Search results for: unknown input observer

Authors: Ademuyiwa Agbonyin, Stamatis Zoras, Mohammad Zandi

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This paper investigates the extent to which building energy modelling can be informed based on preliminary information provided by infrared thermography using a thermal imaging camera in a walkthrough audit. The case-study building is the Sheffield Cathedral, built in the early 1400s. Based on an informative qualitative report generated from the thermal images taken at the site, the regions showing significant heat loss are input into a computer model of the cathedral within the integrated environmental solution (IES) virtual environment software which performs an energy simulation to determine quantitative heat losses through the building envelope. Building data such as material thermal properties and building plans are provided by the architects, Thomas Ford and Partners Ltd. The results of the modelling revealed the portions of the building with the highest heat loss and these aligned with those suggested by the thermal camera. Retrofit options for the building are also considered, however, may not see implementation due to a desire to conserve the architectural heritage of the building. Results show that thermal imaging in a walk-through audit serves as a useful guide for the energy modelling process. Hand calculations were also performed to serve as a 'control' to estimate losses, providing a second set of data points of comparison.

Keywords: historic buildings, energy retrofit, thermal comfort, software modelling, energy modelling

Procedia PDF Downloads 167

Authors: E. I. Ugwu

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Theoretical analysis of the optical and Solid State properties of ZnS thin film using beam propagation technique in which a scalar wave is propagated through the material thin film deposited on a substrate with the assumption that the dielectric medium is section into a homogenous reference dielectric constant term, and a perturbed dielectric term, representing the deposited thin film medium is presented in this work. These two terms, constitute arbitrary complex dielectric function that describes dielectric perturbation imposed by the medium of for the system. This is substituted into a defined scalar wave equation in which the appropriate Green’s Function was defined on it and solved using series technique. The green’s value obtained from Green’s Function was used in Dyson’s and Lippmann Schwinger equations in conjunction with Born approximation method in computing the propagated field for different input regions of field wavelength during which the influence of the dielectric constants and mesh size of the thin film on the propagating field were depicted. The results obtained from the computed field were used in turn to generate the data that were used to compute the band gaps, solid state and optical properties of the thin film such as reflectance, Transmittance and reflectance with which the band gap obtained was found to be in close approximate to that of experimental value.

Keywords: scalar wave, optical and solid state properties, thin film, dielectric medium, perturbation, Lippmann Schwinger equations, Green’s Function, propagation

Procedia PDF Downloads 434

Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

Procedia PDF Downloads 81

Authors: Bagul Abhijeet

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Background: Client-Server model is the backbone of today’s internet communication. In which normal user can not have control over particular website or server? By using the same processing model one can have unauthorized access to particular server. In this paper, we discussed about application scenario of hacking for simple website or server consist of unauthorized way to access the server database. This application emerges to autonomously take direct access of simple website or server and retrieve all essential information maintain by administrator. In this system, IP address of server given as input to retrieve user-id and password of server. This leads to breaking administrative security of server and acquires the control of server database. Whereas virus helps to escape from server security by crashing the whole server. Objective: To control malicious attack and preventing all government website, and also find out illegal work to do hackers activity. Results: After implementing different hacking as well as non-hacking techniques, this system hacks simple web sites with normal security credentials. It provides access to server database and allow attacker to perform database operations from client machine. Above Figure shows the experimental result of this application upon different servers and provides satisfactory results as required. Conclusion: In this paper, we have presented a to view to hack the server which include some hacking as well as non-hacking methods. These algorithms and methods provide efficient way to hack server database. By breaking the network security allow to introduce new and better security framework. The terms “Hacking” not only consider for its illegal activities but also it should be use for strengthen our global network.

Keywords: Hacking, Vulnerabilities, Dummy request, Virus, Server monitoring

Procedia PDF Downloads 249

Authors: Saliha Gachi, Mouloud Aissani, Fouad Boubenider

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Friction Stir Welding (FSW) is a solid-state welding technique that can join material without melting the plates to be welded. In this work, we are interested to demonstrate the potentiality of FSW for joining the heat-treatable aluminum alloy 2024-T3 which is reputed as difficult to be welded by fusion techniques. Thereafter, the FSW joint is compared with another one obtained from a conventional fusion process Tungsten Inert Gas (TIG). FSW welds are made up using an FSW tool mounted on a milling machine. Single pass welding was applied to fabricated TIG joint. The comparison between the two processes has been made on the temperature evolution, mechanical and microstructure behavior. The microstructural examination revealed that FSW weld is composed of four zones: Base metal (BM), Heat affected zone (HAZ), Thermo-mechanical affected zone (THAZ) and the nugget zone (NZ). The NZ exhibits a recrystallized equiaxed refined grains that induce better mechanical properties and good ductility compared to TIG joint where the grains have a larger size in the welded region compared with the BM due to the elevated heat input. The microhardness results show that, in FSW weld, the THAZ contains the lowest microhardness values and increase in the NZ; however, in TIG process, the lowest values are localized on the NZ.

