Search results for: RGB channel extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3217

Search results for: RGB channel extraction

1237 New Strategy for Breeding of Artemisia annua L. for a Sustainable Production of the Antimalarial Drug Artemisinin

Authors: Nadali Babaeian Jelodar, Chan Lai Keng, Arvind Bhatt, Laleh Bordbar, Leow E Shuen, Kamaruzaman Mohamed

Abstract:

Recently artemisinin (the endoperoxide sesquiterpene lactone) has received considerable attention because of its antimalarial activity. It is isolated from the aerial part of the Artemisia annua L. Artemisinin is very difficult to synthesise also its production by mean of cell, tissue or organ cultures is very low. Presently, only its extraction from A. annua L. plants remains the only source of the drug. The reported yield of artemisinin from leaves of A. annua L. is very low and unstable, with yields typically less than 1% of leaf dry weight. To increase the percentage of artemisinin, researchers have been engaged in developing new varieties. A review concerning the breeding of A. annua L. is presented. The aim of this review is to bring together most of the available scientific research papers about the breeding conducted on the genus A. annua L., which is currently scattered across various publications. Through this review the authors hope to attract the attention of breeders throughout the world to focus on the unexplored potential of A. annua L. species. Also the future scope of this plant has been emphasized with a view of the importance of breeding of A. annua L. for increasing of artemisinin content. By releasing of new cultivar of A. annua L. and cultivation of this plant offers the opportunity to optimize yield and achieve a uniform, high quality product.

Keywords: Artemisia annua L., breeding, artemisinin, cultivation, medicinal plant

Procedia PDF Downloads 260
1236 Genetic Association of SIX6 Gene with Pathogenesis of Glaucoma

Authors: Riffat Iqbal, Sidra Ihsan, Andleeb Batool, Maryam Mukhtar

Abstract:

Glaucoma is a gathering of optic neuropathies described by dynamic degeneration of retinal ganglionic cells. It is clinically and innately heterogenous illness containing a couple of particular forms each with various causes and severities. Primary open-angle glaucoma (POAG) is the most generally perceived kind of glaucoma. This study investigated the genetic association of single nucleotide polymorphisms (SNPs; rs10483727 and rs33912345) at the SIX1/SIX6 locus with primary open-angle glaucoma (POAG) in the Pakistani population. The SIX6 gene plays an important role in ocular development and has been associated with morphology of the optic nerve. A total of 100 patients clinically diagnosed with glaucoma and 100 control individuals of age over 40 were enrolled in the study. Genomic DNA was extracted by organic extraction method. The SNP genotyping was done by (i) PCR based restriction fragment length polymorphism (RFLP) and sequencing method. Significant genetic associations were observed for rs10483727 (risk allele T) and rs33912345 (risk allele C) with POAG. Hence, it was concluded that Six6 gene is genetically associated with pathogenesis of Glaucoma in Pakistan.

Keywords: genotyping, Pakistani population, primary open-angle glaucoma, SIX6 gene

Procedia PDF Downloads 181
1235 Influence of Compactive Efforts on the Hydraulic Conductivity of Bagasse Ash Treated Black Cotton Soil

Authors: T. S. Ijimdiya, K. J. Osinubi

Abstract:

This study examines the influence of compactive efforts on hydraulic conductivity behaviour of compacted black cotton soil treated with bagasse ash which is necessary in assessing the performance of the soil - bagasse ash mixture for use as a suitable barrier material in waste containment application. Black cotton soil treated with up to 12% bagasse ash (obtained from burning the fibrous residue from the extraction of sugar juice from sugarcane) by dry weight of soil for use in waste containment application. The natural soil classifies as A-7-6 or CH in accordance with the AASHTO and the Unified Soil Classification System, respectively. The treated soil samples were prepared at molding water contents of -2, 0, +2, and +4 % of optimum moisture contents and compacted using four compactive efforts of Reduced British Standard Light (RBSL), British Standard light (BSL), West African Standard (WAS) and British Standard Heavy (BSH). The results obtained show that hydraulic conductivity decreased with increase in bagasse ash content, moulding water content and compaction energy.

