Search results for: optical techniques

Authors: Guorong Sui, Xingwei Jia, Fei Tong, Xiumin Gao

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Camera calibration is a fundamental issue of high precision noncontact measurement. And it is necessary to analyze and study the reliability and application range of its linear model which is often used in the camera calibration. According to the imaging features of monocular cameras, a camera model which is based on the image pixel coordinates and three dimensional space coordinates is built. Using our own customized template, the image pixel coordinate is obtained by the subpixel corner detection method. Without considering the aberration of the optical system, the feature extraction and linearity analysis of the line segment in the template are performed. Moreover, the experiment is repeated 11 times by constantly varying the measuring distance. At last, the linearity of the camera is achieved by fitting 11 groups of data. The camera model measurement results show that the relative error does not exceed 1%, and the repeated measurement error is not more than 0.1 mm magnitude. Meanwhile, it is found that the model has some measurement differences in the different region and object distance. The experiment results show this linear model is simple and practical, and have good linearity within a certain object distance. These experiment results provide a powerful basis for establishment of the linear model of camera. These works will have potential value to the actual engineering measurement.

Keywords: camera linear model, geometric imaging relationship, image pixel coordinates, three dimensional space coordinates, sub-pixel corner detection

Procedia PDF Downloads 271

Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

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This paper investigates stability problem for linear systems of neutral type with time-varying delay. By constructing various Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient stability conditions for the systems are established in terms of linear matrix inequalities (LMIs), which can be easily solved by various effective optimization algorithms. Finally, some illustrative examples are given to show the effectiveness of the proposed criterion.

Keywords: neutral systems, time-delay, stability, Lyapnov method, LMI

Procedia PDF Downloads 342

Authors: Abdeta Bayissa Mekessa

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The purpose of this study was to examine the effects of plyometric exercises on agility, power, and speed and improvement of U-17 female sprinters in the case of the Burayu Athletics project. The true experimental research design was employed for conducting this study. The total populations of the study were 14 U-17 female sprinters from Burayu athletics project. The populations were small in numbers; therefore, the researcher took all as a sample by using comprehensive sampling techniques. These subjects were classified into the Experimental group (N=7) and the Control group (N=7) by using simple random sampling techniques. The Experimental group participated in plyometric training for 8 weeks, 3 days per week and 60 minutes duration per day in addition to their regular training. But, the control groups were following their only regular training program. The variables selected for the purpose of this study were agility, power and speed. The tests were the Illinois agility test, standing long jump test, and 30m sprint test, respectively. Both groups were tested before (pre-test) and after (post-test) 8 weeks of plyometric training. For data analysis, the researcher used SPSS version 26.0 software. The collected data was analyzed using a paired sample t-test to observe the difference between the pre-test and post-test results of the plyometric exercises of the study. The significant level of p<0.05 was considered. The result of the study shows that after 8 weeks of plyometric training, significant improvements were found in Agility (MD=0.45, p<0.05), power (MD=-1.157, P<0.05) and speed (MD=0.37, P<0.05) for experimental group subjects. On the other hand, there was no significant change (P>0.05) in those variables in the control groups. Finally, the findings of the study showed that eight (8) weeks of plyometric exercises had a positive effect on agility, power and speed improvement of female sprinters. Therefore, Athletics coaches and athletes are highly recommended to include plyometric exercise in their training program.

Keywords: ploymetric exercise, speed power, aglity, female sprinter

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Authors: Hanan Alenezi

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Membrane performance depends on the kind of solvent used in preparation. A membrane made by Polyetherimide (PEI) was evaluated for gas separation using X-Ray Diffraction (XRD), Scanning electron microscope (SEM), and Energy Dispersive X-Ray Spectroscopy (EDS). The purity and the thickness are detected to evaluate the membrane in order to optimize PEI membrane preparation.

Keywords: Energy Dispersive X-Ray Spectroscopy (EDS), Membrane, Polyetherimide PEI, Scanning electron microscope (SEM), Solvent, X-Ray Diffraction (XRD)

Procedia PDF Downloads 171

Authors: M. Aherrahrou

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Moroccan education is currently facing many difficulties and problems due to traditional methods of teaching. Neuro -Linguistic Programming (NLP) appears to hold much potential for education at all levels. In this paper, the major aim is to explore the effect of certain Neuro -Linguistic Programming techniques in one educational institution in Morocco. Quantitative and Qualitative methods are used. The findings prove the effectiveness of this new approach regarding Moroccan education, and it is a promising tool to improve the quality of learning.

