Search results for: blue color detection
1487 Comparative in vitro Anticancer Activity of Two Siddha Formulations: Neeradi Muthu Vallathymezugu and Thamira Kattu Chendooram
Authors: Vasudha Devi, Arul Amuthan, K. Narayanan, Praveen KS, Venkata Rao J
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Background: Siddha Medicine is one of the Indian traditional medical systems, in which the cancer disease is mentioned as 'putrunoi' which literally means the disease of growth like termite mound. There are number of formulations available for the treatment of cancer disease. Neeradi muthu vallathymezugu (NMV) and thamira kattu chendooram (TKC) are two drugs commonly prescribed by Siddha physicians. These drugs have been clinically reported to be safe and effective when given orally. Though these formulations are in practice for centuries, no efforts have been made to standardize them and explore their anti-cancer potential systematically. Objective: To compare the cytotoxic activity of NMV and TKC with doxorubicin using cancer cell lines. Materials and methods: For this study, ethanol extract of NMV was taken, whereas TKC was used as such. In vitro cytotoxic activity was evaluated by sulphorhodamine (SRB) assay against human hepatic cancer cells (HepG2), human breast cancer cells (MCF-7) and human cervical cancer cells [KeLa]. Doxorubicin was used as the standard. The SRB assay is based on the ability of cellular proteins to bind with sulphorhodamine-B. The number of live cells in drug treated cell lines directly affects the color formation in the assay, which is estimated calorimetrically by measuring the absorbance at 540 nm to calculate the cytotoxicity (inhibitory concentration - IC50 value) of the drug. Results: The IC50values of NMV, TKC and doxorubicin against HepG2 were 3.08 µg/ml, 20.21 µg/ml and 1.21µg/ml respectively. In MCF-7, it was 11.75 µg/ml, 17.67 µg/ml and 2.8µg/ml. In HeLa, the values were 24.76 µg/ml, 73.35 µg/ml and 1.12µg/ml. Conclusions: The study proves the possible anti-cancer potential of these two formulations. Compared to TKC, NMV showed good cytotoxic effect even at low dose. Human hepatic cancer cells responded well even at very low dose, when compared to other cancer cells. Though, cytotoxic potential of these compounds was found to be less compared to doxorubicin, the isolated lead compound may have the potential to be used as an anticancer drug clinically.Keywords: Neeradi muthu vallathymezugu (Hydnocarpus laurifolia), thamira kattu chendooram, cytotoxicity, in-vitro, Siddha Medicine
Procedia PDF Downloads 4731486 Detection of Leishmania Mixed Infection from Phlebotomus papatasi in Central Iran
Authors: Nassibeh Hosseini-Vasoukolaei, Amir Ahmad Akhavan, Mahmood Jeddi-Tehrani, Ali Khamesipour, Mohammad Reza Yaghoobi Ershadi, Kamhawi Shaden, Valenzuela Jesus, Hossein Mirhendi, Mohammad Hossein Arandian
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Zoonotic cutaneous leishmaniasis (ZCL) is an endemic disease in many rural areas of Iran. Sand flies were collected from rural areas of Esfahan province and were identified using valid identification keys. DNA was extracted from sand flies and Nested PCRs were done using specific primers. In this study, 44 out of 152 (28.9 %) sand flies were infected with L. majoralone. Eight sand flies showed mixed infection: four sand flies (2.6 %) were infected with L. major, L. turanicaand L. gerbili, one sand fly (0.7 %) was infected with L. major and L. turanica and three sand flies (2 %) were infected with L. turanicaand L. gerbili. Our results demonstrate the natural infection of P. papatasi sand fly with three species of L. major, L. turanica and L. gerbili which are circulating among R. opimusreservoir host and P. papatasi sand fly vector in central Iran.Keywords: Phlebotomus papatasi, Leishmania major, Leishmania turanica, Leishmania gerbili, mixed infection, Iran
Procedia PDF Downloads 4711485 Mothers and Moneymakers: A Case Study of How Citizen-Women Shape U.S. Marriage Migration Politics Online
Authors: Gina Longo
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Social media, internet technology, and affordable travel have created avenues like tourism and internet chatrooms for Western women to meet foreign partners without paid, third-party intermediaries in regions like the Middle East/North Africa (MENA) and Sub-Saharan Africa (SSA), where men from mid-level developing countries meet and marry Western women and try to relocate. Foreign nationals who marry U.S. citizens have an expedited track to naturalization. U.S. immigration officials require that “green card” petitioning couples demonstrate that their relationships are “valid and subsisting” (i.e., for love) and not fraudulent (i.e., for immigration papers). These requirements are ostensibly gender- and