Search results for: lane marking filter

Authors: Syahira Ibrahim, Herlina Abdul Rahim

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The amylose content is an essential element in determining the texture and taste of rice grains. This paper evaluates the use of VIS-SWNIRS in estimating the amylose content for seven varieties of rice grains available in the Malaysian market. Each type consists of 30 samples and all the samples are scanned using the spectroscopy to obtain a range of values between 680-1000nm. The Savitzky-Golay (SG) smoothing filter is applied to each sample’s data before the Principal Component Regression (PCR) technique is used to examine the data and produce a single value for each sample. This value is then compared with reference values obtained from the standard iodine colorimetric test in terms of its coefficient of determination, R2. Results show that this technique produced low R2 values of less than 0.50. In order to improve the result, the range should include a wavelength range of 1100-2500nm and the number of samples processed should also be increased.

Keywords: amylose content, diffuse reflectance, Malaysia rice grain, principal component regression (PCR), Visible and Shortwave near-infrared spectroscopy (VIS-SWNIRS)

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Authors: Martins Onyekwelu Onuorah, Jnr Dahiru Usman

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Introduction: In the realm of public health, the threat posed by Monkeypox continues to elicit concern, prompting rigorous studies to understand its dynamics and devise effective containment strategies. Particularly significant is its recurrence in variable populations, such as the observed outbreak in Nigeria in 2022. In light of this, our study undertakes a meticulous analysis, employing a data-driven approach to explore, validate, and propose optimized intervention strategies tailored to the distinct dynamics of Monkeypox within varying demographic structures. Utilizing a deterministic mathematical model, we delved into the intricate dynamics of Monkeypox, with a particular focus on a variable population context. Our qualitative analysis provided insights into the disease-free equilibrium, revealing its stability when R0 is less than one and discounting the possibility of backward bifurcation, as substantiated by the presence of a single stable endemic equilibrium. The model was rigorously validated using real-time data from the Nigerian 2022 recorded cases for Epi weeks 1 – 52. Transitioning from qualitative to quantitative, we augmented our deterministic model with optimal control, introducing three time-dependent interventions to scrutinize their efficacy and influence on the epidemic's trajectory. Numerical simulations unveiled a pronounced impact of the interventions, offering a data-supported blueprint for informed decision-making in containing the disease. A comprehensive cost-effectiveness analysis employing the Infection Averted Ratio (IAR), Average Cost-Effectiveness Ratio (ACER), and Incremental Cost-Effectiveness Ratio (ICER) facilitated a balanced evaluation of the interventions’ economic and health impacts. In essence, our study epitomizes a holistic approach to understanding and mitigating Monkeypox, intertwining rigorous mathematical modeling, empirical validation, and economic evaluation. The insights derived not only bolster our comprehension of Monkeypox's intricate dynamics but also unveil optimized, cost-effective interventions. This integration of methodologies and findings underscores a pivotal stride towards aligning public health imperatives with economic sustainability, marking a significant contribution to global efforts in combating infectious diseases.

Keywords: monkeypox, equilibrium states, stability, bifurcation, optimal control, cost-effectiveness

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Authors: Chapman Eze Nnadozie

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Relational databases constitute a very vital tool for the effective management and administration of both personal and organizational data. Data access ranges from a single user database management software to a more complex distributed server system. This paper intends to appraise the use a programming language extension like structured query language (SQL) to establish links to a relational database (Microsoft Access 2013) using Visual C++ 9 programming language environment. The methodology used involves the creation of tables to form a database using Microsoft Access 2013, which is Object Linking and Embedding (OLE) database compliant. The SQL command is used to query the tables in the database for easy extraction of expected records inside the visual C++ environment. The findings of this paper reveal that records can easily be accessed and manipulated to filter exactly what the user wants, such as retrieval of records with specified criteria, updating of records, and deletion of part or the whole records in a table.

Keywords: data access, database, database management system, OLE, programming language, records, relational database, software, SQL, table

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Authors: Myung Ho Lee, Hee Seung Lim, Young Jae Maeng, Chang Hoon Lee

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This study presents an automatic sequential extraction device for Pu and Am isotopes in radioactive waste samples from the nuclear power plant with anion exchange resin and TRU resin. After radionuclides were leached from the radioactive waste samples with concentrated HCl and HNO₃, the sample was allowed to evaporate to dryness after filtering the leaching solution with 0.45 micron filter. The Pu isotopes were separated in HNO₃ medium with anion exchange resin. For leaching solution passed through the anion exchange column, the Am isotopes were sequentially separated with TRU resin. Automatic sequential extraction device built-in software information of separation for Pu and Am isotopes was developed. The purified Pu and Am isotopes were measured by alpha spectrometer, respectively, after the micro-precipitation of neodymium. The data of Pu and Am isotopes in radioactive waste with an automatic sequential extraction device developed in this study were validated with the ICP-MS system.