Keywords: learning and teaching environment, Neuro- Linguistic Programming, education, quality of learning

Procedia PDF Downloads 350

Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: J. Hajnys, M. Pagac, J. Petru, P. Stefek, J. Mesicek, J. Kratochvil

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The new progressive method of 3D metal printing SLM (Selective Laser Melting) is increasingly expanded into the normal operation. As a result, greater demands are placed on the surface quality of the parts produced in this way. The article deals with research of selected finishing methods (tumbling, face milling, sandblasting, shot peening and brushing) and their impact on the final surface roughness. The 20 x 20 x 7 mm produced specimens using SLM additive technology on the Renishaw AM400 were subjected to testing of these finishing methods by adjusting various parameters. Surface parameters of roughness Sa, Sz were chosen as the evaluation criteria and profile parameters Ra, Rz were used as additional measurements. Optical measurement of surface roughness was performed on Alicona Infinite Focus 5. An experiment conducted to optimize the surface roughness revealed, as expected, that the best roughness parameters were achieved through a face milling operation. Tumbling is particularly suitable for 3D printing components, as tumbling media are able to reach even complex shapes and, after changing to polishing bodies, achieve a high surface gloss. Surface quality after tumbling depends on the process time. Other methods with satisfactory results are shot peening and tumbling, which should be the focus of further research.

Keywords: additive manufacturing, selective laser melting, SLM, surface roughness, stainless steel

Procedia PDF Downloads 128

Authors: B. Laurita

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The importance of Water Harvesting (WH) as an effective mean to deal with water scarcity is universally recognized. The collection and storage of rainwater, floodwater or quick runoff and their conversion to productive uses can ensure water availability for domestic and agricultural use, enabling a lower exploitation of the aquifer, preventing erosion events and providing significant ecosystem services. At the same time, it has been proven that it can reduce the insurgence of water conflicts if supported by a cooperative process of planning and management. On the other hand, the construction of water harvesting structures changes the hydrological regime, affecting upstream-downstream dynamics and changing water allocation, often causing contentions. Furthermore, dynamics existing between water harvesting and water conflict are not properly investigated yet. Thus, objective of this study is to analyze the relations between water harvesting and the insurgence of water conflicts, providing a solid theoretical basis and foundations for future studies. Two search engines were selected in order to perform the study: Google Scholar and Scopus. Separate researches were conducted on the mutual influences between water conflicts and the four main water harvesting techniques: rooftop harvesting, surface harvesting, underground harvesting, runoff harvesting. Some of the aforementioned water harvesting techniques have been developed and implemented on scales ranging from the small, household-sided ones, to gargantuan dam systems. Instead of focusing on the collisions related to large-scale systems, this review is aimed to look for and collect examples of the effects that the implementation of small water harvesting systems has had on the access to the water resource and on water governance. The present research allowed to highlight that in the studies that have been conducted up to now, water harvesting, and in particular those structures that allow the collection and storage of water for domestic use, is usually recognized as a positive, palliative element during contentions. On the other hand, water harvesting can worsen and, in some cases, even generate conflicts for water management. This shows the necessity of studies that consider both benefits and negative influences of water harvesting, analyzing its role respectively as triggering or as mitigating factor of conflicting situations.

Keywords: arid areas, governance, water conflicts, water harvesting

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Authors: Armin Bodaghkhani, Bruce Colbourne, Yuri S. Muzychka

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The process of spray-cloud formation and flow kinematics produced from breaking wave impact on vertical and slant lab-scale bow-shaped models were experimentally investigated. Bubble Image Velocimetry (BIV) and Image Processing (IP) techniques were applied to study the various types of wave-model impacts. Different wave characteristics were generated in a tow tank to investigate the effects of wave characteristics, such as wave phase velocity, wave steepness on droplet velocities, and behavior of the process of spray cloud formation. The phase ensemble-averaged vertical velocity and turbulent intensity were computed. A high-speed camera and diffused LED backlights were utilized to capture images for further post processing. Various pressure sensors and capacitive wave probes were used to measure the wave impact pressure and the free surface profile at different locations of the model and wave-tank, respectively. Droplet sizes and velocities were measured using BIV and IP techniques to trace bubbles and droplets in order to measure their velocities and sizes by correlating the texture in these images. The impact pressure and droplet size distributions were compared to several previously experimental models, and satisfactory agreements were achieved. The distribution of droplets in front of both models are demonstrated. Due to the highly transient process of spray formation, the drag coefficient for several stages of this transient displacement for various droplet size ranges and different Reynolds number were calculated based on the ensemble average method. From the experimental results, the slant model produces less spray in comparison with the vertical model, and the droplet velocities generated from the wave impact with the slant model have a lower velocity as compared with the vertical model.

