Search results for: metal ion detection

Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

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Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: FSDWT, key frame extraction, shot detection, singular value decomposition

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Beata Pospiech

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Separation of metal ions from aqueous solutions is important as well as difficult process in hydrometallurgical technology. This process is necessary for obtaining of clean metals. Solvent extraction and membrane processes are well known as separation methods. Recently, ionic liquids (ILs) are very often applied and studied as extractants and carriers of metal ions from aqueous solutions due to their good extractability properties for various metals. This work discusses a method to separate copper(II) and iron(III) from hydrochloric acid solutions by solvent extraction and transport across polymer inclusion membranes (PIM) with the selected ionic liquids as extractants/ion carriers. Cyphos IL 101 (trihexyl(tetradecyl)phosphonium chloride), Cyphos IL 104 (trihexyl(tetradecyl)phosphonium bis(2,4,4 trimethylpentyl)phosphi-nate), trioctylmethylammonium thiosalicylate [A336][TS] and trihexyl(tetradecyl)phosphonium thiosalicylate [PR4][TS] were used for the investigations. Effect of different parameters such as hydrochloric acid concentration in aqueous phase on iron(III) and copper(II) extraction has been investigated. Cellulose triacetate membranes with the selected ionic liquids as carriers have been prepared and applied for transport of iron(IIII) and copper(II) from hydrochloric acid solutions.

Keywords: copper, iron, ionic liquids, solvent extraction

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Authors: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents results from the AF3 project “Advanced Forest Fire Fighting” focused on Unmanned Aircraft Systems (UAS)-based 3D surveillance and 3D area mapping using high-resolution photogrammetric methods from multispectral imaging, also taking advantage of the 3D scanning techniques from the SCAN4RECO project. We also present a proprietary embedded sensor system used for the detection of fire ignitions in the forest using near-infrared based scanner with weight and form factors allowing it to be easily deployed on standard commercial micro-UAVs, such as DJI Inspire or Mavic. Results from real-life pilot trials in Greece, Spain, and Israel demonstrated added-value in the use of UAS for precise and reliable detection of forest fires, as well as high-resolution 3D aerial modeling for accurate quantification of human resources and equipment required for firefighting.

Keywords: forest wildfires, surveillance, fuel volume estimation, firefighting, ignition detectors, 3D modelling, UAV

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Authors: Morsy Ahmed Morsy Ismail

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In this paper, the structure of a coherent homodyne receiver for the Binary Phase Shift Keying (BPSK) Optical Code Division Multiple Access (OCDMA) network is introduced based on the Multi-Length Weighted Modified Prime Code (ML-WMPC) for multimedia applications. The Bit Error Rate (BER) of this homodyne detection is evaluated as a function of the number of active users and the signal to noise ratio for different code lengths according to the multimedia application such as audio, voice, and video. Besides, the Mach-Zehnder interferometer is used as an external phase modulator in homodyne detection. Furthermore, the Multiple Access Interference (MAI) and the receiver noise in a shot-noise limited regime are taken into consideration in the BER calculations.

Keywords: OCDMA networks, bit error rate, multiple access interference, binary phase-shift keying, multimedia

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Authors: Waziralilah N. Fathiah, A. Aminudin, U. Alyaa Hashim, T. Vikneshvaran D. Shakirah Shukor

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This paper presents the experimental analysis conducted on a structure borne noise in a rectangular enclosure prototype made by joining of sheet aluminum metal and plywood. The study is significant as many did not realized the annoyance caused by structural borne-noise. In this study, modal analysis is carried out to seek the structure’s behaviour in order to identify the characteristics of enclosure in frequency domain ranging from 0 Hz to 200 Hz. Here, numbers of modes are identified and the characteristic of mode shape is categorized. Modal experiment is used to diagnose the structural behaviour while microphone is used to diagnose the sound. Spectral testing is performed on the enclosure. It is acoustically excited using shaker and as it vibrates, the vibrational and noise responses sensed by tri-axis accelerometer and microphone sensors are recorded respectively. Experimental works is performed on each node lies on the gridded surface of the enclosure. Both experimental measurement is carried out simultaneously. The modal experimental results of the modal modes are validated by simulation performed using MSC Nastran software. In pursuance of reducing the structure borne-noise, mitigation method is used whereby the stiffener plates are perpendicularly placed on the sheet aluminum metal. By using this method, reduction in structure borne-noise is successfully made at the end of the study.