Keywords: automatic sequential extraction device, Pu isotopes, Am isotopes, alpha spectrometer, radioactive waste samples, ICP-MS system

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Authors: Robin Root

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A fundamental premise of medical anthropology is that clinical phenomena are simultaneously cultural, political, and economic: none more so than the linked acronyms HIV/AIDS. For the medical researcher, HIV/AIDS signals an epidemiological pandemic and a pathophysiology. For persons diagnosed with an HIV-related condition, the acronym often conjures dread, too often marking and marginalizing the afflicted irretrievably. Critical medical anthropology is uniquely equipped to theorize the linkages that bind individual and social wellbeing to global structural and culture-specific phenomena. This paper reports findings from an anthropological study of HIV/AIDS in Swaziland, site of the highest HIV prevalence in the world. The project, initiated in 2005, has documented experiences of HIV/AIDS, religiosity, and treatment and care as well as drought and famine. Drawing on interviews with Swazi religious and traditional leaders about their experiences of leadership amidst worsening economic conditions, environmental degradation, and an ongoing global health crisis, the paper provides uncommon insights for global health practitioners whose singular paradigm for designing and delivering interventions is biomedically-based. In contrast, this paper details the role of local leaders in mediating extreme social suffering and resilience in ways that medical science cannot model but which radically impact how sickness is experienced and health services are delivered and accessed. Two concepts help to organize the paper’s argument. First, a ‘moral economy of language’ is central to showing up the implicit ‘technologies of knowledge’ that inhere in scientific and religious discourses of HIV/AIDS; people draw upon these discourses strategically to navigate highly vulnerable conditions. Second, Paulo Freire’s ethnographic focus on a culture’s 'dangerous words' opens up for examination how ‘sex’ is dangerous for religion and ‘god’ is dangerous for science. The paper interrogates hegemonic and ‘lived’ discourses, both biomedical and religious, and contributes to an important literature on the moral economies of health, a framework of explication and, importantly, action appropriate to a wide-range of contemporary global health phenomena. The paper concludes by asserting that it is imperative that global health planners reflect upon and ‘check’ their hegemonic policy platforms by, one, collaborating with local authoritative agents of ‘what sickness means and how it is best treated,’ and, two, taking account of the structural barriers to achieving good health.

Keywords: Africa, biomedicine, HIV/AIDS, qualitative research , religion

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Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

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Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

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Authors: Lottie Lane

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It is habitually assumed and stated that the World Bank should engage and comply with international human rights standards. However, the basis for holding the Bank to such standards is unclear. Most advocates of the idea invoke aspects of international law to argue that the Bank has existing obligations to act in compliance with human rights standards. The Bank itself, however, does not appear to accept such arguments, despite having endorsed the importance of human rights for a considerable length of time. A substantial challenge is that under the current international human rights law framework, the World Bank is considered a non-state actor, and as such, has no direct human rights obligations. In the absence of clear legal duties for the Bank, it is necessary to look at the tools available beyond the international human rights framework to encourage the Bank to comply with human rights standards. This article critically examines several bases for arguing that the Bank should comply and engage with human rights through its policies and practices. Drawing on the Bank’s own ‘good governance’ approach as well as the United Nations’ ‘human rights-based-approach’ to development, a new basis is suggested. First, the relationship between the World Bank and human rights is examined. Three perspectives are considered: (1) the legal position – what the status of the World Bank is under international human rights law, and whether it can be said to have existing legal human rights obligations; (2) the Bank’s own official position – how the Bank envisages its relationship with and role in the protection of human rights; and (3) the relationship between the Bank’s policies and practices and human rights (including how its attitudes are reflected in its policies and how the Bank’s operations impact human rights enjoyment in practice). Here, the article focuses on two examples – the (revised) 2016 Environmental and Social Safeguard Policies and the 2012 case-study regarding Gambella, Ethiopia. Both examples are widely considered missed opportunities for the Bank to actively engage with human rights. The analysis shows that however much pressure is placed on the Bank to improve its human rights footprint, it is extremely reluctant to do so explicitly, and the legal bases available are insufficient for requiring concrete, ex ante action by the Bank. Instead, the Bank’s own ‘good governance’ approach to development – which it has been advocating since the 1990s – can be relied upon. ‘Good governance’ has been used and applied by many actors in many contexts, receiving numerous different definitions. This article argues that human rights protection can now be considered a crucial component of good governance, at least in the context of development. In doing so, the article explains the relationship and interdependence between the two concepts, and provides three rationales for the Bank to take a ‘human rights-based approach’ to good governance. Ultimately, this article seeks to look beyond international human rights law and take a governance approach to provide a convincing basis upon which to argue that the World Bank should comply with human rights standards.

