Search results for: short-term electricity price forecast

Authors: Jaewook Ha, Jin-beak Kim, Seongmin Kim

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In order to solve global warming and climate change issues, increased efforts have been devoted towards clean and sustainable energy sources as well as new energy generating devices. Nanogenerator is a device that converts mechanical/thermal energy as produced by small-scale physical change into electricity. Here we propose that nature-leaf surface could be used for preparation of a triboelectric nanogenerator. The nature-leaf surface consists of polydimethylsiloxane microscale pillars and polytetrafluoroethylene nanoparticles. Interaction between the nature-leaf surface and water was studied and the electrical outputs from the motion of single water drop were measured. A 40-μL water drop can generate a peak voltage of 1 V and a peak current of 0.7 μA. This nanogenerator might be used to drive electric devices in the outdoor environments in a sustainable manner.

Keywords: hierarchical surface, lotus-leaf, electrical generator, waterdrop

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Authors: Hemendra Singh Rathod

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Frequency is, among other factors, one of the governing parameters for maintaining electrical grid stability. The quality of an electrical transmission and supply system is mainly described by the stability of the grid frequency. Over the past few decades, energy generation by intermittent sustainable sources like wind and solar has seen a significant increase globally. Consequently, controlling the associated deviations in grid frequency within safe limits has been gaining momentum so that the balance between demand and supply can be maintained. Lithium-ion battery energy storage system (Li-Ion BESS) has been a promising technology to tackle the challenges associated with grid instability. BESS is, therefore, an effective response to the ongoing debate whether it is feasible to have an electrical grid constantly functioning on a hundred percent renewable power in the near future. In recent years, large-scale manufacturing and capital investment into battery production processes have made the Li-ion battery systems cost-effective and increasingly efficient. The Li-ion systems require very low maintenance and are also independent of geographical constraints while being easily scalable. The paper highlights the use of stationary and moving BESS for balancing electrical energy, thereby maintaining grid frequency at a rapid rate. Moving BESS technology, as implemented in the selected railway network in Germany, is here considered as an exemplary concept for demonstrating the same functionality in the electrical grid system. Further, using certain applications of Li-ion batteries, such as self-consumption of wind and solar parks or their ancillary services, wind and solar energy storage during low demand, black start, island operation, residential home storage, etc. offers a solution to effectively integrate the renewables and support Europe’s future smart grid. EMT software tool DIgSILENT PowerFactory has been utilised to model an electrical transmission system with 100% renewable energy penetration. The stability of such a transmission system has been evaluated together with BESS within a defined frequency band. The transmission system operators (TSO) have the superordinate responsibility for system stability and must also coordinate with the other European transmission system operators. Frequency control is implemented by TSO by maintaining a balance between electricity generation and consumption. Li-ion battery systems are here seen as flexible, controllable loads and flexible, controllable generation for balancing energy pools. Thus using Li-ion battery storage solution, frequency-dependent load shedding, i.e., automatic gradual disconnection of loads from the grid, and frequency-dependent electricity generation, i.e., automatic gradual connection of BESS to the grid, is used as a perfect security measure to maintain grid stability in any case scenario. The paper emphasizes the use of stationary and moving Li-ion battery storage for meeting the demands of maintaining grid frequency and stability for near future operations.

Keywords: frequency control, grid stability, li-ion battery storage, smart grid

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Authors: Anocha Rojanapanich

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This research aimed to identify important factors that effect customer satisfaction in boutique hotels and the important factors effecting customer loyalty in returning to boutique hotels. Furthermore, this study also aimed to study demographics, which effect variable factors. Four hundred questionnaires were completed by customers of the boutique hotels. The descriptive statistics used in this paper were percentages, means, and standard deviation (S.D.), while hypothesis testing was done using T-test, Anova, Correlation and Regression to analyze the relationship among those factors. In terms of the purpose in staying, it was found that the largest respondent was for ‘leisure purposes’. While the frequency indicated that most of the customers who stayed ‘once’in the last two years in the hotels had less concern in the hotel’s image than other groups. For customer’s perceived value and income levels had an influence on customer perceived values in both functional value price and emotional value.