Keywords: bagasse ash treatment, black cotton soil, hydraulic conductivity, moulding water contents, compactive efforts

Procedia PDF Downloads 431
1234 Omani Community in Digital Age: A Study of Omani Women Using Back Channel Media to Empower Themselves for Frontline Entrepreneurship

Authors: Sangeeta Tripathi, Muna Al Shahri

Abstract:

This research article presents the changing role and status of women in Oman. Transformation of women’s status started with the regime of His Majesty Sultan Qaboos Bin Said in 1970. It is always desired by the Sultan to enable women in all the ways for the balance growth of the country. Forbidding full face veil for women in public offices is one of the best efforts for their empowerment. Women education is also increasing rapidly. They are getting friendly with new information communication technology and using different social media applications such as WhatsApp, Instagram and Facebook for interaction and economic growth. Though there are some traditional and tribal boundaries, women are infused with courage and enjoying fair treatment and equal opportunities in different career positions. The study will try to explore changing mindset of young Omani women towards these traditional tribal boundaries, cultural heritage, business and career: ‘How are young Omani women making balance between work and social prestige?’, ‘How are they preserving their cultural values, embracing new technologies and approaching social network to enhance their economic power.’ This paper will discover their hurdles while using internet for their new entrepreneur. It will also examine the prospects of online business in Oman. The mixed research methodology is applied to find out the result.

Keywords: advertising, business, entrepreneurship, tribal barrier

Procedia PDF Downloads 298
1233 α-Amylase Inhibitory Activity of Some Tunisian Aromatic and Medicinal Plants

Authors: Hamdi Belfeki, Belgacem Chandoul, Mnasser Hassouna, Mondher Mejri

Abstract:

Aqueous and ethanolic extracts of eight Tunisian aromatic and medicinal plants (TAMP) were characterized by studying their composition in polyphenols and also their antiradical and antioxidant capacities. In absence and in the presence of the various extracts, α-amylase from Bacillus subtlis activity, was measured in order to detect a potential inhibition. The total contents of polyphenols and flavonoid vary in function of TAMP and the mobile phase used for the extraction (distilled water or ethanol). The ethanolic extracts showed the most significant antiradical and antioxidant activities. Only the extracts from Coriandrum sativum showed a significant inhibiting effect on the α-amylase activity. This inhibiting capacity could be correlated with the chemical profile of the two extracts, due to the fact that they have the greatest amount of total flavonoid. The ethanolic extract has the most important antioxidant and anti-radicalizing activities among the sixteen extracts studied. The inhibition kinetics of the two coriander extracts were evaluated by pre-incubation method, using Lineweaver-Burk’s equation, obtained by linearization of Michaeilis-Menten’s expression. The results showed that both extracts exercised a competitive inhibition mechanism.

Keywords: α-amylase, antioxidant activity, aromatic and medicinal plants, inhibition

Procedia PDF Downloads 441
1232 Chemical Composition, Antioxidant and Antimicrobial Activities of the Essential Oils of Different Pinus Species from Kosovo

Authors: Fatbardhë Kurti, Giangiacomo Beretta, Behxhet Mustafa, Fabrizio Gelmini, Avni Hajdari

Abstract:

Chemical profile, antioxidant and antimicrobial activity of total and fractionated essential oils (EOs) (F1 – hexane, F2 – hexane/diethyl ether, F3 – diethyl ether) derived from five Pinus species (Pinus heldreichii, P. peuce, P. mugo, Pinus nigra, P. sylvestris), were investigated. The hydrodistilled EOs and their chromatographic fractions (direct solid phase extraction, SPE) were analysed by GC-MS and 112 compounds separated and identified. The main constituents were α-pinene, β-pinene, D-limonene, β-caryophyllene, germacrene D, bornyl acetate and 3-carene. The antioxidant activities of total EOs were lower than those of the corresponding fractions, with F2 the strongest in all cases. EOs and fractions showed different degrees of antibacterial efficacy against different microbial pathogens (moderately strong antimicrobial activity against C. albicans and C. krusei ,while low or no activity against E. faecalis and E. coli strains). The detected inhibition zones and MICs for the EOs and fractions were in the range of 14 -35 mm and 0.125 - 1% (v/v), respectively. The components responsible for the antioxidant and antimicrobial activity were oxygenated monoterpenes and sesquiterpenes recovered in the polar EO fractions. These activities seem to be regulated by reciprocal interactions among the different subclasses of phytochemical species present in the EOs.