Keywords: spray charachteristics, droplet size and velocity, wave-body interactions, bubble image velocimetry, image processing

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Authors: Akbar Khodavirdizadeh, Ali Nemati Babaylou, Hassan Moomivand

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The history of human access to water technique has been one of the factors in the formation of human civilizations in the ancient world. The technique that makes surface water and groundwater accessible to humans on the ground has been a clever technique in human life to reach the water. In this study, while examining the water technique of ancient Iran using the Qanats technique, the water supply system of different regions of the ancient world were also studied and compared. Six groups of the ancient region of ancient Greece (Archaic 480-750 BC and Classical 223-480 BC), Urartu in Tuspa (600-850 BC), Petra (106-168 BC), Ancient Rome (265 BC), and the ancient United States (1450 BC) and ancient Iranian water technologies were studied under water supply systems. Past water technologies in these areas: water transmission systems in primary urban centers, use of water structures in water control, use of bridges in water transfer, construction of waterways for water transfer, storage of rainfall, construction of various types of pottery- ceramic, lead, wood and stone pipes have been used in water transfer, flood control, water reservoirs, dams, channel, wells, and Qanat. The central plateau of Iran is one of the arid and desert regions. Archaeological, geomorphological, and paleontological studies of the central region of the Iranian plateau showed that without the use of Qanats, the possibility of urban civilization in this region was difficult and even impossible. Zarch aqueduct is the most important aqueduct in Yazd region. Qanat of Zarch is a plain Qanat with a gallery length of 80 km; its mother well is 85 m deep and has 2115 well shafts. The main purpose of building the Qanat of Zārch was to access the groundwater source and transfer it to the surface of the ground. Regarding the structure of the aqueduct and the technique of transferring water from the groundwater source to the surface, it has a great impact on being different from other water techniques in the ancient world. The results show that the use of water technologies in ancient is very important to understand the history of humanity in the use of hydraulic techniques.

Keywords: ancient water technologies, groundwaters, qanat, human history, Ancient Iran

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Authors: Arda Ozkurt, Ozlem Bozkurt

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Brain-computer interfaces (BCIs) are devices that output commands by interpreting the data collected from the brain. Electroencephalography (EEG) is a non-invasive method to measure the brain's electrical activity. Since it was invented by Hans Berger in 1929, it has led to many neurological discoveries and has become one of the essential components of non-invasive measuring methods. Despite the fact that it has a low spatial resolution -meaning it is able to detect when a group of neurons fires at the same time-, it is a non-invasive method, making it easy to use without possessing any risks. In EEG, electrodes are placed on the scalp, and the voltage difference between a minimum of two electrodes is recorded, which is then used to accomplish the intended task. The recordings of EEGs include, but are not limited to, the currents along dendrites from synapses to the soma, the action potentials along the axons connecting neurons, and the currents through the synaptic clefts connecting axons with dendrites. However, there are some sources of noise that may affect the reliability of the EEG signals as it is a non-invasive method. For instance, the noise from the EEG equipment, the leads, and the signals coming from the subject -such as the activity of the heart or muscle movements- affect the signals detected by the electrodes of the EEG. However, new techniques have been developed to differentiate between those signals and the intended ones. Furthermore, an EEG device is not enough to analyze the data from the brain to be used by the BCI implication. Because the EEG signal is very complex, to analyze it, artificial intelligence algorithms are required. These algorithms convert complex data into meaningful and useful information for neuroscientists to use the data to design BCI devices. Even though for neurological diseases which require highly precise data, invasive BCIs are needed; non-invasive BCIs - such as EEGs - are used in many cases to help disabled people's lives or even to ease people's lives by helping them with basic tasks. For example, EEG is used to detect before a seizure occurs in epilepsy patients, which can then prevent the seizure with the help of a BCI device. Overall, EEG is a commonly used non-invasive BCI technique that has helped develop BCIs and will continue to be used to detect data to ease people's lives as more BCI techniques will be developed in the future.