Keywords: boutique hotels, customer attitude, customer satisfaction, customer loyalty

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Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

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Authors: Hande Begum Bumin Doyduk, Elif Okan Yolbulan

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Innovation is very important for success and competitiveness of countries, as well as business sectors and individuals' firms. In order to have successful and sustainable innovations, the other side of the game, consumers, should be aware of the innovations and appreciate them. In this study, the consumer innovativeness is focused and the relationship between motivated consumer innovativeness and consumer shopping styles is analyzed. Motivated consumer innovativeness scale by (Vandecasteele & Geuens, 2010) and consumer shopping styles scale by (Sproles & Kendall, 1986) is used. Data is analyzed by SPSS 20 program through realibility, factor, and correlation analysis. According to the findings of the study, there are strong positive relationships between hedonic innovativeness and recreational shopping style; social innovativeness and brand consciousness; cognitive innovativeness and price consciousness and functional innovativeness and perfectionistic high-quality conscious shopping styles.

Keywords: consumer innovativeness, consumer decision making, shopping styles, innovativeness

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Authors: Nnadi Ezekiel Oluwaseun Ejiofor

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This research investigates the effects of poor cost estimation, material cost variations, and payment punctuality on the financial health and execution of construction projects in Nigeria. To achieve the objectives of the study, a quantitative research approach was employed, and data was gathered through an online survey of 74 construction industry professionals consisting of quantity surveyors, contractors, and other professionals. The study surveyed input on cost estimation errors, price fluctuations, and payment delays, among other factors. The responses of the respondents were analyzed using a five-point Likert scale and the Relative Importance Index (RII). The findings demonstrated that the errors in cost estimating in the Bill of Quantity (BOQ) have a high degree of negative impact on the reputation and image of the participants in the projects. The greatest effect was experienced on the likelihood of obtaining future endeavors for contractors (mean value = 3.42), followed by the likelihood of obtaining new commissions by quantity surveyors (mean value = 3.40). The level of inaccuracy in costing that undershoots exposes them to risks was most serious in terms of easement of construction and effects of shortage of funds to pursue bankruptcy (hence fears of mean value = 3.78). There was also considerable financial damage as a result of cost underestimation, whereby contractors suffered the worst loss in profit (mean value = 3.88). Every expense comes with its own peculiar risk and uncertainty. Pressure on the cost of materials and every other expense attributed to the building and completion of a structure adds risks to the performance figures of a project. The greatest weight (mean importance score = 4.92) was attributed to issues like market inflation in building materials, while the second greatest weight (mean importance score = 4.76) was due to increased transportation charges. On the other hand, delays in payments arising from issues of the clients like poor availability of funds (RII=0.71) and contracting issues such as disagreements on the valuation of works done (RII=0.72) or other reasons were also found to lead to project delays and additional costs. The results affirm the importance of proper cost estimation on the health of organization finances and project risks and finishes within set time limits. As for the suggestions, it is proposed to progress on the methods of costing, engender better communications with the stakeholders, and manage the delays by way of contracting and financial control. This study enhances the existing literature on construction project management by suggesting ways to deal with adverse cost inaccuracies and availability of materials due to delays in payments which, if addressed, would greatly improve the economic performance of the construction business.

Keywords: cost estimation, construction project management, material price fluctuations, payment delays, financial impact

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Authors: A. A. Hussen, I. N. Jleta

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Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to the low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effect of these random errors, they must be accurately modeled. Where the key is the successful implementation that depends on how well the noise statistics of the inertial sensors is selected. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Keywords: Allan variance, accelerometer, gyroscope, stochastic errors

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Authors: Farzaneh Khorram

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This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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Authors: Majdi Abid