Keywords: antagonism, antioxidant activity, antibacterial activity, essential oil, fractions, GC-MS, pinus

Procedia PDF Downloads 225
1231 Diabetes Diagnosis Model Using Rough Set and K- Nearest Neighbor Classifier

Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

Abstract:

Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 332
1230 Effect of Ethyl Cellulose and Hydroxy Propyl Methyl Cellulose Polymer on the Release Profile of Diltiazem Hydrochloride Sustained Release Pellets

Authors: Shahana Sharmin

Abstract:

In the present study, the effect of cellulose polymers Ethyl Cellulose and Hydroxy Propyl Methyl Cellulose was evaluated on the release profile of drug from sustained release pellet. Diltiazem Hydrochloride, an antihypertensive, cardio-protective agent and slow channel blocker were used as a model drug to evaluate its release characteristics from different pellets formulations. Diltiazem Hydrochloride sustained release pellets were prepared by drug loading (drug binder suspension) on neutral pellets followed by different percentages of spraying, i.e. 2%,4%, 6%, 8% and 10% coating suspension using ethyl cellulose and hydroxy-propyl methyl cellulose polymer in a fixed 85:15 ratios respectively. The in vitro dissolution studies of Diltiazem Hydrochloride from these sustained release pellets were carried out in pH 7.2 phosphate buffer for 1, 2, 3, 4, 5, 6, 7, and 8 hrs using USP-I method. Statistically, significant differences were found among the drug release profile from different formulations. Polymer content with the highest concentration of Ethyl cellulose on the pellets shows the highest release retarding rate of the drug. The retarding capacity decreases with the decreased concentration of ethyl cellulose. The release mechanism was explored and explained with zero order, first order, Higuchi and Korsmeyer’s equations. Finally, the study showed that the profile and kinetics of drug release were functions of polymer type, polymer concentration & the physico-chemical properties of the drug.

Keywords: diltiazem hydrochloride, ethyl cellulose, hydroxy propyl methyl cellulose, release kinetics, sustained release pellets

Procedia PDF Downloads 407
1229 Asymmetrically Contacted Tellurium Short-Wave Infrared Photodetector with Low Dark Current and High Sensitivity at Room Temperature

Authors: Huang Haoxin

Abstract:

Large dark current at room temperature has long been the major bottleneck that impedes the development of high-performance infrared photodetectors towards miniaturization and integration. Although infrared photodetectors based on layered 2D narrow bandgap semiconductors have shown admirable advantages compared with those based on conventional compounds, which typically suffer from expensive cryogenic operations, it is still urgent to develop a simple but effective strategy to further reduce the dark current. Herein, a tellurium (Te) based infrared photodetector is reported with a specifically designed asymmetric electrical contact area. The deliberately introduced asymmetric electrical contact raises the electric field intensity difference in the Te channel near the drain and the source electrodes, resulting in spontaneous asymmetric carrier diffusion under global infrared light illumination under zero bias. Specifically, the Te-based photodetector presents promising detector performance at room temperature, including a low dark current of≈1 nA, an ultrahigh photocurrent/dark current ratio of 1.57×10⁴, a high specific detectivity (D*) of 3.24×10⁹ Jones, and relatively fast response speed of ≈720 μs at zero bias. The results prove that the simple design of asymmetric electrical contact areas can provide a promising solution to high-performance 2D semiconductor-based infrared photodetectors working at room temperature.

Keywords: asymmetrical contact, tellurium, dark current, infrared photodetector, sensitivity

Procedia PDF Downloads 46
1228 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

Procedia PDF Downloads 106
1227 Spatio-Temporal Variability in Reciprocal Resource Subsidies across Adjacent Terrestrial and Aquatic Eastern Cape Ecosystems

Authors: Tiyisani L. Chavalala, Nicole B. Richoux, Martin H. Villet

Abstract:

