Search results for: laser line detection

Authors: Nirav J. Patel, Kalpesh K. Dudani

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Partial discharge (PD) is the dissipation of energy caused by localized breakdown of insulation. Power transformers are one of the most important components in the electrical energy network. Insulation degradation of transformer is frequently linked to PD. This is why PD detection is used in power system to monitor the health of high voltage transformer. If such problem are not detected and repaired, the strength and frequency of PD may increase and eventually lead to the catastrophic failure of the transformer. This can further cause external equipment damage, fires and loss of revenue due to an unscheduled outage. Hence, reliable online PD detection is a critical need for power companies to improve personnel safety and decrease the probability of loss of service. The PD phenomenon is manifested in a variety of physically observable signals including Ultra High Frequency (UHF) radiation and Acoustic Disturbances, Electrical pulses. Acoustic method is based on sensing the radiated acoustic emission from discharge sites in the insulation. Propagated wave from the PD fault site are captured sensor are consequently pre-amplified, filtered, recorded and analyze.

Keywords: acoustic, partial discharge, perfectly matched layer, sensor

Procedia PDF Downloads 527

Authors: Vipulkumar Jagodana

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Recently the use of renewable sources has increased, these sources include fuel cell, photo voltaic, and wind turbine. Islanding occurs when one portion of grid is isolated from remaining grid. Use of the renewable sources can provide continuous power to isolated portion in islanding condition. One of the common renewable sources is wind generation using wind turbine. The efficiency of wind generation can be increased in combination with conventional sources. When islanding occurs, few parameters change which may be frequency, voltage, active power, and harmonics. According to large change in one of these parameters islanding is detected. In this paper, two passive methods Rate of Change of Frequency (ROCOF) and Rate of change of Power (ROCOP) have been implemented for islanding detection of small wind-turbine. Islanding detection of both methods have been simulated in PSCAD. Simulation results show at different islanding inception angle response of ROCOF and ROCOP.

Keywords: islanding, adopted methods, PSCAD simulation, comparison

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Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

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In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

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Authors: J. F. Reinoso-Gordo, F. J. Ariza-López, A. Mozas-Calvache, J. L. García-Balboa, S. Eddargani

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The DEMs quality may depend on several factors such as data source, capture method, processing type used to derive them, or the cell size of the DEM. The two most important capture methods to produce regional-sized DEMs are photogrammetry and LiDAR; DEMs covering entire countries have been obtained with these methods. The quality of these DEMs has traditionally been evaluated by the national cartographic agencies through punctual sampling that focused on its vertical component. For this type of evaluation there are standards such as NMAS and ASPRS Positional Accuracy Standards for Digital Geospatial Data. However, it seems more appropriate to carry out this evaluation by means of a method that takes into account the superficial nature of the DEM and, therefore, its sampling is superficial and not punctual. This work is part of the Research Project "Functional Quality of Digital Elevation Models in Engineering" where it is necessary to control the quality of a DEM whose data source is an experimental LiDAR flight with a density of 14 points per square meter to which we call Point Cloud Product (PCpro). In the present work it is described the capture data on the ground and the postprocessing tasks until getting the point cloud that will be used as reference (PCref) to evaluate the PCpro quality. Each PCref consists of a patch 50x50 m size coming from a registration of 4 different scan stations. The area studied was the Spanish region of Navarra that covers an area of 10,391 km2; 30 patches homogeneously distributed were necessary to sample the entire surface. The patches have been captured using a Leica BLK360 terrestrial laser scanner mounted on a pole that reached heights of up to 7 meters; the position of the scanner was inverted so that the characteristic shadow circle does not exist when the scanner is in direct position. To ensure that the accuracy of the PCref is greater than that of the PCpro, the georeferencing of the PCref has been carried out with real-time GNSS, and its accuracy positioning was better than 4 cm; this accuracy is much better than the altimetric mean square error estimated for the PCpro (<15 cm); The kind of DEM of interest is the corresponding to the bare earth, so that it was necessary to apply a filter to eliminate vegetation and auxiliary elements such as poles, tripods, etc. After the postprocessing tasks the PCref is ready to be compared with the PCpro using different techniques: cloud to cloud or after a resampling process DEM to DEM.

Keywords: data quality, DEM, LiDAR, terrestrial laser scanner, accuracy

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Authors: Muñiz-Lino Marcos A.