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During the last few decades, great efforts have been made for the development of innovative materials using vegetal biomass. This strategy is understandable for different reasons including the predictable dwindling of the petrochemical feedstock and their price increase as well as the counterbalancing of the environmental problems. As novel bio-based monomers used in polyesters synthesis, two families, namely 1,4:3,6-dianhydrohexitols and furanics were prepared for saccharidic renewable resources. The present work deals with a detail investigation on the synthesis of poly(ethylene-co-isosorbide terephthalate-co-furoate) (PEITF) by melt polycondensation of dimethylterephtalate (DMT), 5,5’-isopropylidene-bis (ethyl 2-furoate) (DEF) ethan-1,2-diol (ED) and isosorbide (IS). Polycondensationwas achieved in two steps: (i) the formation of a hydroxyethylterminated oligomer by reaction of starting diester mixture with excess ED and, (ii) a polycondensation step with elimination of ED was used to obtain high molar mass copolyesters. Copolymers of various compositions were synthesized and characterized by 1H NMR, SEC, DSC and TGA. The resulting materials are amorphous polymers (Tg = 104–127 °C) with good thermal stability.

Keywords: bio-based monomers, furan, isosrbide, polycondensation

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Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Selman Selim Akyüz, Mete Kazaz

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Since The First Gulf War, USA, “Leader of The Free World” has been in trouble with terror. The USA created a complexity in The Middle East and paid the price with terrorist attacks in homeland. USA has made serious mistakes in terms of antiterrorism and fight against its supporters. Democrats have repaired damages caused by the Republican Party's management. Old methods about antiterrorism have been slowly abandoned. Hollywood, too, has played an important part in this war. Sometimes, Hollywood became an unquestioned patriot, sometimes it cried for the death of American Soldiers far away. In this study, messages in The Homeland, broadcast in the USA and a lot of countries around the world, are analyzed in terms of Washington’s foreign policy and position of the CIA in the fight against antiterrorism. The series reflect an orientalist viewpoint and has been criticized for offensive policy against the government. Homeland wanted to offer a perspective for the USA to be the “Leader of The Free World” again but with a liberal-democrat approach, dialogue and rational intelligence methods.

Keywords: antiterrorism, CIA, homeland, USA

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Authors: A.N. Zhilkaidarov, G.K. Iskakova, V.Y. Chernyh

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High-qualified and not-expensive products of daily usage have a big demand on food products’ market. Moreover, it is about independent and irreplaceable product as pasta. Pasta is a product, which represents itself the conserved dough from wheat flour made through special milling process. A wide assortment of the product and its pleasant taste properties allow to use pasta products in very different combinations with other food products. Pasta industry of Kazakhstan has large perspectives of development. There are many premises for it, which includes first an importance of pasta as a social product. Due to for its nutritional and energetically value pasta is the part of must have food. Besides that, the pasta production in Kazakhstan has traditional bases, and nowadays the market of this product develops rapidly as in quantity as well as in quality aspects. Moreover, one of the advantages of this branch is an economical aspect – pasta is the product of secondary processing, and therefore price for sailing is much higher as its own costs.

Keywords: pasta, new wheat sorts, domesic sorts of wheat, macaronic flour

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Authors: Clarinda Vitorino Nhangumbe, Fredericks Ebrahim, Betuel Canhanga

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The price of an option weather derivatives can be approximated as a solution of the two-dimensional convection-diffusion dominant partial differential equation derived from the Ornstein-Uhlenbeck process, where one variable represents the weather dynamics and the other variable represent the underlying weather index. With appropriate financial boundary conditions, the solution of the pricing equation is approximated using a nonstandard finite difference method. It is shown that the proposed numerical scheme preserves positivity as well as stability and consistency. In order to illustrate the accuracy of the method, the numerical results are compared with other methods. The model is tested for real weather data.

