Search results for: driving techniques
3990 Multi-Disciplinary Optimisation Methodology for Aircraft Load Prediction
Authors: Sudhir Kumar Tiwari
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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model
Procedia PDF Downloads 3503989 Synthesis, Spectroscopic and XRD Study of Transition Metal Complex Derived from Low-Schiff Acyl-Hydrazone Ligand
Authors: Mohamedou El Boukhary, Farba Bouyagui Tamboura, A. Hamady Barry, T. Moussa Seck, Mohamed L. Gaye
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Nowadays, low-schiff acyl-hydrazone ligands are highly sought after due to their wide applications in various fields of biology, coordination chemistry, and catalysis. They are studied for their antioxidant, antibacterial and antiviral properties. The complexes of transition metals and the lanthanide they derive are well known for their magnetic, optical, and catalytic properties. In this work, we present the synthesis of an acyl-hydrazone (H2L) schiff base and their 3d transition complexes. The ligand (H2L) is characterized by IR, NMR (1H; 13C) spectroscopy. The complexes are characterized by different physic-chemical techniques such as IR, UV-visible, conductivity, measurement of magnetic susceptibility. The study of XRD allowed us to elucidate the crystalline structure of the manganese (Mn) complex. The asymmetric unit of the complex is composed of two molecules of the ligand, one manganese (II) ion, and two coordinate chloride ions; the environment around Mn is described as a pentagonal base bipyramid. In the crystal lattice, the asymmetric unit is bound by hydrogen bonds.Keywords: synthene, acyl-hydrazone, 3D transition metal complex, application
Procedia PDF Downloads 513988 High-Capacity Image Steganography using Wavelet-based Fusion on Deep Convolutional Neural Networks
Authors: Amal Khalifa, Nicolas Vana Santos
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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.Keywords: deep learning, steganography, image, discrete wavelet transform, fusion
Procedia PDF Downloads 893987 Urban Security through Urban Transformation: Case of Saraycik District
Authors: Emir Sunguroglu, Merve Sunguroglu, Yesim Aliefendioglu, Harun Tanrivermis
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Basic human needs range from physiological needs such as food, water and shelter to safety needs such as security, protection from natural disasters and even urban terrorism which are extant and not fulfilled even in urban areas where people live civilly in large communities. These basic needs when arose in urban life lead to a different kind of crime set defined as urban crimes. Urban crimes mostly result from differences between socioeconomic conditions in society. Income inequality increases tendency towards urban crimes. Especially in slum areas and suburbs, urban crimes not only threaten public security but they also affect deliverance of public services. It is highlighted that, construction of urban security against problems caused by urban crimes is not only achieved by involvement of urban security in security of the community but also comprises juridical development and staying above a level of legal standards concurrently. The idea of urban transformation emerged as interventions to demolishment and rebuilding of built environment to solve the unhealthy urban environment, inadequate infrastructure and socioeconomic problems came up during the industrialization process. Considering the probability of urbanization process driving citizens to commit crimes, The United Nations Commission on Human Security’s focus on this theme is conferred to be a proper approach. In this study, the analysis and change in security before, through and after urban transformation, which is one of the tools related to urbanization process, is strived to be discussed through the case of Sincan County Saraycik District. The study also aims to suggest improvements to current legislation on public safety, urban resilience, and urban transformation. In spite of Saraycik District residing in a developing County in Ankara, Turkey, from urbanization perspective as well as socioeconomic and demographic indicators the District exhibits a negative view throughout the County and the country. When related to the county, rates of intentional harm reports, burglary reports, the offense of libel and threat reports and narcotic crime reports are higher. The District is defined as ‘crime hotspot’. Interviews with residents of Saraycik claim that the greatest issue of the neighborhood is Public Order and Security (82.44 %). The District becomes prominent with negative aspects, especially with the presence of unlicensed constructions, occurrence of important social issues such as crime and insecurity and complicated lives of inhabitants from poverty and low standard conditions of living. Additionally, the social structure and demographic properties and crime and insecurity of the field have been addressed in this study. Consequently, it is claimed that urban crime rates were related to level of education, employment and household income, poverty trap, physical condition of housing and structuration, accessibility of public services, security, migration, safety in terms of disasters and emphasized that urban transformation is one of the most important tools in order to provide urban security.Keywords: urban security, urban crimes, urban transformation, Saraycik district
