Search results for: wild fire detection

Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

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One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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Authors: Rodrigo M. Falleiro, Joaquim P. L. Parime, Luciano C. Santos, Rodrigo D. Silva

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The Cerrado biome is the most biodiverse savanna on the planet. Located in central Brazil, its preservation is seriously threatened by the advance of intensive agriculture and livestock. Conservation Units and Indigenous Lands are increasingly isolated and subject to mega wildfires. Among the characteristics of this savanna, we highlight the high rate of primary biomass production and the reduced occurrence of large grazing animals. In this biome, the predominant fauna is more dependent on the fruits produced by the dicotyledonous species in relation to other tropical savannas. Fire is a key element in the balance between mono and dicotyledons or between the arboreal and herbaceous strata. Therefore, applying fire regimes that maintain the balance between these strata without harming fruit production is essential in the conservation strategies of Cerrado's biodiversity. Recently, Integrated Fire Management has started to be implemented in Brazilian protected areas. As a result, management with prescribed burns has increasingly replaced strategies based on fire exclusion, which in practice have resulted in large wildfires, with highly negative impacts on fruit and fauna production. In the Indigenous Lands, these fires were carried out respecting traditional knowledge. The indigenous people showed great concern about the effects of fire on fruit plants and important animals. They recommended that the burns be carried out between April and May, as it would result in a greater production of edible fruits ("fruiting burning"). In other tropical savannas in the southern hemisphere, the preferential period tends to be later, in the middle of the dry season, when the grasses are dormant (June to August). However, in the Cerrado, this late period coincides with the flowering and sprouting of several important fruit species. To verify the best burning season, the present work evaluated the effects of fire on flowering and fruit production of theByrsonima sp., Mouriri pusa, Caryocar brasiliense, Anacardium occidentale, Pouteria ramiflora, Hancornia speciosa, Byrsonima verbascifolia, Anacardium humille and Talisia subalbens. The evaluations were carried out in the field, covering 31 Indigenous Lands that cover 104,241.18 Km², where 3,386 prescribed burns were carried out between 2015 and 2018. The burning periods were divided into early (carried out during the rainy season), modal or “fruiting” (carried out during the transition between seasons) and late (carried out in the middle of the dry season, when the grasses are dormant). The results corroborate the traditional knowledge, demonstrating that the modal burns result in higher rates of reproduction and fruit production. Late burns showed intermediate results, followed by early burns. We conclude that management strategies based mainly on forage production, which are usually applied in savannas populated by grazing ungulates, may not be the best management strategy for South American savannas. The effects of fire on fruit plants, which have a particular phenologicalsynchronization with the fauna cycle, also need to be observed during the prescription of burns.

Keywords: cerrado biome, fire regimes, native fruits, prescribed burns

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Authors: Yoftahe Nigussie

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This report presents a final year project pertaining to the design of Fire tube boiler for the purpose of producing saturated steam. The objective of the project is to produce saturated steam for different purpose with a capacity of 2000kg/h at 12bar design pressure by performing a design of a higher performance fire tube boiler that considered the requirements of cost minimization and parameters improvement. This is mostly done in selection of appropriate material for component parts, construction materials and production methods in different steps of analysis. In the analysis process, most of the design parameters are obtained by iterating with related formulas like selection of diameter of tubes with overall heat transfer coefficient optimization, and the other selections are also as like considered. The number of passes is two because of the size and area of the tubes and shell. As the analysis express by using heavy oil fuel no6 with a higher heating value of 44000kJ/kg and lower heating value of 41300kJ/kg and the amount of fuel consumed 140.37kg/hr. and produce 1610kw of heat with efficiency of 85.25%. The flow of the fluid is a cross flow because of its own advantage and the arrangement of the tube in-side the shell is welded with the tube sheet, and the tube sheet is attached with the shell and the end by using a gasket and weld. The design of the shell, using European Standard code section, is as like pressure vessel by considering the weight, including content and the supplementary accessories such as lifting lugs, openings, ends, man hole and supports with detail and assembly drawing.

