Search results for: participatory error correction process

Authors: Hasan Hassoun, Jaafar Hallal, Denis Duhamel, Mohammad Hammoud, Ali Hage Diab

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This paper aims to prove the accuracy of an inexpensive smartphone camera as a non-contact vibration sensor to recover the vibration modes of a vibrating structure such as a cantilever beam. A video of a vibrating beam is filmed using a smartphone camera and then processed by the motion magnification technique. Based on this method, the first two natural frequencies and their associated mode shapes are estimated experimentally and compared to the analytical ones. Results show a relative error of less than 4% between the experimental and analytical approaches for the first two natural frequencies of the beam. Also, for the first two-mode shapes, a Modal Assurance Criterion (MAC) value of above 0.9 between the two approaches is obtained. This slight error between the different techniques ensures the viability of a cheap smartphone camera as a non-contact vibration sensor, particularly for structures vibrating at relatively low natural frequencies.

Keywords: modal analysis, motion magnification, smartphone camera, structural vibration, vibration modes

Procedia PDF Downloads 146

Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of Decode and Forward (DF) multihop Free Space Optical ( FSO) scheme deploying Multiple Input Multiple Output (MIMO) configuration under Gamma-Gamma (GG) statistical distribution, that adopts M-ary Pulse Position Modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of Symbol-Error Rates (SERs) respectively. A closed form formula related to the Probability Density Function (PDF) is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, multiple input multiple output, M-ary pulse position modulation, multihop, decode and forward, symbol error rate, gamma-gamma channel

Procedia PDF Downloads 197

Authors: Yang Fu, Jaime Rodrigo Navarro, Jose F. Monserrat, Faiza Bouchmal, Oscar Carrasco Quilis

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Cellular Vehicle to Everything (C-V2X) is considered a promising solution for future autonomous driving. From Release 16 to Release 17, the Third Generation Partnership Project (3GPP) has introduced the definitions and services for 5G New Radio (NR) V2X. Experience from previous generations has shown that establishing a simulator for C-V2X communications is an essential preliminary step to achieve reliable and stable communication links. This paper proposes a complete framework of a link-level simulator based on the 3GPP specifications for the Physical Sidelink Share Channel (PSSCH) of the 5G NR Physical Layer (PHY). In this framework, several algorithms in the receiver part, i.e., sliding window in channel estimation and Minimum Mean Square Error (MMSE)-based equalization, are developed. Finally, the performance of the developed PSSCH receiver is validated through extensive simulations under different assumptions.

Keywords: C-V2X, channel estimation, link-level simulator, sidelink, 3GPP

Procedia PDF Downloads 125

Authors: Rigers Dodaj

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Nowadays, the environment is a critical goal for civil engineers, human activity, construction projects, economic growth, and whole national development. Regarding the development of Albania's economy, people's living standards are increasing, and the requirements for the living environment are also increasing. Under these circumstances, environmental protection and sustainability this is the critical issue. The rising industrialization, urbanization, and energy demand affect the environment by emission of carbon dioxide gas (CO2), a significant parameter known to impact air pollution directly. Consequently, many governments and international organizations conducted policies and regulations to address environmental degradation in the pursuit of economic development, for instance in Albania, the CO2 emission calculated in metric tons per capita has increased by 23% in the last 20 years. This paper analyzes the importance of civil engineering and economic growth in the sustainability of the environment focusing on CO2 emission. The analyzed data are time series 2001 - 2020 (with annual frequency), based on official publications of the World Bank. The statistical approach with vector error correction model and time series forecasting model are used to perform the parameter’s estimations and long-run equilibrium. The research in this paper adds a new perspective to the evaluation of a sustainable environment in the context of carbon emission reduction. Also, it provides reference and technical support for the government toward green and sustainable environmental policies. In the context of low-carbon development, effectively improving carbon emission efficiency is an inevitable requirement for achieving sustainable economic and environmental protection. Also, the study reveals that civil engineering development projects impact greatly the environment in the long run, especially in areas of flooding, noise pollution, water pollution, erosion, ecological disorder, natural hazards, etc. The potential for reducing industrial carbon emissions in recent years indicates that reduction is becoming more difficult, it needs another economic growth policy and more civil engineering development, by improving the level of industrialization and promoting technological innovation in industrial low-carbonization.