Procedia PDF Downloads 3033986 A Deep Learning Based Approach for Dynamically Selecting Pre-processing Technique for Images
Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav
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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining
Procedia PDF Downloads 1623985 Heart Attack Prediction Using Several Machine Learning Methods
Authors: Suzan Anwar, Utkarsh Goyal
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Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest
Procedia PDF Downloads 1363984 Evaluation of Wound Healing Activity of Curcuma purpurascens BI. Rhizomes in Rats
Authors: Elham Rouhollahi, Soheil Zorofchian Moghadamtousi, Salma Baig, Mahmood Ameen Abdulla, Zahurin Mohamed
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This study was designed to assess cutaneous wound healing potential of hexane extract of Curcuma purpurascens rhizomes (HECP). Twenty-four rats were divided into 4 groups: 1. Negative, 2. Low dose, 3. High dose and 4. Treatment, with 6 rats in each group. Full-thickness incisions with a diameter of 2 cm were made on the back of each rat. Rats were topically treated two times a day for 15 days. Group 1-4 were treated with sterile distilled water, 5% and 10% of extract and intrasite gel, respectively. Masson's trichrome and hematoxylin staining techniques are employed for histological analysis revealed strong wound healing potential closer to that of conventional drug intrasite gel. HECP significantly decreased wound area and an increase in hydroxyproline, cellular proliferation, the number of blood vessels and the level of collagen synthesis was observed. Thus, it could be concluded that HECP possesses strong wound healing potential.Keywords: Curcuma purpurascens, wound healing, histopathology, hematoxylin staining
Procedia PDF Downloads 4363983 A Machine Learning-Based Approach to Capture Extreme Rainfall Events
Authors: Willy Mbenza, Sho Kenjiro
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Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.Keywords: machine learning (ML), predictions, rainfall events, regional variables
Procedia PDF Downloads 853982 Effects of Analogy Method on Children's Learning: Practice of Rainbow Experiments
Authors: Hediye Saglam
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This research has been carried out to bring in the 6 acquisitions in the 2014 Preschool Teaching Programme of the Turkish Ministry of Education through the method of analogy. This research is practiced based on the experimental pattern with pre-test and final test controlling groups. The working group of the study covers the group between 5-6 ages. The study takes 5 weeks including the 2 weeks spent for pre-test and the final test. It is conducted with the preschool teacher who gives the lesson along with the researcher in the in-class and out-of-class rainbow experiments of the students for 5 weeks. 'One Sample T Test' is used for the evaluation of the pre-test and final test. SPSS 17 programme is applied for the analysis of the data. Results: As an outcome of the study it is observed that analogy method affects children’s learning of the rainbow. For this very reason teachers should receive inservice training for different methods and techniques like analogy. This method should be included in preschool education programme and should be applied by teachers more often.Keywords: acquisitions of preschool education programme, analogy method, pre-test/final test, rainbow experiments
Procedia PDF Downloads 5043981 Talent Sourcing Practices in Sri Lankan Software Industry
Authors: Malmi Amadoru, Chandana Gamage
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Sri Lanka is emerging as a global IT-BPO hub topping up among the 20 global outsourcing destinations. When setting up a new venture in Sri Lanka, talent sourcing plays one of the key functions due to the rapid growth of workforce. Getting competent people with right skills for right positions leads organizations achieving its vision, mission and objectives. It also drives in earning competitive advantage over industry competitors. Thus it is crucial to scan and recruit the best employees to an organization. However there is no published information available on recruitment methods utilized in Sri Lankan software industry, as a study of this nature had not being conducted previously in Sri Lanka. The main objective of this study was to explore various talent sourcing practices exploited in Sri Lankan software industry. Also this study analyses the extent which Sri Lanka has adopted different recruitment strategies utilized in worldwide and its deviations. The research outcome is beneficial for HR professionals to identify the current trends in recruitment practices. Moreover investors who are interested in IT-BPO engagements can gain a thorough knowledge about talent sourcing techniques in Sri Lankan software industry. Finally, this research clues trending areas which can be further investigated in future.Keywords: IT-BPO, recruitment, Sri Lanka, software industry, talent