Keywords: steam generation, external treatment, internal treatment, steam velocity

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Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

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Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

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Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

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Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

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The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

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Authors: Dedy Pratama, Akhmadu Muradi, Hilman Ibrahim, Patrianef Darwis, Alexander Jayadi Utama, Raden Suhartono, D. Suryandari, Luluk Yunaini, Tom Ch Adriani

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Objective: Diabetic Foot Ulcer (DFU) is one of the complications of Type 2 Diabetes Mellitus (T2DM) that can lead to disability and death. Inadequate vascularization condition will affect healing process of DFU. Therefore, we investigated the expression of polymorphism TGF- β1 in the relation of the occurrence of DFU in T2DM. Methods: We designed a case-control study to investigate the polymorphism TGF- β1 gene 1800469 C > T and 1982073 C > T in T2DM in Cipto Mangunkusumo National Hospital (RSCM) Jakarta from June to December 2016. We used PCR techniques and compared the results in a group of T2DM patients with DFU as the case study and without DFU as the control group. Results: There were 203 patients, 102 patients with DFU and 101 patients control without DFU. 49,8% is male and 50,2% female with mean age about 56 years. Distribution of wild-type genotype TGF-B1 1800469 C > T wild type CC was found in 44,8%, the number of mutant heterozygote CT was 10,8% and mutant homozygote is 11,3%. Distribution of TGF-B1 1982073 C>T wild type CC was 32,5%, mutant heterozygote is 38,9% and mutant homozygote 25,1%. Conclusion: Distribution of alleles from TGF-B1 1800469 C > T is C 75% and T 25% and from TGF-B1 1982073 C > T is C53,8% and T 46,2%. In the other word polymorphism TGF- β1 plays a role in the occurrence and healing process of the DFU in T2DM patients.

Keywords: diabetic foot ulcers, diabetes mellitus, polymorphism, TGF-β1

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Authors: Rachel Thomas Tharmabalan

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The growing unease over the matter of food security in the world is the result of a maturing realization that the genetic base of most human caloric intake from plants is dangerously narrow. Malaysia’s tropical rainforests have the potential to contribute to diet diversification and provide a source of nutrient-rich food as the Orang Asli communities in Malaysia have relied almost entirely on the jungle for food, fodder, medicine and fuel antithetical to what is happening today. This segregation of the Orang Asli from traditional lands and resources leads to severe loss of knowledge of biodiversity. In order to preserve these wild edibles, four different types of vegetables that are frequently consumed by the Orang Asli which consists of Rebu, Meranti, Saya and Pama were selected. These vegetables were then analysed to determine its proximate and mineral content to help ascertain claims and reaffirm the impact it can play in ensuring food and nutrition security, in addition to combating chronic diseases. From the results obtained, the Meranti had the highest crude fiber, iron and calcium content. Other minerals such as potassium, magnesium and copper were also found in varying content. These wild edibles could also contribute to education and bring awareness to younger generations as well as urban populations to start consuming more of these in their daily life as it could prevent various chronic diseases in Malaysia.

Keywords: food and nutrition security, Orang Asli, underutilized plants, wild edible food systems

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Authors: Enqing Chen, Jianbo Wang

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It is well known that the wavelet transform provides a very effective framework for multiscale edges analysis. However, wavelets are not very effective in representing images containing distributed discontinuities such as edges. In this paper, we propose a novel multiscale edge detection method in nonsubsampled contourlet transform (NSCT) domain, which is based on the dominant multiscale, multidirection edge expression and outstanding edge location of NSCT. Through real images experiments, simulation results demonstrate that the proposed method is better than other edge detection methods based on Canny operator, wavelet and contourlet. Additionally, the proposed method also works well for noisy images.

Keywords: edge detection, NSCT, shift invariant, modulus maxima

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Authors: Murad Aydin Şanda, Hasan Hüseyi̇n Doğan

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Twenty-two element contents were analyzed in five wild Agaricus and Agrocybe taxa [Agaricus bresadolanus Bohus, Agaricus essettei Bon, Agaricus xanthoderma Genev. Agrocybe paludosa (J.E. Lange) Kühner & Romagn. Ex Bon and Agrocybe praecox (Pers.) Fayod] from Marmara region of Turkey by ICP-AES equipment. The element uptake levels were observed at different amounts in each Agaricus and Agrocybe species. The highest Pb and P concentrations were determined as 16.74 and 1.501 mg.kg-1 in A. essettei and A.bresadolanus respectively. Ag, P, and Hg concentrations were determined as 30685, 1,501, and 5978 mg.kg-1 in A. bresadolanus respectively. A. essettei has highest Ni, Cu, and Mn concentrations as 37.1, 43.63 and 1476 mg.kg-1 respectively, whereas A. praecox has highest Mo, Ni and P as 0.54, 10.20 and 27.9 mg.kg-1 respectively. A. paludosa has highest Zn, Cd, and Ba concentration as 336.8, 2.26 and 571.5 mg.kg-1 respectively. The highest K concentration was found in A. xanthoderma with 5.31 mg.kg-1. According to Who and FAO critters, identified metals in Agaricus and Agrocybe genera are not harmful to People if they would be consumed.