Rivers and their adjacent ecosystems are linked by reciprocal ecological subsidies. Rivers receive nutrients and energy from land, and these transfers can represent important food subsidies, a phenomenon known as allochthony. Emergence of adult aquatic invertebrates can also provide important food sources to terrestrial consumers. Reciprocal subsidies are influenced by factors such as canopy cover, river flow rate and channel width, which can be highly variable through space and time. The aim of this study is to identify and quantify the main trophic links between adjacent ecosystems (terrestrial and freshwater systems) in several Eastern Cape Rivers with different catchment sizes and flow rates and to develop an understanding of the factors that affect the strength of these links and their spatial dynamics. Food sources and consumers were sampled during four seasons (August 2016, November 2016, February 2017 and May 2017), and stable isotope ratios will serve as tracers to estimate the food web structures. Emergence traps are being used to quantify the rates of emergence of adult aquatic insects, and infall-pan traps are being used to quantify the terrestrial insects falling into rivers as potential food subsidies.

Keywords: emerging aquatic insects, in-falling terrestrial insects, reciprocal resource subsidies, stable isotopes

Procedia PDF Downloads 200
1226 Simple and Scalable Thermal-Assisted Bar-Coating Process for Perovskite Solar Cell Fabrication in Open Atmosphere

Authors: Gizachew Belay Adugna

Abstract:

Perovskite solar cells (PSCs) shows rapid development as an emerging photovoltaic material; however, the fast device degradation due to the organic nature, mainly hole transporting material (HTM) and lack of robust and reliable upscaling process for photovoltaic module hindered its commercialization. Herein, HTM molecules with/without fluorine-substituted cyclopenta[2,1-b;3,4-b’]dithiophene derivatives (HYC-oF, HYC-mF, and HYC-H) were developed for PSCs application. The fluorinated HTM molecules exhibited better hole mobility and overall charge extraction in the devices mainly due to strong molecular interaction and packing in the film. Thus, the highest power conversion efficiency (PCE) of 19.64% with improved long stability was achieved for PSCs based on HYC-oF HTM. Moreover, the fluorinated HYC-oF demonstrated excellent film processability in a larger-area substrate (10 cm×10 cm) prepared sequentially with the absorption perovskite underlayer via a scalable bar coating process in ambient air and owned a higher PCE of 18.49% compared to the conventional spiro-OMeTAD (17.51%). The result demonstrates a facile development of HTM towards stable and efficient PSCs for future industrial-scale PV modules.

Keywords: perovskite solar cells, upscaling film coating, power conversion efficiency, solution processing

Procedia PDF Downloads 69
1225 Dissipation of Tebuconazole in Cropland Soils as Affected by Soil Factors

Authors: Bipul Behari Saha, Sunil Kumar Singh, P. Padmaja, Kamlesh Vishwakarma

Abstract:

Dissipation study of tebuconazole in alluvial, black and deep-black clayey soils collected from paddy, mango and peanut cropland of tropical agro-climatic zone of India at three concentration levels were carried out for monitoring the water contamination through persisted residual toxicity. The soil-slurry samples were analyzed by capillary GC-NPD methods followed by ultrasound-assisted extraction (UAE) technique and cleanup process. An excellent linear relationship between peak area and concentration obtained in the range 1 to 50 μgkg-1. The detection (S/N, 3 ± 0.5) and quantification (S/N, 7.5 ± 2.5) limits were 3 and 10 μgkg-1 respectively. Well spiked recoveries were achieved from 96.28 to 99.33 % at levels 5 and 20 μgkg-1 and method precision (% RSD) was ≤ 5%. The soils dissipation of tebuconazole was fitted in first order kinetic-model with half-life between 34.48 to 48.13 days. The soil organic-carbon (SOC) content correlated well with the dissipation rate constants (DRC) of the fungicide Tebuconazole. An increase in the SOC content resulted in faster dissipation. The results indicate that the soil organic carbon and tebuconazole concentrations plays dominant role in dissipation processes. The initial concentration illustrated that the degradation rate of tebuconazole in soils was concentration dependent.