Procedia PDF Downloads 4853980 Software Quality Assurance in Component Based Software Development – a Survey Analysis
Authors: Abeer Toheed Quadri, Maria Abubakar, Mehreen Sirshar
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Component Based Software Development (CBSD) is a new trend in software development. Selection of quality components is not enough to ensure software quality in Component Based Software System (CBSS). A software product is considered to be a quality product if it satisfies its customer’s needs and has minimum defects. Authors’ survey different research papers and analyzes various techniques which ensure software quality in component based software development. This paper includes an investigation about how to improve the quality of a component based software system without effecting quality attributes. The reported information is identified from literature survey. The developments of component based systems are rising as they reduce the development time, effort and cost by means of reuse. After analysis, it has been explored that in order to achieve the quality in a CBSS we need to have the components that are certified through software measure because the predictability of software quality attributes of system depend on the quality attributes of the constituent components, integration process and the framework used.Keywords: CBSD (component based software development), CBSS (component based software system), quality components, SQA (software quality assurance)
Procedia PDF Downloads 4103979 Vibration Measurements of Single-Lap Cantilevered SPR Beams
Authors: Xiaocong He
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Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. Mechanical structures assembled by SPR are expected to possess a high damping capacity. In this study, experimental measurement techniques were proposed for the prediction of vibration behavior of single-lap cantilevered SPR beams. The dynamic test software and the data acquisition hardware were used in the experimental measurement of the dynamic response of the single-lap cantilevered SPR beams. Free and forced vibration behavior of the single-lap cantilevered SPR beams was measured using the LMS CADA-X experimental modal analysis software and the LMS-DIFA Scadas II data acquisition hardware. The frequency response functions of the SPR beams of different rivet number were compared. The main goal of the paper is to provide a basic measuring method for further research on vibration based non-destructive damage detection in single-lap cantilevered SPR beams.Keywords: self-piercing riveting, dynamic response, experimental measurement, frequency response functions
Procedia PDF Downloads 4283978 Data Analysis to Uncover Terrorist Attacks Using Data Mining Techniques
Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari
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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.Keywords: data mining, counter terrorism, machine learning, SVM
Procedia PDF Downloads 4053977 Experimental, Computational Fluid Dynamics and Theoretical Study of Cyclone Performance Based on Inlet Velocity and Particle Loading Rate
Authors: Sakura Ganegama Bogodage, Andrew Yee Tat Leung
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This paper describes experimental, Computational Fluid Dynamics (CFD) and theoretical analysis of a cyclone performance, operated 1.0 g/m3 solid loading rate, at two different inlet velocities (5 m/s and 10 m/s). Comparing experimental results with theoretical and CFD simulation results, it is pronounced that the influence of solid in processing flow is significant than expected. Experimental studies based on gas- solid flows of cyclone separators are complicated as they required advanced sensitive measuring techniques, especially flow characteristics. Thus, CFD modelling and theoretical analysis are economical in analyzing cyclone separator performance but detailed clarifications of the application of these in cyclone separator performance evaluation is not yet discussed. The present study shows the limitations of influencing parameters of CFD and theoretical considerations, comparing experimental results and flow characteristics from CFD modelling.Keywords: cyclone performance, inlet velocity, pressure drop, solid loading rate
Procedia PDF Downloads 2363976 DNA Barcoding of Tree Endemic Campanula Species From Artvi̇n, Türki̇ye
Authors: Hayal Akyildirim Beğen, Özgür Emi̇nağaoğlu