Keywords: agaricus, element, macrofungi, Turkey

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Authors: Sumira Jan, Javid Iqbal Mir, Desh Beer Singh, Anil Sharma, Shafia Zaffar Faktoo

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Background and Aims: Climatic and edaphic factors immensely influence crop quality and proper development. Regardless of economic potential, Himalayan Oregano has not subjected to phytonutrient and chemometric evaluation and its relationship with environmental conditions are scarce. The central objective of this research was to investigate microclimatic variation among wild and cultivated populations located in a microclimatic gradient in north-western Himalaya, Kashmir and analyse if such disparity was related with diverse climatic and edaphic conditions. Methods: Micrometeorological, Atomic absorption spectroscopy for micro elemental analysis was carried for soil. HPLC was carried out to estimate variation in phytonutrients and phytochemicals. Results: Geographic variation in phytonutrient was observed among cultivated and wild populations and among populations diverse within regions. Cultivated populations exhibited comparatively lesser phytonutrient value than wild populations. Moreover, our results observed higher vegetative growth of O. vulgare L. with higher pH (6-7), elevated organic carbon (2.42%), high nitrogen (97.41Kg/ha) and manganese (10-12ppm) and zinc contents (0.39-0.50) produce higher phytonutrients. HPLC data of phytonutrients like quercetin, betacarotene, ascorbic acid, arbutin and catechin revealed direct relationship with UV-B flux (r2=0.82), potassium (r2=0.97) displaying parallel relationship with phytonutrient value. Conclusions: Catechin was found as predominant phytonutrient among all populations with maximum accumulation of 163.8 ppm while as quercetin exhibited lesser value. Maximum arbutin (53.42ppm) and quercetin (2.87ppm) accumulated in plants thriving under intense and high UV-B flux. Minimum variation was demonstrated by beta carotene and ascorbic acid.

Keywords: phytonutrient, ascorbic acid, beta carotene, quercetin, catechin

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

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Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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Authors: Preeti Virkar, V. P. Uniyal, Vinod Kumar Bhatt

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With 50% decline in managed honey bee hives in the continents of Europe and America, farmers and landscape managers are turning to native wild bees for their essential ecosystem services of pollination. Wild bees population are too under danger due to the rapid land use changes from anthropogenic activities. With an escalating population reaching 9.0 billion by 2050, human-induced land use changes are predicted to further deteriorate the habitats of numerous species by the turn of this century. The status of bees are uncertain, especially in the tropical regions of the world, which also questions the crisis of global pollinator decline and their essential services to wild and managed flora. Our investigation collectively compares wild native bee diversity and their status in forests and agroecosystems in Doon Valley landscape, situated at the foothills of Himalayan ranges, Uttarakhand, India. We seek to ask whether (1) natural habitat are refuge to richer and rarer bees communities than the agroecosystems, (2) Are agroecosystems closer to natural habitats similar to them than agroecosystems farther away; hence support richer bee communities and hence, (3) Do polyculture farms support richer bee communities than monoculture. The data was collected using observation and pantrap sampling form February to May, 2012 to 2014. We recorded 43 species of bees in Doon Valley. They belonged to 5 families; Megachilidae, Apidae, Andrenidae, Halictidae and Collitidae. A multinomial model approach was used to classify the bees into 2 habitats, in which forests demonstrated to support greater number of specialist (26%, n= 11) species than agroecosystems (7%, n= 3). The valley had many species categorized as the rare (58%, n= 25) and very few generalists (9%, n=4). A linear regression model run on our data demonstrated higher bee diversity in agro-ecosystems in close proximity to forests (H’ for < 200 m = 1.60) compared to those further away (H’ for > 600 m = 0.56) (R2=0.782, SE=0.148, p value=0.004). Organic agriculture supported significantly greater species richness in comparison to conventional farms (Mann-Whitney U test, n1 = 33, n2 = 35; P = 0.001). Forests ecosystems are refuge to rare specialist groups and support bee communities in nearby agroecosystems. The findings of our investigation demonstrate the importance of natural habitats as a potential refuge for rare native wild bee pollinators. Polyculture in the valley behaves similar to natural habitats and supports diverse bee communities in comparison to conventional monocultures. Our study suggests that the farming communities adopt diverse organic agriculture systems to attract wild pollinators beneficial for better crop production. Forests are sanctuaries for bees to nest, forage, and breed. Therefore, our outcome also suggests landscape managers not only preserve protected areas but also enhance the floral diversity in semi-natural and urban areas.