Keywords: cropland soil, dissipation, laboratory incubation, tebuconazole

Procedia PDF Downloads 248
1224 Masked Candlestick Model: A Pre-Trained Model for Trading Prediction

Authors: Ling Qi, Matloob Khushi, Josiah Poon

Abstract:

This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

Procedia PDF Downloads 120
1223 Study on Construction of 3D Topography by UAV-Based Images

Authors: Yun-Yao Chi, Chieh-Kai Tsai, Dai-Ling Li

Abstract:

In this paper, a method of fast 3D topography modeling using the high-resolution camera images is studied based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D) urban landscape modeling. Firstly, the existing high-resolution digital camera with special design of overlap images is designed by reconstructing and analyzing the auto-flying paths of UAVs, which improves the self-calibration function to achieve the high precision imaging by software, and further increased the resolution of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of urban land surfaces and the texture extraction. Finally, the aerial photography and 3D topography construction are both developed in campus of Chang-Jung University and in Guerin district area in Tainan, Taiwan, provide authentication model for construction of 3D topography based on combined UAV-based camera images from system. The results demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D topography production, and the technology solution in this paper offers a new, fast, and technical plan for the 3D expression of the city landscape, fine modeling and visualization.

Keywords: 3D, topography, UAV, images

Procedia PDF Downloads 300
1222 LCA/CFD Studies of Artisanal Brick Manufacture in Mexico

Authors: H. A. Lopez-Aguilar, E. A. Huerta-Reynoso, J. A. Gomez, J. A. Duarte-Moller, A. Perez-Hernandez

Abstract:

Environmental performance of artisanal brick manufacture was studied by Lifecycle Assessment (LCA) methodology and Computational Fluid Dynamics (CFD) analysis in Mexico. The main objective of this paper is to evaluate the environmental impact during artisanal brick manufacture. LCA cradle-to-gate approach was complemented with CFD analysis to carry out an Environmental Impact Assessment (EIA). The lifecycle includes the stages of extraction, baking and transportation to the gate. The functional unit of this study was the production of a single brick in Chihuahua, Mexico and the impact categories studied were carcinogens, respiratory organics and inorganics, climate change radiation, ozone layer depletion, ecotoxicity, acidification/ eutrophication, land use, mineral use and fossil fuels. Laboratory techniques for fuel characterization, gas measurements in situ, and AP42 emission factors were employed in order to calculate gas emissions for inventory data. The results revealed that the categories with greater impacts are ecotoxicity and carcinogens. The CFD analysis is helpful in predicting the thermal diffusion and contaminants from a defined source. LCA-CFD synergy complemented the EIA and allowed us to identify the problem of thermal efficiency within the system.

Keywords: LCA, CFD, brick, artisanal

Procedia PDF Downloads 389
1221 Rising Velocity of a Non-Newtonian Liquids in Capillary Tubes

Authors: Reza Sabbagh, Linda Hasanovich, Aleksey Baldygin, David S. Nobes, Prashant R. Waghmare

Abstract:

The capillary filling process is significantly important to study for numerous applications such as the under filling of the material in electronic packaging or liquid hydrocarbons seepage through porous structure. The approximation of the fluid being Newtonian, i.e., linear relationship between the shear stress and deformation rate cannot be justified in cases where the extent of non-Newtonian behavior of liquid governs the surface driven transport, i.e., capillarity action. In this study, the capillary action of a non-Newtonian fluid is not only analyzed, but also the modified generalized theoretical analysis for the capillary transport is proposed. The commonly observed three regimes: surface forces dominant (travelling air-liquid interface), developing flow (viscous force dominant), and developed regimes (interfacial, inertial and viscous forces are comparable) are identified. The velocity field along each regime is quantified with Newtonian and non-Newtonian fluid in square shaped vertically oriented channel. Theoretical understanding of capillary imbibition process, particularly in the case of Newtonian fluids, is relied on the simplified assumption of a fully developed velocity profile which has been revisited for developing a modified theory for the capillary transport of non-Newtonian fluids. Furthermore, the development of the velocity profile from the entrance regime to the developed regime, for different power law fluids, is also investigated theoretically and experimentally.