Keywords: BCI, EEG, non-invasive, spatial resolution

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Authors: M. J. Suriani, F. Mansor, W. Siti Maizurah, I. Nurizwani

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Silicon Carbide (SiC) is one of the Silicon-based materials, which get interested by the researcher. SiC is an emerging semiconductor material, which has received a great deal of attention due to their application in high frequency and high power systems. Although its superior characteristic for a semiconductor material, its outstanding mechanical properties, chemical inertness and thermal stability has gained important aspect for a surface coating for deployment in extreme environments. Very high frequency (VHF)-PECVD technique utilized to deposit nano ns-SiC film in which variation in chamber pressure, substrate temperature, RF power and precursor gases flow rate will be investigated in order to get a good quality of thin film coating. Characterization of the coating performed in order to study the surface morphology, structural information. This performance of coating evaluated through corrosion test to determine the effectiveness of the coating for corrosion prevention. Ns-SiC film expected to possess better corrosion resistance and optical properties, as well as preserving the metal from the marine environment. Through this research project, corrosion protection performance by applying coating will be explored to obtain a great corrosion prevention method to the shipping and oil and gas industry in Malaysia. Besides, the cost of repair and maintenance spending by the government of Malaysia can be reduced through practicing this method.

Keywords: composite materials, marine corrosion, nano-composite, nano structure–coating

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Authors: Shoeb Ahmed Adeel, Vivek Paul, K. Prajwal, Michael Fenelon

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Techniques have been used to tether and stabilize a multi-rotor MAV but carrying out the same process to a fixed wing MAV is a novel method which can be utilized in order to reduce damage occurring to the fixed wing MAVs while conducting flight test trials and PID tuning. A few sensors and on board controller is required to carry out this experiment in horizontal and vertical plane of the vehicle. Here we will be discussing issues such as sensitivity of the air vehicle, endurance and external load of the string acting on the vehicle.

Keywords: MAV, PID tuning, tethered flight, UAV

Procedia PDF Downloads 628

Authors: Chitra Rajagopal, Indra Deo Kumar, Ila Chauhan, Ruchi Joshi, Binoy Bhargavan

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Reliability and safety are essential for the success of mission-critical and safety-critical defense systems. Humans are part of the entire life cycle of defense systems development and deployment. The majority of industrial accidents or disasters are attributed to human errors. Therefore, considerations of human performance and human reliability are critical in all complex systems, including defense systems. Defense systems are operating from the ground, naval and aerial platforms in diverse conditions impose unique physical and psychological challenges to the human operators. Some of the safety and mission-critical defense systems with human-machine interactions are fighter planes, submarines, warships, combat vehicles, aerial and naval platforms based missiles, etc. Human roles and responsibilities are also going through a transition due to the infusion of artificial intelligence and cyber technologies. Human operators, not accustomed to such challenges, are more likely to commit errors, which may lead to accidents or loss events. In such a scenario, it is imperative to understand the human factors in defense systems for better systems performance, safety, and cost-effectiveness. A case study using Task Analysis (TA) based methodology for assessment and reduction of human errors in the Air and Missile Defense System in the context of emerging technologies were presented. Action-oriented task analysis techniques such as Hierarchical Task Analysis (HTA) and Operator Action Event Tree (OAET) along with Critical Action and Decision Event Tree (CADET) for cognitive task analysis was used. Human factors assessment based on the task analysis helps in realizing safe and reliable defense systems. These techniques helped in the identification of human errors during different phases of Air and Missile Defence operations, leading to meet the requirement of a safe, reliable and cost-effective mission.

Keywords: defence systems, reliability, risk, safety

Procedia PDF Downloads 131

Authors: H. H. Elewa, E. M. Ramadan, A. M. Nosair

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Rainfall water harvesting is considered as an important tool for overcoming water scarcity in arid and semi-arid region. Wadi Watir in the southeastern part of Sinai Peninsula is considered as one of the main and active basins in the Gulf of Aqaba drainage system. It is characterized by steep hills mainly consist of impermeable rocks, whereas the streambeds are covered by a highly permeable mixture of gravel and sand. A comprehensive approach involving the integration of geographic information systems, remote sensing and watershed modeling was followed to identify the RWH capability in this area. Eight thematic layers, viz volume of annual flood, overland flow distance, maximum flow distance, rock or soil infiltration, drainage frequency density, basin area, basin slope and basin length were used as a multi-parametric decision support system for conducting weighted spatial probability models (WSPMs) to determine the potential areas for the RWH. The WSPMs maps classified the area into five RWH potentiality classes ranging from the very low to very high. Three performed WSPMs' scenarios for W. Watir reflected identical results among their maps for the high and very high RWH potentiality classes, which are the most suitable ones for conducting surface water harvesting techniques. There is also a reasonable match with respect to the potentiality of runoff harvesting areas with a probability of moderate, low and very low among the three scenarios. WSPM results have shown that the high and very high classes, which are the most suitable for the RWH are representing approximately 40.23% of the total area of the basin. Accordingly, several locations were decided for the establishment of water harvesting dams and cisterns to improve the water conditions and living environment in the study area.