Keywords: friction stir welding, tungsten inert gaz, aluminum, microstructure

Procedia PDF Downloads 273

Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: multi-temporal satellite image, urban growth, non-stationary, stochastic model

Procedia PDF Downloads 424

Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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Authors: Ahmad Helman Hamdani, Diana Putri Hamdiana

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The Sajau coal measures of Berau Basin, northeastern Kalimantan were deposited within a range of facies associations spanning a spectrum of settings from fluvial to marine. The transitional to terrestrial coal measures are dominated by siliciclastics, but they also contain three laterally extensive marine bands (mudstone). These bands act as marker horizons that enable correlation between fully marine and terrestrial facies. Examination of this range of facies and their sedimentology has enabled the development of a high-resolution sequence stratigraphic framework. Set against the established backdrop of third-order Sajau transgression, nine fourth-order sequences are recognized. Results show that, in the composite sequences, peat accumulation predominantly correlates in transitional areas with early transgressive sequence sets (TSS) and highstand sequence set (HSS), while in more landward areas it correlates with the middle TSS to late highstand sequence sets (HSS). Differences in peat accumulation regimes within the sequence stratigraphic framework are attributed to variations in subsidence and background siliciclastic input rates in different depositional settings, with these combining to produce differences in the rate of accommodation change. The preservation of coal resources in the middle to late HSS in this area was most likely related to the rise of the regional base level throughout the Sajau.

Keywords: sequence stratigraphy, coal, Pliocene, Berau basin

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Authors: Desta Brhanu Gebrehiwot

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The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

Procedia PDF Downloads 83

Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Irena Basaric Ikodinovic, Dragoslav Rakic, Mirjana Vukicevic, Sanja Jockovic, Jovana Jankovic Pantic

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Large long-term settlement occurs at the municipal solid waste landfills over an extended period of time which may lead to breakage of the geomembrane, damage of the cover systems, other protective systems or facilities constructed on top of a landfill. Also, municipal solid waste is an extremely heterogeneous material and its properties vary over location and time within a landfill. These material characteristics require the formulation of a new constitutive model to predict the long-term settlement of municipal solid waste. The paper presents a new constitutive model which is formulated to describe the mechanical behavior of municipal solid waste. Model is based on Modified Cam Clay model and the critical state soil mechanics framework incorporating time-dependent components: mechanical creep and biodegradation of municipal solid waste. The formulated constitutive model is optimized and defined with eight input parameters: five Modified Cam Clay parameters, one parameter for mechanical creep and two parameters for biodegradation of municipal solid waste. Thereafter, the constitutive model is implemented in the software suite for finite element analysis (ABAQUS) and numerical analysis of the experimental landfill settlement is performed. The proposed model predicts the total settlement which is in good agreement with field measured settlement at the experimental landfill.

Keywords: constitutive model, finite element analysis, municipal solid waste, settlement

Procedia PDF Downloads 223

Authors: Justin Morton, Mohammad Khavari, Abhinav Priyadarshi, Nicole Grobert, Dmitry G. Eskin, Jiawei Mi, Kriakos Porfyrakis, Paul Prentice

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Ultrasonic cavitation is used for various processes and applications. Recently, ultrasonic assisted liquid phase exfoliation has been implemented to produce two dimensional nanomaterials. Depending on parameters such as input transducer power and the operational frequency used to induce the cavitation, bubble dynamics can be controlled and optimised. Using ultra-high-speed imagining and acoustic pressure measurements, a dual-frequency systemand its effect on bubble dynamics was investigated. A high frequency transducer (1.174 MHz) showed that bubble fragments and satellite bubbles induced from a low frequency transducer (24 kHz) were able to extend their lifecycle. In addition, this combination of ultrasonic frequencies generated higher acoustic emissions (∼24%) than the sum of the individual transducers. The dual-frequency system also produced an increase in cavitation zone size of∼3 times compared to the low frequency sonotrode. Furthermore, the high frequency induced cavitation bubbleswere shown to rapidly oscillate, although remained stable and did not transiently collapse, even in the presence of a low pressure field. Finally, the spatial distribution of satellite and fragment bubbles from the sonotrode were shown to increase, extending the active cavitation zone. These observations elucidated the benefits of using a dual-frequency system for generating nanomaterials with the aid of ultrasound, in deionised water.

