Search results for: automated drift detection and adaptation

Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

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Authors: Swanand Patil, Pankaj Agarwal

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In past few decades, seismic performance objectives have shifted from earthquake resistance to earthquake resilience of the structures, especially for the lifeline buildings. Features such as negligible post-earthquake damage and replaceable damaged components, makes energy dissipating systems a valid choice for a seismically resilient building. In this study, various energy dissipation devices are applied on an eight-storey moment resisting RC building model. The energy dissipating devices include both hysteresis-based and viscous type of devices. The seismic response of the building is obtained for different positioning and mechanical properties of the devices. The investigation is carried forward to the deficiently ductile RC frame also. The performance assessment is done on the basis of drift ratio, mode shapes and displacement response of the model structures. Nonlinear dynamic analysis shows largely improved displacement response. The damping devices improve displacement response more efficiently in the deficient ductile frames than that in the perfectly moment resisting frames. This finding is important considering the number of deficient buildings in India and the world. The placement and mechanical properties of the dampers prove to be a crucial part in modelling, analyzing and designing of the structures with supplemental energy dissipation.

Keywords: earthquake resilient structures, lifeline buildings, retrofitting of structures, supplemental energy dissipation

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Authors: Ahmed Elbeheri, Tarek Zayed

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Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.

Keywords: steel bridge, bridge inspection, steel corrosion, image processing

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Authors: Azeez O. Idris, Benjamin O. Orimolade, Potlako J. Mafa, Alex T. Kuvarega, Usisipho Feleni, Bhekie B. Mamba

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We report a simple and cheaper method for the electrochemical detection of Se(IV) using carbon nanodots (CNDTs) prepared from oat. The carbon nanodots were synthesised by green and facile approach and characterised using scanning electron microscopy, high-resolution transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and Raman spectroscopy. The CNDT was used to fabricate an electrochemical sensor for the quantification of Se(IV) in water. The modification of glassy carbon electrode (GCE) with carbon nanodots led to an increase in the electroactive surface area of the electrode, which enhances the redox current peak of [Fe(CN)₆]₃₋/₄‒ in comparison to the bare GCE. Using the square wave voltammetry, the detection limit and quantification limit of 0.05 and 0.167 ppb were obtained under the optimised parameters using deposition potential of -200 mV, 0.1 M HNO₃ electrolyte, electrodeposition time of 60 s, and pH 1. The results further revealed that the GCE-CNDT was not susceptible to many interfering cations except Cu(II) and Pb(II), and Fe(II). The sensor fabrication involves a one-step electrode modification and was used to detect Se(IV) in a real water sample, and the result obtained is in agreement with the inductively coupled plasma technique. Overall, the electrode offers a cheap, fast, and sensitive way of detecting selenium in environmental matrices.

Keywords: carbon nanodots, square wave voltammetry, nanomaterials, selenium, sensor

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Authors: Sameer Muhammad Aslam, Nura Said Mohsin Al-Saifi

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This research shows the process of creating a blood donation website for Oman. Blood donation is a widespread, crucial, ongoing process, so it is important that this website is easy to use. Several automated blood management systems are available, but none provides an effective algorithm that takes into account variables such as frequency of donation, donation date, and gender. In Oman, the Ministry of Health maintains a blood bank and keeps donors informed about the need for blood through a website. They also inform donors and the wider public where and when is their next blood donation event. The website's main goals are to educate the community about the benefits of blood donation. It also manages donor and receiver documentation and encourages voluntary blood donation by providing easy access to information about blood types and blood distribution in various hospitals in Oman, based on hospital needs.

Keywords: Oman, blood bank, blood donors, donor website

Procedia PDF Downloads 216

Authors: Allan F. F. Alves, Fernando A. Bacchim Neto, Guilherme Giacomini, Marcela de Oliveira, Ana L. M. Pavan, Maria E. D. Rosa, Diana R. Pina

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Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke.