Keywords: Sinai, Wadi Watir, remote sensing, geographic information systems, watershed modeling, runoff water harvesting

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Authors: Javeria Arain, Saad Malik

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The management of solid waste is a crucial and essential aspect of urban environmental management especially in a city with an ever increasing population such as Karachi. The total amount of municipal solid waste generated from Gulshan e Iqbal town on average is 444.48 tons per day and landfill sites are a widely accepted solution for final disposal of this waste. However, an improperly selected site can have immense environmental, economical and ecological impacts. To select an appropriate landfill site a number of factors should be kept into consideration to minimize the potential hazards of solid waste. The purpose of this research is to analyse the study area for the construction of an appropriate landfill site for disposal of municipal solid waste generated from Gulshan e-Iqbal Town by using geospatial techniques considering hydrological, geological, social and geomorphological factors. This was achieved using analytical hierarchy process and fuzzy analysis as a decision support tool with integration of geographic information sciences techniques. Eight most critical parameters, relevant to the study area, were selected. After generation of thematic layers for each parameter, overlay analysis was performed in ArcGIS 10.0 software. The results produced by both methods were then compared with each other and the final suitability map using AHP shows that 19% of the total area is Least Suitable, 6% is Suitable but avoided, 46% is Moderately Suitable, 26% is Suitable, 2% is Most Suitable and 1% is Restricted. In comparison the output map of fuzzy set theory is not in crisp logic rather it provides an output map with a range of 0-1, where 0 indicates least suitable and 1 indicates most suitable site. Considering the results it is deduced that the northern part of the city is appropriate for constructing the landfill site though a final decision for an optimal site could be made after field survey and considering economical and political factors.

Keywords: Analytical Hierarchy Process (AHP), fuzzy set theory, Geographic Information Sciences (GIS), Multi-Criteria Decision Analysis (MCDA)

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Imen Hamed, Burcu Ak, Oya Işık, Leyla Uslu, Kubilay Kazım Vursavuş

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In this study, 3 species of Dunaliella (Dunaliella sp. Salt Lake isoalte (Tuz Gölü), Dunaliella salina CCAP19/18, and Dunaliella bardawil LB 2538) and their optical density, dry matter, chlorophyll a, total carotenoids, and β-carotene production were investigated in a batch system. The aim of this research was to compare carotenoids, and β-carotene production were investigated in a batch those 3 species. Therefore 2 stress factors were used: 2 different temperatures (20°C and 30°C) and 2 different salinities (30‰, and 60‰) were tested over a 17-day study. The highest growth and chlorophyll a was reported for Dunaliella sp. under 20°C/30‰ and 20°C/60‰ conditions respectively followed by D. bardawil and D. salina. Significant differences were noticed (p<0.05) for the other 3 species. The growth decreased as temperature and salinity increased since the lowest growth was noticed for the 30°C/60‰ group. The chlorophyll a content decreased also as temperature increased however when the NaCl concentration increased an augmentation of the content was noticed . In the 17^th day of experiment the highest carotenoids concentration was reported for D. bardawil 20°C/30‰ (65,639±0,400 μg.mL⁻¹) and the most important β carotene concentration was for D. salina 20°C/60‰ (8,98E-07±0,013 mol/L).

Keywords: Dunaliella sp., Dunaliella salina, Dunaliella bardawil, growth, pigments, stress factors

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Authors: Ayesha Asma, Aqsa Arooj

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It is an essential need in this era of Science and Technology to investigate some unique and appropriate materials for optoelectronic applications. Here, we deliberated, for the first time, the structural, optoelectronic, mechanical, vibrational, and thermo dynamical properties of hexagonal structure selenium-based ternary chalcogenides AScSe₂ (A= K, Cs) by using Perdew-Burke-Ernzerhof Generalized-Gradient-Approximation (PBE-GGA). The lattice angles for these materials are found as α=β=90o and γ=120o. KScSe₂ optimized with lattice parameters a=b=4.3 (Å), c=7.81 (Å) whereas CsScSe₂ got relaxed at a=b=4.43 (Å) and c=8.51 (Å). However, HSE06 functional has overestimated the lattice parameters to the extent that for KScSe₂ a=b=4.92 (Å), c=7.10 (Å), and CsScSe₂ a=b=5.15 (Å), c=7.09 (Å). The energy band gap of these materials calculated via PBE-GGA and HSE06 functionals confirms their semiconducting nature. Concerning Born’s criteria, these materials are mechanically stable ones. Moreover, the temperature dependence of thermodynamic potentials and specific heat at constant volume are also determined while using the harmonic approximation. The negative values of free energy ensure their thermodynamic stability. The vibrational modes are calculated by plotting the phonon dispersion and the vibrational density of states (VDOS), where infrared (IR) and Raman spectroscopy are used to characterize the vibrational modes. The various optical parameters are examined at a smearing value of 0.5eV. These parameters unveil that these materials are good absorbers of incident light in ultra-violet (UV) regions and may be utilized in photovoltaic applications.