Keywords: CO₂ emission, civil engineering, economic growth, environmental sustainability

Procedia PDF Downloads 83

Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

Procedia PDF Downloads 465

Authors: Odón R. Sánchez-Ccoyllo, Elizabeth Ayma-Choque, Alan Llacza

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Sulphur dioxide (SO₂) and surface-ozone (O₃) concentrations are associated with diseases. The objective of this research is to evaluate the effectiveness of the air-quality-WRF-Chem model with a horizontal resolution of 5 km x 5 km. For this purpose, the measurements of the hourly SO₂ and O₃ concentrations available in three air quality monitoring stations in Lima, Peru were used for the purpose of validating the simulations of the SO₂ and O₃ concentrations obtained with the WRF-Chem model in February 2018. For the quantitative evaluation of the simulations of these gases, statistical techniques were implemented, such as the average of the simulations; the average of the measurements; the Mean Bias (MeB); the Mean Error (MeE); and the Root Mean Square Error (RMSE). The results of these statistical metrics indicated that the simulated SO₂ and O₃ values over-predicted the SO₂ and O₃ measurements. For the SO₂ concentration, the MeB values varied from 0.58 to 26.35 µg/m³; the MeE values varied from 8.75 to 26.5 µg/m³; the RMSE values varied from 13.3 to 31.79 µg/m³; while for O₃ concentrations the statistical values of the MeB varied from 37.52 to 56.29 µg/m³; the MeE values varied from 37.54 to 56.70 µg/m³; the RMSE values varied from 43.05 to 69.56 µg/m³.

Keywords: ground-ozone, lima, sulphur dioxide, WRF-chem

Procedia PDF Downloads 135

Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Ju-Hong Lee, Ding-Chen Chung

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The paper deals with the optimal design of two-channel linear-phase (LP) quadrature mirror filter (QMF) banks using a metaheuristic based optimization technique. Based on the theory of two-channel QMF banks using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the group delay error of the designed QMF bank and the magnitude response error of the designed low-pass analysis filter. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a particle swarm optimization algorithm. The resulting two-channel QMF banks can possess approximately LP response without magnitude distortion. Simulation results are presented for illustration and comparison.

Keywords: quadrature mirror filter bank, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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Authors: A. Ramachandra Reddy, V. Murugan, Prema Kumari

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Residual solvents in Pharmaceutical samples are monitored using gas chromatography with headspace (GC-HS). Based on current regulatory and compendial requirements, measuring the residual solvents are mandatory for all release testing of active pharmaceutical ingredients (API). Generally, isopropyl alcohol is used as the residual solvent in proline and tryptophan; methanol in cysteine monohydrate hydrochloride, glycine, methionine and serine; ethanol in glycine and lysine monohydrate; acetic acid in methionine. In order to have a single method for determining these residual solvents (isopropyl alcohol, ethanol, methanol and acetic acid) in all these 7 amino acids a sensitive and simple method was developed by using gas chromatography headspace technique with flame ionization detection. During development, no reproducibility, retention time variation and bad peak shape of acetic acid peaks were identified due to the reaction of acetic acid with the stationary phase (cyanopropyl dimethyl polysiloxane phase) of column and dissociation of acetic acid with water (if diluent) while applying temperature gradient. Therefore, dimethyl sulfoxide was used as diluent to avoid these issues. But most the methods published for acetic acid quantification by GC-HS uses derivatisation technique to protect acetic acid. As per compendia, risk-based approach was selected as appropriate to determine the degree and extent of the validation process to assure the fitness of the procedure. Therefore, Total error concept was selected to validate the analytical procedure. An accuracy profile of ±40% was selected for lower level (quantitation limit level) and for other levels ±30% with 95% confidence interval (risk profile 5%). The method was developed using DB-Waxetr column manufactured by Agilent contains 530 µm internal diameter, thickness: 2.0 µm, and length: 30 m. A constant flow of 6.0 mL/min. with constant make up mode of Helium gas was selected as a carrier gas. The present method is simple, rapid, and accurate, which is suitable for rapid analysis of isopropyl alcohol, ethanol, methanol and acetic acid in amino acids. The range of the method for isopropyl alcohol is 50ppm to 200ppm, ethanol is 50ppm to 3000ppm, methanol is 50ppm to 400ppm and acetic acid 100ppm to 400ppm, which covers the specification limits provided in European pharmacopeia. The accuracy profile and risk profile generated as part of validation were found to be satisfactory. Therefore, this method can be used for testing of residual solvents in amino acids drug substances.