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DNA barcoding is the method of description of species based on gene diversity. In current studies, registration, genetic identification and protection of especially endemic plants pecies are carried out by DNA barcoding techniques. Molecular studies are based on the amplification and sequencing of the barcode gene region by the PCR method. Endemic Campanula choruhensis Kit Tan & Sorger, Campanula troegera Damboldt and Campanula betulifolia K.Koch is widespread in Artvin, Erzurum and around Çoruh valley passing through it. Intense road and dam constructions are carried out in and around the distribution area of this species. This situation harms the habitat of the species and puts its extinction. In this study, the plastid matK barcode gene regions (650 bp) of three Campanula species were created. To make the identification of this species quickly and accurately, gene sequence compared with sequences of other Campanula L. species. As a result of phylogenetic analysis, C. choruhensis is close relative to C. betulifolia. Morphologically, these species were determined to be more similar to each other with flower and leaf characters. C. troegera formed a separate branch.Keywords: campanula, DNA barcoding, endemic, türkiye, artvin
Procedia PDF Downloads 663975 Ontology-Based Backpropagation Neural Network Classification and Reasoning Strategy for NoSQL and SQL Databases
Authors: Hao-Hsiang Ku, Ching-Ho Chi
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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system
Procedia PDF Downloads 2613974 Synthesis, Characterization and Coating of the Zinc Oxide Nanoparticles on Cotton Fabric by Mechanical Thermo-Fixation Techniques to Impart Antimicrobial Activity
Authors: Imana Shahrin Tania, Mohammad Ali
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The present study reports the synthesis, characterization and application of nano-sized zinc-oxide (ZnO) particles on a cotton fabric surface. The aim of the investigations is to impart the antimicrobial activity on textile cloth. Nanoparticle is synthesized by wet chemical method from zinc sulphate and sodium hydroxide. SEM (scanning electron micrograph) images are taken to demonstrate the surface morphology of nanoparticles. XRD analysis is done to determine the crystal size of the nanoparticle. With the conformation of nanoformation, the cotton woven fabric is treated with ZnO nanoparticle by mechanical thermo-fixation (pad-dry-cure) technique. To increase the wash durability of nano treated fabric, an acrylic binder is used as a fixing agent. The treated fabric shows up to 90% bacterial reduction for S. aureus (Staphylococcus aureus) and 87% for E. coli (Escherichia coli) which is appreciable for bacteria protective clothing.Keywords: nanoparticle, zinc oxide, cotton fabric, antibacterial activity, binder
Procedia PDF Downloads 1313973 Evaluating Hourly Sulphur Dioxide and Ground Ozone Simulated with the Air Quality Model in Lima, Peru
Authors: Odón R. Sánchez-Ccoyllo, Elizabeth Ayma-Choque, Alan Llacza
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Sulphur dioxide (SO₂) and surface-ozone (O₃) concentrations are associated with diseases. The objective of this research is to evaluate the effectiveness of the air-quality-WRF-Chem model with a horizontal resolution of 5 km x 5 km. For this purpose, the measurements of the hourly SO₂ and O₃ concentrations available in three air quality monitoring stations in Lima, Peru were used for the purpose of validating the simulations of the SO₂ and O₃ concentrations obtained with the WRF-Chem model in February 2018. For the quantitative evaluation of the simulations of these gases, statistical techniques were implemented, such as the average of the simulations; the average of the measurements; the Mean Bias (MeB); the Mean Error (MeE); and the Root Mean Square Error (RMSE). The results of these statistical metrics indicated that the simulated SO₂ and O₃ values over-predicted the SO₂ and O₃ measurements. For the SO₂ concentration, the MeB values varied from 0.58 to 26.35 µg/m³; the MeE values varied from 8.75 to 26.5 µg/m³; the RMSE values varied from 13.3 to 31.79 µg/m³; while for O₃ concentrations the statistical values of the MeB varied from 37.52 to 56.29 µg/m³; the MeE values varied from 37.54 to 56.70 µg/m³; the RMSE values varied from 43.05 to 69.56 µg/m³.Keywords: ground-ozone, lima, sulphur dioxide, WRF-chem
Procedia PDF Downloads 1353972 Impact Assessment of Tropical Cyclone Hudhud on Visakhapatnam, Andhra Pradesh
Authors: Vivek Ganesh
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Tropical cyclones are some of the most damaging events. They occur in yearly cycles and affect the coastal population with three dangerous effects: heavy rain, strong wind and storm surge. In order to estimate the area and the population affected by a cyclone, all the three types of physical impacts must be taken into account. Storm surge is an abnormal rise of water above the astronomical tides, generated by strong winds and drop in the atmospheric pressure. The main aim of the study is to identify the impact by comparing three different months data. The technique used here is NDVI classification technique for change detection and other techniques like storm surge modelling for finding the tide height. Current study emphasize on recent very severe cyclonic storm Hud Hud of category 3 hurricane which had developed on 8 October 2014 and hit the coast on 12 October 2014 which caused significant changes on land and coast of Visakhapatnam, Andhra Pradesh. In the present study, we have used Remote Sensing and GIS tools for investigating and quantifying the changes in vegetation and settlement.Keywords: inundation map, NDVI map, storm tide map, track map
