Search results for: grid synchronization technique

Authors: J. D. García Espinel, Paula Pérez Sánchez, Carlos Egea Ruiz, Carlos Lardín Mifsut, Andrés López-Aranguren Oliver

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This paper shortly describes three main actuations over a Waste Water Treatment Plant (WWTP) for reducing its energy consumption: Optimization of the biological reactor in the aeration stage by including new control algorithms and introducing new efficient equipment, the installation of an innovative hybrid system with zero Grid injection (formed by 100kW of PV energy and 5 kW of mini-wind energy generation) and an intelligent management system for load consumption and energy generation control in the most optimum way. This project called RENEWAT, involved in the European Commission call LIFE 2013, has the main objective of reducing the energy consumptions through different actions on the processes which take place in a WWTP and introducing renewable energies on these treatment plants, with the purpose of promoting the usage of treated waste water for irrigation and decreasing the C02 gas emissions. WWTP is always required before waste water can be reused for irrigation or discharged in water bodies. However, the energetic demand of the treatment process is high enough for making the price of treated water to exceed the one for drinkable water. This makes any policy very difficult to encourage the re-use of treated water, with a great impact on the water cycle, particularly in those areas suffering hydric stress or deficiency. The cost of treating waste water involves another climate-change related burden: the energy necessary for the process is obtained mainly from the electric network, which is, in most of the cases in Europe, energy obtained from the burning of fossil fuels. The innovative part of this project is based on the implementation, adaptation and integration of solutions for this problem, together with a new concept of the integration of energy input and operative energy demand. Moreover, there is an important qualitative jump between the technologies used and the alleged technologies to use in the project which give it an innovative character, due to the fact that there are no similar previous experiences of a WWTP including an intelligent discrimination of energy sources, integrating renewable ones (PV and Wind) and the grid.

Keywords: aeration system, biological reactor, CO2 emissions, energy efficiency, hybrid systems, LIFE 2013 call, process optimization, renewable energy sources, wasted water treatment plants

Procedia PDF Downloads 352

Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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Authors: Boukhalfa Djemouai, Belkadi Souhila, Safsaf Boubakeur

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To increase the profitability of the national herd so that it can meet the needs of the population, Algeria has proceeded to the introduction of new reproductive biotechnologies, including artificial insemination on natural heat, by induction and heat synchronization. This biotechnology uses the male way for the creation and dissemination of genetic progress. The study has focused on 30 goat kids and bucks local breed aged between 03 and 24 months, divided into 03 groups 03-06 months[Grp 1; n=9], 07-10 months [Grp 2; n=13] and 11-24 months [Grp 3; n=8], in order to determine the influence of age on testicular evolution by measurements of testis and scrotum, and the epididymis sperm parameters evaluation. These parameters are influenced by age variations (sperm and spermocytogram). The examined parameters have focused on testicular weight (grams), the scrotal circumference (cm), mass mobility (%), vitality rate (%), sperm concentration (x 109), and percentage of abnormal spermatozoa (%). The ANOVA reveals a significance effect of age on parameters: testis weight, scrotal circumference, sperm concentration, motility varying between high (p < 0.01) to very high significance (p < 0.001), while in viability and abnormalities no significance was observed between all groups. The value of these parameters increased significantly until the age of 02 years, while that of sperm abnormalities has increased in Grp2. The histological study of testicular development shows that the genetic spermatozoa function characterized by cell proliferation, which is more and more intense starting from the age of 05 months and can be considered as an age of puberty in the local breed goat Arbia and increases with animal age.

Keywords: kids and bucks, epididymis sperm, testicular measurements, Arbia breed

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Authors: Shagufta Tabassum, V. P. Pawar

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The study of static dielectric properties in a binary mixture of 1,2 dichloroethane (DE) and n,n dimethylformamide (DMF) polar liquids has been carried out in the frequency range of 10 MHz to 30 GHz for 11 different concentration using time domain reflectometry technique at 10ºC temperature. The dielectric relaxation study of solute-solvent mixture at microwave frequencies gives information regarding the creation of monomers and multimers as well as interaction between the molecules of the binary mixture. The least squares fit method is used to determine the values of dielectric parameters such as static dielectric constant (ε₀), dielectric constant at high frequency (ε_∞) and relaxation time (τ).