Keywords: capillary, non-Newtonian flow, shadowgraphy, rising velocity

Procedia PDF Downloads 201
1220 Exploring Syntactic and Semantic Features for Text-Based Authorship Attribution

Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

Abstract:

Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

Procedia PDF Downloads 133
1219 Enhanced COVID-19 Pharmaceuticals and Microplastics Removal from Wastewater Using Hybrid Reactor System

Authors: Reda Dzingelevičienė, Vytautas Abromaitis, Nerijus Dzingelevičius, Kęstutis Baranauskis, Saulius Raugelė, Malgorzata Mlynska-Szultka, Sergej Suzdalev, Reza Pashaei, Sajjad Abbasi, Boguslaw Buszewski

Abstract:

A unique hybrid technology was developed for the removal of COVID-19 specific contaminants from wastewater. Reactor testing was performed using model water samples contaminated with COVID-19 pharmaceuticals and microplastics. Different hydraulic retention times, concentrations of pollutants and dissolved ozone were tested. Liquid Chromatography-Mass Spectrometry, solid phase extraction, surface area and porosity, analytical tools were used to monitor the treatment efficiency and remaining sorption capacity of the spent adsorbent. The combination of advanced oxidation and adsorption processes was found to be the most effective, with the highest 90-99% and 89-95% molnupiravir and microplastics contaminants removal efficiency from the model wastewater. The research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0014) under a grant agreement with the Research Council of Lithuania (LMTLT), and it was funded as part of the European Union’s measure in response to the COVID-19 pandemic.

Keywords: adsorption, hybrid reactor system, pharmaceuticals-microplastics, wastewater

Procedia PDF Downloads 83
1218 Impacts of Applying Automated Vehicle Location Systems to Public Bus Transport Management

Authors: Vani Chintapally

Abstract:

The expansion of modest and minimized Global Positioning System (GPS) beneficiaries has prompted most Automatic Vehicle Location (AVL) frameworks today depending solely on satellite-based finding frameworks, as GPS is the most stable usage of these. This paper shows the attributes of a proposed framework for following and dissecting open transport in a run of the mill medium-sized city and complexities the qualities of such a framework to those of broadly useful AVL frameworks. Particular properties of the courses broke down by the AVL framework utilized for the examination of open transport in our study incorporate cyclic vehicle courses, the requirement for particular execution reports, and so forth. This paper particularly manages vehicle movement forecasts and the estimation of station landing time, combined with consequently produced reports on timetable conformance and other execution measures. Another side of the watched issue is proficient exchange of information from the vehicles to the control focus. The pervasiveness of GSM bundle information exchange advancements combined with decreased information exchange expenses have brought on today's AVL frameworks to depend predominantly on parcel information exchange administrations from portable administrators as the correspondences channel in the middle of vehicles and the control focus. This methodology brings numerous security issues up in this conceivably touchy application field.

Keywords: automatic vehicle location (AVL), expectation of landing times, AVL security, data administrations, wise transport frameworks (ITS), guide coordinating

Procedia PDF Downloads 379
1217 Functional Properties of Sunflower Protein Concentrates Extracted Using Different Anti-greening Agents - Low-Fat Whipping Cream Preparation

Authors: Tamer M. El-Messery

Abstract:

By-products from sunflower oil extraction, such as sunflower cakes, are rich sources of proteins with desirable functional properties for the food industry. However, challenges such as sensory drawbacks and the presence of phenolic compounds have hindered their widespread use. In this study, sunflower protein concentrates were obtained from sunflower cakes using different ant-greening solvents (ascorbic acid (ASC) and N-acetylcysteine (NAC)), and their functional properties were evaluated. The color of extracted proteins ranged from dark green to yellow, where the using of ASC and NAC agents enhanced the color. The protein concentrates exhibited high solubility (>70%) and antioxidant activity, with hydrophobicity influencing emulsifying activity. Emulsions prepared with these proteins showed stability and microencapsulation efficiency. Incorporation of protein concentrates into low-fat whipping cream formulations increased overrun and affected color characteristics. Rheological studies demonstrated pseudoplastic behavior in whipped cream, influenced by shear rates and protein content. Overall, sunflower protein isolates showed promising functional properties, indicating their potential as valuable ingredients in food formulations.

Keywords: functional properties, sunflower protein concentrates, antioxidant capacity, ant-greening agents, low-fat whipping cream

Procedia PDF Downloads 42
1216 Digital Retinal Images: Background and Damaged Areas Segmentation

Authors: Eman A. Gani, Loay E. George, Faisel G. Mohammed, Kamal H. Sager

Abstract:

Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy.

