Search results for: fault detection

Authors: Naime Boudemagh

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In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

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Authors: Soner Cubuk, Ozge Yilmaz, Ece Kok Yetimoglu, M. Vezir Kahraman

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In this work, a polymer based highly selective fluorescence sensor membrane was prepared by the photopolymerization technique for the determination Cd(II) ion. Sensor characteristics such as effects of pH, response time and foreign ions on the fluorescence intensity of the sensor were also studied. Under optimized conditions, the polymeric sensor shows a rapid, stable and linear response for 4.45x10-⁹ mol L-¹ - 4.45x10-⁸ mol L-¹ Cd(II) ion with the detection limit of 6.23x10-¹⁰ mol L-¹. In addition, sensor membrane was selective which is not affected by common foreign metal ions. The concentrations of the foreign ions such as Pb²+, Co²+, Ag+, Zn²+, Cu²+, Cr³+ are 1000-fold higher than Cd(II) ions. Moreover, the developed polymeric sensor was successfully applied to the determination of cadmium ions in food and water samples. This work was supported by Marmara University, Commission of Scientific Research Project.

Keywords: cadmium(II), fluorescence, photopolymerization, polymeric sensor

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Authors: Mohammad Mokhtari, Mehdi Masoodi, Parvaneh Faridi

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history of tsunami generating earthquakes along the Makran Subduction Zone provides evidence of the potential tsunami hazard for the whole coastal area. In comparison with other subduction zone in the world, the Makran region of southern Pakistan and southeastern Iran remains low seismicity. Also, it is one of the least studied area in the northwest of the Indian Ocean regarding tsunami studies. We present a review of studies dealing with the historical /and ongoing palaeotsunamis supported by IGCP of UNESCO in the Makran Subduction Zone. The historical tsunami presented here includes about nine tsunamis in the Makran Subduction Zone, of which over 7 tsunamis occur in the eastern Makran. Tsunami is not as common in the western Makran as in the eastern Makran, where a database of historical events exists. The historically well-documented event is related to the 1945 earthquake with a magnitude of 8.1moment magnitude and tsunami in the western and eastern Makran. There are no details as to whether a tsunami was generated by a seismic event before 1945 off western Makran. But several potentially large tsunamigenic events in the MSZ before 1945 occurred in 325 B.C., 1008, 1483, 1524, 1765, 1851, 1864, and 1897. Here we will present new findings from a historical point of view, immediately, we would like to emphasize that the area needs to be considered with higher research investigation. As mentioned above, a palaeotsunami (geological evidence) is now being planned, and here we will present the first phase result. From a risk point of view, the study shows as preliminary achievement within 20 minutes the wave reaches to Iranian as well Pakistan and Oman coastal zone with very much destructive tsunami waves capable of inundating destructive effect. It is important to note that all the coastal areas of all states surrounding the MSZ are being developed very rapidly, so any event would have a devastating effect on this region. Although several papers published about modelling, seismology, tsunami deposits in the last decades; as Makran is a forgotten subduction zone, more data such as the main crustal structure, fault location, and its related parameter are required.

Keywords: historical tsunami, Indian ocean, makran subduction zone, palaeotsunami

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Authors: Noshin Mehrabian, Mohammad Reza Abedi, Hassan Ali Zamani

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A highly selective poly(vinyl chloride)-based membrane sensor produced by using 1,2-Diaminopropane-N,N,N',N'-tetraacetic acid (DAPTA) as active material is described. The electrode displays Nernstian behavior over the concentration range 1.0×10⁻⁶ to 1.0×10⁻² M. The detection limit of the electrode is 7.2×10⁻⁷ M. The best performance was obtained with the membrane containing 30% polyvinyl chloride (PVC), 65% nitrobenzene (NB), 2% sodium tetra phenyl borate (Na TPB), 3% DAPTA. The potentiometric response of the proposed electrode is pH independent in the range of 2.5–‎‎9.1. ‎The proposed sensor displays a fast response time 'less than 10s'. The electrode shows a good selectivity for Eu (III) ion with respect to most common cations including alkali, alkaline earth, transition, and heavy metal ions. It was used as an indicator electrode in potentiometric ‎titration of 25 mL of a 1.0×10⁻⁴ M Eu (III) solution with a 1.0×10⁻² M EDTA solution.

