Search results for: Detect

Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen

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Pulse wave velocity (PWV) of blood flow provides important information of vessel property and blood pressure which can be used to assess cardiovascular disease. However, the above measurements need expensive equipment, such as Doppler ultrasound, MRI, angiography etc. The photoplethysmograph (PPG) signals are commonly utilized to detect blood volume changes. In this study, two infrared (IR) probes are designed and placed at a fixed distance from finger base and fingertip. An analog circuit with automatic gain adjustment is implemented to get the stable original PPG signals from above two IR probes. In order to obtain the time delay precisely between two PPG signals, we obtain the pulse transit time from the second derivative of the original PPG signals. To get a portable, wireless and low power consumption PWV measurement device, the low energy Bluetooth 4.0 (BLE) and the microprocessor (Cortex™-M3) are used in this study. The PWV is highly correlated with blood pressure. This portable device has potential to be used for continuous blood pressure monitoring.

Keywords: pulse wave velocity, photoplethysmography, portable device, biomedical engineering

Procedia PDF Downloads 511

Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto

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The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.

Keywords: radar for safe mobility, railroad crossing, railway, transport safety

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Authors: Shiuh-Jer Huang, Yu-Sheng Hsu

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On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.

Keywords: vehicle auto-parking, parking space detection, parking path tracking control, intelligent fuzzy controller

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Authors: Tine Cencič, Marko Hočevar, Brane Širok

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An experimental investigation has been made to detect cavitation in pump–storage hydro power plant prototype suffering from cavitation in pump mode. Vibrations and acoustic emission on the housing of turbine bearing and pressure fluctuations in the draft tube were measured and the corresponding signals have been recorded and analyzed. The analysis was based on the analysis of high-frequency content of measured variables. The pump-storage hydro power plant prototype has been operated at various input loads and Thoma numbers. Several estimators of cavitation were evaluated according to coefficient of determination between Thoma number and cavitation estimators. The best results were achieved with a compound discharge coefficient cavitation estimator. Cavitation estimators were evaluated in several intervals of frequencies. Also, a prediction of cavitation erosion was made in order to choose the appropriate maintenance and repair periods.

Keywords: cavitation erosion, turbine, cavitation measurement, fluid dynamics

Procedia PDF Downloads 388

Authors: Rabail Shafique Satti, Sidra Ejaz, Madiha Arshad, Marwa Khalid, Sadia Majeed

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The paper presents the development of an automated security system to automate the entry of visitors, providing more flexibility of managing their record and securing homes or workplaces. Face recognition is part of this system to authenticate the visitors. A cost effective and SMS based door security module has been developed and integrated with the GSM network and made part of this system to allow communication between system and owner. This system functions in real time as when the visitor’s arrived it will detect and recognizes his face and on the result of face recognition process it will open the door for authorized visitors or notifies and allows the owner’s to take further action in case of unauthorized visitor. The proposed system is developed and it is successfully ensuring security, managing records and operating gate without physical interaction of owner.

Keywords: SMS, e-mail, GSM modem, authenticate, face recognition, authorized

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Authors: Yinan Cao, Francine Herrmann

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Adversary emulation is a very effective concrete way to evaluate the defense of an information system or network. It is about building an emulator, which depending on the vulnerability of a target system, will allow to detect and execute a set of identified attacks. However, emulating an adversary is very costly in terms of time and resources. Verifying the information of each technique and building up the countermeasures in the middle of the test is also needed to be accomplished manually. In this article, a synthesis of previous MITRE research on the creation of the ATT&CK matrix will be as the knowledge base of the known techniques and a well-designed adversary emulation software CALDERA based on ATT&CK Matrix will be used as our platform. Inspired and guided by the previous study, a plugin in CALDERA called Tinker will be implemented, which is aiming to help the tester to get more information and also the mitigation of each technique used in the previous operation. Furthermore, the optional countermeasures for some techniques are also implemented and preset in Tinker in order to facilitate and fasten the process of the defense improvement of the tested system.

