Search results for: Anomaly Detection Model

Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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Authors: Md. Afroz Ansari

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The Bengal basin is a spectacular example of a peripheral foreland basin formed by the convergence of the Indian plate beneath the Eurasian and Burmese plates. The basin is embraced on three sides; north, west and east by different fault-controlled tectonic features whereas released in the south where the rivers are drained into the Bay of Bengal. The Bengal basin in the eastern part of the Indian subcontinent constitutes the largest fluvio-deltaic to shallow marine sedimentary basin in the world today. This continental basin coupled with the offshore Bengal Fan under the Bay of Bengal forms the biggest sediment dispersal system. The continental basin is continuously receiving the sediments by the two major rivers Ganga and Brahmaputra (known as Jamuna in Bengal), and Meghna (emerging from the point of conflux of the Ganga and Brahmaputra) and large number of rain-fed, small tributaries originating from the eastern Indian Shield. The drained sediments are ultimately delivered into the Bengal fan. The significance of the present study is to delineate the variations in thicknesses of the sediments, different crustal structures, and the mantle lithosphere throughout the onshore-offshore Bengal basin. In the present study, the different crustal/geological units and the shallower mantle lithosphere were delineated by analyzing the Bouguer Gravity Anomaly (BGA) data along two long traverses South-North (running from Bengal fan cutting across the transition offshore-onshore of the Bengal basin and intersecting the Main Frontal Thrust of India-Himalaya collision zone in Sikkim-Bhutan Himalaya) and West-East (running from the Peninsular Indian Shield across the Bengal basin to the Chittagong–Tripura Fold Belt). The BGA map was derived from the analysis of topex data after incorporating Bouguer correction and all terrain corrections. The anomaly map was compared with the available ground gravity data in the western Bengal basin and the sub-continents of India for consistency of the data used. Initially, the anisotropy associated with the thicknesses of the different crustal units, crustal interfaces and moho boundary was estimated through spectral analysis of the gravity data with varying window size over the study area. The 2D density sections along the traverses were finalized after a number of iterations with the acceptable root mean square (RMS) errors. The estimated thicknesses of the different crustal units and dips of the Moho boundary along both the profiles are consistent with the earlier results. Further the results were encouraged by examining the earthquake database and focal mechanism solutions for better understanding the geodynamics. The earthquake data were taken from the catalogue of US Geological Survey, and the focal mechanism solutions were compiled from the Harvard Centroid Moment Tensor Catalogue. The concentrations of seismic events at different depth levels are not uncommon. The occurrences of earthquakes may be due to stress accumulation as a result of resistance from three sides.

Keywords: anisotropy, interfaces, seismicity, spectrum analysis

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Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

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Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network protocols, node-disjoint paths

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Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

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Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

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Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

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Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

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Authors: Martin Goubej, Tomas Popule, Alois Krejci

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This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.

Keywords: mechanical friction, LuGre model, friction identification, motion control

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Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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Authors: Shafqat Ullah Khan, Ammar Nasir

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Using planar antenna array (PAA) in radars, Broadcasting, satellite antennas, and sonar for the detection of targets, Helps provide instant beam pattern control. High flexibility and Adaptability are achieved by multiple beam steering by using a Planar array and are particularly needed in real-life Sanrio’s where the need arises for several high-directivity beams. Faulty sensors in planar arrays generate asymmetry, which leads to service degradation, radiation pattern distortion, and increased levels of sidelobe. The POA, a nature-inspired optimization algorithm, accurately determines faulty sensors within an array, enhancing the reliability and performance of planar array antennas through extensive simulations and experiments. The analysis was done for different types of faults in 7 x 7 and 8 x 8 planar arrays in MATLAB.