Keywords: potentiometry, PVC membrane, sensor, ion-selective electrode

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Authors: Rohana Musa, Yuzman Yusoff, Chia Chieu Yin, Hanif Che Lah

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This paper presents the design and characterization of a low power Complementary Metal Oxide Semiconductor (CMOS) process sensor. The design is targeted for implementation using Silterra’s 180 nm CMOS process technology. The proposed process sensor employs a voltage threshold (V_th) extractor architecture for detection of variations in the fabrication process. The process sensor generates output voltages in the range of 401 mV (fast-fast corner) to 443 mV (slow-slow corner) at nominal condition. The power dissipation for this process sensor is 6.3 µW with a supply voltage of 1.8V with a silicon area of 190 µm X 60 µm. The preliminary result of this process sensor that was fabricated indicates a close resemblance between test and simulated results.

Keywords: CMOS process sensor, PVT sensor, threshold extractor circuit, Vth extractor circuit

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Authors: Lokeswara Rao P., Naga Venkata Rakesh N., V. Anantha Subramanian

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It is important to estimate, predict, and avoid the dynamic instability of high speed planing crafts. It is known that design parameters like relative location of center of gravity with respect to the dynamic lift centre and length to beam ratio of the craft have influence on the tendency to porpoise. This paper analyzes the hydrodynamic performance on the basis of the semi-empirical Savitsky method and also estimates the same by numerical simulations based on Reynolds Averaged Navier Stokes (RANS) equations using a commercial code namely, STAR- CCM+. The paper examines through the same numerical simulation considering dynamic equilibrium, the changing running trim, which results in porpoising. Some interesting results emerge from the study and this leads to early detection of the instability.

Keywords: CFD, planing hull, porpoising, Savitsky method

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Authors: M. Taibeche, L. Guerbous, M. Kechouane, R. Nedjar, T. Zergoug

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It is known that Y2O3 Material is the most important among the sesquioxides within the general class of refractory ceramics. Indeed, this compound has many applications such as sintering optical windows, components for rare-earth doped lasers as well as inorganic scintillators in the detection scintillation. In particular Eu2+ and Ce3+ are favored dopants in many the scintillators due to its allowed optical 5d-4f transition. In this work, we present new results concerning structural and electronic properties of Ce-doped Y2O3, investigated by density functional theory (DFT), using the Heyd–Scuseria–Ernzerhof (HSE) hybrid functional and DFT+U two approaches. When, we compared the results from the two methods we obtain a good agreement available experimental data. Furthermore, the effect of cerium on the material has also been studied and discussed in the same framework.

Keywords: DFT, vienne ab initio simulation packages, scintillators, Heyd–Scuseria–Ernzerhof (HSE) hybrid functional

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Authors: Ayman M. Mansour, Bilal Hawashin, Mohammed A. Mansour

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In this paper, we propose a cooperative learning mechanism in a multi-agent intelligent system. The basic idea is that intelligent agents are capable of collaborating with one another by sharing their knowledge. The agents will start collaboration by providing their knowledge rules to the other agents. This will allow the most important and insightful detection rules produced by the most experienced agent to bubble up for the benefit of the entire agent community. The updated rules will lead to improving the agents’ decision performance. To evaluate our approach, we designed a five–agent system and implemented it using JADE and FuzzyJess software packages. The agents will work with each other to make a decision about a suspicious medical case. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: intelligent, multi-agent system, cooperative, fuzzy, learning

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Authors: Sonu Gandhi, Neena Capalash, Prince Sharma, C. Raman Suri