Keywords: enclosure, modal analysis, sound analysis, structure borne-noise

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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: M. T. Z. Butt, T. Ahmad, N. A. Siddiqui

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Commercially SA 516 Grade 70 is frequently used for the manufacturing of pressure vessels, boilers and storage tanks etc. in fabrication industry. Heat input is the major parameter during welding that may bring significant changes in the microstructure as well as the mechanical properties. Different welding technique has different heat input rate per unit surface area. Materials with large thickness are dealt with different combination of welding techniques to achieve required mechanical properties. In the present research two schemes: Scheme 1: SMAW (Shielded Metal Arc Welding) & GTAW (Gas Tungsten Arc Welding) and Scheme 2: SMAW & SAW (Submerged Arc Welding) of hybrid welding techniques have been studied. The purpose of these schemes was to study hybrid welding effect on the microstructure and mechanical properties of the weldment, heat affected zone and base metal area. It is significant to note that the thickness of base plate was 12 mm, also welding conditions and parameters were set according to ASME Section IX. It was observed that two different hybrid welding techniques performed on two different plates demonstrated that the mechanical properties of both schemes are more or less similar. It means that the heat input, welding techniques and varying welding operating conditions & temperatures did not make any detrimental effect on the mechanical properties. Hence, the hybrid welding techniques mentioned in the present study are favorable to implicate for the industry using the plate thickness around 12 mm thick.

Keywords: grade 70, GTAW, hybrid welding, SAW, SMAW

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Authors: Prateek Goyal, Archini Paruthi, Superb K. Misra

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Contamination of water resources has been a major concern, which has drawn attention to the need to develop new material models for treatment of effluents. Existing conventional waste water treatment methods remain ineffective sometimes and uneconomical in terms of remediating contaminants like heavy metal ions (mercury, arsenic, lead, cadmium and chromium); organic matter (dyes, chlorinated solvents) and high salt concentration, which makes water unfit for consumption. We believe that nanotechnology based strategy, where we use nanoparticles as a tool to remediate a class of pollutants would prove to be effective due to its property of high surface area to volume ratio, higher selectivity, sensitivity and affinity. In recent years, scientific advancement has been made to study the application of photocatalytic (ZnO, TiO2 etc.) nanomaterials and magnetic nanomaterials in remediating contaminants (like heavy metals and organic dyes) from water/wastewater. Our study focuses on the synthesis and monitoring remediation efficiency of ZnO, Fe3O4 and Fe3O4 coated ZnO nanoparticulate system for the removal of heavy metals and dyes simultaneously. Multitude of ZnO nanostructures (spheres, rods and flowers) using multiple routes (microwave & hydrothermal approach) offers a wide range of light active photo catalytic property. The phase purity, morphology, size distribution, zeta potential, surface area and porosity in addition to the magnetic susceptibility of the particles were characterized by XRD, TEM, CPS, DLS, BET and VSM measurements respectively. Further on, the introduction of crystalline defects into ZnO nanostructures can also assist in light activation for improved dye degradation. Band gap of a material and its absorbance is a concrete indicator for photocatalytic activity of the material. Due to high surface area, high porosity and affinity towards metal ions and availability of active surface sites, iron oxide nanoparticles show promising application in adsorption of heavy metal ions. An additional advantage of having magnetic based nanocomposite is, it offers magnetic field responsive separation and recovery of the catalyst. Therefore, we believe that ZnO linked Fe3O4 nanosystem would be efficient and reusable. Improved photocatalytic efficiency in addition to adsorption for environmental remediation has been a long standing challenge, and the nano-composite system offers the best of features which the two individual metal oxides provide for nanoremediation.