Keywords: nonstandard finite differences, Ornstein-Uhlenbeck process, partial differential equations approach, weather derivatives

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Authors: Hasan Vural

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The purpose of this study was to determine energy equivalents of inputs and output in tomato production in Bursa province. The data in this study were collected from tomato farms in Bursa province, Karacabey and Mustafakemalpasa district. Questionnaires were administered through face-to-face interview in 2011-2012. The results of the study show that diesel have the highest rate of energy equivalency of all the inputs used in tomato production at 60,07%. The energy equivalent rate of electricity is 4,26% and the energy equivalent rate of water is 0,87%. The energy equivalent rates for human power, machinery, chemicals and water for irrigation were determined to be low in tomato production. According to the output/input ratio calculated, the energy ratio is 1,50 in tomato production in the research area. This ratio implies that the inputs used in tomato production have not been used effectively. Ineffective use of these resources also causes environmental problems.

Keywords: Tomato production, energy ratio, energy input, Turkey

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian automotive sector, stock market decisions, equity portfolio analysis, decision tree classifiers, statistical data analysis

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Authors: A. Benatiallah, A. Hadjadj, D. Benatiallah, F. Abaidi, A. Harrouz

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Photovoltaic system is established as a reliable and economical source of electricity in rural and Sahara areas, especially in developing countries where the population is dispersed, has low consumption of energy and the grid power is not extended to these areas due to viability and financial problems. The production of energy by the photovoltaic system is very fluctuates and depend of meteorological conditions. Wind is a very important and often neglected parameter in the behavior of the solar module. The electric performances of a solar module to the silicon are very appreciable to the blows; in the present work we have studies the behavior of multi-crystal solar module according to the density of dust, and the principals electric feature of the solar module. An evaluation permits to affirm that a solar module under the effect of sand will collect a lower flux to the normal conditions.

Keywords: photovoltaic, multi-crystal module, experimental, effect of dust, performances

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Authors: Wolfram Jahn, Jose Manuel Munita

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While computational fluid dynamics (CFD) simulations of fire scenarios are commonly used in the design of buildings, less attention has been given to the use of CFD simulations as an operational tool for the fire services. The reason of this lack of attention lies mainly in the fact that CFD simulations typically take large periods of time to complete, and their results would thus not be available in time to be of use during an emergency. Firefighters often face uncertain conditions when entering a building to attack a fire. They would greatly benefit from a technology based on predictive fire simulations, able to assist their decision-making process. The principal constraint to faster CFD simulations is the fine grid necessary to solve accurately the physical processes that govern a fire. This paper explores the possibility of overcoming this constraint and using coarse grid CFD simulations for fire scenarios, and proposes a methodology to use the simulation results in a meaningful way that can be used by the fire fighters during an emergency. Data from real scale compartment fire tests were used to compare CFD fire models with different grid arrangements, and empirical correlations were obtained to interpolate data points into the grids. The results show that the strongly predominant effect of the heat release rate of the fire on the fluid dynamics allows for the use of coarse grids with relatively low overall impact of simulation results. Simulations with an acceptable level of accuracy could be run in real time, thus making them useful as a forecasting tool for emergency response purposes.

Keywords: CFD, fire simulations, emergency response, forecast

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Authors: Obioma Uche

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Due to the recent volatility in oil & gas prices as well as increased development of non-conventional resources, it has become even more essential to critically evaluate the profitability of petroleum prospects prior to making any investment decisions. Traditionally, simple Monte Carlo (MC) algorithms have been used to randomly sample probability distributions of economic and geological factors (e.g. price, OPEX, CAPEX, reserves, productive life, etc.) in order to obtain probability distributions for profitability metrics such as Net Present Value (NPV). In recent years, second-order MC algorithms have been shown to offer an advantage over simple MC techniques due to the added consideration of uncertainties associated with the probability distributions of the relevant variables. Here, a strategy for the application of the second-order MC technique to a case study is demonstrated to analyze its effectiveness as a tool for portfolio management.