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A sensitive chemiluminescence immunoassay (CIA) for heroin and its major metabolites is reported. The method is based on the competitive reaction of horseradish peroxidase (HRP)-labeled anti-MAM antibody and free drug in spiked urine samples. A hapten-protein conjugate was synthesized by using acidic derivative of monoacetyl morphine (MAM) coupled to carrier protein BSA and was used as an immunogen for the generation of anti-MAM (monoacetyl morphine) antibody. A high titer of antibody (1:64,0000) was obtained and the relative affinity constant (Kaff) of antibody was 3.1×107 l/mol. Under the optimal conditions, linear range and reactivity for heroin, mono acetyl morphine (MAM), morphine and codeine were 0.08, 0.09, 0.095 and 0.092 ng/mL respectively. The developed chemiluminescence inhibition assay could detect heroin and its metabolites in standard and urine samples up to 0.01 ng/ml.

Keywords: heroin, metabolites, chemiluminescence immunoassay, horse radish peroxidase

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Authors: Muhammad A. Khan, Waseem Shahzad

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Analysis of protein sequences is carried out for the purpose to discover their structural and ancestry relationship. Sequence similarity determines similar protein structures, similar function, and homology detection. Biological sequences composed of amino acid residues or nucleotides provide significant information through sequence alignment. In this paper, we present a new similarity/dissimilarity measure to sequence alignment based on the primary structure of a protein. The approach finds the distance between the two given sequences using the novel sequence alignment algorithm and a mathematical model. The algorithm runs at a time complexity of O(n²). A distance matrix is generated to construct a phylogenetic tree of different species. The new similarity/dissimilarity measure outperforms other existing methods.

Keywords: alignment, distance, homology, mathematical model, phylogenetic tree

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Authors: Rutusha Bhutada, Gaurav Chavan, Sarvesh Kasat, Varsha Mujumdar

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This software system will be an Augmented Reality application designed to maximize the doctor’s productivity by providing tools to assist in automating the patient recognition and updating patient’s records using face and voice recognition features, which would otherwise have to be performed manually. By maximizing the doctor’s work efficiency and production, the application will meet the doctor’s needs while remaining easy to understand and use. More specifically, this application is designed to allow a doctor to manage his productive time in handling the patient without losing eye-contact with him and communicate with a group of other doctors for consultation, for in-place treatments through video streaming, as a video study. The system also contains a relational database containing a list of doctor, patient and display techniques.

Keywords: augmented reality, hand-held devices, head-mounted devices, marker based systems, speech recognition, face detection

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Authors: O. S. Omorogiuwa, E. J. Omozusi

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The monitoring of spectrum usage and signal identification, using cognitive radio, is done to identify frequencies that are vacant for reuse. It has been established that ‘internet of things’ device uses secondary frequency which is free, thereby facing the challenge of interference from other users, where some primary frequencies are not being utilised. The design was done by analysing a specific frequency spectrum, checking if all the frequency stations that range from 87.5-108 MHz are presently being used in Benin City, Edo State, Nigeria. From the results, it was noticed that by using Software Defined Radio/Simulink, we were able to identify vacant frequencies in the range of frequency under consideration. Also, we were able to use the significance of energy detection threshold to reuse this vacant frequency spectrum, when the cognitive radio displays a zero output (that is decision H0), meaning that the channel is unoccupied. Hence, the analysis was able to find the spectrum hole and identify how it can be reused.

Keywords: spectrum, interference, telecommunication, cognitive radio, frequency

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Authors: Piyush Samant, Ravinder Agarwal

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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: Jesus Alfredo Ortega Granados, Pandiyan Thangarasu