Procedia PDF Downloads 2653971 Challenges and Prospects of Small and Medium Scale Enterprises in Somolu Local Government Area
Authors: A. A. Akharayi, B. E. Anjola
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The economic development of a country depends greatly on internally built revenue. Small and Medium-scale Enterprise (SMEs) contributes to the economic buoyancy as it provides employment for the teeming population, encourages job creation by youths who believes in themselves and also by others who have gathered finance enough to invest in growable investment. SMEs is faced with several challenges. The study investigates the role and challenges of SMEs Somolu Local Government Area. Simple random sampling techniques were used to select entrepreneurs (SMEs owners and managers). One hundred and fifty (150) registered SMEs were selected across the LGA data collection with the use of well-structured questionnaire. The data collected were analysed using Statistical Package for Social Science (SPSS) version 21. The result of the analysis indicated that marketing, finance, social facilities and indiscriminate taxes among other high level of fund available significantly (p <0 .05) increase firm capacity while marketing showed a significant (p < 0.05) relationship with profit level.Keywords: challenge, development, economic, small and medium scale enterprise
Procedia PDF Downloads 2393970 Development of Solar Poly House Tunnel Dryer (STD) for Medicinal Plants
Authors: N. C. Shahi, Anupama Singh, E. Kate
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Drying is practiced to enhance the storage life, to minimize losses during storage, and to reduce transportation costs of agricultural products. Drying processes range from open sun drying to industrial drying. In most of the developing countries, use of fossil fuels for drying of agricultural products has not been practically feasible due to unaffordable costs to majority of the farmers. On the other hand, traditional open sun drying practiced on a large scale in the rural areas of the developing countries suffers from high product losses due to inadequate drying, fungal growth, encroachment of insects, birds and rodents, etc. To overcome these problems a middle technology dryer having low cost need to be developed for farmers. In case of mechanical dryers, the heated air is the main driving force for removal of moisture. The air is heated either electrically or by burning wood, coal, natural gas etc. using heaters. But, all these common sources have finite supplies. The lifetime is estimated to range from 15 years for a natural gas to nearly 250 years for coal. So, mankind must turn towards its safe and reliable utilization and may have undesirable side effects. The mechanical drying involves higher cost of drying and open sun drying deteriorates the quality. The solar tunnel dryer is one of promising option for drying various agricultural and agro-industrial products on large scale. The advantage of Solar tunnel dryer is its relatively cheaper cost of construction and operation. Although many solar dryers have been developed, still there is a scope of modification in them. Therefore, an attempt was made to develop Solar tunnel dryer and test its performance using highly perishable commodity i.e. leafy vegetables (spinach). The effect of air velocity, loading density and shade net on performance parameters namely, collector efficiency, drying efficiency, overall efficiency of dryer and specific heat energy consumption were also studied. Thus, the need for an intermediate level technology was realized and an effort was made to develop a small scale Solar Tunnel Dryer . A dryer consisted of base frame, semi cylindrical drying chamber, solar collector and absorber, air distribution system with chimney and auxiliary heating system, and wheels for its mobility were the main functional components. Drying of fenugreek was carried out to analyze the performance of the dryer. The Solar Tunnel Dryer temperature was maintained using the auxiliary heating system. The ambient temperature was in the range of 12-33oC. The relative humidity was found inside and outside the Solar Tunnel Dryer in the range of 21-75% and 35-79%, respectively. The solar radiation was recorded in the range of 350-780W/m2 during the experimental period. Studies revealed that total drying time was in range of 230 to 420 min. The drying time in Solar Tunnel Dryer was considerably reduced by 67% as compared to sun drying. The collector efficiency, drying efficiency, overall efficiency and specific heat consumption were determined and were found to be in the range of 50.06- 38.71%, 15.53-24.72%, 4.25 to 13.34% and 1897.54-3241.36 kJ/kg, respectively.Keywords: overall efficiency, solar tunnel dryer, specific heat consumption, sun drying
Procedia PDF Downloads 3093969 Robust Medical Image Watermarking Using Frequency Domain and Least Significant Bits Algorithms
Authors: Volkan Kaya, Ersin Elbasi
