Search results for: metal detection

Authors: Claudiu Marcu, Cristina Paul, Adelina Andelescu, Corneliu Mircea Davidescu, Francisc Péter

Abstract:

Heavy metal pollution has become a more serious environmental problem in the last several decades as a result of its toxicity and insusceptibility to the environment. Methods for removing metal ions from aqueous solution mainly consist of physical, chemical and biochemical procedures. Biosorption is defined as the removal of metal or metalloid species, compounds and particulates from solution by a biological material. Biosorption represents a very attractive method for the removal of toxic metal ions from aqueous effluents because it uses the ability of various biomass to bind the metal ions without the risk of releasing other toxic chemical compounds into the environment. The problem with using biomass or living cells as biosorbents is that their regeneration/reuse is often either impossible or very laborious. One of the most common chelating group found in biosorbents is the thiol group in cysteine. Therefore, we immobilized cysteine using covalent binding using glutaraldehyde as a linker on a synthetic sol-gel support obtained using 3-amino-propyl-trimetoxysilane and trimetoxysilane as precursors. The obtained adsorbents were used for removal of cadmium from aqueous solutions and the removal capacity was investigated in relation to the composition of the sol-gel hybrid composite, the loading of the biomolecule and the physical parameters of the biosorption process. In the same conditions, the bare sol-gel support without cysteine had no Cd removal effect, while the adsorbent with cysteine had an adsorption capacity up to 25.8 mg Cd/g adsorbent at pH 2.0 and 119 mg Cd/g adsorbent at pH 6.6, depending on cadmium concentration and adsorption conditions. We used atomic adsorption spectrometry to assess the cadmium concentration in the samples after the biosorbtion process. The parameters for the Freundlich and Langmuir adsorption isotherms where calculated from plotting the results of the adsorption experiments. The results for cysteine immobilization show a good loading capacity of the sol-gel support which indicates it could be used to immobilize metal binding proteins and by doing so boosting the heavy metal adsorption capacity of the biosorbent.

Keywords: biosorbtion, cadmium, cysteine covalent binding, sol-gel

Procedia PDF Downloads 294

Authors: M. E. Turan, H. Zengin, E. Cevik, Y. Sun, Y. Turen, H. Ahlatci

Abstract:

In this study, the effects of B₄C and SiC particle reinforcements on wear properties of magnesium matrix metal composites produced by pressure infiltration method were investigated. AZ91 (9%Al-1%Zn) magnesium alloy was used as a matrix. AZ91 magnesium alloy was melted under an argon atmosphere. The melt was infiltrated to the particles with an appropriate pressure. Wear tests, hardness tests were performed respectively. Microstructure characterizations were examined by light optical (LOM) and scanning electron microscope (SEM). The results showed that uniform particle distributions were achieved in both B₄C and SiC reinforced composites. Wear behaviors of magnesium matrix metal composites changed as a function of type of particles. SiC reinforced composite has better wear performance and higher hardness than B₄C reinforced composite.

Keywords: magnesium matrix composite, pressure infiltration, SEM, wear

Procedia PDF Downloads 360

Authors: Aneek Kuila, Yaron Paz

Abstract:

MIP 177 LT and HT are two-phase transformable metal organic frameworks consisting of a Ti12O15 oxocluster and a tetracarboxylate ligand that exhibits robust chemical stability and improved photoactivity. LT to HT only shows the changes in dimensionality from 0D to 1D without any change in the overall chemical structure. In terms of chemical and photoactivity MIP 177 LT is found to perform better than the MIP 177HT. Step-scan Fourier transform absorption difference time-resolved spectroscopy has been used to collect mid-IR time-resolved infrared spectra of the transient electronic excited states of a nano-porous metal–organic framework MIP 177-LT and HT with 2.5 ns time resolution. Analyzing the time-resolved vibrational data after 355nm LASER excitation reveals the presence of the temporal changes of ν (O-Ti-O) of Ti-O metal cluster and ν (-COO) of the ligand concluding the fact that these moieties are the ultimate acceptors of the excited charges which are localized over those regions on the nanosecond timescale. A direct negative correlation between the differential absorbance (Δ Absorbance) reveals the charge transfer relation among these two moieties. A longer-lived transient signal up to 180ns for MIP 177 LT compared to the 100 ns of MIP 177 HT shows the extended lifetime of the reactive charges over the surface that exerts in their effectivity. An ultrafast change of bidentate to monodentate bridging in the -COO-Ti-O ligand-metal coordination environment was observed after the photoexcitation of MIP 177 LT which remains and lives with for seconds after photoexcitation is halted. This phenomenon is very unique to MIP 177 LT but not observed with HT. This in-situ change in the coordination denticity during the photoexcitation was not observed previously which can rationalize the reason behind the ability of MIP 177 LT to accumulate electrons during continuous photoexcitation leading to a superior photocatalytic activity.