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Antibiotic tetracycline presents as a micro-contaminant in fresh water, wastewater and soils, causing environmental and health problems. In this work, tetracycline (TC) has been employed as chemo-sensor for the recognition of Al³⁺ without interring other ions, and the results show that it enhances the fluorescence intensity for Al³⁺ and there is no interference from other coexisting cation ions (Cd²⁺, Ni²⁺, Co²⁺, Sr²⁺, Mg²⁺, Fe³⁺, K⁺, Sm³⁺, Ag⁺, Na⁺, Ba²⁺, Zn²⁺, and Mn²⁺). For the addition of Cu²⁺ to [TET-Al³⁺], it appears that the intensity of fluorescence has been quenched. Other combinations of metal ions in addition to TC do not change the fluorescence behavior. The stoichiometry determined by Job´s plot for the interaction of TC with Al³⁺ was found to be 1:1. Importantly, the detection of Al³⁺⁺ successfully employed in the real samples like living cells, and it was found that TC efficiently performs as a fluorescent probe for Al³⁺ ion in living systems, especially in Saccharomyces cerevisiae; this is confirmed by confocal laser scanning microscopy.

Keywords: chemo-sensor, recognition of Al³⁺ ion, Saccharomyces cerevisiae, tetracycline,

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Authors: Bi Yan-Qiang, Shang Yonghong, Lin Boying, Ji Xinyan, Li Xiyuan

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The heat-resistant material has important application in the aerospace field. The reliability of the connection between the heat-resisting material and the body determines the success or failure of the project. In this paper, lock-in infrared thermography non-destructive testing technology is used to detect the stability of the thermal-resistant structure. The phase relationship between the temperature and the heat flow is calculated by the numerical method, and the influence of the heating frequency and power is obtained. The correctness of the analysis is verified by the experimental method. Through the research, it can provide the basis for the parameter setting of heat flux including frequency and power, improve the efficiency of detection and the reliability of connection between the heat-resisting material and the body.

Keywords: infrared non-destructive, thermal insulation material, reliability, connection

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-of-the-art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking

Procedia PDF Downloads 393

Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

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Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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Authors: Hayrettin Eroglu, Adem Kara

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Recently there has been significant attention given to imaging of the biological tissues via microwave imaging techniques. In this study, a phantom for the test and calibration of Microwave imaging used in detecting unhealthy breast structure or tumors was produced by using sol gel method. The liquid and gel phantoms being used nowadays are not durable due to evaporation and their organic ingredients, hence a new design was proposed. This phantom was fabricated from materials that were widely available (water, salt, gelatin, and glycerol) and was easy to make. This phantom was aimed to be better from the ones already proposed in the literature in terms of its durability and stability. S Parameters of phantom was measured with 1-18 GHz Probe Kit and permittivity was calculated via Debye method in “85070” commercial software. One, three, and five-week measurements were taken for this phantom. Finally, it was verified that measurement results were very close to the real biological tissue measurement results.

Keywords: phantom, breast tissue, cancer, microwave imaging

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Authors: Agnė Mikalauskaitė, Renata Karpicz, Vitalijus Karabanovas, Arūnas Jagminas

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The use of biocompatible precursors for the synthesis and stabilization of fluorescent gold nanoclusters (NCs) with strong red photoluminescence creates an important link between natural sciences and nanotechnology. Herein, we report the cost-effective synthesis of Au nanoclusters by templating and reduction of chloroauric acid with the cheap amino acid food supplements. This synthesis under the optimized conditions leads to the formation of biocompatible Au NCs having good stability and intense red photoluminescence, peaked at 680 to 705 nm, with a quantum yield (QY) of ≈7% and the average lifetime of up to several µs. The composition and luminescent properties of the obtained NCs were compared with ones formed via well-known bovine serum albumin reduction approach. Our findings implied that synthesized Au NCs tend to accumulate in more tumorigenic breast cancer cells (line MDA-MB-213) and after dialysis can be prospective for bio imagining.