Keywords: retinal images, fundus images, diabetic retinopathy, background segmentation, damaged areas segmentation

Procedia PDF Downloads 395
1215 DCDNet: Lightweight Document Corner Detection Network Based on Attention Mechanism

Authors: Kun Xu, Yuan Xu, Jia Qiao

Abstract:

The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

Procedia PDF Downloads 351
1214 Enabling Wire Arc Additive Manufacturing in Aircraft Landing Gear Production and Its Benefits

Authors: Jun Wang, Chenglei Diao, Emanuele Pagone, Jialuo Ding, Stewart Williams

Abstract:

As a crucial component in aircraft, landing gear systems are responsible for supporting the plane during parking, taxiing, takeoff, and landing. Given the need for high load-bearing capacity over extended periods, 300M ultra-high strength steel (UHSS) is often the material of choice for crafting these systems due to its exceptional strength, toughness, and fatigue resistance. In the quest for cost-effective and sustainable manufacturing solutions, Wire Arc Additive Manufacturing (WAAM) emerges as a promising alternative for fabricating 300M UHSS landing gears. This is due to its advantages in near-net-shape forming of large components, cost-efficiency, and reduced lead times. Cranfield University has conducted an extensive preliminary study on WAAM 300M UHSS, covering feature deposition, interface analysis, and post-heat treatment. Both Gas Metal Arc (GMA) and Plasma Transferred Arc (PTA)-based WAAM methods were explored, revealing their feasibility for defect-free manufacturing. However, as-deposited 300M features showed lower strength but higher ductility compared to their forged counterparts. Subsequent post-heat treatments were effective in normalising the microstructure and mechanical properties, meeting qualification standards. A 300M UHSS landing gear demonstrator was successfully created using PTA-based WAAM, showcasing the method's precision and cost-effectiveness. The demonstrator, measuring Ф200mm x 700mm, was completed in 16 hours, using 7 kg of material at a deposition rate of 1.3kg/hr. This resulted in a significant reduction in the Buy-to-Fly (BTF) ratio compared to traditional manufacturing methods, further validating WAAM's potential for this application. A "cradle-to-gate" environmental impact assessment, which considers the cumulative effects from raw material extraction to customer shipment, has revealed promising outcomes. Utilising Wire Arc Additive Manufacturing (WAAM) for landing gear components significantly reduces the need for raw material extraction and refinement compared to traditional subtractive methods. This, in turn, lessens the burden on subsequent manufacturing processes, including heat treatment, machining, and transportation. Our estimates indicate that the carbon footprint of the component could be halved when switching from traditional machining to WAAM. Similar reductions are observed in embodied energy consumption and other environmental impact indicators, such as emissions to air, water, and land. Additionally, WAAM offers the unique advantage of part repair by redepositing only the necessary material, a capability not available through conventional methods. Our research shows that WAAM-based repairs can drastically reduce environmental impact, even when accounting for additional transportation for repairs. Consequently, WAAM emerges as a pivotal technology for reducing environmental impact in manufacturing, aiding the industry in its crucial and ambitious journey towards Net Zero. This study paves the way for transformative benefits across the aerospace industry, as we integrate manufacturing into a hybrid solution that offers substantial savings and access to more sustainable technologies for critical component production.

Keywords: WAAM, aircraft landing gear, microstructure, mechanical performance, life cycle assessment

Procedia PDF Downloads 155
1213 Distributed Processing for Content Based Lecture Video Retrieval on Hadoop Framework

Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

Abstract:

There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

Procedia PDF Downloads 527
1212 Understanding the Effectiveness of Branding Strategies in Car Rental Service Business in India

Authors: Vrajesh Chokshi

Abstract:

In last three decades, the global economy is substantially changed. Today, we are living in highly inter-connected world. The global markets are more open and consumers are well informed about products and services. The information technology revolution has broken all barriers in global business. The E-commerce has given opportunities of global trades to corporate. The IT is extensively used in almost all industries. After liberalization in 1992, the Indian economy is also significantly changed. The IT (information technology) and ITES (IT enable services) are extensively used in supply chain management. In India, previously car rental service business was dominated by local organization and operated through local contact. This industry is very lucrative and to catch this opportunity, many new corporate have ventured into e-commerce car rental service business in India. As the market is very competitive, branding is also very important part of marketing strategy. Now, the E-commerce portals those are in car rental business in India have realized the importance of the same and have started usage of all types of communication channel to promote their brand in different Indian markets. At consumer side, the awareness is also being considerably increased due to marketing communication campaign run by these companies. This paper aims to understand effectiveness of branding strategies in car rental business in India and also tries to identify unique promotional strategies to consolidate brand image of this business in different Indian markets.