Keywords: dual-frequency, cavitation, bubble dynamics, graphene

Procedia PDF Downloads 191

Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

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Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: factors of social innovation, methodological combination, social innovation process, supporting decision-making

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Authors: Satish Kumar Peddapelli

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This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have become popular and considerable interest by researcher are given on them. A fast Space-Vector Pulse Width Modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analysed.

Keywords: five-level inverter, space vector pulse wide modulation, diode clamped inverter, electrical engineering

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Authors: Qin Long, Li Xiaoge

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The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

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Authors: A. Sreedevi, G. Anantaramu

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The present space research organizations are striving towards the development of lighter, smaller, more efficient, low cost, and highly reliable power supply. Switch mode power supplies (SMPS) overcome the demerits of linear power supplies such as low efficiency, difficulties in thermal management, and in boosting the output voltage. Space applications require a constant DC voltage to supply its load. As the load varies, the battery terminal voltage tends to vary accordingly. To avoid this variation in the load terminal voltage, a DC-DC regulator is required. The conventional regulator for space applications is isolated boost topology. The proposed topology uses an interleaved push-pull converter with a current doubler secondary to reduce the EMI issues and increase efficiency. The proposed topology uses a floating technique where the converter derives power from the battery and generates only the voltage that is required to fill the gap between the bus and the battery voltage. The direct voltage sense and current loop provide tight regulation of output and better stability. Converter is designed with 50 kHz switching frequency using UC 1825 PWM controller employing both voltage and peak current mode control. Experimental tests have been carried out on the converter under different input and load conditions to validate the design. The experimental results showed that the efficiency was greater than 91%. Stability analysis is done using venable stability analyzer.

Keywords: push pull converter, current doubler, converter, PWM control

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Muhammad Zafarullah Khan, Sumeera Abbasi

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The Farmers Field School (FFS) aims at benefiting poor farmers by improving their knowledge of existing agricultural technologies and integrated crop management to become independent and confident in their decision. The study on effect of farmer’s field school on vegetables production before and after FFS implementation in district Peshawar in four selected villages on each crop in 2011 was conducted from 80 farmers. The results were compared by using paired t-test. It was observed that 80% of the respondents were satisfied with FFS approach as there was a significant increase in vegetable production. The seed rate of tomato and cucumber decreased from 0.185kg/kanal to 0.1 kg/ kanal and 0.120kg/kanal to 0.01kg/kanal while production of tomato and cucumber were increased from 8158.75kgs/kanal to 1030.25kgs/kanal and 3230kgs/kanal to 5340kgs/kanal, respectively after the activities of FFS. FFS brought a positive effect on vegetable production and technology adoption improving their income, skills and knowledge ultimately lead farmers towards empowerment. The input cost including seed, crop management, FYM, and weedicides for tomato were reduced by Rs.28, Rs. 3170 and Rs.658 and cucumber reduced by Rs.35, Rs.570 and Rs.430. Only fertilizers cost was increased by Rs. 2200 in case of tomato and 465 in case of cucumber. FFS facilitator and coordinator should be more skilled and practical oriented to facilitate poor farmers. In light of the above study, more FFS should be planned so that the more farmers should be benefited.

Keywords: effect, farmer field school, vegetables production, integrated crop management

Procedia PDF Downloads 391

Authors: Ismail Tas, Yusuf Ersoy Yildirim, Yavuz Fatih Fidantemiz, Aysegul Boyacioglu, Demet Uygan, Ozgur Ates, Erdinc Savasli, Oguz Onder, Murat Tugrul

