Search results for: sales process ARIMA models

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

Procedia PDF Downloads 420

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

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Authors: Ceyhun Aksoylu, Rifat Sezer

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In this study, a strengthening method applicable without any evacuation process was investigated. In this analytical study, the pushover analysis results carry out by using the software of SAP2000. For this purpose, 1/3 scaled, 1-bay and 2-story R/C seven frames having usual deficiencies faults produced, one of which were not strengthened, but having brick-infill wall and the other 3 frames with infill walls strengthened with various shaped of high strength-precast diagonal concrete panels. The prepared analytical models investigated under reversed-cyclic loading that resembles the seismic effect. As a result of the analytical study, the properties of the reinforced concrete frames, such as strength, rigidity, energy dissipation capacity, etc. were determined and the strengthened models were compared with the unstrengthened one having the same properties. As a result of this study, the contributions of precast diagonal concrete applied on the infill walls of the existing frame systems against seismic effects were introduced with its advantages and disadvantages.

Keywords: RC frame, seismic effect, infill wall, strengthening, precast diagonal concrete panel, pushover analysis

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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

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Authors: Alemaw Kefale, Aramde Fetene, Hayal Desta

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This study analyzed the users' and experts' views on the green space quality and planning models in Debre Berhan (DB) and Debre Markos (DM) cities in Ethiopia. A questionnaire survey was conducted on 350 park users (148 from DB and 202 from DM) to rate the accessibility, size, shape, vegetation cover, social and cultural context, conservation and heritage, community participation, attractiveness, comfort, safety, inclusiveness, and maintenance of green spaces using a Likert scale. A key informant interview was held with 13 experts in DB and 12 in DM. Descriptive statistics and tests of independence of variables using the chi-square test were done. A statistically significant association existed between the perception of green space quality attributes and users' occupation (χ² (160, N = 350) = 224.463, p < 0.001), age (χ² (128, N = 350) = 212.812, p < 0.001), gender (χ² (32, N = 350) = 68.443, p < 0.001), and education level (χ² (192, N = 350) = 293.396, p < 0.001). 61.7 % of park users were unsatisfied with the quality of urban green spaces. The users perceived dense vegetation cover as "good," with a mean value of 3.41, while the remaining were perceived as "medium with a mean value of 2.62 – 3.32". Only quantitative space standards are practiced as a green space planning model, while other models are unfamiliar and never used in either city. Therefore, experts need to be aware of and practice urban green models during urban planning to ensure that new developments include green spaces to accommodate the community's and the environment's needs.

Keywords: urban green space, quality, users and experts, green space planning models, Ethiopia

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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: Forrest Kaatz, Adhemar Bultheel

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Au-Cu and Pt-M (M = Fe, Co, and Ni) nanocluster alloys are currently being investigated worldwide by many researchers for their interesting catalytic and nanophase properties. The low-temperature behavior of the phase diagrams is not well understood for alloys with nanometer sizes and shapes. These systems have similar bulk phase diagrams with the L12 (Au3Cu, Pt3M, AuCu3, and PtM3) structurally ordered intermetallics and the L10 structure for the AuCu and PtM intermetallics. We consider three models for low temperature ordering in the phase diagrams of Au–Cu and Pt–M nanocluster alloys. These models are valid for sizes ~ 5 nm and approach bulk values for sizes ~ 20 nm. We study the phase transition in nanoclusters with cubic, octahedral, and cuboctahedral shapes, covering the compositions of interest. These models are based on studying the melting temperatures in nanoclusters using the regular solution, mixing model for alloys. Experimentally, it is extremely challenging to determine thermodynamic data on nano–sized alloys. Reasonable agreement is found between these models and recent experimental data on nanometer clusters in the Au–Cu and Pt–M nanophase systems. From our data, experiments on nanocubes about 5 nm in size, of stoichiometric AuCu and PtM composition, could help differentiate between the models. Some available evidence indicates that ordered intermetallic nanoclusters have better catalytic properties than disordered ones. We conclude with a discussion of physical mechanisms whereby ordering could improve the catalytic properties of nanocluster alloys.

