. Here, an in-band transmission is considered in which both the data frames and control frames are transmitted in the same channel. We also provide a simple mathematical model for the proposed protocol and give the simulation result of WLAN scenario under various capture thresholds.

Keywords: 802.11, WLAN, capture effect, collision detection, collision resolution, receiver initiated

Procedia PDF Downloads 353
5760 Angle of Arrival Estimation Using Maximum Likelihood Method

Authors: Olomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr, Zekeriya Aliyazicioglu, H. K. Hwang

Abstract:

Multiple Input Multiple Output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection, resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO Uniformly-Spaced Linear Array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, Pseudo Random (PN) sequence length, number of snapshots, and Signal to Noise Ratio (SNR). The results of MIMO are compared to a traditional array antenna.

Keywords: MIMO radar, phased array antenna, target detection, radar signal processing

Procedia PDF Downloads 533
5759 Non-Destructive Static Damage Detection of Structures Using Genetic Algorithm

Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

Abstract:

To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

Procedia PDF Downloads 225
5758 Detecting and Thwarting Interest Flooding Attack in Information Centric Network

Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

Abstract:

Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

Procedia PDF Downloads 199
5757 Determination of Benzatropine in Hair by GC/MS after Liquid-Liquid Extraction (LLE)

Authors: Abdulsallam A. Bakdash, Aiyshah M. Alshehri, Hind M. Alenzi

Abstract:

Benzatropine (benztropine) is used to treat symptoms of Parkinson's disease or involuntary movements due to the side effects of certain psychiatric drugs. We report in this study, results of a procedure for the determination of benzatropine in hair using LLE, once with methanol and second with phosphate buffer (pH 6.0), followed by filtration and then re-extraction with dichloromethane. A GC/MS method was developed and validated for this determination using selected ion monitoring (SIM) detection without derivatization. Linearity established over the concentration range 0.1-20.0 ng/mg hair, and the correlation coefficients were greater than 0.99. Recoveries were 52.2% and 21.1% using methanol and phosphate buffer extraction, respectively. Detection limits of benzatropine in hair were between 0.65 and 3.0 ng/mg hair, while the accuracy were 10.4% and 18.5% (RSD), respectively. We also applied this method to the analysis of soaked hair samples and demonstrated that the LLE using methanol meets the requirement for the analysis of benzatropine in hair.

Keywords: hair analysis, benzatropine, liquid-liquid extraction, GC/MS

Procedia PDF Downloads 394
5756 Thermal Performance and Environmental Assessment of Evaporative Cooling Systems: Case of Mina Valley, Saudi Arabia

Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

Abstract:

This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

Procedia PDF Downloads 423
5755 ADCOR © Muscle Damage Rapid Detection Test Based on Skeletal Troponin I Immunochromatography Reaction

Authors: Muhammad Solikhudin Nafi, Wahyu Afif Mufida, Mita Erna Wati, Fitri Setyani Rokim, M. Al-Rizqi Dharma Fauzi

Abstract:

High dose activity without any pre-exercise will impact Delayed Onset Muscle Soreness (DOMS). DOMS known as delayed pain post-exercise and induce skeletal injury which will decrease athletes’ performances. From now on, post-exercise muscle damage can be detected by measuring skeletal troponin I (sTnI) concentration in serum using ELISA but this method needs more time and cost. To prevent decreased athletes performances, screening need to be done rapidly. We want to introduce our new prototype to detect DOMS acutely. Rapid detection tests are based on immunological reaction between skeletal troponin I antibodies and sTnI in human serum or whole blood. Chemical methods that are used in the manufacture of diagnostic test is lateral flow immunoassay. The material used is rat monoclonal antibody sTnI, colloidal gold, anti-mouse IgG, nitrocellulose membrane, conjugate pad, sample pad, wick and backing card. The procedure are made conjugate (colloidal gold and mAb sTnI) and insert into the conjugate pad, gives spray sTnI mAb and anti-mouse IgG into nitrocellulose membrane, and assemble RDT. RDT had been evaluated by measuring the sensitivity of positive human serum (n = 30) and negative human serum (n = 30). Overall sensitivity value was 93% and specificity value was 90%. ADCOR as the first rapid detection test qualitatively showed antigen-antibody reaction and showed good overall performances for screening of muscle damage. Furthermore, these finding still need more improvements to get best results.