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The ectomesenchymal tissues involved in tooth development and their remnants are the origin of different odontogenic lesions, including tumors and cysts of the jaws, with a wide range of clinical behaviors. A dentigerous cyst (DC) represents approximately 20% of all cases of odontogenic cysts, and it has been demonstrated that it can develop benign and malignant odontogenic tumors. DC is characterized by bone destruction of the area surrounding the crown of a tooth that has not erupted and contains liquid. The treatment of odontogenic tumors and cysts usually involves a partial or total removal of the jaw, causing important secondary co-morbidities. However, molecules implicated in DC pathogenesis, as well as in its development into odontogenic tumors, remain unknown. A cellular model may be useful to study these molecules, but that model has not been established yet. Here, we reported the establishment of a cell culture derived from a dentigerous cyst. This cell line was named DeCy-1. In spite of its ectomesenchymal morphology, DeCy-1 cells express epithelial markers such as cytokeratins 5, 6, and 8. Furthermore, these cells express the ODAM protein, which is present in odontogenesis and in dental follicles, indicating that DeCy-1 cells are derived from odontogenic epithelium. Analysis by electron microscopy of this cell line showed that it has a high vesicular activity, suggesting that DeCy-1 could secrete molecules that may be involved in DC pathogenesis. Thus, secreted proteins were analyzed by PAGE-SDS where we observed approximately 11 bands. In addition, the capacity of these secretions to degrade proteins was analyzed by gelatin substrate zymography. A degradation band of about 62 kDa was found in these assays. Western blot assays suggested that the matrix metalloproteinase 2 (MMP-2) is responsible for this protease activity. Thus, our results indicate that the establishment of a cell line derived from DC is a useful in vitro model to study the biology of this odontogenic lesion and its participation in the development of odontogenic tumors.

Keywords: dentigerous cyst, ameloblastoma, MMP-2, odontogenic tumors

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Authors: Mingqian Zhang

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Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

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Authors: Ahmed Noor Al-Qayyim

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During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

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Authors: Izabela Nowicka, Jacek Dworzecki

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The paper will be presented to selected legal and organizational solutions for the prevention and combating of terrorism by the police in Poland. Development will include information on the organization and functioning of the police anti-terrorist sub-units, whose officers are on the front line of the fight against terrorism. They will be presented to the conditions and cases of use of firearms by police officers in the course of special operations aimed against organizations and terrorist groups, and the perpetrators of criminal acts of terrorism as well as the legal foundation for the Polish police to take immediate counterterrorism operations. Article will be prepared in the context of an international research project entitled. Understand the Dimensions of Organised Crime and Terrorist Networks for Developing Effective and Efficient Security Solutions for First-line-practitioners and Professionals [Project: H2020-FCT-2015, No: 700688].

Keywords: the fight against terrorism, police, Poland, takedown

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Authors: Satyasen Panda, Urmila Bhanja

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In this paper, we have presented and analyzed three-dimensional (3-D) matrices of wavelength/time/space code for optical code division multiple access (OCDMA) networks with NAND subtraction detection technique. The 3-D codes are constructed by integrating a two-dimensional modified quadratic congruence (MQC) code with one-dimensional modified prime (MP) code. The respective encoders and decoders were designed using fiber Bragg gratings and optical delay lines to minimize the bit error rate (BER). The performance analysis of the 3D-OCDMA system is based on measurement of signal to noise ratio (SNR), BER and eye diagram for a different number of simultaneous users. Also, in the analysis, various types of noises and multiple access interference (MAI) effects were considered. The results obtained with NAND detection technique were compared with those obtained with OR and AND subtraction techniques. The comparison results proved that the NAND detection technique with 3-D MQC\MP code can accommodate more number of simultaneous users for longer distances of fiber with minimum BER as compared to OR and AND subtraction techniques. The received optical power is also measured at various levels of BER to analyze the effect of attenuation.