Keywords: ischemic stroke, image processing, CT scans, Fuzzy C-means

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Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

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Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: fire detector, rack, response characteristic, warehouse

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Authors: S. Shaaban, T. McNamara, S. Hudson

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This paper reports on the performance of deliberately unbalanced, reliable, non-automated and assembly lines that merge, whose workstations differ in terms of their mean operation times. Simulations are carried out on 5- and 8-station lines with 1, 2 and 4 buffer capacity units, % degrees of line imbalance of 2, 5 and 12, and 24 different patterns of means imbalance. Data on two performance measures, namely throughput and average buffer level were gathered, statistically analysed and compared to a merging balanced line counterpart. It was found that the best configurations are a balanced line arrangement and a monotone decreasing order for each of the parallel merging lines, with the first generally resulting in a lower throughput and the second leading to a lower average buffer level than those of a balanced line.

Keywords: average buffer level, merging lines, simulation, throughput, unbalanced

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Authors: M. V. A. Raju Bahubalendruni, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

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Achieving an appropriate assembly sequence needs deep verification for its physical feasibility. For this purpose, industrial engineers use several assembly predicates; namely, liaison, geometric feasibility, stability and mechanical feasibility. However, testing an assembly sequence for these predicates requires huge assembly information. Extracting such assembly information from an assembled product is a time consuming and highly skillful task with complex reasoning methods. In this paper, computer aided methods are proposed to extract all the necessary assembly information from computer aided design (CAD) environment in order to perform the assembly sequence planning efficiently. These methods use preliminary capabilities of three-dimensional solid modelling and assembly modelling methods used in CAD software considering equilibrium laws of physical bodies.

Keywords: assembly automation, assembly attributes, assembly, CAD

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Authors: Zeineb Ben Azzouz, Wahiba Ben Abdessalem Karaa

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The automated extraction of UML class diagram from natural language requirements is a highly challenging task. Many approaches, frameworks and tools have been presented in this field. Nonetheless, the experiments of these tools have shown that there is no approach that can work best all the time. In this context, we propose a new accurate approach to facilitate the automatic mapping from textual requirements to UML class diagram. Our new approach integrates the best properties of statistical Natural Language Processing (NLP) techniques to reduce ambiguity when analysing natural language requirements text. In addition, our approach follows the best practices defined by conceptual modelling experts to determine some patterns indispensable for the extraction of basic elements and concepts of the class diagram. Once the relevant information of class diagram is captured, a XMI document is generated and imported with a CASE tool to build the corresponding UML class diagram.

Keywords: class diagram, user’s requirements, XMI, software engineering

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Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

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Authors: Ali Azam Talukder, Jamsheda Ferdous Tuli, Tanzina Islam Reba, Shuvra Kanti Dey, Mamoru Yamada

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Recent global warming created by various pollutants prompted us to find new energy sources instead of fossil fuels. Fossil fuels are one of the key factors to emit various toxic gases in this planet. To solve this problem, along with the scarcity of the worldwide energy crisis, scientists are looking for various alternative options to mitigate the necessity of required future fuels. In this context, bioethanol can be one of the most suitable alternative energy sources. Bioethanol is a renewable, environment-friendly and carbon-neutral sustainable energy. In our previous study, we identified several bioethanol-producing microbes from the natural fermented sources of Bangladesh. Among them, the strain 4C encoded Saccharomyces cerevisiae produced maximum bioethanol when the fermentation temperature was 25˚C. In this study, we have established high-temperature simultaneous saccharification and fermentation process (HTSSF) by co-culturing of thermally adapted thermosensitive 4C as a fermenting agent and Bacillus amyloliquefaciens (C7), as a saccharifying agent under various physiological conditions or treatments. Conventional methods were applied for cell culture, media preparation and other experimental purposes. High-temperature adaptation of strain 4C was made from 30-42ᵒC, using either YPD or YPS media. In brief, for thermal adaptation, the temperature was periodically increased by 2ᵒC, 1ᵒC and 0.5ᵒC when medium growth temperatures were 30-36ᵒC, 36-40ᵒC, and 40-42ᵒC, respectively, where applicable. Amylase activity and bioethanol content were measured by DNS (3, 5-dinitrosalicylic acid) and solvent extraction and dichromate oxidation method, respectively. Among the various growth parameters like temperatures (30˚C, 37˚C and 42˚C), pHs (5.0, 6.0 and 7.0), carbon sources (5.0-10.0%) and ethanol stress tolerance (0.0-12.0%) etc. were tested, maximum Amylase activity (4.0 IU/ml/min) was recorded for Bacillus amyloliquefaciens (C7) at 42˚C, pH 6.0 and 10% starch. On the other hand, 4.10% bioethanol content was recorded when the thermally adapted strain 4C was co-cultured with C7 at 37ᵒC, pH 6.0 and 10.0% starch for 72 hours at HTSSF process. On the other hand, thermally non-adapted strains gave only 0.5-2.0% bioethanol content under the same physiological conditions. The thermally adapted strain 4C and strain C7, both can tolerate ethanol stress up to 12%. Altogether, a comparative study revealed that our established HTSSF process may be suitable for pilot scale and subsequently at industrial level bioethanol production.