Keywords: DOMS, sTnI, rapid detection test, ELISA

Procedia PDF Downloads 504
5754 Complex Technology of Virtual Reconstruction: The Case of Kazan Imperial University of XIX-Early XX Centuries

Authors: L. K. Karimova, K. I. Shariukova, A. A. Kirpichnikova, E. A. Razuvalova

Abstract:

This article deals with technology of virtual reconstruction of Kazan Imperial University of XIX - early XX centuries. The paper describes technologies of 3D-visualization of high-resolution models of objects of university space, creation of multi-agent system and connected with these objects organized database of historical sources, variants of use of technologies of immersion into the virtual environment.

Keywords: 3D-reconstruction, multi-agent system, database, university space, virtual reconstruction, virtual heritage

Procedia PDF Downloads 260
5753 Duplex Real-Time Loop-Mediated Isothermal Amplification Assay for Simultaneous Detection of Beef and Pork

Authors: Mi-Ju Kim, Hae-Yeong Kim

Abstract:

Product mislabeling and adulteration have been increasing the concerns in processed meat products. Relatively inexpensive pork meat compared to meat such as beef was adulterated for economic benefit. These food fraud incidents related to pork were concerned due to economic, religious and health reasons. In this study, a rapid on-site detection method using loop-mediated isothermal amplification (LAMP) was developed for the simultaneous identification of beef and pork. Each specific LAMP primer for beef and pork was designed targeting on mitochondrial D-loop region. The LAMP assay reaction was performed at 65 ℃ for 40 min. The specificity of each primer for beef and pork was evaluated using DNAs extracted from 13 animal species including beef and pork. The sensitivity of duplex LAMP assay was examined by serial dilution of beef and pork DNAs, and reference binary mixtures. This assay was applied to processed meat products including beef and pork meat for monitoring. Each set of primers amplified only the targeted species with no cross-reactivity with animal species. The limit of detection of duplex real-time LAMP was 1 pg for each DNA of beef and pork and 1% pork in a beef-meat mixture. Commercial meat products that declared the presence of beef and/or pork meat on the label showed positive results for those species. This method was successfully applied to detect simultaneous beef and pork meats in processed meat products. The optimized duplex LAMP assay can identify simultaneously beef and pork meat within less than 40 min. A portable real-time fluorescence device used in this study is applicable for on-site detection of beef and pork in processed meat products. Thus, this developed assay was considered to be an efficient tool for monitoring meat products.

Keywords: beef, duplex real-time LAMP, meat identification, pork

Procedia PDF Downloads 213
5752 Vortex Separator for More Accurate Air Dry-Bulb Temperature Measurement

Authors: Ahmed N. Shmroukh, I. M. S. Taha, A. M. Abdel-Ghany, M. Attalla

Abstract:

Fog systems application for cooling and humidification is still limited, although these systems require less initial cost compared with that of other cooling systems such as pad-and-fan systems. The undesirable relative humidity and air temperature inside the space which have been cooled or humidified are the main reasons for its limited use, which results from the poor control of fog systems. Any accurate control system essentially needs air dry bulb temperature as an input parameter. Therefore, the air dry-bulb temperature in the space needs to be measured accurately. The Scope of the present work is the separation of the fog droplets from the air in a fogged space to measure the air dry bulb temperature accurately. The separation is to be done in a small device inside which the sensor of the temperature measuring instrument is positioned. Vortex separator will be designed and used. Another reference device will be used for measuring the air temperature without separation. A comparative study will be performed to reach at the best device which leads to the most accurate measurement of air dry bulb temperature. The results showed that the proposed devices improved the measured air dry bulb temperature toward the correct direction over that of the free junction. Vortex device was the best. It respectively increased the temperature measured by the free junction in the range from around 2 to around 6°C for different fog on-off duration.

Keywords: fog systems, measuring air dry bulb temperature, temperature measurement, vortex separator

Procedia PDF Downloads 288
5751 Brain Tumor Detection and Classification Using Pre-Trained Deep Learning Models

Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

Abstract:

Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

Procedia PDF Downloads 64
5750 Enhancing Precision Agriculture through Object Detection Algorithms: A Study of YOLOv5 and YOLOv8 in Detecting Armillaria spp.