Keywords: Monte Carlo algorithms, portfolio management, profitability, risk analysis

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Authors: A. K. M. Kamrul Islam, Abdelhamid Bouchachia, Suang Cang, Hongnian Yu

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Forecasting model has a great impact in terms of prediction and continues to do so into the future. Although many forecasting models have been studied in recent years, most researchers focus on different forecasting methods based on fuzzy time series to solve forecasting problems. The forecasted models accuracy fully depends on the two terms that are the length of the interval in the universe of discourse and the content of the forecast rules. Moreover, a hybrid forecasting method can be an effective and efficient way to improve forecasts rather than an individual forecasting model. There are different hybrids forecasting models which combined fuzzy time series with evolutionary algorithms, but the performances are not quite satisfactory. In this paper, we proposed a hybrid forecasting model which deals with the first order as well as high order fuzzy time series and particle swarm optimization to improve the forecasted accuracy. The proposed method used the historical enrollments of the University of Alabama as dataset in the forecasting process. Firstly, we considered an automatic clustering algorithm to calculate the appropriate interval for the historical enrollments. Then particle swarm optimization and fuzzy time series are combined that shows better forecasting accuracy than other existing forecasting models.

Keywords: fuzzy time series (fts), particle swarm optimization, clustering algorithm, hybrid forecasting model

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Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay

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Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.

Keywords: annotated facial expression dataset, gesture recognition, sequenced facial expression dataset, sign language recognition

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Authors: Raif Parlakkaya, Ahmet Diken, Erkan Kara

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This paper examines the relationship between corporate governance rating and stock prices of 26 Turkish firms listed in Turkish stock exchange (Borsa Istanbul) by using panel data analysis over five-year period. The paper also investigates the stock performance of firms with governance rating with regards to the market portfolio (i.e. BIST 100 Index) both prior and after governance scoring began. The empirical results show that there is no relation between corporate governance rating and stock prices when using panel data for annual variation in both rating score and stock prices. Further analysis indicates surprising results that while the selected firms outperform the market significantly prior to rating, the same performance does not continue afterwards.

Keywords: corporate governance, stock price, performance, panel data analysis

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Authors: Olivia Garcia, Sandra Tullio-Pow

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The purpose of this study was to understand what design attributes make the most ideal (wearable and memorable) national soccer jersey. The research probed Canadian soccer enthusiasts to better understand their jersey-purchasing rationale. The research questions framing this study were: how do consumers feel about their jerseys? How do these feelings influence their choices? There has been limited research on soccer jerseys from a material culture perspective, and it is not inclusive of national soccer jerseys. The results of this study may be used for product developers and advertisers who are looking to better understand the consumer base for national soccer jersey design. A mixed methods approach informed the research. To begin, a content analysis of all the home jerseys from the 2018 World Cup was done. Information such as size range, main colour, fibre content, brand, collar details, availability, sleeve length, place of manufacturing, pattern, price, fabric as per company, neckline, availability on company website, jersey inspiration, and badge/crest details were noted. Following the content analysis, wardrobe interviews were conducted with six consumers/fans. Participants brought two or more jerseys to the interviews, where the jerseys acted as clothing probes to recount information. Interview questions were semi-structured and focused on the participants’ relationship with the sport, their personal background, who they cheered for, why they bought the jerseys, and fit preferences. The goal of the inquiry was to pull out information on how participants feel about their jerseys and why. Finally, an interview with an industry professional was done. This interview was semi-structured, focusing on basic questions regarding sportswear design, sales, the popularity of soccer, and the manufacturing and marketing process. The findings proved that national soccer jerseys are an integral part of material culture. Women liked more fitted jerseys, and men liked more comfortable jerseys. Jerseys should be made with a cooling, comfortable fabric and should always prevent peeling. The symbols on jerseys are there to convey a team’s history and are most typically placed on the left chest. Jerseys should always represent the flag and/or the country’s colours and should use designs that are both fashionable and innovative. Jersey design should always consider the opinions of the consumers to help influence the design process. Jerseys should always use concepts surrounding culture, as consumers feel connected to the jerseys that represent the culture and/or family they have grown up with. Jerseys should use a team’s history, as well as the nostalgia associated with the team, as consumers prefer jerseys that reflect important moments in soccer. Jerseys must also sit at a reasonable price point for consumers, with an experience to go along with the jersey purchase. In conclusion, national soccer jerseys are considered sites of attachment and memories and play an integral part in the study of material culture.