Keywords: bioethanol, co-culture, fermentation, saccharification

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Authors: W. J. Zhang, Y. Q. Du, M. L. Wang

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Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancement in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Eight DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, cirrhosis and diabetes. Our tests indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, reproducibility, and repeatability. Furthermore, different molecules can be distinguished through pattern recognition enabled by this sensor array. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or bimolecular detection for the noninvasive diagnostics of diseases and health monitoring.

Keywords: breath analysis, diagnosis, DNA-SWNT sensor array, noninvasive

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Authors: Shah Sufaid, Hussain Shahid, Tianyan You, Liu Guiwu, Qiao Guanjun

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Nickel oxide (NiO) is an optimal material for precise detection of hydrogen (H₂) gas due to its high catalytic activity and low resistivity. However, the gas response kinetics of H₂ gas molecules with the surface of NiO concurrence limitation imposed by its solid structure, leading to a diminished gas response value and slow electron-hole transport. Herein, NiO@CuO NFs with porous sharp-tip and nanospheres morphology were successfully synthesized by using a metal-organic framework (MOFs) as a precursor. The fabricated porous 2 wt% NiO@CuO NFs present outstanding selectivity towards H₂ gas, including a high sensitivity of a response value (170 to 20 ppm at 150 °C) higher than that of porous Ni-MOF (6), low detection limit (300 ppb) with a notable response (21), short response and recovery times at (300 ppb, 40/63 s and 20 ppm, 100/167 s), exceptional long-term stability and repeatability. Furthermore, an understanding of NiO@CuO sensor functioning in an actual environment has been obtained by using the impact of relative humidity as well. The boosted hydrogen sensing properties may be attributed due to synergistic effects of numerous facts including p-p heterojunction at the interface between NiO and CuO nanoflowers. Particularly, a porous Ni-MOF structure combined with the chemical sensitization effect of NiO with the rough surface of CuO nanosphere, are examined. This research presents an effective method for development of Ni-MOF derived metal oxide semiconductor (MOS) heterostructures with rigorous morphology and composition, suitable for gas sensing application.

Keywords: NiO@CuO NFs, metal organic framework, porous structure, H₂, gas sensing

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Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: K. Piórkowska

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The overarching aim of the paper is to incorporate the micro-foundations perspective in strategic management and offering possibilities to bridge the macro–micro divide, to review the concept of habits, as well as to propose research findings and directions in terms of further exploring the habit construct and its impact on higher epistemological level phenomena (for instance organizational routines, which is a domain inherently multilevel in nature). To realize this aim, the following sections have been developed: (1) habits’ origins, (2) habits – cognitive constellations, (3) interrelationships between habits and mental representations, intentions, (4) habits and organizational routines, and (5) habits and routines linkages with adaptation. The conclusions that have been made support recent and current studies linking the level of individual heterogeneous agents with the level of macro (organizational) outcomes.