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The biggest input of agricultural production is irrigation, water and energy. Although it varies according to the conditions in drip and sprinkler irrigation systems compared to surface irrigation systems, there is a significant amount of energy expenditure. However, this expense not only increases the user's control over the irrigation water but also provides an increase in water savings and water application efficiency. Thus, while irrigation water is used more effectively, it also contributes to reducing production costs. The Mobile Drip Irrigation System (MDIS) is a system in which new technologies are used, and it is one of the systems that are thought to play an important role in increasing the irrigation water utilization rate of plants and reducing water losses, as well as using irrigation water effectively. MDIS is currently considered the most effective method for irrigation, with the development of both linear and central motion systems. MDIS is potentially more advantageous than sprinkler irrigation systems in terms of reducing wind-induced water losses and reducing evaporation losses on the soil and plant surface. Another feature of MDIS is that the sprinkler heads on the systems (such as the liner and center pivot) can remain operational even when the drip irrigation system is installed. This allows the user to use both irrigation methods. In this study, the effect of MDIS and linear sprinkler irrigation method on sugar beet yield at different irrigation water levels will be revealed.

Keywords: MDIS, linear sprinkler, sugar beet, irrigation efficiency

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: block rotor test, DC test, no load test, virtual environment, voltage source inverter

Procedia PDF Downloads 348

Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

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Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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Authors: Carlos Caro, Ernest Blade, Nestor Rojas

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This study determined the relationship between basic geo-technical parameters and parameters of the hydro logical model Thomas for water balance of rural watersheds, as a methodological calibration application, applicable in distributed models as IBER model, which represents a distributed system simulation models for unsteady flow numerical free surface. There was an exploration in 25 points (on 15 sub) basin of Rio Piedras (Boy.) obtaining soil samples, to which geo-technical characterization was performed by laboratory tests. Thomas model has a physical characterization of the input area by only four parameters (a, b, c, d). Achieve measurable relationship between geo technical parameters and 4 values of hydro logical parameters helps to determine subsurface, underground and surface flow more agile manner. It is intended in this way to reach some solutions regarding limits initial model parameters on the basis of Thomas geo-technical characterization. In hydro geological models of rural watersheds, calibration is an important process in the characterization of the study area. This step can require a significant computational cost and time, especially if the initial values or parameters before calibration are outside of the geo-technical reality. A better approach in these initial values means optimization of these process through a geo-technical materials area, where is obtained an important approach to the study as in the starting range of variation for the calibration parameters.

Keywords: distributed hydrology, hydrological and geotechnical characterization, Iber model

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Authors: Maryam Beiranvand

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Multi-drug resistance in various microorganisms has increased globally in many healthcare facilities. Less effective antimicrobial activity of drug therapies for infection control becomes trouble. Since 1980, no new type of antimicrobial drug has been identified, even though combinations of antibiotic drugs have been discovered almost every decade. Between 1981 and 2006, over 70% of novel pharmaceuticals and chemical agents came from natural sources. Microorganisms have yielded almost 22,000 natural compounds. The identification of antimicrobial components from endophytes bacteria could help overcome the threat posed by multi-drug resistant strains. The project aims to analyze and identify antimicrobial peptides isolated from entophytic bacteria and their activity against multidrug-resistant Gram-negative bacteria in South Korea. Endophytic Paenibacillus polymyxa. 4G3 isolated from the plant, Gynura procumbery exhibited considerable antimicrobial activity against Methicillin-resistant Staphylococcus aureus, and Escherichia coli. The Rapid Annotations using Subsystems Technology showed that the total size of the draft genome was 5,739,603bp, containing 5178 genes with 45.8% G+C content. Genome annotation using antiSMASH version 6.0.0 was performed, which predicted the most common types of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). In this study, diethyl aminoethyl cellulose (DEAEC) resin was used as the first step in purifying for unknown peptides, and then the target protein was identified using hydrophilic and hydrophobic solutions, optimal pH, and step-by-step tests for antimicrobial activity. This crude was subjected to C18 chromatography and elution with 0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% methanol, respectively. Only the fraction eluted with 20% -60% methanol demonstrated good antimicrobial activity against MDR E. coli. The concentration of the active fragment was measured by the Brad-ford test, and Protein A280 - Thermo Fisher Scientific at the end by examining the SDS PAGE Resolving Gel, 10% Acrylamide and purity were confirmed. Our study showed that, based on the combined results of the analysis and purification. P polymyxa. 4G3 has a high potential exists for producing novel functions of polymyxin E and bacitracin against bacterial pathogens.