Keywords: Cross Correlation (CC), Three dimensional Optical Code Division Multiple Access (3-D OCDMA), Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA), Multiple Access Interference (MAI), Phase Induced Intensity Noise (PIIN), Three Dimensional Modified Quadratic Congruence/Modified Prime (3-D MQC/MP) code

Procedia PDF Downloads 413

Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

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Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection

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Authors: Tze-Sian Pui, Aung Than, Song-Wei Loo, Yuan-Li Hoe

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A paper-based electrode devised from an array of carboxylated multi-walled carbon nanotubes (MWNTs) and poly (diallyldimethylammonium chloride) (PDDA) has been successfully developed for the simultaneous detection of dopamine (DA) and ascorbic acid (AA) in 0.1 M phosphate buffer solution (PBS). The PDDA/MWNTs electrodes were fabricated by allowing PDDA to absorb onto the surface of carboxylated MWNTs, followed by drop-casting the resulting mixture onto a paper. Cyclic voltammetry performed using 5 mM [Fe(CN)₆]³⁻/⁴⁻ as the redox marker showed that the PDDA/MWNTs electrode has higher redox activity compared to non-functionalized carboxylated MWNT electrode. Differential pulse voltammetry was conducted with DA concentration ranging from 2 µM to 500 µM in the presence of 1 mM AA. The distinctive potential of 0.156 and -0.068 V (vs. Ag/AgCl) measured on the surface of the PDDA/MWNTs electrode revealed that both DA and AA were oxidized. The detection limit of DA was estimated to be 0.8 µM. This nanocomposite paper-based electrode has great potential for future applications in bioanalysis and biomedicine.

Keywords: dopamine, differential pulse voltammetry, paper sensor, carbon nanotube

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Authors: JooYoung Lee, Rasheed Hussain

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Understanding the relationships among communities of users is the key to blueprint the evolution of human society. Majority of people are equipped with GPS devices, such as smart phones and smart cars, which can trace their whereabouts. In this paper, we discover communities of device users based on real locations in a given time frame. We, then, study the associations of discovered communities, referred to as temporal communities, and generate temporal and probabilistic association rules. The rules describe how strong communities are associated. By studying the generated rules, we can automatically extract underlying hierarchies of communities and permanent communities such as work places.

Keywords: association rules, community detection, evolution of communities, spatiotemporal

Procedia PDF Downloads 371

Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: Rajiv Kumar Srivastava

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Manufacturing of complex products such as automobiles and computers requires a very large number of parts and sub-assemblies. The design of mechanisms for delivery of these materials to the point of assembly is an important manufacturing system and supply chain challenge. Different approaches to this problem have been evolved for assembly lines designed to make large volumes of standardized products. However, contemporary assembly systems are required to concurrently produce a variety of products using approaches such as mixed model production, and at times even mass customization. In this paper we examine the material supply approaches for variety production in moderate to large volumes. The conventional approach for material delivery to high volume assembly lines is to supply and stock materials line-side. However for certain materials, especially when the same or similar items are used along the line, it is more convenient to supply materials in kits. Kitting becomes more preferable when lines concurrently produce multiple products in mixed model mode, since space requirements could increase as product/ part variety increases. At times such kits may travel along with the product, while in some situations it may be better to have delivery and station-specific kits rather than product-based kits. Further, in some mass customization situations it may even be better to have a single delivery and assembly station, to which an entire kit is delivered for fitment, rather than a normal assembly line. Finally, in low-moderate volume assembly such as in engineered machinery, it may be logistically more economical to gather materials in an order-specific kit prior to launching final assembly. We have studied material supply mechanisms to support assembly systems as observed in case studies of firms with different combinations of volume and variety/ customization. It is found that the appropriate approach tends to be a hybrid between direct line supply and different kitting modes, with the best mix being a function of the manufacturing and supply chain environment, as well as space and handling considerations. In our continuing work we are studying these scenarios further, through the use of descriptive models and progressing towards prescriptive models to help achieve the optimal approach, capturing the trade-offs between inventory, material handling, space, and efficient line supply.

Keywords: assembly systems, kitting, material supply, variety production

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Authors: Alonggot Limcharoen, Jintana Wannarat, Vorawat Panich