Keywords: World Bank, international human rights law, good governance, human rights-based approach

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Authors: Yadpiroon Onmek, Jean Triboulet, Sebastien Druon, Bruno Jouvencel

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The objective of this paper is to develop the 3D underwater reconstruction of archaeology object, which is based on the fusion between a sonar system and stereo camera system. The underwater images are obtained from a calibrated camera system. The multiples image pairs are input, and we first solve the problem of image processing by applying the well-known filter, therefore to improve the quality of underwater images. The features of interest between image pairs are selected by well-known methods: a FAST detector and FLANN descriptor. Subsequently, the RANSAC method is applied to reject outlier points. The putative inliers are matched by triangulation to produce the local sparse point clouds in 3D space, using a pinhole camera model and Euclidean distance estimation. The SFM technique is used to carry out the global sparse point clouds. Finally, the ICP method is used to fusion the sonar information with the stereo model. The final 3D models have a précised by measurement comparing with the real object.

Keywords: 3D reconstruction, archaeology, fusion, stereo system, sonar system, underwater

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

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The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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Authors: A. Isahakyan, A. Terzyan, V. Stepanyan, N. Zulumyan, H. Beglaryan

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The involvement of silica hydrogel derived from serpentine minerals (Mg(Fe))6[Si4O10](OH)8 as a source of silicon dioxide in SiO2–NaOH–BaCl2–H2O system results in precipitating via one-hour stirring of boiling suspension such intermediates that on heating up to 800 °C crystallize into the product composed of barium ortho- Ba2SiO4 and metasilicates BaSiO3. Based on the positive results, this approach has been decided to be adapted to inserting europium (III) ions into the structure of the synthesized compounds. Intermediates previously precipitated in silica hydrogel–NaOH–BaCl2–Eu(NO3)3 system via one-hour stirring at room temperature underwent one-hour heat-treatment at different temperatures (6001200 °C). Prior to calcination, the suspension produced in the mixer was heated on a boiling-water bath until a powder-like sample was obtained. When the silica hydrogel was metered, SiO2 content in the silica hydrogel that is 5.8 % was taken into consideration in order to guaranty the molar ratios of both SiO2 to BaO and SiO2 to Na2O equal to 1:2. BaCl2 and Eu(NO3)3 reagents were weighted so that the formation of appropriate compositions was guaranteed. Samples including various concentrations of Eu3+ ions (1.25, 2.5, 3.75, 5, 6.35, 8.65, 10, 17.5, 18.75 and 20 mol%) were synthesized by the described method. Luminescence excitation, emission spectra of the products were recorded on the Agilent Cary Eclipes fluorescence spectrophotometer using Agilent Xenon flash lamp (80 Hz) as the excitation source (scanning rate=30 nm/min, excitation and emission slits width=5 nm, excitation filter set to auto, emission filter set to auto and PMT detector Voltage=800 V). Prior to optical properties measurements, each of the powder samples was put in the solid sample-holder. X-ray powder diffraction (XRPD) measurements were made on the SmartLab SE diffractometer. Emission spectra recorded for all the samples at an excitation wavelength of 394 nm exhibit peaks centered at around 536, 555, 587, 614, 653, 690 and 702.5 nm. The most intensive emission peak is observed at 614nm due to 5D0→7F2 of europium (III) ions transition. Luminescence intensity achieves its maximum for Eu3+ 17.5 mol% and heat-treatment at 1200 °C. The XRPD patterns revealed that the diffraction peaks recorded for this sample are identical to NaBa6Nd(SiO4)4 reflections. As Nd-containing reagents were not involved into the synthesis, the maximum luminescent intensity is most likely to be conditioned by NaBa6Eu(SiO4)4 formation whose reflections are not available in the ICDD-JCPDS database of crystallographic 2024. Up to Eu3+ 2.5 mol% the samples demonstrate the phases corresponding to Ba2SiO4 and BaSiO3 standards. Subsequent increasing of europium (III) concentration in the system leads to NaBa6Eu(SiO4)4 formation along with Ba2SiO4 and BaSiO3. NaBa6Eu(SiO4)4 share gradually increases and starting from 17.5 mol% and more NaBa6Eu(SiO4)4 phase is only registered. Thus, the variation of europium (III) concentration in silica hydrogel–NaOH–BaCl2–Eu(NO3)3 system allows producing by the precipitation method the products composed of europium (III)-doped Ba2SiO4 and BaSiO3 and/or NaBa6Eu(SiO4)4 distinguished by different luminescent properties. The work was supported by the Science Committee of RA, in the frames of the research projects № 21T-1D131 and № 21SCG-1D013.