racially-neutral, but migration itself is not; black and white women petitioners who seek partners from these regions and solicit advice from similar others about the potential obstacles to their petitions’ success online. Using an online ethnography and textual analysis of conversation threads on a large on-line immigration forum where U.S. petitioners exchange such information, this study examines how gendered and racialized standards of legitimacy are applied to family and sexuality and used discursively online among women petitioners differently to achieve “genuineness” and define “red flags” indicating potential marriage fraud. This paper argues that forum-women members police immigration requests even before cases reach an immigration officer, and use this social media platform to reconstruct gendered and racialized hierarchies of U.S. citizenship. Women petitioners use the formal criteria of U.S. immigration in ways that reveal gender and racial ideologies, expectations for conformity to a gendered hegemonic family ideal, and policing of women’s sexual agency, fertility, and desirability. These intersectional norms shape their online discussions about the suitability of marriages and of the migration of non-citizen male partners of color to the United States.Keywords: marriage fraud, migration, online forums, women
Procedia PDF Downloads 1201484 Addressing Security and Privacy Issues in a Smart Environment by Using Block-Chain as a Preemptive Technique
Authors: Shahbaz Pervez, Aljawharah Almuhana, Zahida Parveen, Samina Naz, Hira Tariq, Seyed Hosseini, Muhammad Awais Azam
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With the latest development in the field of cutting-edge technologies, there is a rapid increase in the use of technology-oriented gadgets. In a recent scenario of the tech era, there is increasing demand to fulfill our day-to-day routine tasks with the help of technological gadgets. We are living in an era of technology where trends have been changing, and a race to introduce a new technology gadget has already begun. Smart cities are getting more popular with every passing day; city councils and governments are under enormous pressure to provide the latest services for their citizens and equip them with all the latest facilities. Thus, ultimately, they are going more into smart cities infrastructure building, providing services to their inhabitants with a single click from their smart devices. This trend is very exciting, but on the other hand, if some incident of security breach happens due to any weaker link, the results would be catastrophic. This paper addresses potential security and privacy breaches with a possible solution by using Blockchain technology in IoT enabled environment.Keywords: blockchain, cybersecurity, DDOS, intrusion detection, IoT, RFID, smart devices security, smart services
Procedia PDF Downloads 1191483 Evaluation of Biochemical Parameters in the Blood of Dromedary (Camelus Dromedarius)
Authors: M. Titaouine, T. Meziane, K. Deghnouche
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The purpose of this study was to determine reference serum biochemistry values from dromedary (Camelus dromedarius) in Algeria and to evaluate potential sources of physiological variability such as the sex, age and season on serum data. Usual serum biochemistry values were determined in blood samples from 26 apparently healthy dromedaries, 11 males and 15 females, divided into 3 lots (ender 4years), (between 5 and 10 years), (up 10 years). Parametric reference ranges and physiological variations are determined for calcium (Ca), organic phosphate (P), magnesium (Mg), natrium (Na), potassium (K), iron (Fe), glucose, triglycerides (TG), cholesterol, urea, creatinine, total proteins and albumin. The results demonstrate: * Values which agreed with literature * Significant statistically differences (Anova test, p < 0.05) depending on: -the sex for Na, glucose, TG, cholesterol, urea, creatinine, albumin, -the age for Ca, P, K, Mg, glucose, TG, b and g globulin, -and season for Fe, urea, total proteins, TG, cholesterol and glucose. These reference ranges for serum biochemical analysis can be used for metabolic and nutritional disorders detection in dromedary.Keywords: age, biochemistry, dromadery, season, sex
Procedia PDF Downloads 3751482 Vision Aided INS for Soft Landing
Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj
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The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering
Procedia PDF Downloads 4661481 Novel NIR System for Detection of Internal Disorder and Quality of Apple Fruit
Authors: Eid Alharbi, Yaser Miaji
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The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology
Procedia PDF Downloads 3861480 Biodiversity of Pathogenic and Toxigenic Fungi Associated with Maize Grains Sampled across Egypt
Authors: Yasser Shabana, Khaled Ghoneem, Nehal Arafat, Younes Rashad, Dalia Aseel, Bruce Fitt, Aiming Qi, Benjamine Richard
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Providing food for more than 100 million people is one of Egypt's main challenges facing development. The overall goal is to formulate strategies to enhance food security in light of population growth. Two hundred samples of maize grains from 25 governates were collected. For the detection of seed-borne fungi, the deep-freezing blotter method (DFB) and washing method (ISTA 1999) were used. A total of 41 fungal species was recovered from maize seed samples. Weather data from 30 stations scattered all over Egypt and covering the major maize growing areas were obtained. Canonical correspondence analysis of data for the obtained fungal genera with temperature, relative humidity, precipitation, wind speed, or solar radiation revealed that relative humidity, temperature and wind speed were the most influential weather variables.Keywords: biodiversity, climate change, maize, seed-borne fungi
Procedia PDF Downloads 1621479 Simple Ecofriendly Cyclodextrine-Surfactant Modified UHPLC Method for Quantification of Multivitamins in Pharmaceutical and Food Samples
Authors: Hassan M. Albishri, Abdullah Almalawi, Deia Abd El-Hady
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A simple and ecofriendly cyclodextrine-surfactant modified UHPLC (CDS-UPLC) method for rapid and sensitive simultaneous determination of multi water-soluble vitamins such as ascorbic acid, pyridoxine hydrochloride and thiamine hydrochloride in commercial pharmaceuticals and milk samples have been firstly developed. Several chromatographic effective parameters have been changed in a systematic way. Adequate results have been achieved by a mixture of β-cyclodextrine (β-CD) and cationic surfactant under acidic conditions as an eco-friendly isocratic mobile phase at 0.02 mL/min flow rate. The proposed CDS- UHPLC method has been validated for the quantitative determination of multivitamins within 8 min in food and pharmaceutical samples. The method showed excellent linearity for analytes in a wide range of 10-1000 ng/µL. The repeatability and reproducibility of data were about 2.14 and 4.69 RSD%, respectively. The limits of detection (LODs) of analytes ranged between 0.86 and 5.6 ng/µL with a range of 81.8 -115.8% recoveries in tablets and milk samples. The current first CDS- UHPLC method could have vast applications for the precise analysis of multivitamins in complicated matrices.Keywords: ecofriendly, cyclodextrine-surfactant, multivitamins, UHPLC
Procedia PDF Downloads 2731478 Optimization of Solar Tracking Systems
Authors: A. Zaher, A. Traore, F. Thiéry, T. Talbert, B. Shaer
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In this paper, an intelligent approach is proposed to optimize the orientation of continuous solar tracking systems on cloudy days. Considering the weather case, the direct sunlight is more important than the diffuse radiation in case of clear sky. Thus, the panel is always pointed towards the sun. In case of an overcast sky, the solar beam is close to zero, and the panel is placed horizontally to receive the maximum of diffuse radiation. Under partly covered conditions, the panel must be pointed towards the source that emits the maximum of solar energy and it may be anywhere in the sky dome. Thus, the idea of our approach is to analyze the images, captured by ground-based sky camera system, in order to detect the zone in the sky dome which is considered as the optimal source of energy under cloudy conditions. The proposed approach is implemented using experimental setup developed at PROMES-CNRS laboratory in Perpignan city (France). Under overcast conditions, the results were very satisfactory, and the intelligent approach has provided efficiency gains of up to 9% relative to conventional continuous sun tracking systems.Keywords: clouds detection, fuzzy inference systems, images processing, sun trackers
Procedia PDF Downloads 1921477 Identification of the Usage of Some Special Places in the Prehistoric Site of Tapeh Zagheh through Multi-Elemental Chemical Analysis of the Soil Samples
Authors: Iraj Rezaei, Kamal Al Din Niknami