Keywords: shagufta shaikhexcess parameters, relaxation time, static dielectric constant, time domain reflectometry

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Authors: Yan Zhang, Jan Awrejcewicz, Lin Fu

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High-heeled shoes force the foot into plantar flexion position resulting in foot arch rising and disturbance of the articular congruence between the talus and tibiofibular mortice, all of which may increase the challenge of balance maintenance. Plantar pressure distribution of the stance limb during the star excursion balance test (SEBT) contributes to the understanding of potential sources of reaching excursions in SEBT. The purpose of this study is to evaluate the dynamic posture control while wearing high-heeled shoes using SEBT in a combination of plantar pressure measurement. Twenty healthy young females were recruited. Shoes of three heel heights were used: flat (0.8 cm), low (4.0 cm), high (6.6 cm). The testing grid of SEBT consists of three lines extending out at 120° from each other, which were defined as anterior, posteromedial, and posterolateral directions. Participants were instructed to stand on their dominant limb with the heel in the middle of the testing grid and hands on hips and to reach the non-stance limb as far as possible towards each direction. The distal portion of the reaching limb lightly touched the ground without shifting weight. Then returned the reaching limb to the beginning position. The excursion distances were normalized to leg length. The insole plantar measurement system was used to record peak pressure, contact area, and pressure-time integral of the stance limb. Results showed that normalized excursion distance decreased significantly as heel height increased. The changes of plantar pressure in SEBT as heel height increased were more obvious in the medial forefoot (MF), medial midfoot (MM), rearfoot areas. At MF, the peak pressure and pressure-time integral of low and high shoes increased significantly compared with that of flat shoes, while the contact area decreased significantly as heel height increased. At MM, peak pressure, contact area, and pressure-time integral of high and low shoes were significantly lower than that of flat shoes. To reduce posture instability, the stance limb plantar loading shifted to medial forefoot. Knowledge of this study identified dynamic posture control deficits while wearing high-heeled shoes and the critical role of the medial forefoot in dynamic balance maintenance.

Keywords: dynamic posture control, high-heeled shoes, plantar pressure, star excursion balance test.

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Authors: Rade M. Ciric, Nikola L. J. Rajakovic

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This paper presents a curriculum of the subject small power plants and renewable energy sources, dealing with the concept of distributed generation, renewable energy sources, hydropower, wind farms, geothermal power plants, cogeneration plants, biogas plants of agriculture and animal origin, solar power and fuel cells. The course is taught the manner of connecting small power plants to the grid, the impact of small generators on the distribution system, as well as economic, environmental and legal aspects of operation of distributed generators.

Keywords: distributed generation, renewable energy sources, energy policy, curriculum

Procedia PDF Downloads 357

Authors: P. Azimi, B. Behtoiy, A. A. Najafi, H. R. Charmchi

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According to the previous studies, one of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: assembly line balancing problem, optimization via simulation, production planning

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Authors: Weeraya Samnuknit, Apichat Boontawan

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A vacuum fractionation technique was introduced to remove ethanol from fermentation broth. The effect of initial glucose and ethanol concentrations were investigated for specific productivity. The inhibitory ethanol concentration was observed at 100 g/L. In order to increase the fermentation performance, the ethanol product was removed as soon as it is produced. The broth was boiled at 35°C by reducing the pressure to 65 mBar. The ethanol/water vapor was fractionated for up to 90 wt% before leaving the column. Ethanol concentration in the broth was kept lower than 25 g/L, thus minimized the product inhibition effect to the yeast cells. For batch extractive fermentation, a high substrate utilization rate was obtained at 26.6 g/L.h and most of glucose was consumed within 21 h. For repeated-batch extractive fermentation, addition of glucose was carried out up to 9 times and ethanol was produced more than 8-fold higher than batch fermentation.