Keywords: Planar antenna array, , Pelican optimisation Algorithm, , Faculty sensor, Antenna arrays

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: Marco Lopes, Pedro D. Gaspar, Maria P. Simões

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This paper reviews the different concepts that have been investigated concerning the mechanization of fruit thinning as well as multiple working principles and solutions that have been developed for feature extraction of horticultural products, both in the field and industrial environments. The research should be committed towards selective methods, which inevitably need to incorporate some kinds of sensor technology. Computer vision often comes out as an obvious solution for unstructured detection problems, although leaves despite the chosen point of view frequently occlude fruits. Further research on non-traditional sensors that are capable of object differentiation is needed. Ultrasonic and Near Infrared (NIR) technologies have been investigated for applications related to horticultural produce and show a potential to satisfy this need while simultaneously providing spatial information as time of flight sensors. Light Detection and Ranging (LIDAR) technology also shows a huge potential but it implies much greater costs and the related equipment is usually much larger, making it less suitable for portable devices, which may serve a purpose on smaller unstructured orchards. Portable devices may serve a purpose on these types of orchards. In what concerns sensor methods, on-tree fruit detection, major challenge is to overcome the problem of fruits’ occlusion by leaves and branches. Hence, nontraditional sensors capable of providing some type of differentiation should be investigated.

Keywords: fruit thinning, horticultural field, portable devices, sensor technologies

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Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

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The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Ragu Sasikumar, Palraj Ranganathan, Shen-Ming Chen, Syang-Peng Rwei

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A highly sensitive, and selective α-Lipoic acid (ALA) sensor based on a functionalized multi-walled carbon nanotubes-polyindole/Ti2O3 (f-MWCNTs-PIN/Ti2O3) nanocomposite modified glassy carbon electrode (GCE) was developed. The fabricated f-MWCNTs-PIN/Ti2O3/GCE displayed an enhanced voltammetric response for oxidation towards ALA relative to that of a f-MWCNTs/GCE, f-MWCNTs-PIN/GCE, Ti2O3/GCE, and a bare GCE. Under optimum conditions, the f-MWCNTs-PIN/Ti2O3/GCE showed a wide linear range at ALA concentrations of 0.39-115.8 µM. The limit of detection of 12 nM and sensitivity of about 6.39 µA µM-1cm-2. The developed sensor showed anti-interference, reproducibility, good repeatability, and operational stability. Applied possibility of the sensor has been confirmed in vegetable samples.

Keywords: f-MWCNT, polyindole, Ti2O3, Alzheimer’s diseases, ALA sensor

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Authors: Monisha Elumalai, Joana Guerreiro, Joana Carvalho, Marta Prado

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DNA biosensors popularity has been increasing over the past few years. Traditional analytical techniques tend to require complex steps and expensive equipment however DNA biosensors have the advantage of getting simple, fast and economic. Additionally, the combination of DNA biosensors with nanomaterials offers the opportunity to improve the selectivity, sensitivity and the overall performance of the devices. DNA biosensors are based on oligonucleotides as sensing elements. These oligonucleotides are highly specific to complementary DNA sequences resulting in the hybridization of the strands. DNA biosensors are not only an advantage in the clinical field but also applicable in numerous research areas such as food analysis or environmental control. Zebra Mussels (ZM), Dreissena polymorpha are invasive species responsible for enormous negative impacts on the environment and ecosystems. Generally, the detection of ZM is made when the observation of adult or macroscopic larvae's is made however at this stage is too late to avoid the harmful effects. Therefore, there is a need to develop an analytical tool for the early detection of ZM. Here, we present a portable plasmonic biosensor for the detection of environmental DNA (eDNA) released to the environment from this invasive species. The plasmonic DNA biosensor combines gold nanoparticles, as transducer elements, due to their great optical properties and high sensitivity. The detection strategy is based on the immobilization of a short base pair DNA sequence on the nanoparticles surface followed by specific hybridization in the presence of a complementary target DNA. The hybridization events are tracked by the optical response provided by the nanospheres and their surrounding environment. The identification of the DNA sequences (synthetic target and probes) to detect Zebra mussel were designed by using Geneious software in order to maximize the specificity. Moreover, to increase the optical response enzyme amplification of DNA might be used. The gold nanospheres were synthesized and characterized by UV-visible spectrophotometry and transmission electron microscopy (TEM). The obtained nanospheres present the maximum localized surface plasmon resonance (LSPR) peak position are found to be around 519 nm and a diameter of 17nm. The DNA probes modified with a sulfur group at one end of the sequence were then loaded on the gold nanospheres at different ionic strengths and DNA probe concentrations. The optimal DNA probe loading will be selected based on the stability of the optical signal followed by the hybridization study. Hybridization process leads to either nanoparticle dispersion or aggregation based on the presence or absence of the target DNA. Finally, this detection system will be integrated into an optical sensing platform. Considering that the developed device will be used in the field, it should fulfill the inexpensive and portability requirements. The sensing devices based on specific DNA detection holds great potential and can be exploited for sensing applications in-loco.