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This study aims to investigate the balancing of the number of operators (Line Balancing technique) in the production line of hard disk drive components in order to increase efficiency. At present, the trend of using hard disk drives has continuously declined leading to limits in a company’s revenue potential. It is important to improve and develop the production process to create market share and to have the ability to compete with competitors with a higher value and quality. Therefore, an effective tool is needed to support such matters. In this research, the Arena program was applied to analyze the results both before and after the improvement. Finally, the precedent was used before proceeding with the real process. There were 14 work stations with 35 operators altogether in the RA production process where this study was conducted. In the actual process, the average production time was 84.03 seconds per product piece (by timing 30 times in each work station) along with a rating assessment by implementing the Westinghouse principles. This process showed that the rating was 123% underlying an assumption of 5% allowance time. Consequently, the standard time was 108.53 seconds per piece. The Takt time was calculated from customer needs divided by working duration in one day; 3.66 seconds per piece. Of these, the proper number of operators was 30 people. That meant five operators should be eliminated in order to increase the production process. After that, a production model was created from the actual process by using the Arena program to confirm model reliability; the outputs from imitation were compared with the original (actual process) and this comparison indicated that the same output meaning was reliable. Then, worker numbers and their job responsibilities were remodeled into the Arena program. Lastly, the efficiency of production process enhanced from 70.82% to 82.63% according to the target.

Keywords: hard disk drive, line balancing, ECRS, simulation, arena program

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Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

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Authors: Kiwon Yeom

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Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Jiangwan Xu, Chunyu Ding

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Lunar exploration is of significant importance in the development and utilization of in-situ lunar resources, water ice exploration, space and astronomical science, as well as in political and military strategy. In recent years, ground-based radar (GBR) has gained increasing attention in the field of lunar exploration due to its flexibility, low cost, and penetrating capabilities. This paper reviews the scientific research on lunar exploration using GBR, outlining the basic principles of GBR and the progress made in lunar exploration studies. It introduces the fundamental principles of lunar imaging using GBR, and systematically reviews studies on lunar surface layer detection, inversion of lunar regolith dielectric properties, and polar water ice detection using GBR. In particular, the paper summarizes the current development status of Chinese GBR and forecasts future development trends in China. This review will enhance the understanding of lunar exploration results using GBR radar, systematically demonstrate the main applications and scientific achievements of GBR in lunar exploration, and provide a reference for future GBR radar lunar exploration missions.

Keywords: ground-based radar, lunar exploration, radar imaging, lunar surface/subsurface detection

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Arpan Kumar Nayak, Debabrata Pradhan

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A simple, single-step and one-pot hydrothermal method was employed to synthesize WO₃-SnO₂ mixed nanostructured metal oxides at 200°C in 12h. The SnO₂ nanoparticles were found to be uniformly decorated on the WO₃ nanoplates. Though it is widely known that noble metals such as Pt, Pd doping or decoration on metal oxides improve the sensing response and sensitivity, we varied the SnO₂ concentration in the WO₃-SnO₂ mixed oxide and demonstrated their performance in ammonia, ethanol and acetone sensing. The sensing performance of WO₃-(x)SnO₂ [x = 0.27, 0.54, 1.08] mixed nanostructured oxides was found to be not only superior to that of pristine oxides but also higher/better than that of reported noble metal-based sensors. The sensing properties (selectivity, limit of detection, response and recovery times) are measured as a function of operating temperature (150-350°C). In particular, the gas selectivity is found to be highly temperature-dependent with optimum performance obtained at 200°C, 300°C and 350°C for ammonia, ethanol, and acetone, respectively. The present results on cost effective WO₃-SnO₂ sensors can find potential application in human breath analysis by noninvasive detection.

Keywords: gas sensing, mixed oxides, nanoplates, ammonia, ethanol, acetone

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Authors: Mustafa Yorgancılar, Emine Atalay, Necdet Akgün, Ali Topal

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In this study, polymerase chain reaction based Inter-simple sequence repeat (ISSR) from DNA fingerprinting techniques were used to investigate the genetic relationships among barley crossbreed genotypes in Turkey. It is important that selection based on the genetic base in breeding programs via ISSR, in terms of breeding time. 14 ISSR primers generated a total of 97 bands, of which 81 (83.35%) were polymorphic. The highest total resolution power (RP) value was obtained from the F2 (0.53) and M16 (0.51) primers. According to the ISSR result, the genetic similarity index changed between 0.64–095; Lane 3 with Line 6 genotypes were the closest, while Line 36 were the most distant ones. The ISSR markers were found to be promising for assessing genetic diversity in barley crossbreed genotypes.