Keywords: structural, optimized, vibrational, ultraviolet

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Proficiency Munsaka, Peter Baricholo, Erich Rohwer

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Pulse evolutions along the 5 cm long, 6.0 ×4.2 μm² cross-section silicon germanium (SiGe) photonic waveguides were simulated and compared with experiments. Simulations were carried out by solving a generalized nonlinear Schrodinger equation (GNLSE) for an optical pulse evolution along the length of the SiGe photonic waveguides by the split-step Fourier method (SSFM). The solution obtained from the SSFM gave the pulse envelope in both time and spectral domain calculated at each distance step along the propagation direction. The SiGe photonic waveguides were pumped in an anomalous group velocity dispersion (GVD) regime using a 4.7 μm, 210 fs femtosecond laser to produce a significant supercontinuum (SC). The simulated propagation of ultrafast pulse along the SiGe photonic waveguides produced an SC covering the atmospheric window (2.5-8.5 μm) containing the molecular fingerprints for important gases. Thus, the mid-infrared supercontinuum generation in SiGe photonic waveguides system can be commercialized for gas spectroscopy for detecting gases that include CO₂, CH₄, H₂O, SO₂, SO₃, NO₂, H₂S, CO, and NO at trace level using absorption spectroscopy technique. The simulated profile evolutions are spectrally and temporally similar to those obtained by other researchers. Obtained evolution profiles are characterized by pulse compression, Soliton fission, dispersive wave generation, stimulated Raman Scattering, and Four Wave mixing.

Keywords: silicon germanium photonic waveguide, supercontinuum generation, spectroscopy, mid infrared

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Authors: Mohamed F. Sadek, Safaa M. Hassan, Safwat S. Gabr

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Several alteration zones hosting gold mineralization are wide spreading in the South Eastern Desert of Egypt where gold has been mined from many localities since the time of the Pharaohs. The Sukkari is the only mine currently producing gold in the Eastern Desert of Egypt. Therefore, it is necessary to conduct more detailed studies on these locations using modern exploratory methods. The remote sensing plays an important role in lithological mapping and detection of associated hydrothermal mineralization particularly the exploration of gold mineralization. This study is focused on three localities in South Eastern Desert of Egypt, namely Beida, Defiet and Hoteib-Eiqat aiming to detect the gold-bearing hydrothermal alteration zones using the integrated data of remote sensing, field study and mineralogical investigation. Generally, these areas are dominated by Precambrian basement rocks including metamorphic and magmatic assemblages. They comprise ophiolitic serpentinite-talc carbonate, island-arc metavolcanics which were intruded by syn to late orogenic mafic and felsic intrusions mainly gabbro, granodiorite and monzogranite. The processed data of Advanced Spaceborne Thermal Emission and Reflection (ASTER) and Landsat-8 images are used in the present study to map the gold bearing-hydrothermal alteration zones. Band rationing and principal component analysis techniques are used to discriminate the different lithologic units exposed in the studied three areas. Field study and mineralogical investigation have been used to verify the remote sensing data. This study concluded that, the integrated remote sensing data with geological, field and mineralogical investigations are very effective in lithological discrimination, detailed geological mapping and detection of the gold-bearing hydrothermal alteration zones. More detailed exploration for gold mineralization with the help of remote sensing techniques is recommended to evaluate its potentiality in the study areas.

Keywords: pan-african, Egypt, landsat-8; ASTER, gold, alteration zones

Procedia PDF Downloads 119

Authors: Talha Ali Khan

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Discovering different energy resources to full fill the world growing demand is now one of the society’s bigger challenge for the next half-century. The main task is to convert the sun radiation into electricity via photovoltaic solar cells which is suddenly decreasing $/watt of delivered solar electricity. Therefore, in this context, the sun trackers are those devices that can be used to ameliorate efficiency. In this paper, a variety of the sun tracking systems are evaluated and their merits and demerits are highlighted. The most adept and proficient sun-tracking devices are polar axis and azimuth-elevation types.