Keywords: gold nanoclusters, proteins, materials chemistry, red-photoluminescence, bioimaging

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: E. Tskitishvili, L. Jgenti, I. Eliava, T. Tskitishvili, N. Bagathuria, M. Gigolashvili

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The nematode fauna of 20 agrocenosis (soil, tuber of potato, green parts of plant, roots) was studied in four regions in South Georgia (Akhaltsikhe, Aspindza, Akhalkalaki, Ninotsminda). In all, there were registered 173 forms of free-living and Phyto-parasitic nematodes, including 132 forms which were specified according to their species. A few exemplars of potato root nematode (Ditylenchus destructor) were identified in soil samples taken in Ninotsminda, Akhalkalaki and Aspinda stations, i.e. invasion is weak. Based on our data, potato Ditylenchus was not found in any of the researched tubers, while based on the data of previous years the most of tubers were infested. The cysts of 'golden nematodes' were not found during inspection of material for detection of Globoderosis

Keywords: ditylenchus, monitoring, nematoda, potato

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Authors: Fahad Alamoudi, Yaser Miaji

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The growing popularity of swimming pools and other activities in the water for sport, fitness, therapy or just enjoyable relaxation have led to the increased use of swimming pools and the establishment of a variety of specific-use pools such as spa pools, water slides, and more recently, hydrotherapy and wave pools. In this research, a few simple equipment is used for test, detect and alert for detection of water cleanness and pollution. YSI Photometer Systems, TDSTestr High model, Rio 12HF and Electrode A1. The researchers used electrolysis as a method of separating bonded elements and compounds by passing an electric current through them. The results which use 41 experiments show the higher the salt concentration, the more efficient the electrode and the smaller the gap between the plates, the lower the electrode voltage. Furthermore, it is proved that the larger the surface area, the lower the cell voltage and the higher current used the more chlorine produced.

Keywords: photometer, electrode, electrolysis, swimming pool chlorination

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Authors: Rodrigo S. Piera, Jailson Sales Ara´ujo, Gabriela B. Lemos, Matthew B. Weiss, John B. DeBrota, Gabriel H. Aguilar, Jacques L. Pienaar

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The Born rule was historically viewed as an independent axiom of quantum mechanics until Gleason derived it in 1957 by assuming the Hilbert space structure of quantum measurements [1]. In subsequent decades there have been diverse proposals to derive the Born rule starting from even more basic assumptions [2]. In this work, we demonstrate that a simple reinforcement-learning algorithm, having no pre-programmed assumptions about quantum theory, will nevertheless converge to a behaviour pattern that accords with the Born rule, when tasked with predicting the output of a quantum optical implementation of a symmetric informationally-complete measurement (SIC). Our findings support a hypothesis due to QBism (the subjective Bayesian approach to quantum theory), which states that the Born rule can be thought of as a normative rule for making decisions in a quantum world [3].

Keywords: quantum Bayesianism, quantum theory, quantum information, quantum measurement

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Authors: Percy Galvez, Anatoly Petukhin, Paul Somerville, Ken Miyakoshi, Kojiro Irikura, Daniel Peter

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Physics-based dynamic rupture modelling is necessary for estimating parameters such as rupture velocity and slip rate function that are important for ground motion simulation, but poorly resolved by observations, e.g. by seismic source inversion. In order to generate a large number of physically self-consistent rupture models, whose rupture process is consistent with the spatio-temporal heterogeneity of past earthquakes, we use multicycle simulations under the heterogeneous rate-and-state (RS) friction law for a 45deg dip-slip fault. We performed a parametrization study by fully dynamic rupture modeling, and then, a set of spontaneous source models was generated in a large magnitude range (Mw > 7.0). In order to validate rupture models, we compare the source scaling relations vs. seismic moment Mo for the modeled rupture area S, as well as average slip Dave and the slip asperity area Sa, with similar scaling relations from the source inversions. Ground motions were also computed from our models. Their peak ground velocities (PGV) agree well with the GMPE values. We obtained good agreement of the permanent surface offset values with empirical relations. From the heterogeneous rupture models, we analyzed parameters, which are critical for ground motion simulations, i.e. distributions of slip, slip rate, rupture initiation points, rupture velocities, and source time functions. We studied cross-correlations between them and with the friction weakening distance Dc value, the only initial heterogeneity parameter in our modeling. The main findings are: (1) high slip-rate areas coincide with or are located on an outer edge of the large slip areas, (2) ruptures have a tendency to initiate in small Dc areas, and (3) high slip-rate areas correlate with areas of small Dc, large rupture velocity and short rise-time.