Keywords: barley, crossbreed, genetic similarity, ISSR

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Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

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Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

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Authors: Rowan Moore, Kai Scheffler, Eugen Damoc, Jennifer Sutton, Aaron Bailey, Stephane Houel, Simon Cubbon, Jonathan Josephs

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Purpose: MS analysis of monoclonal antibodies (mAbs) at the protein and peptide levels is critical during development and production of biopharmaceuticals. The compositions of current generation therapeutic proteins are often complex due to various modifications which may affect efficacy. Intact proteins analyzed by MS are detected in higher charge states that also provide more complexity in mass spectra. Protein analysis in native or native-like conditions with zero or minimal organic solvent and neutral or weakly acidic pH decreases charge state value resulting in mAb detection at higher m/z ranges with more spatial resolution. Methods: Three commercially available mAbs were used for all experiments. Intact proteins were desalted online using size exclusion chromatography (SEC) or reversed phase chromatography coupled on-line with a mass spectrometer. For streamlined use of the LC- MS platform we used a single SEC column and alternately selected specific mobile phases to perform separations in either denaturing or native-like conditions: buffer A (20 % ACN, 0.1 % FA) with Buffer B (100 mM ammonium acetate). For peptide analysis mAbs were proteolytically digested with and without prior reduction and alkylation. The mass spectrometer used for all experiments was a commercially available Thermo Scientific™ hybrid Quadrupole-Orbitrap™ mass spectrometer, equipped with the new BioPharma option which includes a new High Mass Range (HMR) mode that allows for improved high mass transmission and mass detection up to 8000 m/z. Results: We have analyzed the profiles of three mAbs under reducing and native conditions by direct infusion with offline desalting and with on-line desalting via size exclusion and reversed phase type columns. The presence of high salt under denaturing conditions was found to influence the observed charge state envelope and impact mass accuracy after spectral deconvolution. The significantly lower charge states observed under native conditions improves the spatial resolution of protein signals and has significant benefits for the analysis of antibody mixtures, e.g. lysine variants, degradants or sequence variants. This type of analysis requires the detection of masses beyond the standard mass range ranging up to 6000 m/z requiring the extended capabilities available in the new HMR mode. We have compared each antibody sample that was analyzed individually with mixtures in various relative concentrations. For this type of analysis, we observed that apparent native structures persist and ESI is benefited by the addition of low amounts of acetonitrile and formic acid in combination with the ammonium acetate-buffered mobile phase. For analyses on the peptide level we analyzed reduced/alkylated, and non-reduced proteolytic digests of the individual antibodies separated via reversed phase chromatography aiming to retrieve as much information as possible regarding sequence coverage, disulfide bridges, post-translational modifications such as various glycans, sequence variants, and their relative quantification. All data acquired were submitted to a single software package for analysis aiming to obtain a complete picture of the molecules analyzed. Here we demonstrate the capabilities of the mass spectrometer to fully characterize homogeneous and heterogeneous therapeutic proteins on one single platform. Conclusion: Full characterization of heterogeneous intact protein mixtures by improved mass separation on a quadrupole-Orbitrap™ mass spectrometer with extended capabilities has been demonstrated.

Keywords: disulfide bond analysis, intact analysis, native analysis, mass spectrometry, monoclonal antibodies, peptide mapping, post-translational modifications, sequence variants, size exclusion chromatography, therapeutic protein analysis, UHPLC

Procedia PDF Downloads 362

Authors: In-Lee Choi, Min Jae Jeong, Jun Pill Baek, Ho-Min Kang

Abstract:

As the consumption trends of vegetables become different from the past, it is increased using vegetable more convenience such as fresh-cut vegetables, sprouts, baby vegetables rather than an existing hole piece of vegetables. Selected baby vegetables have various functional materials but they have short shelf life. This study was conducted to improve storability by using suitable laser ablation OTR (oxygen transmission rate) films. Baby vegetable of endive (Cichorium endivia L.) and pak choi (Brassica rapa chinensis) for this research, around 10 cm height, cultivated in glass greenhouse during 3 weeks. Harvested endive and pak choi were stored at 8 ℃ for 5 days and were packed by PP (Polypropylene) container and covered different types of laser ablation OTR film (DaeRyung Co., Ltd.) such as 1,300 cc, 10,000 cc, 20,000 cc, 40,000 cc /m2•day•atm, and control (perforated film) with heat sealing machine (SC200-IP, Kumkang, Korea). All the samples conducted 5 times replication. Statistical analysis was carried out using a Microsoft Excel 2010 program and results were expressed as standard deviations. The fresh weight loss rate of both baby vegetables were less than 0.3 % in treated films as maximum weight loss rate. On the other hands, control in the final storage day had around 3.0 % weight loss rate and it followed decreasing quantity. Endive had less 2.0 % carbon dioxide contents as maximum contents in 20,000 cc and 40,000 cc. Oxygen contents was maintained between 17 and 20 % in endive, 19 and 20 % in pak choi. Ethylene concentration of both vegetables maintained little lower contents in 20,000 cc treatments than others at final storage day without statistical significance. In the case of hardness, 40,000 cc film was shown little higher value at both baby vegetables without statistical significance. Visual quality was good at 10,000 cc and 20,000 cc in endive and pak choi, and off-flavor was not appeard any off-flavor in both vegetables. Chlorophyll (SPAD-502, Minolta, Japan) value of endive was shown as similar result with initial in all treatments except 20,000 cc as little lower. And chlorophyll value of pak choi decreased in all treatments compared with initial value but was not shown significantly difference each other. Color of leaves (CR-400, Minolta, Japan) changed significantly in 40,000 cc at endive. In an event of pak choi, all the treatments started yellowing by increasing hunter b value, among them control increased substantially. As above the result, 10,000 cc film was most reasonable packaging film for storing at endive and 20,000 cc at pak choi with good quality.

Keywords: carbon dioxide, shelf-life, visual quality, pak choi

Procedia PDF Downloads 790

Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

Abstract:

Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

Procedia PDF Downloads 480

Authors: Mai M. Farid, Mona El-Shabrawy, Sameh R. Hussein, Ahmed Elkhateeb, El-Said S. Abdel-Hameed, Mona M. Marzouk

Abstract:

Asphodelus aestivus Brot. Is a wild plant distributed in Egypt and is considered one of the five Asphodelus spp. from the family Asphodelaceae; it grows in dry grasslands and on rocky or sandy soil. The chemical components of A. aestivus flowers extract were analyzed using different chromatographic and spectral techniques and led to the isolation of two anthraquinones identified as emodin and emodin-O-glucoside. In addition to, five flavonoid compounds;kaempferol,Kaempferol-3-O-glucoside,Apigenin-6-C-glucoside-7-O-glucoside (Saponarine), luteolin 7-O-β-glucopyranoside, Isoorientin-O-malic acid which is a new compound in nature. The LC-ESI-MS/MS analysis of the flower extract of A. aestivus led to the identification of twenty- two compounds characterized by the presence of flavones, flavonols, and flavone C-glycosides. While GC/MS analysis led to the identification of 24 compounds comprising 98.32% of the oil, the major components of the oil were 9, 12, 15-Octadecatrieoic acid methyl ester 28.72%, and 9, 12-Octadecadieroic acid (Z, Z)-methyl ester 19.96%. In vitro cytotoxic activity of the aqueous methanol extract of A. aestivus flowers against HEPG2, HCT-116, MCF-7, and A549 culture was examined and showed moderate inhibition (62.3±1.1)% on HEPG2 cell line followed by (36.8±0.2)% inhibition on HCT-116 and a weak inhibition (5.7± 0.0.2) on MCF-7 cell line followed by (4.5± 0.4) % inhibition on A549 cell line and this is considered the first cytotoxic report of A. aestivus flowers.

Keywords: Anthraquinones, Asphodelus aestivus, Cytotoxic activity, Flavonoids, LC-ESI-MS/MS

Procedia PDF Downloads 223

Authors: Sadegh Abebi

Abstract:

There are problems with estimating time of product process of products, especially when there is variable serving time, like control stage. These problems will cause overestimation of process time. Layout constraints, reworking constraints and inflexible product schedule in multi product lines, needs a precise planning to reduce volume in particular situation of line stock. In this article, by analyzing real queue systems with layout constraints and by using concepts and principles of Markov chain in queue theory, a hybrid model has been presented. This model can be a base to assess queue systems with probable parameters of service. Here by presenting a case study, the proposed model will be described. so, production lines of a home application manufacturer will be analyzed.

Keywords: Queuing theory, Markov Chain, layout, line balance

Procedia PDF Downloads 626

Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

Abstract:

The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

Procedia PDF Downloads 81

Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

Abstract:

Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

Procedia PDF Downloads 93