Keywords: endophytic bacteria, antimicrobial activity, antimicrobial peptide, whole genome sequencing analysis, multi -drug resistance gram negative bacteria

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Authors: Kai Zhang, Xi Jiang

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Effect of fuel variabilities on premixed combustion of bio-syngas mixtures is of great importance in bio-syngas utilisation. The uncertainties of concentrations of fuel constituents such as H2, CO and CH4 may lead to unpredictable combustion performances, combustion instabilities and hot spots which may deteriorate and damage the combustion hardware. Numerical modelling and simulations can assist in understanding the behaviour of bio-syngas combustion with pre-defined species concentrations, while the evaluation of variabilities of concentrations is expensive. To be more specific, questions such as ‘what is the burning velocity of bio-syngas at specific equivalence ratio?’ have been answered either experimentally or numerically, while questions such as ‘what is the likelihood of burning velocity when precise concentrations of bio-syngas compositions are unknown, but the concentration ranges are pre-described?’ have not yet been answered. Uncertainty quantification (UQ) methods can be used to tackle such questions and assess the effects of fuel compositions. An efficient probabilistic UQ method based on Polynomial Chaos Expansion (PCE) techniques is employed in this study. The method relies on representing random variables (combustion performances) with orthogonal polynomials such as Legendre or Gaussian polynomials. The constructed PCE via Galerkin Projection provides easy access to global sensitivities such as main, joint and total Sobol indices. In this study, impacts of fuel compositions on combustion (adiabatic flame temperature and laminar flame speed) of bio-syngas fuel mixtures are presented invoking this PCE technique at several equivalence ratios. High-pressure effects on bio-syngas combustion instability are obtained using detailed chemical mechanism - the San Diego Mechanism. Guidance on reducing combustion instability from upstream biomass gasification process is provided by quantifying the significant contributions of composition variations to variance of physicochemical properties of bio-syngas combustion. It was found that flame speed is very sensitive to hydrogen variability in bio-syngas, and reducing hydrogen uncertainty from upstream biomass gasification processes can greatly reduce bio-syngas combustion instability. Variation of methane concentration, although thought to be important, has limited impacts on laminar flame instabilities especially for lean combustion. Further studies on the UQ of percentage concentration of hydrogen in bio-syngas can be conducted to guide the safer use of bio-syngas.

Keywords: bio-syngas combustion, clean energy utilisation, fuel variability, PCE, targeted uncertainty reduction, uncertainty quantification

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Authors: Bhaskar Basu

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Universities and higher education institutes are finding it increasingly difficult to engage students fruitfully through traditional pedagogic tools. Web 2.0 technologies comprising social networking sites (SNSs) offer a platform for students to collaborate and share information, thereby enhancing their learning experience. Despite the potential and reach of SNSs, its use has been limited in academic settings promoting higher education. The purpose of this paper is to assess the perception of social networking sites among business school students in India and analyze its role in enhancing quality of student experiences in a business school leading to the proposal of an agenda for future research. In this study, more than 300 students of a reputed business school were involved in a survey of their preferences of different social networking sites and their perceptions and attitudes towards these sites. A questionnaire with three major sections was designed, validated and distributed among  a sample of students, the research method being descriptive in nature. Crucial questions were addressed to the students concerning time commitment, reasons for usage, nature of interaction on these sites, and the propensity to share information leading to direct and indirect modes of learning. It was further supplemented with focus group discussion to analyze the findings. The paper notes the resistance in the adoption of new technology by a section of business school faculty, who are staunch supporters of the classical “face-to-face” instruction. In conclusion, social networking sites like Facebook and LinkedIn provide new avenues for students to express themselves and to interact with one another. Universities could take advantage of the new ways  in which students are communicating with one another. Although interactive educational options such as Moodle exist, social networking sites are rarely used for academic purposes. Using this medium opens new ways of academically-oriented interactions where faculty could discover more about students' interests, and students, in turn, might express and develop more intellectual facets of their lives. hitherto unknown intellectual facets.  This study also throws up the enormous potential of mobile phones as a tool for “blended learning” in business schools going forward.