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Tapeh Zagheh is an important prehistoric site located in the central plateau of Iran, which has settlement layers of the Neolithic and Chalcolithic periods. For this research, 38 soil samples were collected from different parts of the site, as well as two samples from its outside as witnesses. Then the samples were analyzed by XRF. The purpose of this research was to identify some places with special usage for human activities in Tapeh Zagheh by measuring the amount of some special elements in the soil. The result of XRF analysis shows a significant amount of P and K in samples No.3 (fourth floor) and No.4 (third floor), probably due to certain activities such as food preparation and consumption. Samples No.9 and No.10 can be considered suitable examples of the hearths of the prehistoric period in the central plateau of Iran. The color of these samples was completely darkened due to the presence of ash, charcoal, and burnt materials. According to the XRF results, the soil of these hearths has very high amounts of elements such as P, Ca, Mn, S, K, and significant amounts of Ti, Fe, and Na. In addition, the elemental composition of sample No. 14, which was taken from a home waster, also has very high amounts of P, Mn, Mg, Ti, and Fe and high amounts of K and Ca. Sample No. 11, which is related to soil containing large amounts of waster of the kiln, along with a very strong increase in Cl and Na, the amount of elements such as K, Mg, and S has also increased significantly. It seems that the reason for the increase of elements such as Ti and Fe in some Tapeh Zagheh floors (for example, samples number 1, 2, 3, 4, 5) was the use of materials such as ocher mud or fire ash in the composition of these floors. Sample No. 13, which was taken from an oven located in the FIX trench, has very high amounts of Mn, Ti, and Fe and high amounts of P and Ca. Sample No. 15, which is related to House No. VII (probably related to a pen or a place where animals were kept) has much more phosphate compared to the control samples, which is probably due to the addition of animal excrement and urine to the soil. Sample No. 29 was taken from the north of the industrial area of Zagheh village (place of pottery kilns). The very low amount of index elements in sample No. 29 shows that the industrial activities did not extend to the mentioned point, and therefore, the range of this point can be considered as the boundary between the residential part of the Zagheh village and its industrial part.Keywords: prehistory, multi-elemental analysis, Tapeh Zagheh, XRF
Procedia PDF Downloads 921476 Tumor Boundary Extraction Using Intensity and Texture-Based on Gradient Vector
Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi
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In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture
Procedia PDF Downloads 4321475 Microplastics Accumulation and Abundance Standardization for Fluvial Sediments: Case Study for the Tena River
Authors: Mishell E. Cabrera, Bryan G. Valencia, Anderson I. Guamán
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Human dependence on plastic products has led to global pollution, with plastic particles ranging in size from 0.001 to 5 millimeters, which are called microplastics (hereafter, MPs). The abundance of microplastics is used as an indicator of pollution. However, reports of pollution (abundance of MPs) in river sediments do not consider that the accumulation of sediments and MPs depends on the energy of the river. That is, the abundance of microplastics will be underestimated if the sediments analyzed come from places where the river flows with a lot of energy, and the abundance will be overestimated if the sediment analyzed comes from places where the river flows with less energy. This bias can generate an error greater than 300% of the MPs value reported for the same river and should increase when comparisons are made between 2 rivers with different characteristics. Sections where the river flows with higher energy allow sands to be deposited and limit the accumulation of MPs, while sections, where the same river has lower energy, allow fine sediments such as clays and silts to be deposited and should facilitate the accumulation of MPs particles. That is, the abundance of MPs in the same river is underrepresented when the sediment analyzed is sand, and the abundance of MPs is overrepresented if the sediment analyzed is silt or clay. The present investigation establishes a protocol aimed at incorporating sample granulometry to calibrate MPs quantification and eliminate over- or under-representation bias (hereafter granulometric bias). A total of 30 samples were collected by taking five samples within six work zones. The slope of the sampling points was less than 8 degrees, referred to as low slope areas, according to the Van Zuidam slope classification. During sampling, blanks were used to estimate possible contamination by MPs during sampling. Samples were dried at 60 degrees Celsius for three days. A flotation technique was employed to isolate the MPs using sodium metatungstate with a density of 2 gm/l. For organic matter digestion, 30% hydrogen peroxide and Fenton