Keywords: adsorption, nanocomposite, nanoremediation, photocatalysis

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

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Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: lidar, segmentation, clustering, tracking

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Authors: Yavuz Demir, Mucip Genisel, Hulya Turk, Turgay Sisman, Serkan Erdal

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In this study, the changes in contents of inorganic elements in the aquatic plant (Potamogeton natans) as a reflection of the impact of chemical nature pollution in a cement factory region (CFR) was evaluated. For this purpose, P, S, K, Ca, Fe, Cl, Mn, Cu, Zn, Mo, Ni, Si, Al, and Cd concentrations were measured in the aquatic plant (Potamogeton natans) taken from a CFR. As a control, aquatic plant was collected at a distance of 2000 m from the outer zone of the cement factory. Inorganic element compositions were measured by energy dispersive X-ray fluorescence spectrometry (EDXRF). Three aquatic plant exhibited similar changes in contents of microelements and macroelements in their leaves. P, S, K, Cl, Ca, and Mo contents in plant grown in the CFR were reduced significantly compared to control plant, whereas their contents of Al, Mn, Fe, Ni, Cu, Zn and Cd were very high. According to these findings, it is possible that aquatic plant (Potamogeton natans) inhabiting in the vicinity of cement factory sustains the deficiency of important essential elements like P, S, K, Ca, and Mo and greatly accumulate heavy metals like Al, Mn, Fe, Ni, Cu, Zn, and Cd. In addition, results of water analysis showed that heavy metal content such as Cu, Pb, Zn, Co, and Al of water taken from CFR was remarkably high than that of outer zone of CFR. These findings with relation to changes in inorganic composition can contribute to be elucidated of effect mechanism on growth and development of aquatic plant (Potamogeton natans) of pollution resulted from cement factories.

Keywords: aquatic plant, cement factory, heavy metal pollution, inorganic element, Potamogeton natans

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Authors: B. Siva Kumar Reddy, B. Lakshmi

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Cognitive Radio is a turning out technology that empowers viable usage of the spectrum. Energy Detector-based Sensing is the most broadly utilized spectrum sensing strategy. Besides, it is a lot of generic as receivers does not like any information on the primary user's signals, channel data, of even the sort of modulation. This paper puts forth the execution of energy detection sensing for AM (Amplitude Modulated) signal at 710 KHz, FM (Frequency Modulated) signal at 103.45 MHz (local station frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz. The OFDM/OFDMA based WiMAX physical layer with convolutional channel coding is actualized utilizing USRP N210 (Universal Software Radio Peripheral) and GNU Radio based Software Defined Radio (SDR). Test outcomes demonstrated the BER (Bit Error Rate) augmentation with channel noise and BER execution is dissected for different Eb/N0 (the energy per bit to noise power spectral density ratio) values.

Keywords: BER, Cognitive Radio, GNU Radio, OFDM, SDR, WiMAX

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Authors: J. Sharib, D. N. A. Tugi, M. T. Ishak, M. I. A. Adziz

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The main purpose of this research paper conducted was to study the penetration of ⁷Be onto the soil surface for two different seasons in different areas of agricultural activity. The study was conducted during the dry and wet seasons from January to May 2019 in the Sembrong catchment area. The Sembrong Catchment Area is located in the district of Kluang, Johor in the South of Peninsular Malaysia and was selected based on the small size of the catchment and surrounded by various agricultural activities. A total of twenty (20) core soil samples to a depth of 10 cm each were taken using a metal corer made of metal. All these samples were brought to the Radiochemistry and Environment Group (RAS), Nuclear Malaysia, Block 23, Bangi, Malaysia, to enable the preparation, drying and analysis work to be carried out. Furthermore, all samples were oven dried at 45 – 60 ºC so that the dry weight became constant and gently disaggregated. Lastly, dried samples were milled and sieved at 2 mm before being packed into a well-type container and ready for ⁷Be analysis. The result of the analysis shows that the penetration of ⁷Be into the soil surface decreases by an exponential decay. The distribution of profiles to the interior of the soil surface or ho values ranged from 1.56 to 3.62 kg m⁻² and from 2.59 to 4.17 kg m⁻² for both dry and wet seasons. Consequently, the dry season has given a lower ho value when compared to the wet season. In conclusion, ⁷Be is a very suitable tracer to be used in determining the penetration onto the soil surface or ho values for the two different seasons.