Authors: Christos Chaschatzis, Chrysoula Karaiskou, Pantelis Angelidis, Sotirios K. Goudos, Igor Kotsiuba, Panagiotis Sarigiannidis

Abstract:

Over the past few decades, the rapid growth of the global population has led to the need to increase agricultural production and improve the quality of agricultural goods. There is a growing focus on environmentally eco-friendly solutions, sustainable production, and biologically minimally fertilized products in contemporary society. Precision agriculture has the potential to incorporate a wide range of innovative solutions with the development of machine learning algorithms. YOLOv5 and YOLOv8 are two of the most advanced object detection algorithms capable of accurately recognizing objects in real time. Detecting tree diseases is crucial for improving the food production rate and ensuring sustainability. This research aims to evaluate the efficacy of YOLOv5 and YOLOv8 in detecting the symptoms of Armillaria spp. in sweet cherry trees and determining their health status, with the goal of enhancing the robustness of precision agriculture. Additionally, this study will explore Computer Vision (CV) techniques with machine learning algorithms to improve the detection process’s efficiency.

Keywords: Armillaria spp., machine learning, precision agriculture, smart farming, sweet cherries trees, YOLOv5, YOLOv8

Procedia PDF Downloads 104
5749 FLC with 3DSVM for 4LEG 4WIRE Shunt Active Power Filter

Authors: Abdelhalim Kessal, Ali Chebabhi

Abstract:

In this paper, a controller based on fuzzy logic control (FLC) associated to Three Dimensional Space Vector Modulation (3DSVM) is applied for shunt active filter in αβo axes domain. The main goals are to improve power quality under disturbed loads, minimize source currents harmonics and reduce neutral current magnitude in the four-wire structure. FLC is used to obtain the reference current and control the DC-bus voltage at the inverter output. The switching signals of the four-leg inverter are generating through a Three Dimensional Space Vector Modulation (3DSVM). Selected simulation results have been shown to validate the proposed system.

Keywords: flc, 3dsvm, sapf, harmonic, inverter

Procedia PDF Downloads 488
5748 The Impact of Varying the Detector and Modulation Types on Inter Satellite Link (ISL) Realizing the Allowable High Data Rate

Authors: Asmaa Zaki M., Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

Abstract:

ISLs are the most popular choice for deep space communications because these links are attractive alternatives to present day microwave links. This paper explored the allowable high data rate in this link over different orbits, which is affected by variation in modulation scheme and detector type. Moreover, the objective of this paper is to optimize and analyze the performance of ISL in terms of Q-factor and Minimum Bit Error Rate (Min-BER) based on different detectors comprising some parameters.

Keywords: free space optics (FSO), field of view (FOV), inter satellite link (ISL), optical wireless communication (OWC)

Procedia PDF Downloads 385
5747 Enhancing Fault Detection in Rotating Machinery Using Wiener-CNN Method

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 70
5746 Knowledge, Attitudes and Its Associated Factors on the Provision of Psychological First Aid during Response to Disasters among Public Health Midwives in Colombo

Authors: S. P. Hewagama

Abstract:

Different kinds of distressing events happen in the world causing a wide range of reactions and feelings. Psychological first aid (PFA) is humane supportive response for suffering. All health workers especially PHMs who play a major role as first responders in a disaster should be able to provide basic PFA effectively. Aim of this study was to assess the knowledge, attitudes and associated factors on the provision of PFA among PHMs during disasters. A descriptive cross-sectional study was carried out among 307 Public Health Midwives in Colombo RDHS area. In the study population, 86.6% (n=266) of the respondents were aware of the term “Psychological first aid” while 13.4% (n=41) were not aware. The total knowledge score was good in majority 85.4%(n=262) of the respondents while only 14.3%(n=45) had a poor knowledge on PFA. There was the statistically significant difference in relation to the level of education with the total knowledge score. Comprehensive desirable attitudes towards PFA was low (30.61%, n=94). According to the study, only a less than a quarter (21.82%, (n = 67)) of the study population had received training on PFA. More than half (56%, n=172) of the respondents had experience in responding to disasters. Conclusions and Recommendations: The overall knowledge and attitudes were found to be satisfactory. However, it is important to improve the knowledge level of the PHMs by providing training and workshops on PFA.