Keywords: europium (III)-doped barium ortho- Ba2SiO4 and metasilicates BaSiO₃, NaBa₆Eu(SiO₄)₄, luminescence, precipitation method

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Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Edwin Forero-Garcia, Jaime Vitola, Brayan Cardenas, Johan Casagua

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This research article presents the integration of electronic and computer systems, which developed an ultrasonic signal processing system that performs the capture, adaptation, and analog-digital conversion to later carry out its processing and visualization. The capture and adaptation of the signal were carried out from the design and implementation of an analog electronic system distributed in stages: 1. Coupling of impedances; 2. Analog filter; 3. Signal amplifier. After the signal conditioning was carried out, the ultrasonic information was digitized using a digital microcontroller to carry out its respective processing. The digital processing of the signals was carried out in MATLAB software for the elaboration of A-Scan, B and D-Scan types of ultrasonic images. Then, advanced processing was performed using the SAFT technique to improve the resolution of the Scan-B-type images. Thus, the information from the ultrasonic images was displayed in a user interface developed in .Net with Visual Studio. For the validation of the system, ultrasonic signals were acquired, and in this way, the non-invasive inspection of the structures was carried out and thus able to identify the existing pathologies in them.

Keywords: acquisition, signal processing, ultrasound, SAFT, HMI

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Authors: Ellana Boada, Eric Santos-Clotas, Alba Cabrera-Codony, Maria Martin, Lluis Baneras, Frederic Gich

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Volatile methylsiloxanes (VMS) are a group of manmade silicone compounds widely used in household and industrial applications that end up on the biogas produced through the anaerobic digestion of organic matter in landfills and wastewater treatment plants. The presence of VMS during the biogas energy conversion can cause damage on the engines, reducing the efficiency of this renewable energy source. Non regenerative adsorption onto activated carbon is the most widely used technology to remove siloxanes from biogas, while new trends point out that biotechnology offers a low-cost and environmentally friendly alternative to conventional technologies. The first objective of this research was to enrich, isolate and identify bacterial species able to grow using siloxane molecules as a sole carbon source: anoxic wastewater sludge was used as initial inoculum in liquid anoxic enrichments, adding D4 (as representative siloxane compound) previously adsorbed on activated carbon. After several months of acclimatization, liquid enrichments were plated onto solid media containing D4 and thirty-four bacterial isolates were obtained. 16S rRNA gene sequencing allowed the identification of strains belonging to the following species: Ciceribacter lividus, Alicycliphilus denitrificans, Pseudomonas aeruginosa and Pseudomonas citronellolis which are described to be capable to degrade toxic volatile organic compounds. Kinetic assays with 8 representative strains revealed higher cell growth in the presence of D4 compared to the control. Our second objective was to characterize the community composition and diversity of the microbial community present in the enrichments and to elucidate whether the isolated strains were representative members of the community or not. DNA samples were extracted, the 16S rRNA gene was amplified (515F & 806R primer pair), and the microbiome analyzed from sequences obtained with a MiSeq PE250 platform. Results showed that the retrieved isolates only represented a minor fraction of the microorganisms present in the enrichment samples, which were represented by Alpha, Beta, and Gamma proteobacteria as dominant groups in the category class thus suggesting that other microbial species and/or consortia may be important for D4 biodegradation. These results highlight the need of additional protocols for the isolation of relevant D4 degraders. Currently, we are developing molecular tools targeting key genes involved in siloxane biodegradation to identify and quantify the capacity of the isolates to metabolize D4 in batch cultures supplied with a synthetic gas stream of air containing 60 mg m⁻³ of D4 together with other volatile organic compounds found in the biogas mixture (i.e. toluene, hexane and limonene). The isolates were used as inoculum in a biotrickling filter containing lava rocks and activated carbon to assess their capacity for siloxane removal. Preliminary results of biotrickling filter performance showed 35% of siloxane biodegradation in a contact time of 14 minutes, denoting that biological siloxane removal is a promising technology for biogas upgrading.