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Watermarking and stenography are getting importance recently because of copyright protection and authentication. In watermarking we embed stamp, logo, noise or image to multimedia elements such as image, video, audio, animation and text. There are several works have been done in watermarking for different purposes. In this research work, we used watermarking techniques to embed patient information into the medical magnetic resonance (MR) images. There are two methods have been used; frequency domain (Digital Wavelet Transform-DWT, Digital Cosine Transform-DCT, and Digital Fourier Transform-DFT) and spatial domain (Least Significant Bits-LSB) domain. Experimental results show that embedding in frequency domains resist against one type of attacks, and embedding in spatial domain is resist against another group of attacks. Peak Signal Noise Ratio (PSNR) and Similarity Ratio (SR) values are two measurement values for testing. These two values give very promising result for information hiding in medical MR images.Keywords: watermarking, medical image, frequency domain, least significant bits, security
Procedia PDF Downloads 2863968 Using Artificial Vision Techniques for Dust Detection on Photovoltaic Panels
Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano
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It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.Keywords: dust detection, photovoltaic, artificial vision, soiling
Procedia PDF Downloads 473967 AI Tutor: A Computer Science Domain Knowledge Graph-Based QA System on JADE platform
Authors: Yingqi Cui, Changran Huang, Raymond Lee
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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system
Procedia PDF Downloads 1863966 A Less Complexity Deep Learning Method for Drones Detection
Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar
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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet
Procedia PDF Downloads 1783965 Building 1-Well-Covered Graphs by Corona, Join, and Rooted Product of Graphs
Authors: Vadim E. Levit, Eugen Mandrescu
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A graph is well-covered if all its maximal independent sets are of the same size. A well-covered graph is 1-well-covered if deletion of every vertex of the graph leaves it well-covered. It is known that a graph without isolated vertices is 1-well-covered if and only if every two disjoint independent sets are included in two disjoint maximum independent sets. Well-covered graphs are related to combinatorial commutative algebra (e.g., every Cohen-Macaulay graph is well-covered, while each Gorenstein graph without isolated vertices is 1-well-covered). Our intent is to construct several infinite families of 1-well-covered graphs using the following known graph operations: corona, join, and rooted product of graphs. Adopting some known techniques used to advantage for well-covered graphs, one can prove that: if the graph G has no isolated vertices, then the corona of G and H is 1-well-covered if and only if H is a complete graph of order two at least; the join of the graphs G and H is 1-well-covered if and only if G and H have the same independence number and both are 1-well-covered; if H satisfies the property that every three pairwise disjoint independent sets are included in three pairwise disjoint maximum independent sets, then the rooted product of G and H is 1-well-covered, for every graph G. These findings show not only how to generate some more families of 1-well-covered graphs, but also that, to this aim, sometimes, one may use graphs that are not necessarily 1-well-covered.Keywords: maximum independent set, corona, concatenation, join, well-covered graph
Procedia PDF Downloads 2073964 Scenarios of Digitalization and Energy Efficiency in the Building Sector in Brazil: 2050 Horizon
Authors: Maria Fatima Almeida, Rodrigo Calili, George Soares, João Krause, Myrthes Marcele Dos Santos, Anna Carolina Suzano E. Silva, Marcos Alexandre Da
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In Brazil, the building sector accounts for 1/6 of energy consumption and 50% of electricity consumption. A complex sector with several driving actors plays an essential role in the country's economy. Currently, the digitalization readiness in this sector is still low, mainly due to the high investment costs and the difficulty of estimating the benefits of digital technologies in buildings. Nevertheless, the potential contribution of digitalization for increasing energy efficiency in the building sector in Brazil has been pointed out as relevant in the political and sectoral contexts, both in the medium and long-term horizons. To contribute to the debate on the possible evolving trajectories of digitalization in the building sector in Brazil and to subsidize the formulation or revision of current public policies and managerial decisions, three future scenarios were created to anticipate the potential energy efficiency in the building sector in Brazil due to digitalization by 2050. This work aims to present these scenarios as a basis to foresight the potential energy efficiency in this sector, according to different digitalization paces - slow, moderate, or fast in the 2050 horizon. A methodological approach was proposed to create alternative prospective