Keywords: behaviorism, habits, micro-foundations, routines

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Authors: Suwaiba Sabiu Bako, Yaw Debrah

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In spite of the extensive literature available on the human resource management (HRM) systems and practices of multinational companies (MNCs) from developed countries, there are gaps concerning emerging countries’ multinational companies’ (EMNCs) HRM systems and practices. This study examines the transfer of HRM practices in Nigerian subsidiaries of MNCs from South Africa. It reveals that South MNCs hybridise their recruitment and selection processes and localise their compensation and employee relations. It also proves that performance appraisal, talent management and code of conduct practices are largely transferred to subsidiaries with minimal adaptation.

Keywords: EMNCs, HRM practices, HRM systems, Nigeria, South Africa

Procedia PDF Downloads 112

Authors: Jan Jezek, Zdenek Pilat, Filip Smatlo, Pavel Zemanek

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We present a device that combines fluorescence spectroscopy with fiber optics and dielectrophoretic micromanipulation in PDMS (poly-(dimethylsiloxane)) microfluidic chips. The device allows high speed detection (in the order of kHz) of the fluorescence signal, which is coming from the sample by an inserted optical fiber, e.g. from a micro-droplet flow in a microfluidic chip, or even from the liquid flowing in the transparent capillary, etc. The device uses a laser diode at a wavelength suitable for excitation of fluorescence, excitation and emission filters, optics for focusing the laser radiation into the optical fiber, and a highly sensitive fast photodiode for detection of fluorescence. The device is combined with dielectrophoretic sorting on a chip for sorting of micro-droplets according to their fluorescence intensity. The electrodes are created by lift-off technology on a glass substrate, or by using channels filled with a soft metal alloy or an electrolyte. This device found its use in screening of enzymatic reactions and sorting of individual fluorescently labelled microorganisms. The authors acknowledge the support from the Grant Agency of the Czech Republic (GA16-07965S) and Ministry of Education, Youth and Sports of the Czech Republic (LO1212) together with the European Commission (ALISI No. CZ.1.05/2.1.00/01.0017).

Keywords: dielectrophoretic sorting, fiber optics, laser, microfluidic chips, microdroplets, spectroscopy

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Authors: Kara J. Coffman-Rea, Karen E. Samonds

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Microplastic pollution is an urgent global threat to our planet and human health. Microplastic particles have been detected within our food, water, and atmosphere, and found within the human stool, placenta, and lung tissue. However, most spectrometric microplastic detection methods require chemical digestion which can alter or destroy microplastic particles and makes it impossible to acquire information about their in-situ distribution. MALDI TOF MS (Matrix-assisted laser desorption ionization-time of flight mass spectrometry) is an analytical method using a soft ionization technique that can be used for polymer analysis. This method provides a valuable opportunity to both acquire information regarding the in-situ distribution of microplastics and also minimizes the destructive element of chemical digestion. In addition, MALDI TOF MS allows for expanded analysis of the microplastics including detection of specific additives that may be present within them. MALDI TOF MS is particularly sensitive to sample preparation and has not yet been used to analyze environmental microplastics within their specific location (e.g., biological tissues, sediment, water). In this study, microplastics were created using polyethylene gloves, polystyrene micro-foam, and polyethylene terephthalate cable sleeving. Plastics were frozen using liquid nitrogen and ground to obtain small fragments. An artificial tissue was created using a cellulose sponge as scaffolding coated with a MaxGel Extracellular Matrix to simulate human lung tissue. Optimal preparation techniques (e.g., matrix, cationization reagent, solvent, mixing ratio, laser intensity) were first established for each specific polymer type. The artificial tissue sample was subsequently spiked with microplastics, and specific polymers were detected using MALDI-TOF-MS. This study presents a novel method for the detection of environmental polyethylene, polyethylene terephthalate, and polystyrene microplastics within a complex sample. Results of this study provide an effective method that can be used in future microplastics research and can aid in determining the potential threats to environmental and human health that they pose.