Keywords: time resolved FTIR, metal organic framework, denticity, photoacatalysis

Procedia PDF Downloads 60

Authors: Jaemin Kim, Ilsun Pang, Yongrae Cho, Kwanghun Kim, Sungsun Baik

Abstract:

Manufacturing cost reduction is becoming more important due to excessive oversupply of Single crystalline ingot in recent solar market. Many companies are carrying out extensive research to grow more than one Single crystalline ingot in one batch to reduce manufacturing cost. However what most companies are finding difficult in this process is the effect on ingot due to increasing levels of impurities. Every ingot leaves a certain amount of melt after it is fully grown. This is the impurity that lowers the ingot quality. This impurity increase in the batch after second, third and more are grown subsequently in one batch. In order to solve this problem, the experiment to remove the residual melt in high temperature of hot zone was performed and succeeded. Theoretical average metal concentration of second ingot by new method was calculated and compared to it by conventional method.

Keywords: single crystal, solar cell, metal impurity, Ingot

Procedia PDF Downloads 398

Authors: Adewusi Adeoluwawale, Oronti Iyabosola Busola, Akinola Iretiayo, Komolafe Olusola Aderibigbe

Abstract:

The complex and radial structure of the low voltage distribution network (415V) makes it vulnerable to faults which are due to system and the environmental related factors. Besides these, the protective scheme employed on the low voltage network which is the fuse cannot be monitored remotely such that in the event of sustained fault, the utility will have to rely solely on the complaint brought by customers for loss of supply and this tends to increase the length of outages. A microcontroller based fault detection scheme is hereby developed to detect low voltage and high voltage fault conditions which are common faults on this network. Voltages below 198V and above 242V on the distribution feeders are classified and detected as low voltage and high voltages respectively. Results shows that the developed scheme produced a good response time in the detection of these faults.

Keywords: fault detection, low voltage distribution feeders, outage times, sustained faults

Procedia PDF Downloads 543

Authors: Nicole Virgili, Romolo Remetti

Abstract:

The aim of this work is to characterize, from radiation protection point of view, the emission into the environment of air contaminated by argon-41. In this research work, 41Ar is produced by a TR19PET cyclotron, operated at 19 MeV, installed at 'A. Gemelli' University Hospital, Rome, Italy, for fluorine-18 production. The production rate of 41Ar has been calculated on the basis of the scheduled operation cycles of the cyclotron and by utilising proper production algorithms. Then extensive Monte Carlo calculations, carried out by MCNP code, have allowed to determine the absolute detection efficiency to 41Ar gamma rays of a Geiger Muller detector placed in the terminal part of the chimney. Results showed unsatisfactory detection efficiency values and the need for integrating the detection system with more efficient detectors.

Keywords: Cyclotron, Geiger Muller detector, MCNPX, argon-41, emission of radioactive gas, detection efficiency determination

Procedia PDF Downloads 152

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

Procedia PDF Downloads 340

Authors: Aria Vitkova, Hanna Sykulska-Lawrence

Abstract:

In recent years, Europa has been one of the major focus points in astrobiology due to its high potential of harbouring life in the vast ocean underneath its icy crust. However, the detection of life on Europa faces many challenges due to the harsh environmental conditions and mission constraints. Raman spectroscopy is a highly capable and versatile in-situ characterisation technique that does not require any sample preparation. It has only been used on Earth to date; however, recent advances in optical and laser technology have also allowed it to be considered for extraterrestrial exploration. So far, most efforts have been focused on the exploration of Mars, the most imminent planetary target. However, as an emerging technology with high miniaturization potential, Raman spectroscopy also represents a promising tool for the exploration of Europa. In this study, the capabilities of Raman technology in terms of life detection on Europa are explored and assessed. Spectra of biosignatures identified as high priority molecular targets for life detection on Europa were acquired at various excitation wavelengths and conditions analogous to Europa. The effects of extremely low temperatures and low concentrations in water ice were explored and evaluated in terms of the effectiveness of various configurations of Raman instruments. Based on the findings, a design of a miniaturized Raman instrument optimized for in-situ detection of life on Europa is proposed.