Keywords: automation, adversary emulation, CALDERA, countermeasures, MITRE ATT&CK

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Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

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Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

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Authors: Nomfundo Ngombane, Topside E. Mathonsi

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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: H. Bakhshi, E. Khayyamian

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Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

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Authors: Ilham Priadythama, Pringgo Widyo Laksono, Agung Pamungkas

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Myoelectric is prosthetic, flexible, and offered industrial application has been highly developed and widely used. Myoelectric hand use myoelectric signal from muscle to activate and control the membrane part of hand. Commonly myoelectric signal is detected on human arm from skin surface. So that it only small magnitude signal captured. Detecting myoelectric signal on the skin surface takes proper and consistent procedure. This paper provides preliminary study of electrodes position which gives best signal strength for five basic grasping. Two-position scenario used to place three channel electrodes set. A bi-potential amplifier based on AD620 used to amplify the signal. Finally, the signal was analyzed using DSSF3 software. From this study, we found that grasp type was stronger using first scenario electrode placement while the rest type better with another scenario.

Keywords: myoelectric signal, basic grasp, DSSF3, electrode, bi-potential amplifier

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Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

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Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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Authors: Anahita Izadyar

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Using a recombinant enzyme derived from corn and a simple modification, we are fabricating a facile, fast, and cost-beneficial novel biosensor to measure glucose. We are applying Plant Produced Mn Peroxidase (PPMP), glucose oxidase (GOx), polyaniline (PANI) as conductive polymer and gold nanoparticles (AuNPs) on Au electrode using electrochemical response to detect glucose. We applied the entrapment method of enzyme composition, which is generally used to immobilize conductive polymer and facilitate electron transfer from the enzyme oxidation-reduction center to the sample solution. In this work, the oxidation of glucose on the modified gold electrode was quantified with Linear Sweep Voltammetry(LSV). We expect that the modified biosensor has the potential for monitoring various biofluids.

Keywords: plant-produced manganese peroxidase, enzyme-based biosensors, glucose, modified gold nanoparticles electrode, polyaniline

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Authors: Khen Cohen, Daniel Yankelevich, David Mendlovic, Dan Raviv

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We present a 3D stereo system for high-resolution sensing in both the spatial and the temporal domains by combining a frame-based camera and an event-based camera. We establish a method to merge both devices into one unite system and introduce a calibration process, followed by a correspondence technique and interpolation algorithm for 3D reconstruction. We further provide quantitative analysis about our system in terms of depth resolution and additional parameter analysis. We show experimentally how our system performs temporal super-resolution up to effectively 1ms and can detect fast-moving objects and human micro-movements that can be used for micro-expression analysis. We also demonstrate how our method can extract colored events for an event-based camera without any degradation in the spatial resolution, compared to a colored filter array.

Keywords: DVS-CIS stereo vision, micro-movements, temporal super-resolution, 3D reconstruction

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Authors: Rajesh Kumar Gautam, Debabrata Seth

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Thioflavin-T (ThT) play a key role of an important biologically active fluorescent sensor for amyloid fibrils. ThT molecule has been developed a method to detect the analysis of different type of diseases such as neurodegenerative disorders, Alzheimer’s, Parkinson’s, and type II diabetes. ThT was used as a fluorescent marker to detect the formation of amyloid fibril. In the presence of amyloid fibril, ThT becomes highly fluorescent. ThT undergoes twisting motion around C-C bonds of the two adjacent benzothiazole and dimethylaniline aromatic rings, which is predominantly affected by the micro-viscosity of the local environment. The present study articulates photophysics and torsional dynamics of biologically active molecule ThT in the presence of deep-eutectic solvents (DESs). DESs are environment-friendly, low cost and biodegradable alternatives to the ionic liquids. DES resembles ionic liquids, but the constituents of a DES include a hydrogen bond donor and acceptor species, in addition to ions. Due to the presence of the H-bonding network within a DES, it exhibits structural heterogeneity. Herein, we have prepared two different DESs by mixing urea with choline chloride and N, N-diethyl ethanol ammonium chloride at ~ 340 K. It was reported that deep eutectic mixture of choline chloride with urea gave a liquid with a freezing point of 12°C. We have experimented by taking two different concentrations of ThT. It was observed that at higher concentration of ThT (50 µM) it forms aggregates in DES. The photophysics of ThT as a function of temperature have been explored by using steady-state, and picoseconds time-resolved fluorescence emission spectroscopic techniques. From the spectroscopic analysis, we have observed that with rising temperature the fluorescence quantum yields and lifetime values of ThT molecule gradually decreases; this is the cumulative effect of thermal quenching and increase in the rate of the torsional rate constant. The fluorescence quantum yield and fluorescence lifetime decay values were always higher for DES-II (urea & N, N-diethyl ethanol ammonium chloride) than those for DES-I (urea & choline chloride). This was mainly due to the presence of structural heterogeneity of the medium. This was further confirmed by comparison with the activation energy of viscous flow with the activation energy of non-radiative decay. ThT molecule in less viscous media undergoes a very fast twisting process and leads to deactivation from the photoexcited state. In this system, the torsional motion increases with increasing temperature. We have concluded that beside bulk viscosity of the media, structural heterogeneity of the medium play crucial role to guide the photophysics of ThT in DESs. The analysis of the experimental data was carried out in the temperature range 288 ≤ T = 333K. The present articulate is to obtain an insight into the DESs as media for studying various photophysical processes of amyloid fibrils sensing molecule of ThT.