Keywords: environmental plastic pollution, MALDI-TOF MS, microplastics, polymer identification

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Authors: Cristian Patrascioiu, Loredana Negoita

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This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: automatic detection, defects, fracture lines, wavelets

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Authors: Patrycja Pichnicka

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Anime is the Japanese art of animation and a kind of Japanese animated movie, different from the Western ones by its specific features. In the world dominated by live action movies, mostly the ones produced in the United States, Japanese animated movies, which constitute a large part of the Japanese movie industry, play the role of the Other. They adapt elements of Western culture and technology to create something that resists global Western domination. This phenomenon is particularly interesting to observe in the case of narration borrowed from the Western culture, yet transformed in a specific manner: such as Vampire Narration. The phenomenon should be examined using the theory of cultural adaptation of Siergiei Arutiunow, as well as theory of cultural hegemony and postcolonial theories, including the theory of the discourse of resistance. Relations of cultural hegemony and resistance have been mentioned in works of Susan Napier, however they are worth to be fully developed. Anime relations to globally dominating culture reveal tension between submission and resistance in which non-Western identity is constructed and performed. Nonetheless, the tension between the Global/Western and the Japanese is not the only one existing in contemporaneous Japanese society and culture. Sexual, gender, class, and ethnic issues are also expressed in and through pop culture narrations. Using the basic division of the types of cultural adaptation we can trace the line of the evolution of the Japanese cultural attitude towards the West, expressed in the Vampire Narration from the time of American occupation till now. These attitudes changed from the submissive assimilation or reproduction of cultural models, through the simple opposition, to the more nuanced attitude of nowadays. However, according to Kimberlé Crenshaw’s intersectional theory, there is no one category of discrimination or submission. There are individuals or groups existing on the cross of two or more categories of emancipation. If the Japanese were culturally subdued to the Westerner, the Japanese woman was doubly subdued: as a woman and as a Japanese. The emancipation of one group can deepen the submission of another one, of internal Other, of the group in which two or more categories of domination/submission intersect. That is why some Japanese female authors enthusiastically reproduce the Western cultural models, even if this means a cultural hegemony of the West over the Japanese. They see, as women, more liberal attitudes towards their gender in the Western culture than in the Japanese culture, as it is constructed and produced by Japanese men. The Japanese anime is the realm in which sophisticated art meets social tendencies and cultural attitudes. Anime examination permits to study of the composed contemporaneous Japanese identity, as well as general rules of cultural relations.

Keywords: anime, cultural hegemony, intercultural relations, resistance, vampire narration

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: Rinat Gabbay-Benziv, Merav Ben-Natan, Ariel Roguin, Benyamine Abbou, Anna Ofir, Adi Klein, Dikla Dahan-Shriki, Mordechai Hallak, Boris Kessel, Mickey Dudkiewicz

Abstract:

Introduction: Over recent decades, technology has become integral to healthcare, with electronic health records and advanced medical equipment now standard. However, this reliance has made healthcare systems increasingly vulnerable to ransomware attacks. On October 13, 2021, Hillel Yaffe Medical Center experienced a severe ransomware attack that disrupted all IT systems, including electronic health records, laboratory services, and staff communications. The attack, carried out by the group DeepBlueMagic, utilized advanced encryption to lock the hospital's systems and demanded a ransom. This incident caused significant operational and patient care challenges, particularly impacting the obstetrics department. Objective: The objective is to describe the challenges facing the obstetric division following a cyberattack and discuss ways of preparing for and overcoming another one. Methods: A retrospective descriptive study was conducted in a mid-sized medical center. Division activities, including the number of deliveries, cesarean sections, emergency room visits, admissions, maternal-fetal medicine department occupancy, and ambulatory encounters, from 2 weeks before the attack to 8 weeks following it (a total of 11 weeks), were compared with the retrospective period in 2019 (pre-COVID-19). In addition, we present the challenges and adaptation measures taken at the division and hospital levels leading up to the resumption of full division activity. Results: On the day of the cyberattack, critical decisions were made. The media announced the event, calling on patients not to come to our hospital. Also, all elective activities other than cesarean deliveries were stopped. The number of deliveries, admissions, and both emergency room and ambulatory clinic visits decreased by 5%–10% overall for 11 weeks, reflecting the decrease in division activity. Nevertheless, in all stations, there were sufficient activities and adaptation measures to ensure patient safety, decision-making, and workflow of patients were accounted for. Conclusions: The risk of ransomware cyberattacks is growing. Healthcare systems at all levels should recognize this threat and have protocols for dealing with them once they occur.