Keywords: catalytic reactions, gold nanoalloys, phase transitions, platinum nanoalloys

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Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

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The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19^th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: collision, impact models, finite element method, Hertz Theory

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Authors: Saeed Moarrefi, Shou-Han Zhou, Liyuan Fan

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Coupling with solid oxide fuel cells, methane dry reforming is a promising pathway for energy production while mitigating carbon emissions. However, the influence of carbon dioxide and electrochemical reactions on the internal dry reforming reaction within the fuel cells remains debatable, requiring accurate kinetic models to describe the internal reforming behaviors. We employed the Power-Law and Langmuir Hinshelwood–Hougen Watson models in an electrolyte-supported solid oxide fuel cell with a NiO-GDC-YSZ anode. The current density used in this study ranges from 0 to 1000 A/m2 at 973 K to 1173 K to estimate various kinetic parameters. The influence of the electrochemical reactions on the adsorption terms, the equilibrium of the reactions, the activation energy, the pre-exponential factor of the rate constant, and the adsorption equilibrium constant were studied. This study provides essential parameters for future simulations and highlights the need for a more detailed examination of reforming kinetic models.

Keywords: dry reforming kinetics, Langmuir Hinshelwood–Hougen Watson, power-law, SOFC

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

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In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

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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

Procedia PDF Downloads 372

Authors: Subodh Chandra Shakya, Rajendra Sapkota, Aakash Tamang, Shushant Pudasaini, Sujan Adhikari, Sajjan Adhikari

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Lots of efforts have been made in order to measure the semantic similarity between the text corpora in the documents. Techniques have been evolved to measure the similarity of two documents. One such state-of-art technique in the field of Natural Language Processing (NLP) is word to vector models, which converts the words into their word-embedding and measures the similarity between the vectors. We found this to be quite useful for the task of resume ranking. So, this research paper is the implementation of the word2vec model along with other Natural Language Processing techniques in order to rank the resumes for the particular job description so as to automate the process of hiring. The research paper proposes the system and the findings that were made during the process of building the system.

Keywords: chunking, document similarity, information extraction, natural language processing, word2vec, word embedding

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Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

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This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

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Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

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Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

Procedia PDF Downloads 232

Authors: Yu Chen

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This paper investigates the influence of flaw on failure process of rock-like material under uniaxial compression. In laboratory, the uniaxial compression tests of intact specimens and a series of specimens within single flaw were conducted. The inclination angle of flaws includes 0°, 15°, 30°, 45°, 60°, 75° and 90°. Based on the laboratory tests, the corresponding models of numerical simulation were built and loaded in PFC2D. After analysing the crack initiation and failure modes, deformation field, and energy mechanism for both laboratory tests and numerical simulation, it can be concluded that the influence of flaws on the failure process is determined by its inclination. The characteristic stresses increase as flaw angle rising basically. The tensile cracks develop from gentle flaws (α ≤ 30°) and the shear cracks develop from other flaws. The propagation of cracks changes during failure process and the failure mode of a specimen corresponds to the orientation of the flaw. A flaw has significant influence on the transverse deformation field at the middle of the specimen, except the 75° and 90° flaw sample. The input energy, strain energy and dissipation energy of specimens show approximate increase trends with flaw angle rising and it presents large difference on the energy distribution.

Keywords: failure pattern, particle deformation field, energy mechanism, PFC

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Authors: M. A. Brown, K. Hugill, D. Meredith

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Since the establishment of midwifery, as a professional identity in its own right, in the early years of the 20th century, midwifery-led models of childbirth have prevailed in many parts of the world. However, in many locations midwives’ scope of practice remains underdeveloped or absent. In Qatar, all births take place in hospital and are under the professional jurisdiction of obstetricians, predominately supported by internationally trained nurse-midwives and obstetric nurses. The strategic vision for health services in Qatar endorsed a desire to provide women with the ‘Best Care Always’ and the introduction of midwifery was seen as a way to achieve this. In 2015 the process of recruiting postgraduate educated Clinical Midwife Specialists from international sources began. The midwives were brought together to initiate an in hospital and community service transformation plan. This plan set out a series of wide-ranging actions to transform maternity and neonatal services to make care safer and give women more health choices. Change in any organization is a complex and dynamic process. This is made even more complex when multifaceted professional and cross cultural factors are involved. This presentation reports upon the motivations and challenges that exist and the progress around introducing a multicultural midwifery model of childbirth care in the state of Qatar. The paper examines and reflects upon the drivers and unique features of childbirth in the country. Despite accomplishments, progress still needs to be made in order to fully implement sustainable changes to further improve care and ensure women and neonates get the ‘Best Care Always’. The progress within the transformation plan highlights how midwifery may coexist with competing models of maternity care to create an innovative, eclectic and culturally sensitive paradigm that can best serve women and neonatal health needs.