Keywords: depth penetration, dry season, wet season, sembrong catchment, well type container

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Antoine Karam, Lotfi Khiari, Bruno Breton, Alfred Jaouich

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Anthropogenic sources of zinc (Zn), including industrial emissions and effluents, Zn–rich fertilizer materials and pesticides containing Zn, can contribute to increasing the concentration of soluble Zn at levels toxic to plants in acid sandy soils. The application of municipal sewage sludge or biosolids (MBS) which contain metal immobilizing agents on coarse-textured soils could improve the metal sorption capacity of the low-CEC soils. The purpose of this experiment was to evaluate the sorption of Zn in surface samples (0-15 cm) of six Quebec (Canada) soils amended with MBS (pH 6.9) from Val d’Or (Quebec, Canada). Soil samples amended with increasing amounts (0 to 20%) of MBS were equilibrated with various amounts of Zn as ZnCl2 in 0.01 M CaCl2 for 48 hours at room temperature. Sorbed Zn was calculated from the difference between the initial and final Zn concentration in solution. Zn sorption data conformed to the linear form of Freundlich equation. The amount of sorbed Zn increased considerably with increasing MBS rate. Analysis of variance revealed a highly significant effect (p ≤ 0.001) of soil texture and MBS rate on the amount of sorbed Zn. The average values of the Zn-sorption capacity of MBS-amended coarse-textured soils were lower than those of MBS-amended fine textured soils. The two sandy soils (86-99% sand) amended with MBS retained 2- to 5-fold Zn than those without MBS (control). Significant Pearson correlation coefficients between the Zn sorption isotherm parameter, i.e. the Freundlich sorption isotherm (KF), and commonly measured physical and chemical entities were obtained. Among all the soil properties measured, soil pH gave the best significant correlation coefficients (p ≤ 0.001) for soils receiving 0, 5 and 10% MBS. Furthermore, KF values were positively correlated with soil clay content, exchangeable basic cations (Ca, Mg or K), CEC and clay content to CEC ratio. From these results, it can be concluded that (i) municipal biosolids provide sorption sites that have a strong affinity for Zn, (ii) both soil texture, especially clay content, and soil pH are the main factors controlling anthropogenic Zn sorption in the municipal biosolids-amended soils, and (iii) the effect of municipal biosolids on Zn sorption will be more pronounced for a sandy soil than for a clay soil.

Keywords: metal, recycling, sewage sludge, trace element

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Authors: Helga Heylen

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With dogs saving wildlife in New Zealand since 1890 and governments in Africa, Australia and Canada trusting them to give the best results, Conservation Dogs Ireland want to introduce more detection dogs to protect Europe's native wildlife. Conservation detection dogs are fast, portable and endlessly trainable. They are a cost-effective, highly sensitive and non-invasive way to detect protected and invasive species and wildlife disease. Conservation dogs find targets up to 40 times faster than any other method. They give results instantly, with near-perfect accuracy. They can search for multiple targets simultaneously, with no reduction in efficacy The European Red List indicates the decline in biodiversity has been most rapid in the past 50 years, and the risk of extinction never higher. Just two examples of major threats dogs are trained to tackle are: (I)Japanese Knotweed (Fallopia Japonica), not only a serious threat to ecosystems, crops, structures like bridges and roads - it can wipe out the entire value of a house. The property industry and homeowners are only just waking up to the full extent of the nightmare. When those working in construction on the roads move topsoil with a trace of Japanese Knotweed, it suffices to start a new colony. Japanese Knotweed grows up to 7cm a day. It can stay dormant and resprout after 20 years. In the UK, the cost of removing Japanese Knotweed from the London Olympic site in 2012 was around £70m (€83m). UK banks already no longer lend on a house that has Japanese Knotweed on-site. Legally, landowners are now obliged to excavate Japanese Knotweed and have it removed to a landfill. More and more, we see Japanese Knotweed grow where a new house has been constructed, and topsoil has been brought in. Conservation dogs are trained to detect small fragments of any part of the plant on sites and in topsoil. (II)Zebra mussels (Dreissena Polymorpha) are a threat to many waterways in the world. They colonize rivers, canals, docks, lakes, reservoirs, water pipes and cooling systems. They live up to 3 years and will release up to one million eggs each year. Zebra mussels attach to surfaces like rocks, anchors, boat hulls, intake pipes and boat engines. They cause changes in nutrient cycles, reduction of plankton and increased plant growth around lake edges, leading to the decline of Europe's native mussel and fish populations. There is no solution, only costly measures to keep it at bay. With many interconnected networks of waterways, they have spread uncontrollably. Conservation detection dogs detect the Zebra mussel from its early larvae stage, which is still invisible to the human eye. Detection dogs are more thorough and cost-effective than any other conservation method, and will greatly complement and speed up the work of biologists, surveyors, developers, ecologists and researchers.