Keywords: earthquake dynamics, strong ground motion prediction, seismic engineering, source characterization

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Authors: Alexander Kelíšek, Denisa Janasová, Veronika Mitašová

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Weak signals using is often associated with early warning. It is possible to find a link between early warning, respectively early problems detection and risk management. The idea of early warning is very important in the context of crisis management because of the risk prevention possibility. Weak signals are likened to risk symptoms. Nowadays, their usefulness as a tool of proactive problems solving is emphasized. Based on it, it is possible to use weak signals not only in strategic planning, project management, or early warning system, but also as a subsidiary element in risk management. The main question is how to effectively integrate weak signals into risk management. The main aim of the paper is to point out the possibilities of weak signals using in small and medium enterprises risk management.

Keywords: early warning system, weak signals, risk management, small and medium enterprises (SMEs)

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Authors: Turquesa Topper

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The reflection focuses on recording and explaining the considerations, conceptualizations and methodological approach with which from the University, that is to say, from the academic field, the study of Trends is addressed with the intention of training professionals in the area, an area that requires disciplinary boundaries and builds a polyphonic vision. When referring to the objective of our Laboratory the detection of aesthetic trends of consumption, we find ourselves in the requirement to define our object: trends, aesthetic trends of consumption, more specifically. The pages cover a conception of trends from a theoretical framework that incorporates contributions from linguistics, semiotics, sociology, cultural studies and project disciplines, in order to consolidate a polyphonic look. The text investigates in the pre-discursive aspect of the trends, in the circulation of the notion of style and in the dynamics of affirmation - denial as the constitutive dynamics of Fashion linked to any process of innovation. From such inquiry, it is presented to Fashion as a system that operates directly on the construction of socio-individual identities unfolding through the liquefaction of signs in trends.

Keywords: fashion, methodology, narrative, trends

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Authors: Alireza Mohadesi, Ashraf Salmanipour

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A chemically modified glassy carbon electrode for electrocatalytic determination of sulfide was developed using multiwalled carbon nanotubes (MWCNTs) covalently immobilized with 2,6-dichlorophenolindophenol (DPIP). The immobilization of 2,6-dichlorophenolindophenol with MWCNTs was performed with a new synthetic strategy and characterized by UV–visible absorption spectroscopy, Fourier transform infrared spectroscopy and cyclic voltammetry. The cyclic voltammetric response of DPIP grafted onto MWCNTs indicated that it promotes the low potential, sensitive and stable determination of sulfide. The dependence of response currents on the concentration of sulfide was examined and was linear in the range of 10 - 1100 µM. The detection limit of sulfide was 5 µM and RSD for 100 and 500 µM sulfides were 1.8 and 1.3 %. Many interfering species had little or no effect on the determination of sulfide. The procedure was applied to determination of sulfide in waters samples.

Keywords: functionalized carbon nanotubes, sulfide, biological samples, 2, 6-dichlorophenolindophenol

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Authors: Sahar Shahsavaripour Ghazanfarpour

Abstract:

As our daily life depends on quality of built services by systems and using devices in our environment; so education and model of software′s quality will be so important. By daily growth in software′s systems and using them so much, progressing process and requirements′ evaluation in primary level of progress especially architecture level in software get more important. Modern driver architecture changes an in dependent model of a level into some specific models that their purpose is reducing number of software changes into an executive model. Process of designing software engineering is mid-automated. The needed quality attribute in designing architecture and quality attribute in representation are in architecture models. The main problem is the relationship between needs, and elements in some aspect with implicit models and input sources in process. It’s because there is no detection ability. The MART profile is use to describe real-time properties and perform plat form modeling.

Keywords: MDA, DW, OMG, UML, AKB, software architecture, ontology, evaluation

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