Keywords: deep eutectic solvent, photophysics, Thioflavin T, the torsional rate constant

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Authors: Amal Raqib Shameran, Ghanim Aboud Al-Mola

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Respiratory syncytial virus (hRSV) is the major pathogens of respiratory tract infections (RTI) among infants and children in the world. They are classified in family Paramyxoviridae and sub-family Pneumovirinae. The current work aimed to detect the role of RSV in the lower respiratory tract infection (LRTI) in Hilla, Iraq. The samples were collected from 50 children who were admitted to hospital suffering from lower respiratory tract infections (LRTI). 50 nasal and pharyngeal swabs were taken from patients at the period from January 2010 till April 2011, hospitalized in Hilla Maternity and Children Hospital. The results showed that the proportion of children infected with hRSV accounted for 24% 12/50 with lower respiratory tract infections (LRTI) when they tested by polymerase chain reaction (RT-PCR).

Keywords: respiratory syncytial virus, respiratory tract infections, infants, polymerase chain reaction (PCR)

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Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

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Authors: Surapol Raadnui

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This paper describes an experimental investigation on a pair of gears in which wear and pitting were intentionally allowed to occur, namely, moisture corrosion pitting, acid-induced corrosion pitting, hard contaminant-related pitting and mechanical induced wear. A back-to-back spur gear test rig was used. The test samples of wear debris were collected and assessed through the utilization of an optical microscope in order to correlate and compare the debris morphology to pitting and wear degradation of the worn gears. In addition, weight loss from all test gear pairs was assessed with the utilization of the statistical design of the experiment. It can be deduced that wear debris characteristics exhibited a direct relationship with different pitting and wear modes. Thus, it should be possible to detect and diagnose gear pitting and wear utilization of worn surfaces, generated wear debris and quantitative measurement such as weight loss.

Keywords: tribology, spur gear wear, predictive maintenance, wear particle analysis

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Authors: Ahmad N. Shuid, Azri Jalil, Sabarul A. Mokhtar, Mohd F. Khamis, Norliza Muhammad

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Micro-CT provides a 3-D image of fracture callus, which can be used to calculate quantitative parameters. In this study, micro-CT was used to assess the fracture healing of orchidectomised rats, an androgen-deficient osteoporosis model. The effect of testosterone (hormone replacement) on fracture healing was also assessed with micro-CT. The rats were grouped into orchidectomised-control (ORX), sham-operated (SHAM), and orchidectomised; and injected with testosterone intramuscularly once weekly (TEN). Treatment duration was six weeks. The fracture was induced and fixed with plates and screws in the right tibia of all the rats. An in vitro micro-CT was used to scan the fracture callus area which consisted of 100 axial slices above and below fracture line. The analysis has shown that micro-CT was able to detect a significant difference in the fracture healing rate of ORX and TEN groups. In conclusion, micro-CT can be used to assess fracture healing in androgen-deficient osteoporosis. This imaging tool can be used to test agents that influence fracture healing in the androgen-deficient model.