Keywords: amino acid, head space, gas chromatography, total error

Procedia PDF Downloads 147

Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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Authors: Unchalee Inkampa, Tuanjai Somboonwiwat

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Painting process of automobiles and automobile parts, which is a continuous process based on EDP (Electrode position paint, EDP). Through EDP, all work pieces will be continuously sent to the painting process. Work process can be divided into 2 groups based on the running time: Painting Room 1 and Painting Room 2. This leads to continuous operation. The problem that arises is waiting for workloads onto Painting Room. The grading process EDP to Painting Room is a major problem. Therefore, this paper aim to develop production sequencing method by applying EDP to painting process. It also applied fixed rate launching for painting room and earliest due date (EDD) for EDP process and swap pairwise interchange for waiting time to a minimum of machine. The result found that the developed method could improve painting reduced waiting time, on time delivery, meeting customers wants and improved productivity of painting unit.

Keywords: sequencing, mixed model lines, painting process, electrode position paint

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Authors: Mennani Maha, Attak El Houssain

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Under the massive effect of the Covid-19 health crisis, marked by a loss of competitiveness, a slowdown in growth and an accumulation of the repercussions of socio-economic inequalities, a considerable effort must be combined, in Morocco, to put into perspective macro-political, macro-economic and social opportunities. The development of a new economic and social approach is essential in order to respond to the authenticity of the new development model that will be used by the country. The appropriation of strategies of solidarity and social cohesion constitutes a participatory, competitive and inclusive approach to support the functionalities of the economic, social and political system. Therefore, the search for alternative financial resources has become a necessity to achieve the objectives of sustainable socio-economic growth on the one hand; and to promote, on the other hands, the dynamics, of large scale, social investments. The zakat remains a site of the Islamic economy dedicated to stimulating the bases of a collective adhesion of the population on the economic, as well as on the social level, thanks to a fair and equitable distribution of the zakat funds. However, Morocco is one of the few Muslim countries that has not yet had an institution for collecting and distributing this Islamic duty, which makes it difficult to measure the socio-economic impact of zakat. This theoretical document essentially ensures the development of the crucial utility of institutionalizing zakat in order to reinforce the objectives of social solidarity in Morocco in line with the process of conceptualizing a new development model.

Keywords: zakat, socio-economic development, solidarity, social investment

Procedia PDF Downloads 139

Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

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Process mining research discipline bridges the gap between data mining and business process modeling and analysis, it offers the process-centric and end-to-end methods/techniques for analyzing information of real-world process detailed in operational event-logs. In this paper, we have proposed a notation called trace logo for graphically representing control-flow perspective (order of execution of activities) of process. A trace logo consists of a stack of activity names at each position, sizes of the activity name indicates their frequency in the traces and the total height of the activity depicts the information content of the position. A trace logo created from a set of aligned traces generated using Multiple Trace Alignment technique.

Keywords: consensus trace, process mining, multiple trace alignment, trace logo

Procedia PDF Downloads 345

Authors: Nikhil Deshpande, Rahul Mahajan

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Laser Beam Machining (LBM) is a non-traditional machining process that has inherent problems like dross, striation, and Heat Affected Zone (HAZ) which reduce the quality of machining. In the present day scenario, these problems are controlled only by iteratively adjusting a large number of process parameters. This paper applies Axiomatic Design principles to design LBM process so as to eliminate the problem of dross and striation and minimize the effect of HAZ. Process parameters and their ranges are proposed to set-up the LBM process, execute the cut and finish the workpiece so as to obtain the best quality cut.