Keywords: native bees, pollinators, polyculture, agroecosystem, natural habitat, diversity, monoculture, specialists, generalists

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Authors: Oluwole Opeyemi Dina, Saheed E. Elugoke, Peter Olutope Fayemi, Omolola E. Fayemi

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This study presents the detection of epinephrine (EP) at Fe₃O₄ modified screen printed silver electrode (SPSE). The iron oxide (Fe₃O₄) nanoparticles were characterized with UV-visible spectroscopy, Fourier-Transform infrared spectroscopy (FT-IR) and Scanning electron microscopy (SEM) prior to the modification of the SPSE. The EP oxidation peak current (Iap) increased with an increase in the concentration of EP as well as the scan rate (from 25 - 400 mVs⁻¹). Using cyclic voltammetry (CV), the relationship between Iap and EP concentration was linear over a range of 3.8 -118.9 µM and 118.9-175 µM with a detection limit of 41.99 µM and 83.16 µM, respectively. Selective detection of EP in the presence of ascorbic acid was also achieved at this electrode.

Keywords: screenprint electrode, iron oxide nanoparticle, epinephrine, serum, cyclic voltametry

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Authors: Ergun Sakalar, Kubra Bilgic

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Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: A. A. Dare, E. U. Iniegbedion

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Industrial furnaces generally involve enclosures of fire typically initiated by the combustion of gases. The fire leads to temperature distribution inside the enclosure. A proper understanding of the temperature and velocity distribution within the enclosure is often required for optimal design and use of the furnace. This study was therefore directed at numerical modeling of temperature distribution inside an enclosure as typical in a furnace. A mathematical model was developed from the conservation of mass, momentum and energy. The stream function-vorticity formulation of the governing equations was solved by an alternating direction implicit (ADI) finite difference technique. The finite difference formulation obtained were then developed into a computer code. This was used to determine the temperature, velocities, stream function and vorticity. The effect of the wall heat conduction was also considered, by assuming a one-dimensional heat flow through the wall. The computer code (MATLAB program) developed was used for the determination of the aforementioned variables. The results obtained showed that the transient temperature distribution assumed a uniform profile which becomes more chaotic with increasing time. The vertical velocity showed increasing turbulent behavior with time, while the horizontal velocity assumed decreasing laminar behavior with time. All of these behaviours were equally reported in the literature. The developed model has provided understanding of heat transfer process in an industrial furnace.

Keywords: heat source, modelling, enclosure, furnace

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Authors: Bendiabdellah Azzeddine, Cherif Bilal Djamal Eddine

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The three-phase power converter voltage structure is widely used in many power applications but its failure can lead to partial or total loss of control of the phase currents and can cause serious system malfunctions or even a complete system shutdown. To ensure continuity of service in all circumstances, effective and rapid techniques of detection and location of inverter fault is to be implemented. The present paper is dedicated to open-circuit fault detection in a three-phase two-level inverter fed induction motor. For detection purpose, the proposed contribution addresses the Park’s current vectors associated to a polar coordinates calculation tool to compute the exact value of the fault angle corresponding directly to the faulty IGBT switch. The merit of the proposed contribution is illustrated by experimental results.

Keywords: diagnosis, detection, Park’s vectors, polar coordinates, open-circuit fault, inverter, IGBT switch

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Authors: Rana Gill, Chandandeep Kaur

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Segmentation of images can be implemented using different fundamental algorithms like edge detection (discontinuity based segmentation), region growing (similarity based segmentation), iterative thresholding method. A comprehensive literature review relevant to the study gives description of different techniques for vehicle number plate detection and edge detection techniques widely used on different types of images. This research work is based on edge detection techniques and calculating threshold on the basis of five edge operators. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny. Segmentation of characters present in different type of images like vehicle number plate, name plate of house and characters on different sign boards are selected as a case study in this work. The proposed methodology has seven stages. The proposed system has been implemented using MATLAB R2010a. Comparison of all the five operators has been done on the basis of their performance. From the results it is found that Canny operators produce best results among the used operators and performance of different edge operators in decreasing order is: Canny>Log>Sobel>Prewitt>Roberts.

Keywords: segmentation, edge detection, text, extracting characters

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Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

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Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

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Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

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Authors: Peter U. Eze, P. Udaya, Robin J. Evans

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Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

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Authors: Thilivhali Emmanuel Tshikalange, Darky Cheron Modishane, Frederick Tawi Tabit

Abstract:

The fruit pulp extracts of twelve selected ethnobotanical wild edible fruits from Mutale local municipality in Venda (Limpopo Province, South Africa) were investigated for their antimicrobial, antioxidant and cytotoxicity activities. Methanol extracts were prepared and tested against six micro-organisms (Salmonella typhi, Streptococcus pyogenes, Bacillus cereus, Klebsiella pneumoniae, Prevotella intermedia and Candida albicans). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined using the micro-dilution method, while for antioxidant activity the 2,2-diphenyl-1-picrylhydrazyl method was used. Of the 12 extracts tested, Adonsonia digitata, Berchemia discolor, Manilkara mochisia, Xanthocercis zambesiaca, Landolphia kirkii and Garcinia livingstonei showed antimicrobial activity, with MIC values ranging from 12.5 to 0.4 mg/ml. Gram negative bacteria were more resistant to the extracts in comparison to Gram positive bacteria. Antioxidant activity was only detected in Adonsonia digitata extract and the IC50 (substrate concentration to produce 50% reduction) was found to be 16.18µg/ml. The cytotoxicity of the extracts that showed antimicrobial and antioxidant activities was also determined. All plant extracts tested were non-toxic against human kidney cells (HEK293), with IC50 values of >400 µg/ml. The results presented in this study provide support to some traditional uses of wild edible fruits.

Keywords: antimicrobial, antioxidant, cytotoxicity, ethnobotanical, fruits

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Authors: Ji Su Kim, Bo Ram Choi, Ju Yeon Cho, Hyukjin Lee

Abstract:

Epidermal growth factor receptor (EGFR) 19 deletion mutation gene is over-expressed in carcinoma patient. EGFR 19 deletion mutation is known as typical biomarker of non-small cell lung cancer (NSCLC), which one section in the coding exon 19 of EGFR is deleted. Therefore, there have been many attempts over the years to detect EGFR 19 deletion mutation for replacing conventional diagnostic method such as PCR and tissue biopsy. We developed a simple and facile detection platform based on Rolling Circle Amplification (RCA), which provides highly amplified products in isothermal amplification of the ligated DNA template. Limit of detection (~50 nM) and a faster detection time (~30 min) could be achieved by introducing RCA.

Keywords: EGFR19, cancer, diagnosis, rolling circle amplification (RCA), hydrogel

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Tian Xia, Yuan Yan Tang

Abstract:

In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

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Authors: Laid Fekih

Abstract:

Background: It is difficult to detect lying, deception, and misrepresentation just by looking at verbal or non-verbal expression during the criminal investigation process, as there is a common belief that it is possible to tell whether a person is lying or telling the truth just by looking at the way they act or behave. The process of detecting lies and deception during the criminal investigation process needs more studies and research to overcome the difficulties facing the investigators. Method: The present study aimed to identify the effectiveness of cognitive methods and techniques in detecting deception during the criminal investigation. It adopted the quasi-experimental method and covered a sample of (20) defendants distributed randomly into two homogeneous groups, an experimental group of (10) defendants be subject to criminal investigation by applying cognitive techniques to detect deception and a second experimental group of (10) defendants be subject to the direct investigation method. The tool that used is a guided interview based on models of investigative questions according to the cognitive deception detection approach, which consists of three techniques of Vrij: imposing the cognitive burden, encouragement to provide more information, and ask unexpected questions, and the Direct Investigation Method. Results: Results revealed a significant difference between the two groups in term of lie detection accuracy in favour of defendants be subject to criminal investigation by applying cognitive techniques, the cognitive deception detection approach produced superior total accuracy rates both with human observers and through an analysis of objective criteria. The cognitive deception detection approach produced superior accuracy results in truth detection: 71%, deception detection: 70% compared to a direct investigation method truth detection: 52%; deception detection: 49%. Conclusion: The study recommended if practitioners use a cognitive deception detection technique, they will correctly classify more individuals than when they use a direct investigation method.

Keywords: the cognitive lie detection approach, deception, criminal investigation, mental health

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Authors: Pratham Madnur, Prathamkumar Shetty, Sneha Varur, Gouri Parashetti

Abstract:

In order to overcome conventional obstacles, this research paper investigates novel approaches for cricket pitch and ball detection that make use of cutting-edge technologies. The research integrates OpenCV for pitch inspection and modifies the YOLOv8 model for cricket ball detection in order to overcome the shortcomings of manual pitch assessment and traditional ball detection techniques. To ensure flexibility in a range of pitch environments, the pitch detection method leverages OpenCV’s color space transformation, contour extraction, and accurate color range defining features. Regarding ball detection, the YOLOv8 model emphasizes the preservation of minor object details to improve accuracy and is specifically trained to the unique properties of cricket balls. The methods are more reliable because of the careful preparation of the datasets, which include novel ball and pitch information. These cutting-edge methods not only improve cricket analytics but also set the stage for flexible methods in more general sports technology applications.

Keywords: OpenCV, YOLOv8, cricket, custom dataset, computer vision, sports

Procedia PDF Downloads 68