Keywords: business school, India, learning, social media, social networking, university

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Authors: Eleni Karantzola, Athanasios Karasimos, Vasiliki Makri, Ioanna Skouvara

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Historical linguistics unveils the historical depth of languages and traces variation and change by analyzing linguistic variables over time. This field of linguistics usually deals with a closed data set that can only be expanded by the (re)discovery of previously unknown manuscripts or editions. In some cases, it is possible to use (almost) the entire closed corpus of a language for research, as is the case with the Thesaurus Linguae Graecae digital library for Ancient Greek, which contains most of the extant ancient Greek literature. However, concerning ‘dynamic’ periods when the production and circulation of texts in printed as well as manuscript form have not been fully mapped, representative samples and corpora of texts are needed. Such material and tools are utterly lacking for Early Modern Greek (16th-18th c.). In this study, the principles of the creation of EMoGReC, a pilot representative corpus of Early Modern Greek (16th-18th c.) are presented. Its design follows the fundamental principles of historical corpora. The selection of texts aims to create a representative and balanced corpus that gives insight into diachronic, diatopic and diaphasic variation. The pilot sample includes data derived from fully machine-readable vernacular texts, which belong to 4-5 different textual genres and come from different geographical areas. We develop a hierarchical linguistic annotation scheme, further customized to fit the characteristics of our text corpus. Regarding variables and their variants, we use as a point of departure the bundle of twenty-four features (or categories of features) for prose demotic texts of the 16th c. Tags are introduced bearing the variants [+old/archaic] or [+novel/vernacular]. On the other hand, further phenomena that are underway (cf. The Cambridge Grammar of Medieval and Early Modern Greek) are selected for tagging. The annotated texts are enriched with metalinguistic and sociolinguistic metadata to provide a testbed for the development of the first comprehensive set of tools for the Greek language of that period. Based on a relational management system with interconnection of data, annotations, and their metadata, the EMoGReC database aspires to join a state-of-the-art technological ecosystem for the research of observed language variation and change using advanced computational approaches.

Keywords: early modern Greek, variation and change, representative corpus, diachronic variables.

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Authors: Lei Bi, Yunpeng Jiao, Chunjiang Liu, Jianhua Chen, Wei Ge

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Two energy paths are proposed from thermodynamic viewpoints. Energy consumption means total power input to the specific system, and it can be decomposed into energy retention and energy dissipation. Energy retention is the variation of accumulated mechanical energy in the system, and energy dissipation is the energy converted to heat by irreversible processes. Based on the Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) framework, different energy terms are quantified from the specific flow elements of fluid cells and particles as well as their interactions with the wall. Direct energy consumption statistics are carried out for both cold and hot flow in gas-solid fluidization systems. To clarify the statistic method, it is necessary to identify which system is studied: the particle-fluid system or the particle sub-system. For the cold flow, the total energy consumption of the particle sub-system can predict the onset of bubbling and turbulent fluidization, while the trends of local energy consumption can reflect the dynamic evolution of mesoscale structures. For the hot flow, different heat transfer mechanisms are analyzed, and the original solver is modified to reproduce the experimental results. The influence of the heat transfer mechanisms and heat source on energy consumption is also investigated. The proposed statistic method has proven to be energy-conservative and easy to conduct, and it is hopeful to be applied to other multiphase flow systems.

Keywords: energy consumption statistic, gas-solid fluidization, CFD-DEM, regime transition, heat transfer mechanism

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

Procedia PDF Downloads 385

Authors: B. R. Raut

Abstract:

The seismic performance of 20-storey benchmark building with semi-active dampers is investigated under various earthquake ground motions. The Semi-Active Variable Friction Dampers (SAVFD) and Magnetorheological Dampers (MR) are used in this study. A recently proposed predictive control algorithm is employed for SAVFD and a simple mechanical model based on a Bouc–Wen element with clipped optimal control algorithm is employed for MR damper. A parametric study is carried out to ascertain the optimum parameters of the semi-active controllers, which yields the minimum performance indices of controlled benchmark building. The effectiveness of dampers is studied in terms of the reduction in structural responses and performance criteria. To minimize the cost of the dampers, the optimal location of the damper, rather than providing the dampers at all floors, is also investigated. The semi-active dampers installed in benchmark building effectively reduces the earthquake-induced responses. Lesser number of dampers at appropriate locations also provides comparable response of benchmark building, thereby reducing cost of dampers significantly. The effectiveness of two semi-active devices in mitigating seismic responses is cross compared. Among two semi-active devices majority of the performance criteria of MR dampers are lower than SAVFD installed with benchmark building. Thus the performance of the MR dampers is far better than SAVFD in reducing displacement, drift, acceleration and base shear of mid to high-rise building against seismic forces.

Keywords: benchmark building, control strategy, input excitation, MR dampers, peak response, semi-active variable friction dampers

Procedia PDF Downloads 279