Keywords: native biodiversity, conservation detection dogs, invasive species, Japanese Knotweed, zebra mussel

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Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: building envelope, machine learning, perforated metal, multi-factor optimization, façade

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Authors: Hyunki Kang, Hi Won Jeong

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The gas turbine operates for a long period of time under harsh, cyclic conditions of high temperature and pressure, where high turbine inlet temperature (TIT) can range from 1273 to 1873K. Therefore, Ni-base superalloys such as IN738, IN939, Rene 45, Rene 71, Rene 80, Mar M 247, CM 247, and CMSX-4 with excellent mechanical properties and resistance to creep, corrosion and oxidation at high temperatures are indeed used. Among the alloying additions for these alloys, aluminum (Al) and titanium (Ti) form gamma prime and enhance the high-temperature properties. However, when crack-damaged high-temperature turbine components such as blade and vane are repaired by fusion welding, they cause cracks. For example, when arc welding is applied to certain superalloys that contain Al and Ti with more than 3 wt.% and T3.5 wt%, respectively, such as IN738, IN939, Rene 80, Mar M 247, and CM 247, aging cracks occur. Therefore, repair technologies using diffusion brazing, which has less heat input into the base material, are being developed. Analysis of microstructural evolution of the brazed joints with a base metal of IN 939 Ni-base superalloy using brazing different filler metals was also carried out using X-ray diffraction, OEM, SEM-EDS, and EPMA. Stress rupture and high-temperature tensile strength properties were also measured to analyze the effects of different brazing heat cycles. The boron amount in the diffusion-affected zone (DAZ) was decreased towards the base metal and the formation of borides at grain boundaries was detected through EPMA.

Keywords: gas turbine, diffusion brazing, superalloy, gas turbine repair

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Sunil P. Lonkar, Vishnu V. Pillai, Saeed Alhassan

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Design and development of highly efficient, inexpensive, and long-term stable earth-abundant electrocatalysts hold tremendous promise for hydrogen evolution reaction (HER) in water electrolysis. The 2D transition metal dichalcogenides, especially molybdenum disulfide attracted a great deal of interests due to its high electrocatalytic activity. However, due to its poor electrical conductivity and limited exposed active sites, the performance of these catalysts is limited. In this context, a facile and scalable synthesis method for fabrication nanostructured electrocatalysts composed 3D graphene porous aerogels supported with MoS₂ and WS₂ is highly desired. Here we developed a highly active and stable electrocatalyst catalyst for the HER by growing it into a 3D porous architecture on conducting graphene. The resulting nanohybrids were thoroughly investigated by means of several characterization techniques to understand structure and properties. Moreover, the HER performance of these 3D catalysts is expected to greatly improve in compared to other, well-known catalysts which mainly benefits from the improved electrical conductivity of the by graphene and porous structures of the support. This technologically scalable process can afford efficient electrocatalysts for hydrogen evolution reactions (HER) and hydrodesulfurization catalysts for sulfur-rich petroleum fuels. Owing to the lower cost and higher performance, the resulting materials holds high potential for various energy and catalysis applications. In typical hydrothermal method, sonicated GO aqueous dispersion (5 mg mL⁻¹) was mixed with ammonium tetrathiomolybdate (ATTM) and tungsten molybdate was treated in a sealed Teflon autoclave at 200 ◦C for 4h. After cooling, a black solid macroporous hydrogel was recovered washed under running de-ionized water to remove any by products and metal ions. The obtained hydrogels were then freeze-dried for 24 h and was further subjected to thermal annealing driven crystallization at 600 ◦C for 2h to ensure complete thermal reduction of RGO into graphene and formation of highly crystalline MoS₂ and WoS₂ phases. The resulting 3D nanohybrids were characterized to understand the structure and properties. The SEM-EDS clearly reveals the formation of highly porous material with a uniform distribution of MoS₂ and WS₂ phases. In conclusion, a novice strategy for fabrication of 3D nanostructured MoS₂-WS₂/graphene is presented. The characterizations revealed that the in-situ formed promoters uniformly dispersed on to few layered MoS₂¬-WS₂ nanosheets that are well-supported on graphene surface. The resulting 3D hybrids hold high promise as potential electrocatalyst and hydrodesulfurization catalyst.