were used at a ratio of 6:1 for 24 hours. The samples were stained with rose bengal at a concentration of 200 mg/L and were subsequently dried in an oven at 60 degrees Celsius for 1 hour to be identified and photographed in a stereomicroscope with the following conditions: Eyepiece magnification: 10x, Zoom magnification (zoom knob): 4x, Objective lens magnification: 0.35x for analysis in ImageJ. A total of 630 fibers of MPs were identified, mainly red, black, blue, and transparent colors, with an overall average length of 474,310 µm and an overall median length of 368,474 µm. The particle size of the 30 samples was calculated using 100 g per sample using sieves with the following apertures: 2 mm, 1 mm, 500 µm, 250 µm, 125 µm and 0.63 µm. This sieving allowed a visual evaluation and a more precise quantification of the microplastics present. At the same time, the weight of sediment in each fraction was calculated, revealing an evident magnitude: as the presence of sediment in the < 63 µm fraction increases, a significant increase in the number of MPs particles is observed.Keywords: microplastics, pollution, sediments, Tena River
Procedia PDF Downloads 731474 Winter Wheat Yield Forecasting Using Sentinel-2 Imagery at the Early Stages
Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong
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Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale
Procedia PDF Downloads 641473 The Predictive Value of Serum Bilirubin in the Post-Transplant De Novo Malignancy: A Data Mining Approach
Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim
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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantationKeywords: De novo malignancy, bilirubin, data mining, transplantation
Procedia PDF Downloads 1051472 Space Tourism Pricing Model Revolution from Time Independent Model to Time-Space Model
Authors: Kang Lin Peng
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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature
Procedia PDF Downloads 1291471 A Near-Optimal Domain Independent Approach for Detecting Approximate Duplicates
Authors: Abdelaziz Fellah, Allaoua Maamir
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We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery
Procedia PDF Downloads 3871470 Classification of Echo Signals Based on Deep Learning
Authors: Aisulu Tileukulova, Zhexebay Dauren
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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.Keywords: radar, neural network, convolutional neural network, echo signals
Procedia PDF Downloads 3531469 Reinforced Concrete Bridge Deck Condition Assessment Methods Using Ground Penetrating Radar and Infrared Thermography
Authors: Nicole M. Martino
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Reinforced concrete bridge deck condition assessments primarily use visual inspection methods, where an inspector looks for and records locations of cracks, potholes, efflorescence and other signs of probable deterioration. Sounding is another technique used to diagnose the condition of a bridge deck, however this method listens for damage within the subsurface as the surface is struck with a hammer or chain. Even though extensive procedures are in place for using these inspection techniques, neither one provides the inspector with a comprehensive understanding of the internal condition of a bridge deck – the location where damage originates from. In order to make accurate estimates of repair locations and quantities, in addition to allocating the necessary funding, a total understanding of the deck’s deteriorated state is key. The research presented in this paper collected infrared thermography and ground penetrating radar data from reinforced concrete bridge decks without an asphalt overlay. These decks were of various ages and their condition varied from brand new, to in need of replacement. The goals of this work were to first verify that these nondestructive evaluation methods could identify similar areas of healthy and damaged concrete, and then to see if combining the results of both methods would provide a higher confidence than if the condition assessment was completed using only one method. The results from each method were presented as plan view color contour plots. The results from one of the decks assessed as a part of this research, including these plan view plots, are presented in this paper. Furthermore, in order to answer the interest of transportation agencies throughout the United States, this research developed a step-by-step guide which demonstrates how to collect and assess a bridge deck using these nondestructive evaluation methods. This guide addresses setup procedures on the deck during the day of data collection, system setups and settings for different bridge decks, data post-processing for each method, and data visualization and quantification.Keywords: bridge deck deterioration, ground penetrating radar, infrared thermography, NDT of bridge decks