Keywords: ransomware attack, healthcare cybersecurity, obstetrics challenges, IT system disruption

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Authors: Can Mungan, Gokhan Kilic

Abstract:

Structural engineers and tunnel owners have good reason to attach importance to the assessment and inspection of tunnels. Regular inspection is necessary to maintain and monitor the health of the structure not only at the present time but throughout its life cycle. Detection of flaws within the structure, such as corrosion and the formation of cracks within the internal elements of the structure, can go a long way to ensuring that the structure maintains its integrity over the course of its life. Other issues that may be detected earlier through regular assessment include tunnel surface delamination and the corrosion of the rebar. One advantage of new technology such as the ground penetrating radar (GPR) is the early detection of imperfections. This study will aim to discuss and present the effectiveness of GPR as a tool for assessing the structural integrity of the heavily used tunnel. GPR is used with various antennae in frequency and application method (2 GHz and 500 MHz GPR antennae). The paper will attempt to produce a greater understanding of structural defects and identify the correct tool for such purposes. Conquest View with 3D scanning capabilities was involved throughout the analysis, reporting, and interpretation of the results. This study will illustrate GPR mapping and its effectiveness in providing information of value when it comes to rebar position (lower and upper reinforcement). It will also show how such techniques can detect structural features that would otherwise remain unseen, as well as moisture ingress.

Keywords: tunnel, GPR, health monitoring, moisture ingress, rebar position

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Authors: Nicholas Burica, Nina Selak

Abstract:

The ADHCAT (Automated Distribution Hosting Capacity Assessment Tool) was designed to run Hosting Capacity Analysis on the ComEd system via a stochastic DER (Distributed Energy Resource) placement on multiple power flow simulations against a set of violation criteria. The violation criteria in the initial version of the tool captured a limited amount of issues that individual departments design against for DER interconnections. Enhancements were made to the tool to further align with individual department violation and operation criteria, as well as the addition of new modules for use for future load profile analysis. A reporting engine was created for future analytical use based on the simulations and observations in the tool.

Keywords: distributed energy resources, hosting capacity, interconnect, voltage optimization

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Authors: Bashir Ahmad Aasim, Abdul Khaliq Karimi, Jun Tomiyama

Abstract:

Material aging is one of the vital issues among all the civil, mechanical, and aerospace engineering societies. Sustenance and reliability of concrete, which is the widely used material in the world, is the focal point in civil engineering societies. For few decades, researchers have been able to present some form algorithms that could lead to evaluate a structure globally rather than locally without harming its serviceability and traffic interference. The algorithms could help presenting different methods for evaluating structures non-destructively. In this paper, a non-destructive vibration-based damage detection method is adopted to evaluate two concrete beams, one being in a healthy state while the second one contains a crack on its bottom vicinity. The study discusses that damage in a structure affects modal parameters (natural frequency, mode shape, and damping ratio), which are the function of physical properties (mass, stiffness, and damping). The assessment is carried out to acquire the natural frequency of the sound beam. Next, the vibration response is recorded from the cracked beam. Eventually, both results are compared to know the variation in the natural frequencies of both beams. The study concludes that damage can be detected using vibration characteristics of a structural member considering the decline occurred in the natural frequency of the cracked beam.

Keywords: concrete beam, natural frequency, non-destructive testing, vibration characteristics

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Authors: Tarek Dandashi

Abstract:

WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

Abstract:

This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

Procedia PDF Downloads 146