Keywords: electrocatalysts, graphene, transition metal chalcogenide, 3D assembly

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Authors: Xun Li, Haojie Wang

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Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

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Authors: Lei Qi, Rongxin Yan, Lichen Sun

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With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.

Keywords: acoustic sensor array, spacecraft, damage assessment, leakage location

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Authors: F. Z. Tighilt, N. Belhaneche-Bensemra, S. Belhousse, S. Sam, K. Lasmi, N. Gabouze

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Recently, the gold nanoparticles (Au NPs) became an active multidisciplinary research topic. First, Au thin films fabricated by alkylthiol-functionalized Au NPs were found to have vapor sensitive conductivities, they were hence widely investigated as electrical chemiresistors for sensing different vapor analytes and even organic molecules in aqueous solutions. Second, Au thin films were demonstrated to have speciallocalized surface plasmon resonances (LSPR), so that highly ordered 2D Au superlattices showed strong collective LSPR bands due to the near-field coupling of adjacent nanoparticles and were employed to detect biomolecular binding. Particularly when alkylthiol ligands were replaced by thiol-terminated polymers, the resulting polymer-modified Au NPs could be readily assembled into 2D nanostructures on solid substrates. Monolayers of polystyrene-coated Au NPs showed typical dipolar near-field interparticle plasmon coupling of LSPR. Such polymer-modified Au nanoparticle films have an advantage that the polymer thickness can be feasibly controlled by changing the polymer molecular weight. In this article, the effect of tin-doped indium oxide (ITO) coatings on the plasmonic properties of ITO interfaces modified with gold nanostructures (Au NSs) is investigated. The interest in developing ITO overlayers is multiple. The presence of a con-ducting ITO overlayer creates a LSPR-active interface, which can serve simultaneously as a working electrode in an electro-chemical setup. The surface of ITO/ Au NPs contains hydroxyl groups that can be used to link functional groups to the interface. Here the covalent linking of nickel /Au NSs/ITO hybrid LSPR platforms will be presented.

Keywords: conducting polymer, metal nanoparticles (NPs), LSPR, poly (3-(pyrrolyl)–carboxylic acid), polypyrrole

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Authors: I. M. B. Omiogbemi, D. S. Yawas, I. M. Dagwa, F. G. Okibe

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This work present the effects of some gas metal arc welding parameters on the corrosion behavior of austenitic stainless steel, exposed to 0.5M sodium hydroxide at ambient temperatures (298K) using conventional weight loss determination, together with surface morphology evaluation by scanning electron microscopy and the application of factorial design of experiment to determine welding conditions which enhance the integrity of the welded stainless steel. The welding variables evaluated include speed, voltage and current. Different samples of the welded stainless steels were immersed in the corrosion environment for 8, 16, 24, 32 and 40 days and weight loss determined. From the results, it was found that increase in welding current and speed at constant voltage gave the optimum performance of the austenitic stainless steel in the environment. At a of speed 40cm/min, 110Amp current and voltage of 230 volt the welded stainless steel showed only a 0.0015mg loss in weight after 40 days. Pit-like openings were observed on the surface of the metals indicating corrosion but were minimal at the optimum conditions. It was concluded from the research that relatively high welding speed and current at a constant voltage gives a good welded austenitic stainless steel with better integrity.

Keywords: welding, current, speed, austenitic stainless steel, sodium hydroxide

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Authors: Faisal Alshammari, Abdulmajid Addali, Mosab Alrashed, Taihiret Alhashan

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The application of acoustic emission techniques is gaining popularity, as it can monitor the condition of gears and bearings and detect early symptoms of a defect in the form of pitting, wear, and flaking of surfaces. Early detection of these defects is essential as it helps to avoid major failures and the associated catastrophic consequences. Signal processing techniques are required for early defect detection – in this article, a time domain technique called the Energy Index (EI) is used. This article presents an investigation into the Energy Index’s effectiveness to detect early-stage defect initiation and deterioration, and compares it with the common r.m.s. index, Kurtosis, and the Kolmogorov-Smirnov statistical test. It is concluded that EI is a more effective technique for monitoring defect initiation and development than other statistical parameters.