Keywords: laser beam machining, dross, striation, heat affected zone, axiomatic design

Procedia PDF Downloads 368

Authors: Sanjay M. Gulhane, Athar Ravish Khan, Umesh W. Kaware

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Orthogonal frequency and code division multiplexing (OFCDM) has received large attention as a modulation scheme to realize high data rate transmission. Multiband (MB) Orthogonal frequency division multiplexing (OFDM) Ultra Wide Band (UWB) system become promising technique for high data rate due to its large number of advantage over Singleband (UWB) system, but it suffer from coherent frequency diversity problem. In this paper we have proposed MB-OFCDM UWB system, in which two-dimensional (2D) spreading (time and frequency domain spreading), has been introduced, combining OFDM with 2D spreading, proposed system can provide frequency diversity. This paper presents the basic structure and main functions of the MB-OFCDM system, and evaluates the bit error rate BER performance of MB-OFDM and MB-OFCDM system under UWB indoor multi-path channel model. It is observe that BER curve of MB-OFCDM UWB improve its performance by 2dB as compare to MB-OFDM UWB system.

Keywords: MB-OFDM UWB system, MB-OFCDM UWB system, UWB IEEE channel model, BER

Procedia PDF Downloads 547

Authors: Harri Jalonen

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Social media has changed the ways we communicate, collaborate and connect with each other. It has also influenced our habits of consuming sports. Social media has allowed direct interaction between sponsoring companies, athletes/players and fans. Drawing on the service dominant logic of value co-creation, the conceptual paper identifies three operant resources which are beneficial for value co-creation: i) social identity and sense of community, ii) congruence and brand personality, and iii) participatory culture and fan activation. The paper contributes to the theoretical discussion on how social can be media used for value co-creation purposes in the sports industry.

Keywords: sports, value co-creation, social media, service

Procedia PDF Downloads 276

Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

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Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: artificial neural network, EDM, metal removal rate, modeling, surface roughness

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: accident analysis, multi-factorial error modeling, risk, systemic methods

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Authors: Nanine Fouche

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The Cape Flats is a low-lying sand-covered expanse of approximately 460 square kilometres, situated to the southeast of the central business district of Cape Town in the Western Cape of South Africa. The aeolian sands masking this area are often loose and compressible in the upper 1m to 1.5m of the surface, and there is a general exceedance of the maximum allowable settlement in these sands. The settlement of shallow foundations on Cape Flats sands is commonly predicted using the results of in-situ tests such as the SPT or DPSH due to the difficulty of retrieving undisturbed samples for laboratory testing. Varying degrees of accuracy and reliability are associated with these methods. More recently, shear wave velocity (Vs) profiles obtained from seismic testing, such as continuous surface wave tests (CSW), are being used for settlement prediction. Such predictions have the advantage of considering non-linear stress-strain behaviour of soil and the degradation of stiffness with increasing strain. CSW tests are rarely executed in the Cape Flats, whereas SPT’s are commonly performed. For this reason, and to facilitate better settlement predictions in Cape Flats sand, equations representing shear wave velocity (Vs) as a function of SPT blow count (N60) and vertical effective stress (v’) were generated by statistical regression of site investigation data. To reveal the most appropriate method of overburden correction, analyses were performed with a separate overburden term (Pa/σ’v) as well as using stress corrected shear wave velocity and SPT blow counts (correcting Vs. and N60 to Vs1and (N1)60respectively). Shear wave velocity profiles and SPT blow count data from three sites masked by Cape Flats sands were utilised to generate 80 Vs-SPT N data pairs for analysis. Investigated terrains included sites in the suburbs of Athlone, Muizenburg, and Atlantis, all underlain by windblown deposits comprising fine and medium sand with varying fines contents. Elastic settlement analysis was also undertaken for the Cape Flats sands, using a non-linear stepwise method based on small-strain stiffness estimates, which was obtained from the best Vs-N60 model and compared to settlement estimates using the general elastic solution with stiffness profiles determined using Stroud’s (1989) and Webb’s (1969) SPT N60-E transformation models. Stroud’s method considers strain level indirectly whereasWebb’smethod does not take account of the variation in elastic modulus with strain. The expression of Vs. in terms of N60 and Pa/σv’ derived from the Atlantis data set revealed the best fit with R2 = 0.83 and a standard error of 83.5m/s. Less accurate Vs-SPT N relations associated with the combined data set is presumably the result of inversion routines used in the analysis of the CSW results showcasing significant variation in relative density and stiffness with depth. The regression analyses revealed that the inclusion of a separate overburden term in the regression of Vs and N60, produces improved fits, as opposed to the stress corrected equations in which the R2 of the regression is notably lower. It is the correction of Vs and N60 to Vs1 and (N1)60 with empirical constants ‘n’ and ‘m’ prior to regression, that introduces bias with respect to overburden pressure. When comparing settlement prediction methods, both Stroud’s method (considering strain level indirectly) and the small strain stiffness method predict higher stiffnesses for medium dense and dense profiles than Webb’s method, which takes no account of strain level in the determination of soil stiffness. Webb’s method appears to be suitable for loose sands only. The Versak software appears to underestimate differences in settlement between square and strip footings of similar width. In conclusion, settlement analysis using small-strain stiffness data from the proposed Vs-N60 model for Cape Flats sands provides a way to take account of the non-linear stress-strain behaviour of the sands when calculating settlement.