Keywords: ethanol, extractive fermentation, product inhibition, vacuum fractionation

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

Procedia PDF Downloads 329

Authors: Mohammad Khodaei, Mahmood Meratien, Alireza Valanezhad, Serdar Pazarlioglu, Serdar Salman, Ikuya Watanabe

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Pore size and morphology plays a crucial role on mechanical properties of porous scaffolds. In this research, titanium scaffold was prepared using space holder technique. Sodium chloride and ammonium bicarbonate were utilized as spacer agent separately. The effect of the hardness of spacer on the cell morphology was investigated using scanning electron microscopy (SEM) and optical stereo microscopy. Image analyzing software was used to interpret the microscopic images quantitatively. It was shown that sodium chloride, due to its higher hardness, maintain its morphology during cold compaction, and cause better replication in porous scaffolds.

Keywords: Spacer, Titanium Scaffold, Pore Morphology, Space Holder Technique

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Authors: Olga V. Kharchenko

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Applicability of a KTA crystal-based laser system with optical parametric oscillators (OPO) generation to lidar sounding of the atmosphere in the spectral range 3–4 µm is studied in this work. A technique based on differential absorption lidar (DIAL) method and differential optical absorption spectroscopy (DOAS) is developed for lidar sounding of trace atmospheric gases (TAG). The DIAL-DOAS technique is tested to estimate its efficiency for lidar sounding of atmospheric trace gases.

Keywords: atmosphere, lidar sounding, DIAL, DOAS, trace gases, nonlinear crystal

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

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Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: H. Kelkoul, Y. Zaz

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Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: digital cinema, watermarking, wavelet DWT, spread spectrum, JPEG2000 MPEG4

Procedia PDF Downloads 251

Authors: Diana Gomez-Cano, J. C. Ochoa-Botero, Roberto Bernal Correa, Yhan Paul Arias

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To obtain high mechanical performance, the fresh conditions of a mortar are decisive. Measuring the absorption of aggregates used in mortar mixes is a fundamental requirement for proper design of the mixes prior to their placement in construction sites. In this sense, absorption is a determining factor in the design of a mix because it conditions the amount of water, which in turn affects the water/cement ratio and the final porosity of the mortar. Thus, this work focuses on the mechanical behavior of recycled mortars manufactured from moisture correction using the Thermogravimetric Balancing Halogen Light (TBHL) technique in comparison with the traditional ASTM C 128 International Standard method. The advantages of using the TBHL technique are favorable in terms of reduced consumption of resources such as materials, energy, and time. The results show that in contrast to the ASTM C 128 method, the TBHL alternative technique allows obtaining a higher precision in the absorption values of recycled aggregates, which is reflected not only in a more efficient process in terms of sustainability in the characterization of construction materials but also in an effect on the mechanical performance of recycled mortars.

Keywords: alternative raw materials, halogen light, recycled mortar, resources optimization, water absorption

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Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

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Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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Authors: Sanghyun Park

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Influenced by the ideas of collectivism, East Asian contemporary dance is marked by an emphasis on unity and synchronization. A growing element of this discipline that disrupts the path that strives to attain perfection, requiring coordination between multiple parties in order to produce work of their highest artistic potential, with the support from individuals or groups is the presence of disabled dancers. Kawanaka Yo, a Japanese dancer with a mental disability, argues through her '“Dance of Peace' that a dancer should focus on her impulses and natural thoughts through improvisational dancing and eschewal of documentation. Professor and poet Jung-Gyu Jeong, co-founder of the Korea Disability International Art Company, demonstrates with his company’s modernized performances of popular works and musicals that disabled artists do not need perfection so long as they can assert their finesse to mimic or create an equivalence with able-bodied dancers. Yo has studied various forms of modern dance and ballet in Japan and has used her training to ease her mental disability but also accept her handicap as an extension of her identity, representing a trend in disabled dance that favors individuality and acceptance. In contrast, Jeong is an influential figure in South Korea for disabled dancers and artists, believing that disabled artists must overcome a certain threshold in order to reach a status as an artist that is equivalent to a 'normal artist.' East Asian art created by the disabled should not be judged according to different criteria or rubrics compared to able-bodied artists because, as Yo explains, a person’s identity and her handicaps characterize the meaning of, and the value of, the piece.