Keywords: acoustic emission, signal processing, kurtosis, Kolmogorov-Smirnov test

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Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

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Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

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Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

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Authors: Igor B. Sivaev

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Design of molecular machines is an extraordinary growing and very important area of research that it was recognized by awarding Sauvage, Stoddart and Feringa the Nobel Prize in Chemistry in 2016 'for the design and synthesis of molecular machines'. Based on the type of motion being performed, molecular machines can be divided into two main types: molecular motors and molecular switches. Molecular switches are molecules or supramolecular complexes having bistability, i.e., the ability to exist in two or more stable forms, among which may be reversible transitions under external influence (heating, lighting, changing the medium acidity, the action of chemicals, exposure to magnetic or electric field). Molecular switches are the main structural element of any molecular electronics devices. Therefore, the design and the study of molecules and supramolecular systems capable of performing mechanical movement is an important and urgent problem of modern chemistry. There is growing interest in molecular switches and other devices of molecular electronics based on transition metal complexes; therefore choice of suitable stable organometallic unit is of great importance. An example of such unit is bis(dicarbollide) complexes of transition metals [3,3’-M(1,2-C₂B₉H₁₁)₂]ⁿ⁻. The control on the ligand rotation in such complexes can be reached by introducing substituents which could provide stabilization of certain rotamers due to specific interactions between the ligands, on the one hand, and which can participate as Lewis bases in complex formation with external metals resulting in a change in the rotation angle of the ligands, on the other hand. A series of isomeric methyl sulfide derivatives of cobalt bis(dicarbollide) complexes containing methyl sulfide substituents at boron atoms in different positions of the pentagonal face of the dicarbollide ligands [8,8’-(MeS)₂-3,3’-Co(1,2-C₂B₉H₁₀)₂]⁻, rac-[4,4’-(MeS)₂-3,3’-Co(1,2-C₂B₉H₁₀)₂]⁻ and meso-[4,7’-(MeS)₂-3,3’-Co(1,2-C₂B₉H₁₀)₂]⁻ were synthesized by the reaction of CoCl₂ with the corresponding methyl sulfide carborane derivatives [10-MeS-7,8-C₂B₉H₁₁)₂]⁻ and [10-MeS-7,8-C₂B₉H₁₁)₂]⁻. In the case of asymmetrically substituted cobalt bis(dicarbollide) complexes the corresponding rac- and meso-isomers were successfully separated by column chromatography as the tetrabutylammonium salts. The compounds obtained were studied by the methods of ¹H, ¹³C, and ¹¹B NMR spectroscopy, single crystal X-ray diffraction, cyclic voltammetry, controlled potential coulometry and quantum chemical calculations. It was found that in the solid state, the transoid- and gauche-conformations of the 8,8’- and 4,4’-isomers are stabilized by four intramolecular CH···S(Me)B hydrogen bonds each one (2.683-2.712 Å and 2.709-2.752 Å, respectively), whereas gauche-conformation of the 4,7’-isomer is stabilized by two intramolecular CH···S hydrogen bonds (2.699-2.711 Å). The existence of the intramolecular CH·S(Me)B hydrogen bonding in solutions was supported by the 1H NMR spectroscopy. These data are in a good agreement with results of the quantum chemical calculations. The corresponding iron and nickel complexes were synthesized as well. The reaction of the methyl sulfide derivatives of cobalt bis(dicarbollide) with various labile transition metal complexes results in rupture of intramolecular hydrogen bonds and complexation of the methyl sulfide groups with external metal. This results in stabilization of other rotational conformation of cobalt bis(dicarbollide) and can be used in design of molecular switches. This work was supported by the Russian Science Foundation (16-13-10331).

Keywords: molecular switches, NMR spectroscopy, single crystal X-ray diffraction, transition metal bis(dicarbollide) complexes, quantum chemical calculations

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

Procedia PDF Downloads 295

Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

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Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

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