Keywords: Design, Fashion, Material Culture, Sport

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Authors: Daomao Yang, Qizhi Wang

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Monoterpenoids are mainly found in plant essential oils and they are ideal substrates for biotransformation into oxygen-containing derivatives with important commercial value due to their low price and simple structure. In this paper, eleven strains of endophytic fungi from Praxelis clematidea were used as test strains to conduct the whole cell biotransformation of the monoterpenoids: (+)-limonene, (-)-limonene and myrcene. The fungi were inoculated in 50 ml Sabouraud medium and incubated at 30 ℃ with the agitation of 150 r/min for 6 d, and then 0.5% (v/v) substrates were added into the medium and biotransformed for further 3 d. Afterwards the cultures were filtered, and extracted using equal volume of ethyl acetate. The metabolites were analyzed by GC-MS technique with NIST database. The Total Ion Chromatogram of the extractions from the eleven strains showed that the main product of (+)- and (-)-limonene biotransformation was limonene-1,2-diol, while it is limonene and linalool oxide for biotransformation of myrcene. This work will help screen the microorganisms to biotransform the monoterpenes.

Keywords: endophytic fungi, (+)–limonene, (-)–limonene, myrcene

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Authors: Rosyidah, Permata Wulandari

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We investigate the price effect of addition and deletions from the Indonesia Sharia Stock Index (ISSI) and Jakarta Islamic Index (JII). Using event study methodology, we measure abnormal returns for firms over the period June 2019 - to December 2021. Through the sample of 107 additions and 95 deletions, we find evidence to support the theory of Muslim country investment behavior. We find that additions to the Islamic index led to a significant positive stock market reaction and deletions to the Islamic index led to a negative stock market reaction on Jakarta Islamic Index (JII) and there is no significant reaction of addition and deletion on Indonesia Sharia Stock Index (ISSI).

Keywords: abnormal return, abnormal volume, event study, index changes, sharia index

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Authors: Miroslav Gutten, Daniel Korenciak, Milan Simko, Milan Chupac

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Ensure the reliable and correct function of transformers is the main essence of on-line non-destructive diagnostic tool, which allows the accurately track of the status parameters. Devices for on-line diagnostics are very costly. However, there are devices, whose price is relatively low and when used correctly, they can be executed a complex diagnostics. One of these devices is sensor HYDRAN M2, which is used to detect the moisture and gas content in the insulation oil. Using the sensor HYDRAN M2 in combination with temperature, load measurement, and physicochemical analysis can be made the economically inexpensive diagnostic system, which use is not restricted to distribution transformers. This system was tested in educational laboratory environment at measured oil transformer 22/0.4 kV. From the conclusions referred in article is possible to determine, which kind of fault was occurred in the transformer and how was an impact on the temperature, evolution of gases and water content.

Keywords: transformer, diagnostics, gas and moisture sensor, monitoring

Procedia PDF Downloads 383

Authors: Ming-Chan Chung, Wen-Ming Huang, Yi-Chu Liu, Li-Hui Yang, Ming-Jyh Chen

Abstract:

introduction: Hospital buildings require considerable energy, including air conditioning, lighting, elevators, heating, and medical equipment. Energy consumption in hospitals is expected to increase significantly due to innovative equipment and continuous development plans. Consequently, the environment and climate will be adversely affected. Hospitals should therefore consider transforming from their traditional role of saving lives to being at the forefront of global efforts to reduce carbon dioxide emissions. As healthcare providers, it is our responsibility to provide a high-quality environment while using as little energy as possible. Purpose / Methods: Compare the energy-saving benefits of solar photovoltaic systems and solar hot water systems. The proportion of electricity consumption effectively reduced after the installation of solar photovoltaic systems. To comprehensively assess the potential benefits of utilizing solar energy for both photovoltaic (PV) and solar thermal applications in hospitals, a solar PV system was installed covering a total area of 28.95 square meters in 2021. Approval was obtained from the Taiwan Power Company to integrate the system into the hospital's electrical infrastructure for self-use. To measure the performance of the system, a dedicated meter was installed to track monthly power generation, which was then converted into area output using an electric energy conversion factor. This research aims to compare the energy efficiency of solar PV systems and solar thermal systems. Results: Using the conversion formula between electrical and thermal energy, we can compare the energy output of solar heating systems and solar photovoltaic systems. The comparative study draws upon data from February 2021 to February 2023, wherein the solar heating system generated an average of 2.54 kWh of energy per panel per day, while the solar photovoltaic system produced 1.17 kWh of energy per panel per day, resulting in a difference of approximately 2.17 times between the two systems. Conclusions: After conducting statistical analysis and comparisons, it was found that solar thermal heating systems offer higher energy and greater benefits than solar photovoltaic systems. Furthermore, an examination of literature data and simulations of the energy and economic benefits of solar thermal water systems and solar-assisted heat pump systems revealed that solar thermal water systems have higher energy density values, shorter recovery periods, and lower power consumption than solar-assisted heat pump systems. Through monitoring and empirical research in this study, it has been concluded that a heat pump-assisted solar thermal water system represents a relatively superior energy-saving and carbon-reducing solution for medical institutions. Not only can this system help reduce overall electricity consumption and the use of fossil fuels, but it can also provide more effective heating solutions.

Keywords: sustainable development, energy conservation, carbon reduction, renewable energy, heat pump system

Procedia PDF Downloads 80

Authors: Djermani Farouk, Sri Rahayu Hijrah Hati, Fenitra Maminirin, Permata Wulandari

Abstract:

This study investigates the implications of Artificial Intelligence Marketing (AIM) marketing mix (PRD) Product, (PRC) Price, (PRM), Promotion and (PLC) Place on consumption patterns of halal food (CPHF). A quantitative approach was adopted in this study and responses were obtained from 350 Indonesian consumers. Using Partial Least Squares-Structural Equation Modeling (PLS-SEM), the results show that there is a direct support of marketing mix (PRD, PRC, PLC) to AIM and CPHF, while PRM does not play a significant role in CPHF. In addition, the findings reveal that AIM mediates significantly the relationship between PLC, PRC and PRM and CPHF, while AIM indicates no mediation between PRD and CPHF. Indonesian consumer’s exhibit serious concerns with consumption patterns of halal food. it is recommended that managers focus their attention on marketing strategies to predict consumer behavior in terms of consumption patterns of halal food through the integration of AIM.

Keywords: marketing mix, consumption patterns, artificial intelligence marketing, Halal food

Procedia PDF Downloads 31

Authors: Saleh B. Mohamed, Mohamed H. Elhsnawi, Mesbah M. Salem

Abstract:

Current and future applications of small gas turbine engines annular type combustors have requirements presenting difficult disputes to the combustor designer. Reduced cost and fuel consumption and improved durability and reliability as well as higher temperatures and pressures for such application are forecast. Coupled with these performance requirements, irrespective of the engine size, is the demand to control the pollutant emissions, namely the oxides of nitrogen, carbon monoxide, smoke and unburned hydrocarbons. These technical and environmental challenges have made the design of small size combustion system a very hard task. Thus, the main target of this work is to generalize a calculation method of annular type combustors for small gas turbine engines that enables to understand the fundamental concepts of the coupled processes and to identify the proper procedure that formulates and solves the problems in combustion fields in as much simplified and accurate manner as possible. The combustion chamber in task is designed with central vaporizing unit and to deliver 516.3 KW of power. The geometrical constraints are 142 mm & 140 mm overall length and casing diameter, respectively, while the airflow rate is 0.8 kg/sec and the fuel flow rate is 0.012 kg/sec. The relevant design equations are programmed by using MathCAD language for ease and speed up of the calculation process.

Keywords: design of gas turbine, small engine design, annular type combustors, mechanical engineering

Procedia PDF Downloads 406