Keywords: dual axis, fixed axis, sun tracker, MPPT

Procedia PDF Downloads 571

Authors: Fabricio Costa Silva, Samuel Xavier de Souza

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A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information's are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, low complexity, parallelism

Procedia PDF Downloads 493

Authors: Luksanaporn Krungkraipetch

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A pterygium is an eye surface lesion that begins in the limbal conjunctiva and progresses to the cornea. The lesion is more common in the nasal limbus than in the temporal, and it has a distinctive wing-like aspect. Indications for surgery, in decreasing order of significance, are grown over the corneal center, decreased vision due to corneal deformation, documented growth, sensations of discomfort, and aesthetic concerns. Recurrent pterygium results in the loss of time, the expense of therapy, and the potential for vision impairment. The objective of this study is to find out how often the recurrence of pterygium after surgery occurs, what effect the surgery technique has, and what causes them to come back in people with pterygium. Materials and Methods: Observational case control in retrospect: the study involves a retrospective analysis of 164 patient samples. Data analysis is descriptive statistics analysis, i.e., basic data details about pterygium surgery and the risk of recurrent pterygium. For factor analysis, the inferential statistics odds ratio (OR) and 95% confidence interval (CI) ANOVA are utilized. A p-value of 0.05 was deemed statistically important. Results: The majority of patients, according to the results, were female (60.4%). Twenty-four of the 164 (14.6%) patients who underwent surgery exhibited recurrent pterygium. The average age is 55.33 years old. Postoperative recurrence was reported in 19 cases (79.3%) of bare sclera techniques and five cases (20.8%) of conjunctival autograft techniques. The recurrence interval is 10.25 months, with the most common (54.17 percent) being 12 months. In 91.67 percent of cases, all follow-ups are successful. The most common recurrence level is 1 (25%). A surgical complication is a subconjunctival hemorrhage (33.33 percent). Comparing the surgeries done on people with recurrent pterygium didn't show anything important (F = 1.13, p = 0.339). Age significantly affected the recurrence of pterygium (95% CI, 6.79-63.56; OR = 20.78, P 0.001). Conclusion: This study discovered a 14.6% rate of pterygium recurrence after pterygium surgery. Across all surgeries and patients, the rate of recurrence was four times higher with the bare sclera method than with conjunctival autograft. The researchers advise selecting a more conventional surgical technique to avoid a recurrence.

Keywords: pterygium, recurrence pterygium, pterygium surgery, excision pterygium

Procedia PDF Downloads 85

Authors: Tamunotonye Mayowa Braide, Isaac Oluwatayo

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This study investigates multidimensional poverty, and its correlates among rural households in Sekhukhune and Capricorn District municipalities (SDM & CDM) in Limpopo Province, South Africa. Primary data were collected from 407 rural households selected through purposive and simple random sampling techniques. Analytical techniques employed include descriptive statistics, principal component analysis (PCA), and the Alkire Foster (A-F) methodology. The results of the descriptive statistics showed there are more females (66%) than males (34%) in rural areas of Limpopo Province, with about 45% of them having secondary school education as the highest educational level attained and only about 3% do not have formal education. In the analysis of deprivation, eight dimensions of deprivation, constructed from 21 variables, were identified using the PCA. These dimensions include type and condition of dwelling water and sanitation, educational attainment and income, type of fuel for cooking and heating, access to clothing and cell phone, assets and fuel for light, health condition, crowding, and child health. In identifying the poor with poverty cut-off (0.13) of all indicators, about 75.9% of the rural households are deprived in 25% of the total dimensions, with the adjusted headcount ratio (M0) being 0.19. Multidimensional poverty estimates showed higher estimates of poor rural households with 71%, compared to 29%, which fall below the income poverty line. The study conducted poverty decomposition, using sub-groups within the area by examining regions and household characteristics. In SDM, there are more multidimensionally poor households than in CDM. The water and sanitation dimension is the largest contributor to the multidimensional poverty index (MPI) in rural areas of Limpopo Province. The findings can, therefore, assist in better design of welfare policy and target poverty alleviation programs and as well help in efficient resource allocation at the provincial and local municipality levels.