Procedia PDF Downloads 1541468 Quality Assessment of Some Selected Locally Produced and Marketed Soft Drinks
Authors: Gerardette Darkwah, Gloria Ankar Brewoo, John Barimah, Gilbert Owiah Sampson, Vincent Abe-Inge
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Soft drinks which are widely consumed in Ghana have been reported in other countries to contain toxic heavy metals beyond the acceptable limits in other countries. Therefore, the objective of this study was to assess the quality characteristics of selected locally produced and marketed soft drinks. Three (3) different batches of 23 soft drinks were sampled from the Takoradi markets. The samples were prescreened for the presence of reducing sugars, phosphates, alcohol and carbon dioxide. The heavy metal contents and physicochemical properties were also determined with AOAC methods. The results indicated the presence of reducing sugars, carbon dioxide and the absence of alcohol in all the selected soft drink samples. The pH, total sugars, moisture, total soluble solids (TSS) and titratable acidity ranged from 2.42 – 3.44, 3.30 – 10.44%, 85.63 – 94.85%, 5.00 – 13.33°Brix, and 0.21 – 1.99% respectively. The concentration of heavy metals were also below detection limits in all samples. The quality of the selected were within specifications prescribed by regulatory bodies.Keywords: heavy metal contamination, locally manufactured, quality, soft drinks
Procedia PDF Downloads 1481467 Static Eccentricity Fault Diagnosis in Synchronous Reluctance Motor and Permanent Magnet Assisted Synchronous Reluctance Motor
Authors: M. Naeimi, H. Aghazadeh, E. Afjei, A. Siadatan
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In this paper, a novel view of air gap magnetic field analysis of synchronous reluctance motor and permanent magnet assisted synchronous reluctance motor under static eccentricity to provide the precise fault diagnosis based on three-dimensional finite element method is presented. Analytical nature of this method makes it possible to simulate reliable and precise model by considering the end effects and axial fringing effects. The results of the three-dimensional finite element analysis of synchronous reluctance motor and permanent magnet synchronous reluctance motor such as flux linkage, flux density, and compression both of SynRM and PM-SynRM for various eccentric motor conditions are obtained and analyzed. These results present useful information regarding to the detection of static eccentricity.Keywords: synchronous reluctance motor (SynRM), permanent magnet assisted synchronous reluctance motor (PMaSynRM), finite element method, static eccentricity, fault analysis
Procedia PDF Downloads 3111466 Malaria Parasite Detection Using Deep Learning Methods
Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko
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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.Keywords: convolution neural network, deep learning, malaria, thin blood smears
Procedia PDF Downloads 1301465 Natural Radioactivity in Foods Consumed in Turkey
Authors: E. Kam, G. Karahan, H. Aslıyuksek, A. Bozkurt
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This study aims to determine the natural radioactivity levels in some foodstuffs produced in Turkey. For this purpose, 48 different foods samples were collected from different land parcels throughout the country. All samples were analyzed to designate both gross alpha and gross beta radioactivities and the radionuclides’ concentrations. The gross alpha radioactivities were measured as below 1 Bq kg-1 in most of the samples, some of them being due to the detection limit of the counting system. The gross beta radioactivity levels ranged from 1.8 Bq kg-1 to 453 Bq kg-1, larger levels being observed in leguminous seeds while the highest level being in haricot bean. The concentrations of natural radionuclides in the foodstuffs were investigated by the method of gamma spectroscopy. High levels of 40K were measured in all the samples, the highest activities being again in leguminous seeds. Low concentrations of 238U and 226Ra were found in some of the samples, which are comparable to the reported results in the literature. Based on the activity concentrations obtained in this study, average annual effective dose equivalents for the radionuclides 226Ra, 238U, and 40K were calculated as 77.416 µSv y-1, 0.978 µSv y-1, and 140.55 µSv y-1, respectively.Keywords: foods, radioactivity, gross alpha, gross beta, annual equivalent dose, Turkey