Keywords: ZM DNA, DNA probes, nicking enzyme, gold nanoparticles

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Authors: Changtong Wang, Lingyun Wei

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The combination of auctions and supply chains is of great significance in improving the supply chain management system and enhancing the efficiency of economic and social operations. To address the gap in research on supply chain strategies under the auction mechanism, a model is developed for the 1-N auction model in a complete information environment, and it is concluded that the two-part contract auction model for retailers in this model can achieve supply chain coordination. The model is validated by substituting the model into the scenario of a fresh-cut flower industry flower auction in exchange for arithmetic examples to further prove the validity of the conclusions.

Keywords: auction mechanism, supply chain coordination strategy, fresh cut flowers industry, supply chain management

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Authors: B. T. Chew, S. N. Kazi, A. Amiri

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This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC.

Keywords: hot and humid, lecture halls, neutral temperature, adaptive thermal comfort model

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Authors: Golnaz Shahtahmassebi, Jose Maria Sarabia

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In this talk, we introduce a new class of conjugate prior distributions obtained from conditional specification methodology. We illustrate the application of such distribution in Bayesian change point detection in Poisson processes. We obtain the posterior distribution of model parameters using a general bivariate distribution with gamma conditionals. Simulation from the posterior is readily implemented using a Gibbs sampling algorithm. The Gibbs sampling is implemented even when using conditional densities that are incompatible or only compatible with an improper joint density. The application of such methods will be demonstrated using examples of simulated and real data.

Keywords: change point, bayesian inference, Gibbs sampler, conditional specification, gamma conditional distributions

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Authors: Yongbai Yin

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We propose a non-expanding model of the universe based on the non-changing fine-structure constant and Einstein’s space-time relativity theory. This model consistently explains the Redshift, the ‘expanding’ and the age of the universe without introducing the singularity and inflationary issues that occurred in the ‘Big Bang’ model. It also offers an interpretation of the unexpected ‘accelerated expanding’ universe and the origin of the mystery of ‘Dark matter’. It predicts that the universe began with a ‘cold and peaceful’ rather than ‘extremely hot’ stage which is used to explain consistently the microwave background radiation. It predicts mathematically that galaxies could end in blackholes because blackholes should have the same environmental conditions as those at the beginning of the universe in this model, paving the way to offer a model of the cyclic universes without violating the first law of thermodynamics.

Keywords: big bang, accelerated expanding universe, dark matters, blackholes, microwave background radiation, universe modelling

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Authors: Naoum Abderrahmane, Boumehed Meriem, Alshaqaqi Belal

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Background subtraction algorithm is a larger used technique for detecting moving objects in video surveillance to extract the foreground objects from a reference background image. There are many challenges to test a good background subtraction algorithm, like changes in illumination, dynamic background such as swinging leaves, rain, snow, and the changes in the background, for example, moving and stopping of vehicles. In this paper, we propose an efficient and accurate background subtraction method for moving object detection in video surveillance. The main idea is to use a developed fast-independent component analysis (ICA) algorithm to separate background, noise, and foreground masks from an image sequence in practical environments. The fast-ICA algorithm is adapted and adjusted with a matrix calculation and searching for an optimum non-quadratic function to be faster and more robust. Moreover, in order to estimate the de-mixing matrix and the denoising de-mixing matrix parameters, we propose to convert all images to YCrCb color space, where the luma component Y (brightness of the color) gives suitable results. The proposed technique has been verified on the publicly available datasets CD net 2012 and CD net 2014, and experimental results show that our algorithm can detect competently and accurately moving objects in challenging conditions compared to other methods in the literature in terms of quantitative and qualitative evaluations with real-time frame rate.