Keywords: branding strategies, car rental business, CRM (customer relationship management), ITES (information technology enabled services)

Procedia PDF Downloads 299
1211 The “Bright Side” of COVID-19: Effects of Livestream Affordances on Consumer Purchase Willingness: Explicit IT Affordances Perspective

Authors: Isaac Owusu Asante, Yushi Jiang, Hailin Tao

Abstract:

Live streaming marketing, the new electronic commerce element, became an optional marketing channel following the COVID-19 pandemic. Many sellers have leveraged the features presented by live streaming to increase sales. Studies on live streaming have focused on gaming and consumers’ loyalty to brands through live streaming, using interview questionnaires. This study, however, was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during live streaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study introduces a new way of measuring interactions in live streaming commerce and proposes a way to manually gather data on consumer behaviors in live streaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness

Procedia PDF Downloads 76
1210 Classification of Business Models of Italian Bancassurance by Balance Sheet Indicators

Authors: Andrea Bellucci, Martina Tofi

Abstract:

The aim of paper is to analyze business models of bancassurance in Italy for life business. The life insurance business is very developed in the Italian market and banks branches have 80% of the market share. Given its maturity, the life insurance market needs to consolidate its organizational form to allow for the development of non-life business, which nowadays collects few premiums but represents a great opportunity to enlarge the market share of bancassurance using its strength in the distribution channel while the market share of independent agents is decreasing. Starting with the main business model of bancassurance for life business, this paper will analyze the performances of life companies in the Italian market by balance sheet indicators and by main discriminant variables of business models. The study will observe trends from 2013 to 2015 for the Italian market by exploiting a database managed by Associazione Nazionale delle Imprese di Assicurazione (ANIA). The applied approach is based on a bottom-up analysis starting with variables and indicators to define business models’ classification. The statistical classification algorithm proposed by Ward is employed to design business models’ profiles. Results from the analysis will be a representation of the main business models built by their profile related to indicators. In that way, an unsupervised analysis is developed that has the limit of its judgmental dimension based on research opinion, but it is possible to obtain a design of effective business models.

Keywords: bancassurance, business model, non life bancassurance, insurance business value drivers

Procedia PDF Downloads 294
1209 Alumina Supported Copper-Manganese Catalysts for Combustion of Exhaust Gases: Effect of Preparation Method

Authors: Krasimir Ivanov, Elitsa Kolentsova, Dimitar Dimitrov

Abstract:

The development of active and stable catalysts without noble metals for low temperature oxidation of exhaust gases remains a significant challenge. The purpose of this study is to determine the influence of the preparation method on the catalytic activity of the supported copper-manganese mixed oxides in terms of VOCs oxidation. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and acetates and the possibilities for CO, CH3OH and dimethyl ether (DME) oxidation were evaluated using continuous flow equipment with a four-channel isothermal stainless steel reactor. Effect of the support, Cu/Mn mole ratio, heat treatment of the precursor and active component loading were investigated. Highly active alumina supported Cu-Mn catalysts for CO and VOCs oxidation were synthesized. The effect of preparation conditions on the activity behavior of the catalysts was discussed. The synergetic interaction between copper and manganese species increases the activity for complete oxidation over mixed catalysts. Type of support, calcination temperature and active component loading along with catalyst composition are important factors, determining catalytic activity. Cu/Mn molar ratio of 1:5, heat treatment at 450oC and 20 % active component loading are the best compromise for production of active catalyst for simultaneous combustion of CO, CH3OH and DME.

Keywords: copper-manganese catalysts, CO, VOCs oxidation, exhaust gases

Procedia PDF Downloads 409
1208 An Improved K-Means Algorithm for Gene Expression Data Clustering

Authors: Billel Kenidra, Mohamed Benmohammed

Abstract:

Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

Procedia PDF Downloads 187