Keywords: astrobiology, biosignatures, Europa, life detection, Raman Spectroscopy

Procedia PDF Downloads 214

Authors: Mohammad Besharatloo

Abstract:

Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

Procedia PDF Downloads 93

Authors: Mahmoud E. Mohamed, Ahmed F. Shalash, Hanan A. Kamal

Abstract:

In communication systems, frequency jump is a serious problem caused by the oscillators used. Kalman filters are used to detect that jump, Despite the tradeoff between the noise level and the speed of the detection. In this paper, An improvement is introduced in the Kalman filter, Through a nonlinear change in the bandwidth of the filter. Simulation results show a considerable improvement in the filter speed with a very low noise level. Additionally, The effect on the response to false alarms is also presented and false alarm rate show improvement.

Keywords: Kalman filter, innovation, false detection, improvement

Procedia PDF Downloads 603

Authors: Sukhleen Kaur

Abstract:

In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

Procedia PDF Downloads 414

Authors: Khushalini N. Ulman, Samane Maroufi, Veena H. Sahajwalla

Abstract:

Globally, electronic waste (e-waste) continues to grow at an alarming rate. Several technologies have been developed to recover valuable materials from e-waste, however, their efficiency can be increased with a better knowledge of the e-waste components. Random access memory cards (RAMs) are considered as high value scrap for the e-waste recyclers. Despite their high precious metal content, RAMs are still recycled in a conventional manner resulting in huge loss of resources. Our research work highlights the precious metal rich components of a RAM. Inductively coupled plasma (ICP) analysis of RAMs of six different generations have been carried out and the trends in their metal content have been investigated. Over the past decade, the copper content of RAMs has halved and their tin content has increased by 70 %. The stricter environmental laws have facilitated ~96 % drop in the lead content of RAMs. To comprehend the fundamentals of thermal transformation of RAMs, our research provides their detailed kinetic study. This can assist the e-waste recyclers in optimising their metal recovery processes. Thus, understanding the chemical and thermal behaviour of RAMs can open new avenues for efficient e-waste recycling.

Keywords: electronic waste, kinetic study, recycling, thermal transformation

Procedia PDF Downloads 145

Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

Abstract:

Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

Procedia PDF Downloads 103

Authors: Abdelghani Chahmi

Abstract:

This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

Procedia PDF Downloads 139

Authors: Marc Evenst Jn Jacques, Sophie Bernard

Abstract:

Electrical and electronic applications, as well as rechargeable batteries, are common in any economy. They also contain a number of important and valuable metals. It is critical to investigate the impact of these new materials or volume sources on the metal market dynamics. This paper investigates the impact of responsible recycling within the European region on metal price volatility. As far as we know, no empirical studies have been conducted to assess the role of metal recycling in metal market price volatility. The goal of this paper is to test the claim that metal recycling helps to cushion price volatility. A set of circular economy indicators/variables, namely, 1) annual total trade values of recycled metals, 2) annual volume of scrap traded and 3) circular material use rate, and 4) information about recycling, are used to estimate the volatility of monthly spot prices of regular metals. A combination of the GARCH-MIDAS model for mixed frequency data sampling and a simple GARCH (1,1) model for the same frequency variables was adopted to examine the potential links between each variable and price volatility. We discovered that from 2010 to 2019, except for Nickel, scrap consumption (Millions of tons), Scrap Trade Values, and Recycled Material use rate had no significant impact on the price volatility of standard metals (Aluminum, Lead) and precious metals (Gold and Platinum). Worldwide interest in recycling has no impact on returns or volatility. Specific interest in metal recycling did have a link to the mean return equation for Aluminum, Gold and to the volatility equation for lead and Nickel.

Keywords: recycling, circular economy, price volatility, GARCH, mixed data sampling

Procedia PDF Downloads 57

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

Procedia PDF Downloads 490

Authors: Mauricio George Miguel Jardini, Jose Antonio Jardini

Abstract:

Transmission power utilities participate with kilometers of circuits, many with particularities in terms of vegetation growth. To control these rights-of-way, maintenance teams perform ground, and air inspections, and the identification method is subjective (indirect). On a ground inspection, when identifying an irregularity, for example, high vegetation threatening contact with the conductor cable, pruning or suppression is performed immediately. In an aerial inspection, the suppression team is mobilized to the identified point. This work investigates the use of 3D modeling of a transmission line segment using RGB (red, blue, and green) images and LiDAR (Light Detection and Ranging) sensor data. Both sensors are coupled to unmanned aerial vehicle. The goal is the accurate and timely detection of vegetation along the right-of-way that can cause shutdowns.