Keywords: background subtraction, moving object detection, fast-ICA, de-mixing matrix

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Authors: Andreea Campu, Ilinica Muresan, Simona Cainap, Simion Astilean, Monica Focsan

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Acute myocardial infarction (AMI) is the most severe cardiovascular disease, which has threatened human lives for decades, thus a continuous interest is directed towards the detection of cardiac biomarkers such as cardiac troponin I (cTnI) in order to predict risk and, implicitly, fulfill the early diagnosis requirements in AMI settings. Microfluidics is a major technology involved in the development of efficient sensing devices with real-time fast responses and on-site applicability. Microfluidic devices have gathered a lot of attention recently due to their advantageous features such as high sensitivity and specificity, miniaturization and portability, ease-of-use, low-cost, facile fabrication, and reduced sample manipulation. The integration of gold nanoparticles into the structure of microfluidic sensors has led to the development of highly effective detection systems, considering the unique properties of the metallic nanostructures, specifically the Localized Surface Plasmon Resonance (LSPR), which makes them highly sensitive to their microenvironment. In this scientific context, herein, we propose the implementation of a novel detection device, which successfully combines the efficiency of gold bipyramids (AuBPs) as signal transducers and thermal generators with the sample-driven advantages of the microfluidic channels into a miniaturized, portable, low-cost, specific, and sensitive test for the dual LSPR-thermographic cTnI detection. Specifically, AuBPs with longitudinal LSPR response at 830 nm were chemically synthesized using the seed-mediated growth approach and characterized in terms of optical and morphological properties. Further, the colloidal AuBPs were deposited onto pre-treated silanized glass substrates thus, a uniform nanoparticle coverage of the substrate was obtained and confirmed by extinction measurements showing a 43 nm blue-shift of the LSPR response as a consequence of the refractive index change. The as-obtained plasmonic substrate was then integrated into a microfluidic “Y”-shaped polydimethylsiloxane (PDMS) channel, fabricated using a Laser Cutter system. Both plasmonic and microfluidic elements were plasma treated in order to achieve a permanent bond. The as-developed microfluidic plasmonic chip was further coupled to an automated syringe pump system. The proposed biosensing protocol implicates the successive injection inside the microfluidic channel as follows: p-aminothiophenol and glutaraldehyde, to achieve a covalent bond between the metallic surface and cTnI antibody, anti-cTnI, as a recognition element, and target cTnI biomarker. The successful functionalization and capture of cTnI was monitored by LSPR detection thus, after each step, a red-shift of the optical response was recorded. Furthermore, as an innovative detection technique, thermal determinations were made after each injection by exposing the microfluidic plasmonic chip to 785 nm laser excitation, considering that the AuBPs exhibit high light-to-heat conversion performances. By the analysis of the thermographic images, thermal curves were obtained, showing a decrease in the thermal efficiency after the anti-cTnI-cTnI reaction was realized. Thus, we developed a microfluidic plasmonic chip able to operate as both LSPR and thermal sensor for the detection of the cardiac troponin I biomarker, leading thus to the progress of diagnostic devices.

Keywords: gold nanobipyramids, microfluidic device, localized surface plasmon resonance detection, thermographic detection

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Authors: Xiang Zhang, David Rey, S. Travis Waller

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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: parameter calibration, sequential quadratic programming, stochastic user equilibrium, traffic assignment, transportation planning

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Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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Authors: Seung-Yeon Kim

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The Ising model, consisting magnetic spins, is the simplest system showing phase transitions and critical phenomena at finite temperatures. The Ising model has played a central role in our understanding of phase transitions and critical phenomena. Also, the Ising model explains the gas-liquid phase transitions accurately. However, the Ising model in a nonzero magnetic field has been one of the most intriguing and outstanding unsolved problems. We study analytically the partition function zeros in the complex magnetic-field plane and the Yang-Lee edge singularity of the infinite-range Ising model in an external magnetic field. In addition, we compare the Yang-Lee edge singularity of the infinite-range Ising model with that of the square-lattice Ising model in an external magnetic field.