Procedia PDF Downloads 4541464 Clinical and Molecular Characterization of Mycoplasmosis in Sheep in Egypt
Authors: Walid Mousa, Mohamed Nayel, Ahmed Zaghawa, Akram Salama, Ahmed El-Sify, Hesham Rashad, Dina El-Shafey
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Mycoplasmosis in small ruminants constitutes a serious contagious problem in smallholders causing severe economic losses worldwide. This study was conducted to determine the clinical, Minimum Inhibitory Concentration (MIC) and molecular characterization of Mycoplasma species associated in sheep breeding herds in Menoufiya governorate, Egypt. Out of the examination of 400 sheep, 104 (26%) showed respiratory manifestations, nasal discharges, cough and conjunctivitis with systemic body reaction. Meanwhile, out of these examined sheep, only 56 (14%) were positive for mycoplasma isolation onto PPLO(Pleuropneumonia-like organisms) specific medium. The MIC for evaluating the efficacy of sensitivity of Mycoplasma isolates against different antibiotics groups revealed that both the Linospectin and Tylosin with 2ug, 0.25ug/ml concentration were the most effective antibiotics for Mycoplasma isolates. The application of PCR was the rapid, specific and sensitive molecular approach for detection of M. ovipneumoniae, and M. arginine at 390 and 326 bp, respectively, in all tested isolates. In conclusion, the diagnosis of Mycoplsamosis in sheep is important to achieve effective control measures and minimizing the disease dissemination among sheep herds.Keywords: MIC, mycoplasmosis, PCR, sheep
Procedia PDF Downloads 2281463 An Industrial Workplace Alerting and Monitoring Platform to Prevent Workplace Injury and Accidents
Authors: Sanjay Adhikesaven
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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.Keywords: computer vision, deep learning, workplace safety, automation
Procedia PDF Downloads 1031462 Evaluation of Iron Application Method to Remediate Coastal Marine Sediment
Authors: Ahmad Seiar Yasser
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Sediment is an important habitat for organisms and act as a store house for nutrients in aquatic ecosystems. Hydrogen sulfide is produced by microorganisms in the water columns and sediments, which is highly toxic and fatal to benthic organisms. However, the irons have the capacity to regulate the formation of sulfide by poising the redox sequence and to form insoluble iron sulfide and pyrite compounds. Therefore, we conducted two experiments aimed to evaluate the remediation efficiency of iron application to organically enrich and improve sediments environment. Experiments carried out in the laboratory using intact sediment cores taken from Mikawa Bay, Japan at every month from June to September 2017 and October 2018. In Experiment 1, after cores were collected, the iron powder or iron hydroxide were applied to the surface sediment with 5 g/ m2 or 5.6 g/ m2, respectively. In Experiment 2, we experimentally investigated the removal of hydrogen sulfide using (2mm or less and 2 to 5mm) of the steelmaking slag. Experiments are conducted both in the laboratory with the same boundary conditions. The overlying water were replaced with deoxygenated filtered seawater, and cores were sealed a top cap to keep anoxic condition with a stirrer to circulate the overlying water gently. The incubation experiments have been set in three treatments included the control, and each treatment replicated and were conducted with the same temperature of the in-situ conditions. Water samples were collected to measure the dissolved sulfide concentrations in the overlying water at appropriate time intervals by the methylene blue method. Sediment quality was also analyzed after the completion of the experiment. After the 21 days incubation, experimental results using iron powder and ferric hydroxide revealed that application of these iron containing materials significantly reduced sulfide release flux from the sediment into the overlying water. The average dissolved sulfides concentration in the overlying water of the treatment group was significantly decrease (p = .0001). While no significant difference was observed between the control group after 21 day incubation. Therefore, the application of iron to the sediment is a promising method to remediate contaminated sediments in a eutrophic water body, although ferric hydroxide has better hydrogen sulfide removal effects. Experiments using the steelmaking slag also clarified the fact that capping with (2mm or less and 2 to 5mm) of slag steelmaking is an effective technique for remediation of bottom sediments enriched organic containing hydrogen sulfide because it leads to the induction of chemical reaction between Fe and sulfides occur in sediments which did not occur in conditions naturally. Although (2mm or less) of slag steelmaking has better hydrogen sulfide removal effects. Because of economic reasons, the application of steelmaking slag to the sediment is a promising method to remediate contaminated sediments in the eutrophic water body.Keywords: sedimentary, H2S, iron, iron hydroxide