Keywords: disaster, humane supportive assistance, psychological first aid, public health midwives

Procedia PDF Downloads 253
5745 Towards a Conscious Design in AI by Overcoming Dark Patterns

Authors: Ayse Arslan

Abstract:

One of the important elements underpinning a conscious design is the degree of toxicity in communication. This study explores the mechanisms and strategies for identifying toxic content by avoiding dark patterns. Given the breadth of hate and harassment attacks, this study explores a threat model and taxonomy to assist in reasoning about strategies for detection, prevention, mitigation, and recovery. In addition to identifying some relevant techniques such as nudges, automatic detection, or human-ranking, the study suggests the use of major metrics such as the overhead and friction of solutions on platforms and users or balancing false positives (e.g., incorrectly penalizing legitimate users) against false negatives (e.g., users exposed to hate and harassment) to maintain a conscious design towards fairness.

Keywords: AI, ML, algorithms, policy, system design

Procedia PDF Downloads 115
5744 On Space Narrative and American Dream in Martin Eden

Authors: Yangyang Zhang

Abstract:

Martin Eden tells about the tragedy of the protagonist Martin Eden’s suicide after his disillusion about American dream. The author Jack London presents various spatial routines of Martin Eden and reveals the involvement of space in realizing American dream: on the one hand, the Berkeley and Oakland cities contribute to Martin’s material success, making his American dream practical, and on the other hand, the two cities involve in the oppression of bourgeoisie ideology to Martin, promoting the domestic imperialization of bourgeoisie ideology represented by American dream. Molded by bourgeoisie ideology in the city, Martin constructed the oriental South Sea, revealing the oversea imperialization of bourgeoisie ideology behind American dream. By exploring the social, historical and political aspects of space, Martin Eden tries to demonstrate the mere material success and imperialism represented by American dream, revealing the fact of the involvement of American dreamin ideological oppression. When Jack London wrote Martin Eden, he had become a famous writer and realized his personal "American dream". He integrated his struggle experience into the protagonist Martin Eden, and also put his critique of the nature of "American dream" in the novel. The concept of the "American Dream" made the United States the land of dreams, and it also made many Americans believe that through personal struggle, they could climb the social ladder. Under the context of rapid growth in economy in the late 19 th century, American dream was reduced to the satisfaction on a material level. When material wealth was fulfilled, many people felt shattered for a variety of reasons, and such a phenomenon was reflected in the literature of disillusionment in 19th-century America.Martin Eden is such a work about disillusion, in which the geographical space becomes the witness of the realization and disillusionment of the protagonist Martin's "American dream". By analyzing the spatial narrative in Martin Eden, this paper reveals that the "American dream" only represents material success for individuals and the imperialization of capitalist ideology, and exposes the ideological nature of the "American Dream".

Keywords: Martin Eden, space, American dream, ideology of imperialism

Procedia PDF Downloads 125
5743 Examining the Skills of Establishing Number and Space Relations of Science Students with the 'Integrative Perception Test'

Authors: Ni̇sa Yeni̇kalayci, Türkan Aybi̇ke Akarca

Abstract:

The ability of correlation the number and space relations, one of the basic scientific process skills, is being used in the transformation of a two-dimensional object into a three-dimensional image or in the expression of symmetry axes of the object. With this research, it is aimed to determine the ability of science students to establish number and space relations. The research was carried out with a total of 90 students studying in the first semester of the Science Education program of a state university located in the Turkey’s Black Sea Region in the fall semester of 2017-2018 academic year. An ‘Integrative Perception Test (IPT)’ was designed by the researchers to collect the data. Within the scope of IPT, the courses and workbooks specific to the field of science were scanned and the ones without symmetrical structure from the visual items belonging to the ‘Physics - Chemistry – Biology’ sub-fields were selected and listed. During the application, it was expected that students would imagine and draw images of the missing half of the visual items that were given incomplete in the first place. The data obtained from the test in which there are 30 images or pictures in total (f Physics = 10, f Chemistry = 10, f Biology = 10) were analyzed descriptively based on the drawings created by the students as ‘complete (2 points), incomplete/wrong (1 point), empty (0 point)’. For the teaching of new concepts in small aged groups, images or pictures showing symmetrical structures and similar applications can also be used.