Keywords: Ising ferromagnet, magnetic field, partition function zeros, Yang-Lee edge singularity

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Authors: Hiroshi Nakayama, Yuji Ito

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Synthetic cannabinoids have attracted much public attention recently in Japan. 1-pentyl-3-(1-naphthoyl)-indole (JWH-018), 1-pentyl-2-methyl-3-(1-naphthoyl) indole (JWH-015), 1-(5-fluoropentyl)-3- (1-(2,2,3,3- tetramethylcyclopropyl)) indole (XLR-11) and 1-methyl-3- (1-admantyl) indole (JWH-018 adamantyl analog) are known as synthetic cannabinoids and are also considered dangerous illegal drugs in Japan. It has become necessary to develop sensitive and useful methods for detection of synthetic cannabinoids. We produced two monoclonal antibodies (MAb) against synthetic cannabinoids, named NT1 (IgG1) and NT2 (IgG1), using Hybridoma technology. The cross-reactivity of these produced MAbs was evaluated using a competitive enzyme-linked immunosorbent assay (ELISA). In the results, we found both of these antibodies recognize many kinds of synthetic cannabinoids analog. However, neither of these antibodies recognizes naphtoic acid, 1-methyl-indole and indole known as a raw material of synthetic cannabinoid. Thus, the MAbs produced in this study could be a useful tool for the detection of synthetic cannabinoids.

Keywords: ELISA, monoclonal antibody, sensor, synthetic cannabinoid

Procedia PDF Downloads 355

Authors: Xinglu Nie, Feifei Tang, Chuntao Wei, Zhimin Ruan, Qianhong Zhu

Abstract:

Current method of manual-style inspection can not fully meet the requirement of the urban rail transit security in China. In this paper, an intelligent inspection method using unmanned aerial vehicle (UAV) is utilized. A series of orthophoto of rail transit monitored area was collected by UAV, image correction and registration were operated among multi-phase images, then the change detection was used to detect the changes, judging the engineering activities and human activities that may become potential threats to the security of urban rail. Not only qualitative judgment, but also quantitative judgment of changes in the security control area can be provided by this method, which improves the objectives and efficiency of the patrol results. The No.6 line of Chongqing Municipality was taken as an example to verify the validation of this method.

Keywords: rail transit, control of protected areas, intelligent inspection, UAV, change detection

Procedia PDF Downloads 367

Authors: Parvin Samadi Pakchin, Reza Saber, Hossein Ghanbari, Yadollah Omidi

Abstract:

Ovarian cancer is one of the leading cause of mortality among the gynecological malignancies, and it remains the one of the most prevalent cancer in females worldwide. Tumor markers are biochemical molecules in blood or tissues which can indicates cancers occurrence in the human body. So, the sensitive and specific detection of cancer markers typically recruited for diagnosing and evaluating cancers. Recently extensive research efforts are underway to achieve a simple, inexpensive and accurate device for detection of cancer biomarkers. Compared with conventional immunoassay techniques, electrochemical immunosensors are of great interest, because they are specific, simple, inexpensive, easy to handling and miniaturization. Moreover, in the past decade nanotechnology has played a crucial role in the development of biosensors. In this study, a signal-off electrochemical immunosensor for the detection of CA125 antigen has been developed using chitosan-gold nanoparticles (CS-AuNP) and multi-wall carbon nanotubes (MWCNT) composites. Toluidine blue (TB) is used as redox probe which is immobilized on the electrode surface. CS-AuNP is synthesized by a simple one step method that HAuCl4 is reduced by NH2 groups of chitosan. The CS-AuNP-MWCNT modified electrode has shown excellent electrochemical performance compared with bare Au electrode. MWCNTs and AuNPs increased electrochemical conductivity and accelerate electrons transfer between solution and electrode surface while excessive amine groups on chitosan lead to the effective loading of the biological material (CA125 antibody) and TB on the electrode surface. The electrochemical, immobilization and sensing properties CS-AuNP-MWCNT-TB modified electrodes are characterized by cyclic voltammetry, electrochemical impedance spectroscopy, differential pulse voltammetry and square wave voltammetry with Fe(CN)63−/4−as an electrochemical redox indicator.