scenarios, combining the Global Business Network (GBN) and the Laboratory for Investigation in Prospective Strategy and Organisation (LIPSOR) methods. This approach consists of seven steps: (i) definition of the question to be foresighted and time horizon to be considered (2050); (ii) definition and classification of a set of key variables, using the prospective structural analysis; (iii) identification of the main actors with an active role in the digital and energy spheres; (iv) characterization of the current situation (2021) and identification of main uncertainties that were considered critical in the development of alternative future scenarios; (v) scanning possible futures using morphological analysis; (vi) selection and description of the most likely scenarios; (vii) foresighting the potential energy efficiency in each of the three scenarios, namely slow digitalization; moderate digitalization, and fast digitalization. Each scenario begins with a core logic and then encompasses potentially related elements, including potential energy efficiency. Then, the first scenario refers to digitalization at a slow pace, with induction by the government limited to public buildings. In the second scenario, digitalization is implemented at a moderate pace, induced by the government in public, commercial, and service buildings, through regulation integrating digitalization and energy efficiency mechanisms. Finally, in the third scenario, digitalization in the building sector is implemented at a fast pace in the country and is strongly induced by the government, but with broad participation of private investments and accelerated adoption of digital technologies. As a result of the slow pace of digitalization in the sector, the potential for energy efficiency stands at levels below 10% of the total of 161TWh by 2050. In the moderate digitalization scenario, the potential reaches 20 to 30% of the total 161TWh by 2050. Furthermore, in the rapid digitalization scenario, it will reach 30 to 40% of the total 161TWh by 2050.Keywords: building digitalization, energy efficiency, scenario building, prospective structural analysis, morphological analysis
Procedia PDF Downloads 1133963 Automated Process Quality Monitoring and Diagnostics for Large-Scale Measurement Data
Authors: Hyun-Woo Cho
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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring
Procedia PDF Downloads 4003962 Hotel Guests’ Service Fulfillment: Bangkok, Thailand
Authors: Numtana Ladplee, Cherif Haberih
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The value of service evaluation depends critically on guests’ understanding of the evaluation objectives and their roles. The present research presents a three-phase investigation of the impact of evaluating participants’ theories about their roles: (a) identifying the theories, (b) testing the process consequences of participants’ role theories, and (c) gaining insights into the impact of participants’ role theories by testing key moderator/s. The findings of this study will hopefully indicate that (a) when forewarned of an upcoming evaluation task, consumers tend to believe that the evaluation objective is to identify aspects that need improvement, (b) this expectation produces a conscious attempt to identify negative aspects, although the encoding of attribute information is not affected, and (c) cognitive load during the evaluation experience greatly decreases the negativity of expected evaluations. The present study can be applied to other market research techniques and thereby improve our understanding of consumer inputs derived from market research. Such insights can help diminish biases produced by participants’ correct or incorrect theories regarding their roles.Keywords: fulfillment, hotel guests, service, Thailand
Procedia PDF Downloads 2753961 Groundwater Quality Assessment Using Water Quality Index and Geographical Information System Techniques: A Case Study of Busan City, South Korea
Authors: S. Venkatramanan, S. Y. Chung, S. Selvam, E. E. Hussam, G. Gnanachandrasamy
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The quality of groundwater was evaluated by major ions concentration around Busan city, South Korea. The groundwater samples were collected from 40 wells. The order of abundance of major cations concentration in groundwater is Na > Ca > Mg > K, in case of anions are Cl > HCO₃ > SO₄ > NO₃ > F. Based on Piper’s diagram Ca (HCO₃)₂, CaCl₂, and NaCl are the leading groundwater types. While Gibbs diagram suggested that most of groundwater samples belong to rock-weathering zone. Hydrogeochemical condition of groundwater in this city is influenced by evaporation, ion exchange and dissolution of minerals. Water Quality Index (WQI) revealed that 86 % of the samples belong to excellent, 2 % good, 4 % poor to very poor and 8 % unsuitable categories. The results of sodium absorption ratio (SAR), Permeability Index (PI), Residual Sodium Carbonate (RSC) and Magnesium Hazard (MH) exhibit that most of the groundwater samples are suitable for domestic and irrigation purposes.Keywords: WQI (Water Quality Index), saturation index, groundwater types, ion exchange
Procedia PDF Downloads 262