Keywords: sands, settlement prediction, continuous surface wave test, small-strain stiffness, shear wave velocity, penetration resistance

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

Procedia PDF Downloads 178

Authors: Maryam Shayan

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Programming frameworks have been utilized as a part of chemical industry process safety operation and configuration to enhance its effectiveness. This paper gives a brief survey and investigation of the best in class and effects of programming frameworks in process security. A study was completed by talking staff accountable for procedure wellbeing practices in the Iranian chemical process industry and diving into writing of innovation for procedure security. This article investigates the useful and operational attributes of programming frameworks for security and endeavors to sort the product as indicated by its level of effect in the administration chain of importance. The study adds to better comprehension of the parts of Information Communication Technology in procedure security, the future patterns and conceivable gaps for innovative work.

Keywords: programming frameworks, chemical industry process, process security, administration chain, information communication technology

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Authors: S. O. Oyamakin, A. U. Chukwu,

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a stabilizing parameter called θ using hyperbolic sine function into the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while using testing the independence of the error term using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE, and AIC confirmed the predictive power of the Hyperbolic Monomolecular growth models over its source model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz

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Authors: Mahmoudi Noureddine

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In this study the use of two variable refined plate theories of laminated composite plates to static response of laminated plates. The plate theory accounts for parabolic distribution of the transverse shear strains, and satisfies the zero traction boundary conditions on the surfaces of the plate without using shear correction factor. The validity of the present theory is demonstrated by comparison with solutions available in the literature and finite element method. The result is presented for the static response of simply supported rectangular plates under uniform sinusoidal mechanical loadings.

Keywords: bending, composite, laminate, plates, fem

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

Procedia PDF Downloads 548

Authors: Ismaila Olabisi Ogundiji, Hakeem Mayowa Olujide, Qasim Usamot

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The main reasons for site-specific management for agricultural inputs are to increase the profitability of crop production, to protect the environment and to improve products’ quality. Information about the variability of different soil attributes within a field is highly essential for the decision-making process. Lack of fast and accurate acquisition of soil characteristics remains one of the biggest limitations of precision agriculture due to being expensive and time-consuming. Adaptive sampling has been proven as an accurate and affordable sampling technique for planning within a field for site-specific management of agricultural inputs. This study employed spatial uncertainty of soil apparent electrical conductivity (ECa) estimates to identify adaptive re-survey areas in the field. The original dataset was grouped into validation and calibration groups where the calibration group was sub-grouped into three sets of different measurements pass intervals. A conditional simulation was performed on the field ECa to evaluate the ECa spatial uncertainty estimates by the use of the geostatistical technique. The grouping of high-uncertainty areas for each set was done using image segmentation in MATLAB, then, high and low area value-separate was identified. Finally, an adaptive re-survey was carried out on those areas of high-uncertainty. Adding adaptive re-surveying significantly minimized the time required for resampling whole field and resulted in ECa with minimal error. For the most spacious transect, the root mean square error (RMSE) yielded from an initial crude sampling survey was minimized after an adaptive re-survey, which was close to that value of the ECa yielded with an all-field re-survey. The estimated sampling time for the adaptive re-survey was found to be 45% lesser than that of all-field re-survey. The results indicate that designing adaptive sampling through spatial uncertainty models significantly mitigates sampling cost, and there was still conformity in the accuracy of the observations.