Keywords: culture, managing change, midwifery, neonatal, service transformation plan

Procedia PDF Downloads 148

Authors: Tonoyan Lusine

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The Communicative Grammar (CG) of a language deals with semantics and pragmatics in the first place as communication is a process of generating speech. As it is well known people can communicate with the help of limited word expressions and grammatical means. As to non-verbal communication, both vocabulary and grammar are not essential at all. However, the development of the communicative competence lies in verbal, non-verbal, grammatical, socio-cultural and intercultural awareness. There are several important issues and environment management strategies related to effective communication that one might need to consider for a positive learning experience. International students bring a broad range of cultural perspectives to the learning environment, and this diversity has the capacity to improve interaction and to enrich the teaching/learning process. Intercultural setting implies creative and thought-provoking work with different cultural worldviews and international perspectives. It is worth mentioning that the use of Communicative Grammar models creates a profound background for the effective intercultural communication.

Keywords: CG, cross-cultural communication, intercultural awareness, non-verbal behavior

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Authors: Bi-Huei Tsai

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Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightly-distressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models, are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the two-stage model incorporating financial ratios, corporate governance and market factors has the lowest misclassification error rate. The two-stage model is more accurate than the one-stage model as its distressed cut-off indicators are adjusted according to the macroeconomic-based credit cycle index.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Alexandros Pournaras, Anastasia Papadopoulou, Serafim Kontos, Anastasios Karakostas

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The air quality of modern cities is an important concern, as poor air quality contributes to human health and environmental issues. Reliable air quality forecasting has, thus, gained scientific and governmental attention as an essential tool that enables authorities to take proactive measures for public safety. In this study, the potential of Machine Learning (ML) models to forecast PM2.5 at local scale is investigated in the city of Thessaloniki, the second largest city in Greece, which has been struggling with the persistent issue of air pollution. ML models, with proven ability to address timeseries forecasting, are employed to predict the PM2.5 concentrations and the respective Air Quality Index 5-days ahead by learning from daily historical air quality and meteorological data from 2014 to 2016 and gathered from two stations with different land use characteristics in the urban fabric of Thessaloniki. The performance of the ML models on PM2.5 concentrations is evaluated with common statistical methods, such as R squared (r²) and Root Mean Squared Error (RMSE), utilizing a portion of the stations’ measurements as test set. A multi-categorical evaluation is utilized for the assessment of their performance on respective AQIs. Several conclusions were made from the experiments conducted. Experimenting on MLs’ configuration revealed a moderate effect of various parameters and training schemas on the model’s predictions. Their performance of all these models were found to produce satisfactory results on PM2.5 concentrations. In addition, their application on untrained stations showed that these models can perform well, indicating a generalized behavior. Moreover, their performance on AQI was even better, showing that the MLs can be used as predictors for AQI, which is the direct information provided to the general public.

Keywords: Air Quality, AQ Forecasting, AQI, Machine Learning, PM2.5

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Authors: Fatma Ünal, Hasancan Okutan

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Increasing worldwide population and technological requirements lead to an increase in energy demand every year. The demand has been mainly supplied from fossil fuels such as coal and petroleum due to insufficient natural gas resources. In recent years, the amount of coal reserves has reached almost 21 billion tons in Türkiye. These are mostly lignite (%92,7), that contains high levels of moisture and sulfur components. Underground coal gasification technology is one of the most suitable methods in comparison with direct combustion techniques for the evaluation of such coal types. In this study, the applicability of the underground coal gasification process is investigated in the Eskişehir-Alpu lignite reserve as a pilot region, both technologically and economically. It is assumed that the electricity is produced from the obtained synthesis gas in an integrated gasification combined cycle (IGCC). Firstly, an equilibrium model has been developed by using the thermodynamic properties of the gasification reactions. The effect of the type of oxidizing gas, the sulfur content of coal, the rate of water vapor/air, and the pressure of the system have been investigated to find optimum process conditions. Secondly, the parallel and linear controlled recreation and injection point (CRIP) models were implemented as drilling methods, and costs were calculated under the different oxidizing agents (air and high-purity O2). In Parallel CRIP (P-CRIP), drilling cost is found to be lower than the linear CRIP (L-CRIP) since two coal beds simultaneously are gasified. It is seen that CO2 Capture and Storage (CCS) technology was the most effective unit on the total cost in both models. The cost of the synthesis gas produced varies between 0,02 $/Mcal and 0,09 $/Mcal. This is the promising result when considering the selling price of Türkiye natural gas for Q1-2023 (0.103 $ /Mcal).

Keywords: energy, lignite reserve, techno-economic analysis, underground coal gasification.