Keywords: 3D modeling, LiDAR, right-of-way, transmission lines, vegetation

Procedia PDF Downloads 132

Authors: A. Threepanich, S. Youngme, P. Praipipat

Abstract:

Although ground egg shells had the ability to eliminate lead in water, their efficiency may decrease in a case of contaminating of other cations such as Na⁺, Ca²⁺ in the water. The development of ground egg shells may solve this problem in which metal oxides are a good choice for this case since they have the ability to remove any heavy metals including lead in the water. Therefore, this study attempts to use this advantage for improving ground egg shells for the specific lead removal efficiency in the water. X-ray fluorescence (XRF) technique was used for the chemical element contents analysis of ground egg shells (GES) and ground egg shells with metal oxide (GESM), and Transmission electron microscope (TEM) technique was used to examine the material sizes. The batch test studies were designed to investigate the factor effects on dose (5, 10, 15 grams), pH (5, 7, 9), and settling time (1, 3, 5 hours) for the lead removal efficiency in the water. The XRF analysis results showed GES contained calcium (Ca) 91.41% and Silicon (Si) 4.03% and GESM contained calcium (Ca) 91.41%, Silicon (Si) 4.03%, and Iron (Fe) 3.05%. TEM results confirmed the sizes of GES and GESM in the range of 1-20 nm. The batch test studies showed the best optimum conditions for the lead removal in the water of GES and GESM in dose, pH, and settling time were 10 grams, pH 9, 5 hours and 5 grams, pH 9, 3 hours, respectively. The competing ions (Na⁺ and Ca²⁺) study reported GESM had the higher % lead removal efficiency than GES at 90% and 60%, respectively. Therefore, this result can confirm that adding of metal oxide to ground egg shells helps to improve the lead removal efficiency in the water.

Keywords: nano material, ground egg shells, metal oxide, lead

Procedia PDF Downloads 135

Authors: H. V. Jayaprakash, P. V. Krupakara

Abstract:

This paper deals with the high corrosion resistance developed by the metal matrix composites when compared with that of matrix alloy by open circuit potential test. Matrix selected is ZA-27 and reinforcement selected is red mud particulates, which is a ceramic material. The composites are prepared using liquid melt metallurgy technique using vortex method. Preheated but uncoated red mud particulates are added to the melt. Metal matrix composites containing 2, 4 and 6 weight percentage of red mud are casted. Matrix was also casted in the same way for comparison. Specimen are fabricated according to ASTM standards. The corrodents used for the tests were 0.025, 0.05 and 0.1 molar sodium hydroxide solutions. They are subjected to Open Circuit Potential studies and weight loss corrosion tests. Corrosion rate was found to be decreased with increase in exposure time in both experiments. Effect of exposure time and presence of increased percentage of reinforcement red mud is discussed in detail.

Keywords: composites, vortex, particulates, red mud

Procedia PDF Downloads 451

Authors: N. Ghatwary, A. Ahmed, H. Jalab

Abstract:

In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

Procedia PDF Downloads 359

Authors: C. A. C. Castro, D. C. Urashima, E. P. Silva, P. M. L. Silva

Abstract:

Since 1920, the industry has almost completely changed the rivets production techniques for the manufacture of permanent welding join production of structures and manufacture of other products. The welding arc is the process more widely used in industries. This is accomplished by the heat of an electric arc which melts the base metal while the molten metal droplets are transferred through the arc to the welding pool, protected from the atmosphere by a gas curtain. The GMAW (Gas metal arc welding) process is influenced by variables such as: Current, polarity, welding speed, electrode, extension, position, moving direction; type of joint, welder's ability, among others. It is remarkable that the knowledge and control of these variables are essential for obtaining satisfactory quality welds, knowing that are interconnected so that changes in one of them requiring changes in one or more of the other to produce the desired results. The optimum values are affected by the type of base metal, the electrode composition, the welding position and the quality requirements. Thus, this paper proposes a new methodology, adding the variable vibration through a mechanism developed for GMAW welding, in order to improve the mechanical and metallurgical properties which does not affect the ability of the welder and enables repeatability of the welds made. For confirmation metallographic analysis and mechanical tests were made.