Procedia PDF Downloads 1631461 Remote Sensing of Urban Land Cover Change: Trends, Driving Forces, and Indicators
Authors: Wei Ji
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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis
Procedia PDF Downloads 3081460 The Modeling and Effectiveness Evaluation for Vessel Evasion to Acoustic Homing Torpedo
Authors: Li Minghui, Min Shaorong, Zhang Jun
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This paper aims for studying the operational efficiency of surface warship’s motorized evasion to acoustic homing torpedo. It orderly developed trajectory model, self-guide detection model, vessel evasion model, as well as anti-torpedo error model in three-dimensional space to make up for the deficiency of precious researches analyzing two-dimensionally confrontational models. Then, making use of the Monte Carlo method, it carried out the simulation for the confrontation process of evasion in the environment of MATLAB. At last, it quantitatively analyzed the main factors which determine vessel’s survival probability. The results show that evasion relative bearing and speed will affect vessel’s survival probability significantly. Thus, choosing appropriate evasion relative bearing and speed according to alarming range and alarming relative bearing for torpedo, improving alarming range and positioning accuracy and reducing the response time against torpedo will improve the vessel’s survival probability significantly.Keywords: acoustic homing torpedo, vessel evasion, monte carlo method, torpedo defense, vessel's survival probability
Procedia PDF Downloads 4551459 Hybrid Approximate Structural-Semantic Frequent Subgraph Mining
Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi
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Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory
Procedia PDF Downloads 4031458 Humanity's Still Sub-Quantum Core-Self Intelligence
Authors: Andrew Shugyo Daijo Bonnici
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Core-Self Intelligence (CSI) is an absolutely still, non-verbal, non-cerebral intelligence. Our still core-self intelligence is felt at our body's center point of gravity, just an inch below our navel, deep within our lower abdomen. The still sub-quantum depth of core-Self remains untouched by the conditioning influences of family, society, culture, religion, and spiritual views that shape our personalities and ego-self identities. As core-Self intelligence is inborn and unconditioned, it exists within all human beings regardless of age, race, color, creed, mental acuity, or national origin. Our core-self intelligence functions as a wise and compassionate guide that advances our health and well-being, our mental clarity and emotional resiliency, our fearless peace and behavioral wisdom, and our ever-deepening compassion for self and others. Although our core-Self, with its absolutely still non-judgmental intelligence, operates far beneath the functioning of our ego-self identity and our thinking mind, it effectively coexists with our passing thoughts, all of our figuring and thinking, our logical and rational way of knowing, the ebb and flow of our feelings, and the natural or triggered emergence of our emotions. When we allow our whole inner somatic awareness to gently sink into the intelligent center point of gravity within our lower abdomen, the felt arising of our core- Self’s inborn stillness has a serene and relaxing effect on our ego-self and thinking mind. It naturally slows down the speedy passage of our involuntary thoughts, diminishes our ego-self's defensive and reactive functioning, and decreases narcissistic reflections on I, me, and mine. All of these healthy cognitive benefits advance our innate wisdom and compassion, facilitate our personal and interpersonal growth, and liberate the ever-fresh wonder and curiosity of our beginner's heartmind. In conclusion, by studying, exploring, and researching our core-Self intelligence, psychologists and psychotherapists can unlock new avenues for advancing the farther reaches of our mental, emotional, and spiritual health and well-being, our innate behavioral wisdom and boundless empathy, our lucid compassion for self and others, and our unwavering confidence in the still guiding light of our core-Self that exists at the abdominal center point of all human beings.Keywords: intelligence, transpersonal, beginner’s heartmind, compassionate wisdom
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