Keywords: androgen, fracture, orchidectomy, osteoporosis

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Authors: Pierre Moulis, Markus Herderich, Doris Rauhut, Patricia Ballestra

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Nowadays, it is starting to be more frequent to detect wines with mousy off-flavor. The reasons behind this could be the significant decrease in sulphur dioxide, the increase in pH, and the trend for spontaneous fermentation in wine. This off-flavor can be produced by Brettanomyces bruxellensis or some Lactic acid bacteria. So far there is no study working on the influence of the genetic group on the production of these microorganisms. Objectives: The objectives of this research are to increase knowledge and to have a better understanding of the microbiological phenomena related to the production of the mousy off-flavor in the wine. Methodologies: In this research, microorganisms were screened in an N-heterocycle assay medium (this medium contained all known precursors) and the production of mousy compounds was quantified by Stir Bar Sorptive Extraction-Gas Chromatography-Mass Spectrometry (SBSE-GC-MS). Main contributions: Brettanomyces bruxellensis and Oenococcus oeni could produce mousiness at a different amount depending on the strain. But there is no group effect.

Keywords: mousy off-flavor, wine, Brettanomyces bruxellensis, Oenococcus oeni

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Authors: Nurbanu Guzey, S. Jagannathan

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Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

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Authors: Cristina Giosuè, Federica Biondo, Sergio Vitale

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In the last years, the consumers' awareness for environmental concerns has been increasing, and seafood eco-labels are considered as a possible instrument to improve both seafood markets and sustainable fishing management. In this direction, the aim of this study was to carry out a meta-analysis on consumers’ willingness to pay (WTP) for eco-labeled wild seafood, by a meta-regression. Therefore, only papers published on ISI journals were searched on “Web of Knowledge” and “SciVerse Scopus” platforms, using the combinations of the following key words: seafood, ecolabel, eco-label, willingness, WTP and premium. The dataset was built considering: paper’s and survey’s codes, year of publication, first author’s nationality, species’ taxa and family, sample size, survey’s continent and country, data collection (where and how), gender and age of consumers, brand and ΔWTP. From analysis the interest on eco labeled seafood emerged clearly, in particular in developed countries. In general, consumers declared greater willingness to pay than that actually applied for eco-label products, with difference related to taxa and brand.

Keywords: eco label, meta regression, seafood, willingness to pay

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Sumayah Mohammed Asiri A., Aviva Levina B., Elizabeth New C., Peter Lay D.

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Pt compounds have been among the most successful anticancer drugs in the last 40 years, but the development of resistance to them is an increasing problem. Cellular homeostasis of an essential metal, Cu, is known to be involved in Pt resistance, but mechanisms of this process are poorly understood. We used a novel ratiometric Cu(I)-sensitive fluorescent probeInCCu1 dye to detect Cu(I) in the mitochondria. Total Cu and labile Cu pool measured using AAS and InCCu1 dye in A2780 cells and their corresponding resistant cells A2780-cis.R cells treated with Cu and cisplatin. The main difference between both cell lines in the presence and absence of Cu(II) is that resistant cells have lower total Cu content but higher labile Cu levels than cisplatin-sensitive cells. This means that resistant cells can metabolize and export excess Cu more efficiently. Furthermore, InCCu1 has emerged not only as an indicator of labile cellular Cu levels in the mitochondria but as a potentially versatile multi-organelle probe.

Keywords: AAS and ICPMS, A2780 and its resistant cells, ratiometric fluorescent sensors, inCCu1, and total and labile Cu

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Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

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Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

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Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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Authors: Naima Ikken, Abdelhadi Bouknadel, Nour-eddine Tariba Ahmed Haddou, Hafsa El Omari

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The operation of grid-connected inverters necessity a single-phase phase locked loop (PLL) is proposed in this article to accurately and quickly estimate and detect the grid phase angle. This article presents the improvement of a method of phase-locked loop. The novelty is to generate a method (PLL) of synchronizing the grid with a Notch filter based on adaptive fuzzy logic for inverter systems connected to the grid. The performance of the proposed method was tested under normal and abnormal operating conditions (amplitude, frequency and phase shift variations). In addition, simulation results with ISPM software are developed to verify the effectiveness of the proposed method strategy. Finally, the experimental test will be used to extract the result and discuss the validity of the proposed algorithm.

Keywords: phase locked loop, PLL, notch filter, fuzzy logic control, grid connected inverters

Procedia PDF Downloads 125