Keywords: vibration, joining, weldability, GMAW

Procedia PDF Downloads 425

Authors: Ali A. Aldosari

Abstract:

Change detection of Earth surface features is extremely important for better understanding of our environment in order to promote better decision making. Al-Jawf is remarkable for its abundant agricultural water where there is fertile agricultural land due largely to underground water. As result, this region has large areas of cultivation of dates, olives and fruits trees as well as other agricultural products such as Alfa Alfa and wheat. However this agricultural area was declined due to the reduction of government supports in the last decade. This reduction was not officially recorded or measured in this region at large scale or governorate level. Remote sensing data are primary sources extensively used for change detection in agriculture applications. This study is applied the technology of GIS and used the Normalized Difference Vegetation Index (NDVI) which can be used to measure and analyze the spatial and temporal changes in the agriculture areas in the Aljouf region.

Keywords: spatial analysis, geographical information system, change detection

Procedia PDF Downloads 404

Authors: Helmi Baazaoui, Mounir Zrigui

Abstract:

This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.

Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation

Procedia PDF Downloads 15

Authors: Rezki Akkouche

Abstract:

This work exposes metal tanks in general and floating roofs in particular by listing the codes and standards which study this kind of structure. Initial research discusses the types of tanks, how they are designed, and the disadvantages and advantages that each type has. Then, in-depth research was carried out carefully in order to popularize the floating roof tank and the principles of its design and operation while defining the different types of this kind of roof, how and what they are designed, naming the main installation accessories for these roofs and the dangers that a malfunction of these accessories would cause, also exposing the problems likely to be encountered on these roofs and the considerable and important advantages that floating roof tanks bring. A simplification of the two API 650 and Eurocode 3 regulations - Tanks part - has been made by explaining and mentioning the design rules and laws of this type of structure. Thus a comparison of the two regulations is accomplished by exemplifying this with a study of an actual project.

Keywords: tanks of metal, floating roof, performance, comparative analysis

Procedia PDF Downloads 129

Authors: Jeong Min Baik

Abstract:

We present that the electroluminescence (EL) properties and electrical output power of flexible N-face p-type GaN thin films can be tuned by strain-induced piezo-potential generated across the metal-semiconductor-metal structures. Under different staining conditions (convex and concave bending modes), the transport properties of the GaN films can be changed due to the spontaneous polarization of the films. The I-V characteristics with the bending modes show that the convex bending can increase the current across the films by the decrease in the barrier height at the metal-semiconductor contact, increasing the EL intensity of the P-N junction. At convex bending, it is also shown that the flexible p-type GaN films can generate an output voltage of up to 1.0 V, while at concave bending, 0.4 V. The change of the band bending with the crystal polarity of GaN films was investigated using high-resolution photoemission spectroscopy. This study has great significance on the practical applications of GaN in optoelectronic devices and nanogenerators under a working environment.

Keywords: GaN, flexible, laser lift-off, nanogenerator

Procedia PDF Downloads 421

Authors: Duc V. Nguyen

Abstract:

Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

Procedia PDF Downloads 171

Authors: Kolela J Nyembwe, Darlington C. Ashiegbu, Herman J. Potgieter

Abstract:

Over the past few decades, the demand for metals has increased significantly. This has led to a decrease and decline of high-grade ore over time and an increase in mineral complexity and matrix heterogeneity. In addition to that, there are rising concerns about greener processes and a sustainable environment. Due to these challenges, the mining and metal industry has been forced to develop new technologies that are able to economically process and recover metallic values from low-grade ores, materials having a metal content locked up in industrially processed residues (tailings and slag), and complex matrix mineral deposits. Several methods to address these issues have been developed, among which are ionic liquids (IL), heap leaching, and bioleaching. Recently, the gas phase extraction technique has been gaining interest because it eliminates many of the problems encountered in conventional mineral processing methods. The technique relies on the formation of volatile metal complexes, which can be removed from the residual solids by a carrier gas. The complexes can then be reduced using the appropriate method to obtain the metal and regenerate-recover the organic extractant. Laboratory work on the gas phase have been conducted for the extraction and recovery of aluminium (Al), iron (Fe), copper (Cu), chrome (Cr), nickel (Ni), lead (Pb), and vanadium V. In all cases the extraction revealed to depend of temperature and mineral surface area. The process technology appears very promising, offers the feasibility of recirculation, organic reagent regeneration, and has the potential to deliver on all promises of a “greener” process.

Keywords: gas-phase extraction, hydrometallurgy, low-grade ore, sustainable environment

Procedia PDF Downloads 136

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

Abstract:

Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

Procedia PDF Downloads 150

Authors: Bin Liu

Abstract:

Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

Procedia PDF Downloads 163

Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering　severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

Procedia PDF Downloads 557