Keywords: bacterial cultivation, biogas upgrading, microbiome, siloxanes

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Authors: Saumya Srivastava, Rina Maiti

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In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

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Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

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This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Rizwan Ullah, Abdar Ali, Zahid Ullah

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This paper illustrates the study of three isolated zero voltage switched (ZVS) PWM full bridge (FB) converters to charge the high voltage battery in the charger of electric vehicle (EV). EV battery chargers have several challenges such as high efficiency, high reliability, low cost, isolation, and high power density. The cost of magnetic and filter components in the battery charger is reduced when switching frequency is increased. The increase in the switching frequency increases switching losses. ZVS is used to reduce switching losses and to operate the converter in the battery charger at high frequency. The performance of each of the three converters is evaluated on the basis of ZVS range, dead times of the switches, conduction losses of switches, circulating current stress, circulating energy, duty cycle loss, and efficiency. The limitations and merits of each PWM FB converter are reviewed. The converter with broader ZVS range, high efficiency and low switch stresses is selected for battery charger applications in EV.

Keywords: electric vehicle, PWM FB converter, zero voltage switching, circulating energy

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

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Authors: Simon Huston, Ebraheim Lahbash, Ali Parsa

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The development of the United Arab Emirates (UAE) into a regional trade, tourism, finance and logistics hub has transformed its real estate markets. However, speculative activity and price volatility remain concerns. UAE residential market values (MV) are exposed to fluctuations in capital flows and migration which in turn are affected by geopolitical uncertainty, oil price volatility, and global investment market sentiment. Internally, a complex interplay between administrative boundaries, land tenure, building quality and evolving location characteristics fragments UAE residential property markets. In short, the UAE Residential Valuation System (UAE-RVS) confronts multiple challenges to collect, filter and analyze relevant information in complex and dynamic spatial and capital markets. A robust (RVS) can mitigate the risk of unhelpful volatility, speculative excess or investment mistakes. The research outlines the institutional, ontological, dynamic, and epistemological issues at play. We highlight the importance of system capabilities, valuation standard salience and stakeholders trust.

Keywords: valuation, property rights, information, institutions, trust, salience

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: Jennis Delina Giles, Nimesha Liyanage, Damindi Senadheera, Dilan Randima, Kushnara Suriyawansa

Abstract:

Mental health is essential during childhood, adolescence, and adulthood. Mental health issues can influence one's thoughts, disposition, and conduct. A record number of mental health problems are caused by a global pandemic. Prevention of mental disease is vital for both children and adults. We desired to develop a web application for those with mental health difficulties. This web application will provide group chat, discussion, a community feed, and counseling services. The community feed function provides information regarding scheduled conversation space meetings, and the counselor uploads uplifting thoughts and tales of patients who received proper care and overcame mental health issues. Community feed can filter content based on user preferences. The mental health system for adults and adolescents will be updated. The community feed delivers relevant and instructive postings, links, and images so that service recipients can benefit from other platform features and receive encouraging words to assist them in overcoming mental health difficulties.

Keywords: bio medical, mental helath care, empower youths & adults, counselling

Procedia PDF Downloads 135

Authors: Jamuna Loganath

Abstract:

Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

Procedia PDF Downloads 222

Authors: Joe Amalraj, M. Arunkumar

Abstract:

Haze is an atmospheric phenomenon that signicantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. In this method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. This paper demonstrates the utility and effectiveness of a fusion-based technique for de-hazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

Keywords: single image de-hazing, outdoor images, enhancing, DSP

Procedia PDF Downloads 388

Authors: Saugata Bose, Ritambhra Korpal

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The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

Procedia PDF Downloads 339

Authors: Takashi Kaburagi, Takamasa Komura, Yosuke Kurihara

Abstract:

Absolute pitch is the ability to identify a musical note without a reference tone. Training for absolute pitch often occurs in preschool education. It is necessary to clarify how well the trainee can make use of synesthesia in order to evaluate the effect of the training. To the best of our knowledge, there are no existing methods for objectively confirming whether the subject is using synesthesia. Therefore, in this study, we present a method to distinguish the use of color-auditory synesthesia from the separate use of color and audition during absolute pitch training. This method measures blood volume in the prefrontal cortex using functional Near-infrared spectroscopy (fNIRS) and assumes that the cognitive step has two parts, a non-linear step and a linear step. For the linear step, we assume a second order ordinary differential equation. For the non-linear part, it is extremely difficult, if not impossible, to create an inverse filter of such a complex system as the brain. Therefore, we apply a method based on a self-organizing map (SOM) and are guided by the available data. The presented method was tested using 15 subjects, and the estimation accuracy is reported.

Keywords: absolute pitch, functional near-infrared spectroscopy, prefrontal cortex, synesthesia

Procedia PDF Downloads 245

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 129

Authors: Pinghe Wang

Abstract:

In this paper, we demonstrate a tunable long-cavity passive mode-locked fiber laser. The mode locker is a nonlinear amplifying loop mirror (NALM). The cavity frequency of the laser is 465 kHz because that 404m SMF is inserted in the cavity. A tunable bandpass filter with ~1nm 3dB bandwidth is inserted into the cavity to realize tunable mode locking. The passive mode-locked laser at a fixed wavelength is investigated in detail. The experimental results indicate that the laser operates in dissipative soliton resonance (DSR) region. When the pump power is 400mW, the laser generates the rectangular pulses with 10.58 ns pulse duration, 70.28nJ single-pulse energy. When the pump power is 400mW, the laser keeps stable mode locking status in the range from 1523.4nm to 1575nm. During the whole tuning range, the SNR, the pulse duration, the output power and single pulse energy have a little fluctuation because that the gain of the EDF changes with the wavelength.

Keywords: fiber laser, dissipative soliton resonance, mode locking, tunable

Procedia PDF Downloads 217

Authors: Muhammad Hamza

Abstract:

This study attempts to analyze the social media reports regarding Covid-19 that impacted the psyche of Pakistanis. This Study is delimited to hashtags from Tweets on a social media platform. During Covid-19, it has been observed that it affected the psychological conditions of Pakistanis. With the application of the three-dimensional model presented by Fairclough, together with a data analytic software “FireAnt” i.e., social media and data analysis toolkit, which is used to filter, identify, report and export data from social media accurately. A detailed and explicit exploration of the various hashtags by users from different fields was conducted. This study conducted a quantitative as well as qualitative methods of analysis. The study examined the perspectives of the Pakistanis behind the use of various hashtags with the lenses of Critical Discourse Analysis (CDA). While conducting this research, CDA was helpful to reveal the connection between the psyche of the people and the Covid-19 pandemic. It was found that how different Pakistanis used social media and how Covid-19 impacted their psyche. After collecting and analyzing the hashtags from twitter it was concluded that majority of people received negative impact from social media reports, while, some people used their hashtags positively and were found positive during Covid-19, and some people were found neutral.

Keywords: Covid, Covid-19, psyche, Covid Pakistan

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Authors: M. Benhaliliba, A. Ben Ahmed, C.E. Benouis, A.Ayeshamariam

Abstract:

The properties of nonlinear optical NLOs are examined, and the results confirm the 2.19 eV HOMO-LUMO mismatch. In the Al-Pc cluster, certain functional bond lengths and bond angles have been observed. The Quantum chemical method (DFT and TD-DFT) and Vibrational spectra properties of AlPc are studied. X-ray pattern reveals the crystalline structure along with the (242) orientation of the AlPc organic thin layer. UV-Vis shows the frequency selective behavior of the device. The absorbance of such layer exhibits a high value within the UV range and two consecutive peaks within visible range. Spin coating is used to make an organic diode based on the Aluminium-phthalocynanine (AlPc-Cl) molecule. Under dark and light conditions, electrical characterization of Ag/AlPc/Si/Au is obtained. The diode's high rectifying capability (about 1x104) is subsequently discovered. While the height barrier is constant and saturation current is greatly reliant on light, the ideality factor of such a diode increases to 6.9 which confirms the non-ideality of such a device. The Cheung-Cheung technique is employed to further the investigation and gain additional data such as series resistance and barrier height.

Keywords: AlPc-Cl organic material, nonlinear optic, optical filter, diode

Procedia PDF Downloads 114