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Authors: M. Ouassaf, S. Belaid

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A series of quinoline derivatives with antimalarial activity were subjected to two-dimensional quantitative structure-activity relationship (2D-QSAR) studies. Three models were implemented using multiple regression linear MLR, a regression partial least squares (PLS), nonlinear regression (MNLR), to see which descriptors are closely related to the activity biologic. We relied on a principal component analysis (PCA). Based on our results, a comparison of the quality of, MLR, PLS, and MNLR models shows that the MNLR (R = 0.914 and R² = 0.835, RCV= 0.853) models have substantially better predictive capability because the MNLR approach gives better results than MLR (R = 0.835 and R² = 0,752, RCV=0.601)), PLS (R = 0.742 and R² = 0.552, RCV=0.550) The model of MNLR gave statistically significant results and showed good stability to data variation in leave-one-out cross-validation. The obtained results suggested that our proposed model MNLR may be useful to predict the biological activity of derivatives of quinoline.

Keywords: antimalarial, quinoline, QSAR, PCA, MLR , MNLR, MLR

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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: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Manar Al-Ateeq

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The building construction industry plays a major role in the economy of the word and the state of Kuwait. This paper evaluates existing new civil site engineers, describes a new system for improvement and insures the importance of prequalifying and developing for new engineers. In order to have a strong base in engineering, educational institutes and workplaces should be responsible to continuously train engineers and update them with new methods and techniques in engineering. As to achieve that, school of engineering should constantly update computational resources to be used in the professions. A survey was prepared for graduated Engineers based on stated objectives to understand the status of graduate engineers in both the public and private sector. Interviews were made with different sectors in Kuwait, and several visits were made to different training centers within different workplaces in Kuwait to evaluate training process and try to improve it. Virtual Reality (VR) technology could be applied as a complement to three-dimensional (3D) modeling, leading to better communication whether in job training, in education or in professional practice. Techniques of 3D modeling and VR can be applied to develop the models related to the construction process. The 3D models can support rehabilitation design as it can be considered as a great tool for monitoring failure and defaults in structures; also it can support decisions based on the visual analyses of alternative solutions. Therefore, teaching computer-aided design (CAD) and VR techniques in school will help engineering students in order to prepare them to site work and also will assist them to consider these technologies as important supports in their later professional practice. This teaching technique will show how the construction works developed, allow the visual simulation of progression of each type of work and help them to know more about the necessary equipment needed for tasks and how it works on site.

Keywords: three dimensional modeling (3DM), civil engineers (CE), professional practice (PP), virtual reality (VR)

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Authors: Sajjad Negahban, Ruihe Wang, Baojiang Sun

Abstract:

Gas-lift dual gradient drilling is a solution for deepwater drilling challenges. As well, Continuous development of drilling technology leads to increase employment of mineral oil based drilling fluids and synthetic-based drilling fluids, which have adequate characteristics such as: high rate of penetration, lubricity, shale inhibition and low toxicity. The paper discusses utilization of nitrified mineral oil base drilling for deepwater drilling and for more accurate prediction of pressure in DGD at marine riser, solubility and bubble pressure were considered in steady state hydraulic model. The Standing bubble pressure and solubility correlations, and two models which were acquired from experimental determination were applied in hydraulic model. The effect of the black oil correlations, and new solubility and bubble pressure models was evaluated on the PVT parameters such as oil formation volume factor, density, viscosity, volumetric flow rate. Eventually, the consequent simulated pressure profile due to these models was presented.

Keywords: solubility, bubble pressure, gas-lift dual gradient drilling, steady state hydraulic model

Procedia PDF Downloads 275

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: artificial intelligence and office, NLP, deep learning, text classification

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini

Abstract:

The objective of this work is to evaluate the results of solar radiation projections between 2006 and 2013 for the state of Rio Grande do Sul, Brazil. The projections are provided by the General Circulation Models (MCGs) belonging to the Coupled Model Intercomparison Phase 5 (CMIP5). In all, the results of the simulation of six models are evaluated, compared to monthly data, measured by a network of thirteen meteorological stations of the National Meteorological Institute (INMET). The performance of the models is evaluated by the Nash coefficient and the Bias. The results are presented in the form of tables, graphs and spatialization maps. The ACCESS1-0 RCP 4.5 model presented the best results for the solar radiation simulations, for the most optimistic scenario, in much of the state. The efficiency coefficients (CEF) were between 0.95 and 0.98. In the most pessimistic scenario, HADGen2-AO RCP 8.5 had the best accuracy among the analyzed models, presenting coefficients of efficiency between 0.94 and 0.98. From this validation, solar radiation projection maps were elaborated, indicating a seasonal increase of this climatic variable in some regions of the Brazilian territory, mainly in the spring.

Keywords: climate change, projections, solar radiation, validation

Procedia PDF Downloads 205