Keywords: disability studies, modern dance, East Asia, politics of identity

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Authors: Rihab Hamdi, Amel Hadri Hamida, Ouafae Bennis, Sakina Zerouali

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This paper features a performance analysis and robustness assessment of a digitally controlled DC-DC three-cell buck converter associated in parallel, operating in continuous conduction mode (CCM), facing feeding parameters variation and loads disturbance. The control strategy relies on the continuous-time with an averaged modeling technique for high-frequency switching converter. The methodology is to modulate the complete design procedure, in regard to the existence of an instantaneous current operating point for designing the digital closed-loop, to the same continuous-time domain. Moreover, the adopted approach is to include a digital voltage control (DVC) technique, taking an account for digital control delays and sampling effects, which aims at improving efficiency and dynamic response and preventing generally undesired phenomena. The results obtained under load change, input change, and reference change clearly demonstrates an excellent dynamic response of the proposed technique, also as provide stability in any operating conditions, the effectiveness is fast with a smooth tracking of the specified output voltage. Simulations studies in MATLAB/Simulink environment are performed to verify the concept.

Keywords: continuous conduction mode, digital control, parallel multi-cells converter, performance analysis, power electronics

Procedia PDF Downloads 150

Authors: Suchitra Chnadrashekhar

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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

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Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

Procedia PDF Downloads 387

Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

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Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

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Authors: Mattea Carmen Castrovilli, Antonella Cartoni

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Electrospray ionisation (ESI), a well-established technique widely used to produce ion beams of biomolecules in mass spectrometry (ESI-MS), can be used for ambient soft landing of enzymes on a specific substrate. In this work, we show how the ambient electrospray deposition (ESD) technique can be successfully exploited for manufacturing a promising, green-friendly electrochemical amperometric laccase-based biosensor with unprecedented reuse and storage performance. These biosensors have been manufactured by spraying a laccase solution of 2μg/μL at 20% of methanol on a commercial carbon screen printed electrode (C-SPE) using a custom ESD set-up. The laccase-based ESD biosensor has been tested against catechol compounds in the linear range 2-100 μM, with a limit of detection of 1.7 μM, without interference from cadmium, chrome, arsenic, and zinc and without any memory effects, but showing a matrix effect in lake and well water. The ESD biosensor shows enhanced performances compared to the ones fabricated with other immobilization methods, like drop-casting. Indeed, it retains 100% activity up to two months of storage at ambient conditions without any special care and working stability up to 63 measurements on the same electrode just prepared and 20 on a one-year-old electrode subjected to redeposition together with a 100% resistance to use of the same electrode in subsequent days. The ESD method is a one-step, environmentally friendly method that allows the deposition of the bio-recognition layer without using any additional chemicals. The promising results in terms of storage and working stability also obtained with the more fragile lactate oxidase enzyme suggest these improvements should be attributed to the ESD technique rather than to the bioreceptor, highlighting how the ESD could be useful in reducing pollution from disposable devices. Acknowledgment: The understanding at the molecular level of this promising biosensor by using different spectroscopies, microscopies and analytical techniques is the subject of our PRIN 2022 project ESILARANTE.