Keywords: signal-off electrochemical biosensor, CA125, ovarian cancer, chitosan-gold nanoparticles

Procedia PDF Downloads 286

Authors: K. Khanafer

Abstract:

The aim of this investigation was to validate the fluid-structure interaction (FSI) model of type B aortic dissection with our experimental results from a bench-top-model. Another objective was to study the relationship between the size of a septectomy that increases the outflow of the false lumen and its effect on the values of the differential of pressure between true lumen and false lumen. FSI analysis based on Galerkin’s formulation was used in this investigation to study flow pattern and hemodynamics within a flexible type B aortic dissection model using boundary conditions from our experimental data. The numerical results of our model were verified against the experimental data for various tear size and location. Thus, CFD tools have a potential role in evaluating different scenarios and aortic dissection configurations.

Keywords: aortic dissection, fluid-structure interaction, in vitro model, numerical

Procedia PDF Downloads 269

Authors: Muhammad SAFDAR, Mehmet Ozaslan, Musarrat Abbas Khan

Abstract:

Babesiosis is a haemoparasitic disease due to the multiplication of protozoan’s parasite, Babesia ovis in the red blood cells of the host, and contributes numerous economical losses, including sheep and goat ruminants. The early identification and successful treatment of Babesia Ovis spp. belong to the key steps of control and health management of livestock resources. The objective of this study was to construct a polymerase chain reaction (PCR) based method for the detection of Babesia spp. in small ruminants and to determine the risk factors involved in the spreading of babesiosis infections. A total of 100 blood samples were collected from 50 sheep and 50 goats along with different areas of Muzaffargarh, Pakistan, from randomly selected herds. Data on the characteristics of sheep and goats were collected through questionnaires. Of 100 blood samples examined, 18 were positive for Babesia ovis upon microscopic studies, whereas 11 were positive for the presence of Babesia spp. by PCR assay. For the recognition of parasitic DNA, a set of 500bp oligonucleotide was designed by PCR amplification with sequence 18S rRNA gene for B. ovis. The prevalence of babesiosis in small ruminant’s sheep and goat detected by PCR was significantly higher in female animals (28%) than male herds (08%). PCR analysis of the reference samples showed that the detection limit of the PCR assay was 0.01%. Taken together, all data indicated that this PCR assay was a simple, fast, specific detection method for Babesia ovis species in small ruminants compared to other available methods.

Keywords: Babesia ovis, PCR amplification, 18S rRNA, sheep and goat

Procedia PDF Downloads 125

Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith

Abstract:

Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.

Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution

Procedia PDF Downloads 90

Authors: Morteza Raki, Abolghasem Zabihollah, Omid Askari

Abstract:

Cantilever beam is a simplified sample of a lot of mechanical components used in a wide range of applications, including many industries such as gas turbine blade. Due to the nature of the operating conditions, beams are subject to variety of damages especially crack propagates. Crack propagation may lead to catastrophic failure during operation. Therefore, online detection of crack presence and its propagation is very important and may reduce possible significant cost of the whole system failure. This paper aims to investigate the effect of cracks presence and crack propagation on one end fixed beam`s vibration. A finite element model will be developed for the blade in which the modal response of the structure with and without crack will be studied. 

Keywords: blade, crack propagation, health monitoring, modal analysis

Procedia PDF Downloads 342