Keywords: Alkire-Foster methodology, Limpopo province, multidimensional poverty, principal component analysis, South Africa

Procedia PDF Downloads 156

Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

Procedia PDF Downloads 79

Authors: Wed Albalawi, Ebtihaj Jambi, Maha Albazi, Shareefa AlGhamdi

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Heavy metal pollution has become a hard threat to marine ecosystems alongside extremely industrialized and urban (urbanized) zones because of their toxicity, resolution, and non-biodegradable nature. Great interest has been given to a new technique -biosorption- which exploits the cell envelopes of organisms to remove metals from water solutions. The main objective of the present study is to explore the potential of marine algae from the Red Sea for the removal of heavy metals from an aqueous medium. The subsequent objective is to study the effect of pH and agitation time on the adsorption capacity of marine algae. Randomly chosen algae from the Red Sea (Jeddah) with known altitude and depth were collected. Analysis of heavy metal ion concentration was measured by ICP-OES (Inductively coupled plasma - optical emission spectrometry) using air argon gas. A standard solution of heavy metal ions was prepared by diluting the original standard solution with ultrapure water. Types of seaweed were used to study the effect of pH on the biosorption of different heavy metals. The biosorption capacity of Cr is significantly lower in Padina Pavonica (P.P) compared to the biosorption capacity in Sargassum Muticum (S.M). The S.M exhibited significantly higher in Cr removal than the P.P at pH 2 and pH 7. However, the P.P exhibited significantly higher in Cr removal than the S.M at pH 3, pH 4, pH 5, pH 6, and pH 8. In conclusion, the dried cells of algae can be used as an effective tool for the removal of heavy metals.

Keywords: biosorption, heavy metal, pollution, pH value, brown algae

Procedia PDF Downloads 66

Authors: Kishor Chandra Kandpal, Amit Kumar

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The Indian Himalaya region harbours approximately 1748 plants of medicinal importance, and as per International Union for Conservation of Nature (IUCN), the 112 plant species among these are threatened and endangered. To ease the pressure on these plants, the government of India is encouraging its in-situ cultivation. The Saussurea costus, Valeriana jatamansi, and Picrorhiza kurroa have also been prioritized for large scale cultivation owing to their market demand, conservation value and medicinal properties. These species are found from 1000 m to 4000 m elevation ranges in the Indian Himalaya. Identification of these plants in the field requires taxonomic skills, which is one of the major bottleneck in the conservation and management of these plants. In recent years, Hyperspectral remote sensing techniques have been precisely used for the discrimination of plant species with the help of their unique spectral signatures. In this background, a spectral library of the above 03 medicinal plants was prepared by collecting the spectral data using a handheld spectroradiometer (325 to 1075 nm) from farmer’s fields of Himachal Pradesh and Uttarakhand states of Indian Himalaya. The Random forest (RF) model was implied on the spectral data for the classification of the medicinal plants. The 80:20 standard split ratio was followed for training and validation of the RF model, which resulted in training accuracy of 84.39 % (kappa coefficient = 0.72) and testing accuracy of 85.29 % (kappa coefficient = 0.77). This RF classifier has identified green (555 to 598 nm), red (605 nm), and near-infrared (725 to 840 nm) wavelength regions suitable for the discrimination of these species. The findings of this study have provided a technique for rapid and onsite identification of the above medicinal plants in the field. This will also be a key input for the classification of hyperspectral remote sensing images for mapping of these species in farmer’s field on a regional scale. This is a pioneer study in the Indian Himalaya region for medicinal plants in which the applicability of hyperspectral remote sensing has been explored.

Keywords: himalaya, hyperspectral remote sensing, machine learning; medicinal plants, random forests

Procedia PDF Downloads 198

Authors: Renata Adriana Labanca, Gabriela Rezende Costa, Nilton de Oliveira Couto e Silva, José Marcos Gontijo Mandarino, Rodrigo Santos Leite, Nilson César Castanheira Guimarães, Roberto Gonçalves Junqueira

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The objective of this study was to evaluate the differences in composition between six brands of conventional soybean and six genetically modified cultivars (GM), all of them from Minas Gerais State, Brazil. We focused on the isoflavones profile and mineral content questioning the substantial equivalence between conventional and GM organisms. The statement of compliance label for conventional grains was verified for the presence of genetic modified genes by real time polymerase chain reaction (PCR). We did not detect the presence of the 35S promoter in commercial samples, indicating the absence of transgene insertion. For mineral analysis, we used the method of inductively coupled plasma-optical emission spectrometry (ICP-OES). Isoflavones quantification was performed by high performance liquid chromatography (HPLC). The results showed no statistical difference between the conventional and transgenic soybean groups concerning isoflavone content and mineral composition. The concentration of potassium, the main mineral component of soy, was the highest in conventional soybeans compared to that in GM soy, while GM samples presented the highest concentrations of iron.

Keywords: glycine max, genetically modified organism, bioactive compounds, ICP-OES, HPLC

Procedia PDF Downloads 451