Keywords: reuse, storage performance, immobilization, electrospray deposition, biosensor, laccase, catechol detection, green chemistry

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Authors: Ade Dwi Utami

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Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Sharda Nara, Bansi Dhar Malhotra

Abstract:

Investigation of the vitamins as an electron transfer mediator could significantly assist in merging the area of tissue engineering and electronics required for the implantable therapeutic devices. The present study report that the molecules of folic acid released by Providencia rettgeri via fermentation route under the anoxic condition of the microbial fuel cell (MFC) exhibit characteristic electrochemical and optical properties, as indicated by absorption spectroscopy, photoluminescence (PL), and cyclic voltammetry studies. The absorption spectroscopy has depicted an absorption peak at 263 nm with a small bulge around 293 nm on day two of bacterial culture, whereas an additional peak was observed at 365 nm on the twentieth day. Furthermore, the PL spectra has indicated that the maximum emission occurred at various wavelengths 420, 425, 440, and 445 nm when excited by 310, 325, 350, and 365 nm. The change of emission spectra with varying excitation wavelength might be indicating the presence of tunable optical bands in the folic acid molecules co-related with the redox activity of the molecules. The results of cyclic voltammetry studies revealed that the oxidation and reduction occurred at 0.25V and 0.12V, respectively, indicating the electrochemical behavior of the folic acid. This could be inferred that the released folic acid molecules in a MFC might undergo inter as well as intra molecular electron transfer forming different intermediate states while transferring electrons to the electrode surface. Synchronization of electrochemical and optical properties of folic acid molecules could be potentially promising for the designing of electroactive scaffold and biocompatible conductive surface for the applications of tissue engineering and biofuel cells, respectively.

Keywords: biofuel cell, electroactivity, folic acid, tissue engineering

Procedia PDF Downloads 131

Authors: Jyun-Hao Liao, Chien-Ju Chen, Chia-Jui Yu, Meng Chyi Wu, Chia-Ching Wu

Abstract:

In this letter, we reported the fabrication of InGaAs micro-photodiode sensor array with the rapid thermal diffusion (RTD) technique. The spin-on dopant source Zn was used to form the p-type region in InP layer. Through the RTD technique, the InP/InGaAs heterostructure was formed. We improved our fabrication on the p-i-n photodiode to micro size which pixel is 7.8um, and the pitch is 12.8um. The proper SiNx was deposited to form the passivation layer. The leakage current of single pixel decrease to 3.3pA at -5V, and 35fA at -10mV. The leakage current densities of each voltage are 21uA/cm² at -5V and 0.223uA/cm² at -10mV. As we focus on the wavelength from 0.9um to 1.7um, the optimized Si/Al₂O₃ bilayers are deposited to form the AR-coating.

Keywords: InGaAs, micro sensor array, p-i-n photodiode, rapid thermal diffusion, Zn diffusion

Procedia PDF Downloads 318

Authors: K. Selvakumar, J. Kalaiselvimary, B. Jansirani, M. Ramesh Prabhu

Abstract:

Proton conducting sulphonated poly (vinylidene fluoride- hexafluoro propylene) PVdF-HFP membranes were modified with nano – sized montmorillonite (MMT) through homogeneous dispersive mixing and solution casting technique for fuel cell applications. The prepared composite membranes were characterized using Fourier Transform Infrared Spectroscopy and 1HNMR technique. The suitability of the composite membranes for fuel cell application was evaluated in terms of water uptake, swelling behavior, and proton conductivity. These composites showed good conductivities and durability and expected to be used in the development of proton exchange membrane for fuel cells.

Keywords: composite, proton conduction, sulphonation, water uptake

Procedia PDF Downloads 249

Authors: Daniil Karzanov

Abstract:

This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.

Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations

Procedia PDF Downloads 205

Authors: Hwan-Jun Choi, Sung-Bok Choi, Hyoung-Kyu Song

Abstract:

Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMOOFDM system is important issue. In this paper, efficient iterative VBLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6 % less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication.

Keywords: MIMO-OFDM, V-BLAST, QR-decomposition, QRDM, DFE, iterative scheme, channel condition

Procedia PDF Downloads 530