Keywords: integrative perception, number and space relations, science education, scientific process skills

Procedia PDF Downloads 147
5742 The Modeling and Effectiveness Evaluation for Vessel Evasion to Acoustic Homing Torpedo

Authors: Li Minghui, Min Shaorong, Zhang Jun

Abstract:

This paper aims for studying the operational efficiency of surface warship’s motorized evasion to acoustic homing torpedo. It orderly developed trajectory model, self-guide detection model, vessel evasion model, as well as anti-torpedo error model in three-dimensional space to make up for the deficiency of precious researches analyzing two-dimensionally confrontational models. Then, making use of the Monte Carlo method, it carried out the simulation for the confrontation process of evasion in the environment of MATLAB. At last, it quantitatively analyzed the main factors which determine vessel’s survival probability. The results show that evasion relative bearing and speed will affect vessel’s survival probability significantly. Thus, choosing appropriate evasion relative bearing and speed according to alarming range and alarming relative bearing for torpedo, improving alarming range and positioning accuracy and reducing the response time against torpedo will improve the vessel’s survival probability significantly.

Keywords: acoustic homing torpedo, vessel evasion, monte carlo method, torpedo defense, vessel's survival probability

Procedia PDF Downloads 439
5741 Immuno-field Effect Transistor Using Carbon Nanotubes Network – Based for Human Serum Albumin Highly Sensitive Detection

Authors: Muhamad Azuddin Hassan, Siti Shafura Karim, Ambri Mohamed, Iskandar Yahya

Abstract:

Human serum albumin plays a significant part in the physiological functions of the human body system (HSA).HSA level monitoring is critical for early detection of HSA-related illnesses. The goal of this study is to show that a field effect transistor (FET)-based immunosensor can assess HSA using high aspect ratio carbon nanotubes network (CNT) as a transducer. The CNT network were deposited using air brush technique, and the FET device was made using a shadow mask process. Field emission scanning electron microscopy and a current-voltage measurement system were used to examine the morphology and electrical properties of the CNT network, respectively. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy were used to confirm the surface alteration of the CNT. The detection process is based on covalent binding interactions between an antibody and an HSA target, which resulted in a change in the manufactured biosensor's drain current (Id).In a linear range between 1 ng/ml and 10zg/ml, the biosensor has a high sensitivity of 0.826 mA (g/ml)-1 and a LOD value of 1.9zg/ml.HSA was also identified in a genuine serum despite interference from other biomolecules, demonstrating the CNT-FET immunosensor's ability to quantify HSA in a complex biological environment.

Keywords: carbon nanotubes network, biosensor, human serum albumin

Procedia PDF Downloads 132
5740 Thermally Stable Crystalline Triazine-Based Organic Polymeric Nanodendrites for Mercury(2+) Ion Sensing

Authors: Dimitra Das, Anuradha Mitra, Kalyan Kumar Chattopadhyay

Abstract:

Organic polymers, constructed from light elements like carbon, hydrogen, nitrogen, oxygen, sulphur, and boron atoms, are the emergent class of non-toxic, metal-free, environmental benign advanced materials. Covalent triazine-based polymers with a functional triazine group are significant class of organic materials due to their remarkable stability arising out of strong covalent bonds. They can conventionally form hydrogen bonds, favour π–π contacts, and they were recently revealed to be involved in interesting anion–π interactions. The present work mainly focuses upon the development of a single-crystalline, highly cross-linked triazine-based nitrogen-rich organic polymer with nanodendritic morphology and significant thermal stability. The polymer has been synthesized through hydrothermal treatment of melamine and ethylene glycol resulting in cross-polymerization via condensation-polymerization reaction. The crystal structure of the polymer has been evaluated by employing Rietveld whole profile fitting method. The polymer has been found to be composed of monoclinic melamine having space group P21/a. A detailed insight into the chemical structure of the as synthesized polymer has been elucidated by Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopic analysis. X-Ray Photoelectron Spectroscopic (XPS) analysis has also been carried out for further understanding of the different types of linkages required to create the backbone of the polymer. The unique rod-like morphology of the triazine based polymer has been revealed from the images obtained from Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscopy (TEM). Interestingly, this polymer has been found to selectively detect mercury (Hg²⁺) ions at an extremely low concentration through fluorescent quenching with detection limit as low as 0.03 ppb. The high toxicity of mercury ions (Hg²⁺) arise from its strong affinity towards the sulphur atoms of biological building blocks. Even a trace quantity of this metal is dangerous for human health. Furthermore, owing to its small ionic radius and high solvation energy, Hg²⁺ ions remain encapsulated by water molecules making its detection a challenging task. There are some existing reports on fluorescent-based heavy metal ion sensors using covalent organic frameworks (COFs) but reports on mercury sensing using triazine based polymers are rather undeveloped. Thus, the importance of ultra-trace detection of Hg²⁺ ions with high level of selectivity and sensitivity has contemporary significance. A plausible sensing phenomenon by the polymer has been proposed to understand the applicability of the material as a potential sensor. The impressive sensitivity of the polymer sample towards Hg²⁺ is the very first report in the field of highly crystalline triazine based polymers (without the introduction of any sulphur groups or functionalization) towards mercury ion detection through photoluminescence quenching technique. This crystalline metal-free organic polymer being cheap, non-toxic and scalable has current relevance and could be a promising candidate for Hg²⁺ ion sensing at commercial level.

Keywords: fluorescence quenching , mercury ion sensing, single-crystalline, triazine-based polymer

Procedia PDF Downloads 123
5739 Capacity Building on Small Automatic Tracking Antenna Development for Thailand Space Sustainability

Authors: Warinthorn Kiadtikornthaweeyot Evans, Nawattakorn Kaikaew

Abstract:

The communication system between the ground station and the satellite is very important to guarantee contact between both sides. Thailand, led by Geo-Informatics and Space Technology Development Agency (GISTDA), has received satellite images from other nation's satellites for a number of years. In 2008, Thailand Earth Observation Satellite (THEOS) was the first Earth observation satellite owned by Thailand. The mission was monitoring our country with affordable access to space-based Earth imagery. At this time, the control ground station was initially used to control the THEOS satellite by our Thai engineers. The Tele-commands were sent to the satellite according to requests from government and private sectors. Since then, GISTDA's engineers have gained their skill and experience to operate the satellite. Recently the desire to use satellite data is increasing rapidly due to space technology moving fast and giving us more benefits. It is essential to ensure that Thailand remains competitive in space technology. Thai Engineers have started to improve the performance of the control ground station in many different sections, also developing skills and knowledge in areas of satellite communication. Human resource skills are being enforced with development projects through capacity building. This paper focuses on the hands-on capacity building of GISTDA's engineers to develop a small automatic tracking antenna. The final achievement of the project is the first phase prototype of a small automatic tracking antenna to support the new technology of the satellites. There are two main subsystems that have been developed and tested; the tracking system and the monitoring and control software. The prototype first phase functions testing has been performed with Two Line Element (TLE) and the mission planning plan (MPP) file calculated from THEOS satellite by GISTDA.

Keywords: capacity building, small tracking antenna, automatic tracking system, project development procedure

Procedia PDF Downloads 65
5738 Intelligent Decision Support for Wind Park Operation: Machine-Learning Based Detection and Diagnosis of Anomalous Operating States

Authors: Angela Meyer

Abstract:

The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

Procedia PDF Downloads 158
5737 Detection of Intentional Attacks in Images Based on Watermarking

Authors: Hazem Munawer Al-Otum

Abstract:

In this work, an efficient watermarking technique is proposed and can be used for detecting intentional attacks in RGB color images. The proposed technique can be implemented for image authentication and exhibits high robustness against unintentional common image processing attacks. It deploys two measures to discern between intentional and unintentional attacks based on using a quantization-based technique in a modified 2D multi-pyramidal DWT transform. Simulations have shown high accuracy in detecting intentionally attacked regions while exhibiting high robustness under moderate to severe common image processing attacks.

Keywords: image authentication, copyright protection, semi-fragile watermarking, tamper detection

Procedia PDF Downloads 248