Keywords: soil electrical conductivity, adaptive sampling, conditional simulation, spatial uncertainty, site-specific management

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Authors: Hyun-Woo Cho

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The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

Abstract:

Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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Authors: Tatyana Aleksandrovna Barbasova, Lev Sergeevich Kazarinov, Olga Valerevna Kolesnikova, Aleksandra Aleksandrovna Filimonova

Abstract:

We regard forecasting of energy consumption by private production areas of a large industrial facility as well as by the facility itself. As for production areas the forecast is made based on empirical dependencies of the specific energy consumption and the production output. As for the facility itself implementation of the task to minimize the energy consumption forecasting error is based on adjustment of the facility’s actual energy consumption values evaluated with the metering device and the total design energy consumption of separate production areas of the facility. The suggested procedure of optimal energy consumption was tested based on the actual data of core product output and energy consumption by a group of workshops and power plants of the large iron and steel facility. Test results show that implementation of this procedure gives the mean accuracy of energy consumption forecasting for winter 2014 of 0.11% for the group of workshops and 0.137% for the power plants.

Keywords: energy consumption, energy consumption forecasting error, energy efficiency, forecasting accuracy, forecasting

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Authors: Hassan El Ghazi, Mohammed El Jourmi, Tayeb Sadiki, Esmail Ahouzi

Abstract:

The purpose of this paper is to model and analyze a geostationary satellite communication system based on VSAT network and Multicarrier CDMA system scheme which presents a combination of multicarrier modulation scheme and CDMA concepts. In this study the channel coding strategies (Turbo codes and LDPC codes) are adopted to achieve good performance due to iterative decoding. The envisaged system is examined for a transmission over Multipath channel with use of Ku band in the uplink case. The simulation results are obtained for each different case. The performance of the system is given in terms of Bit Error Rate (BER) and energy per bit to noise power spectral density ratio (Eb/N0). The performance results of designed system shown that the communication system coded with LDPC codes can achieve better error rate performance compared to VSAT MC-CDMA system coded with Turbo codes.

Keywords: satellite communication, VSAT Network, MC-CDMA, LDPC codes, turbo codes, uplink

Procedia PDF Downloads 503

Authors: Tuiana A. Aiusheeva, Sergey S. Tamozhnikov, Alexander E. Saprygin, Arina A. Antonenko, Valentina V. Stepanova, Natalia N. Tolstykh, Alexander N. Savostyanov

Abstract:

Situation of choice is an important condition for the formation of essential character qualities of a child, such as being initiative, responsible, hard-working. We have studied the behavioral and EEG reactions in Russian schoolchildren during recognition of syntactic errors in emotionally colored sentences that describe the choice situation. Twenty healthy children (mean age 9,0±0,3 years, 12 boys, 8 girls) were examined. Forty sentences were selected for the experiment; the half of them contained a syntactic error. The experiment additionally had the hidden condition: 50% of the sentences described the children's own choice and were emotionally colored (positive or negative). The other 50% of the sentences described the forced-choice situation, also with positive or negative coloring. EEG were recorded during execution of error-recognition task. Reaction time and quality of syntactic error detection were chosen as behavioral measures. Event-related spectral perturbation (ERSP) was applied to characterize the oscillatory brain activity of children. There were two time-frequency intervals in EEG reactions: (1) 500-800 ms in the 3-7 Hz frequency range (theta synchronization) and (2) 500-1000 ms in the 8-12 Hz range (alpha desynchronization). We found out that behavioral and brain reactions in child brain during recognition of positive and negative sentences describing forced-choice situation did not have significant differences. Theta synchronization and alpha desynchronization were stronger during recognition of sentences with children's own choice, especially with negative coloring. Also, the quality and execution time of the task were higher for this types of sentences. The results of our study will be useful for improvement of teaching methods and diagnostics of children affective disorders.

Keywords: choice situation, electroencephalogram (EEG), emotionally colored sentences, schoolchildren

Procedia PDF Downloads 266