Search results for: stock price prediction

Authors: Ibrahim Makram Ibrahim Salib

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Agriculture plays an essential role in providing food for the world's population. It also offers numerous benefits to countries, including non-food products, transportation, and environmental balance. Precision agriculture, which employs advanced tools to monitor variability and manage inputs, can help achieve these benefits. The increasing demand for food security puts pressure on decision-makers to ensure sufficient food production worldwide. To support sustainable agriculture, unmanned aerial vehicles (UAVs) can be utilized to manage farms and increase yields. This paper aims to provide an understanding of UAV usage and its applications in agriculture. The objective is to review the various applications of UAVs in agriculture. Based on a comprehensive review of existing research, it was found that different sensors provide varying analyses for agriculture applications. Therefore, the purpose of the project must be determined before using UAV technology for better data quality and analysis. In conclusion, identifying a suitable sensor and UAV is crucial to gather accurate data and precise analysis when using UAVs in agriculture.

Keywords: agriculture land, agriculture land loss, Kabul city, urban land expansion, urbanization agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models drone, precision agriculture, farmer income

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Authors: Sadia Munir

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Preeclampsia is the contributor to the worldwide maternal mortality of approximately 100,000 deaths a year. It complicates about 10% of all pregnancies and is the first cause of maternal admission to intensive care units. Predicting preeclampsia is a major challenge in obstetrics. More importantly, no major progress has been achieved in the treatment of preeclampsia. As placenta is the main cause of the disease, the only way to treat the disease is to extract placental and deliver the baby. In developed countries, the cost of an average case of preeclampsia is estimated at £9000. Interestingly, preeclampsia may have an impact on the health of mother or infant, beyond the pregnancy. We performed a systematic search of PubMed including the combination of terms such as preeclampsia, biomarkers, treatment, hypoxia, inflammation, oxidative stress, vascular endothelial growth factor A, activin A, inhibin A, placental growth factor, transforming growth factor β-1, Nodal, placenta, trophoblast cells, microRNAs. In this review, we have summarized current knowledge on the identification of potential biomarkers for the diagnosis of preeclampsia. Although these studies show promising data in early diagnosis of preeclampsia, the current value of these factors as biomarkers, for the precise prediction of preeclampsia, has its limitation. Therefore, future studies need to be done to support some of the very promising and interesting data to develop affordable and widely available tests for early detection and treatment of preeclampsia.

Keywords: activin, biomarkers, growth factors, miroRNA

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Authors: Ria M. Caramoan, Analiza P. Rollon, Karl N. Vergel

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The Simple Interactive Models for Better Air Quality (SIM-air) is an integrated approach model that allows the available information to support the integrated urban air quality management. This study utilized the vehicular air pollution information system module of SIM-air for the assessment of vehicular emissions in Commonwealth Avenue, Quezon City, Philippines. The main objective of the study is to assess and predict the contribution of different types of vehicles to the vehicular emissions in terms of PM₁₀, SOₓ, and NOₓ at different policy and technology scenarios. For the base year 2017, the results show vehicular emissions of 735.46 tons of PM₁₀, 108.90 tons of SOₓ, and 2,101.11 tons of NOₓ. Motorcycle is the major source of particulates contributing about 52% of the PM₁₀ emissions. Meanwhile, Public Utility Jeepneys contribute 27% of SOₓ emissions and private cars using gasoline contribute 39% of NOₓ emissions. Ambient air quality monitoring was also conducted in the study area for the standard parameters of PM₁₀, S0₂, and NO₂. Results show an average of 88.11 µg/Ncm, 47.41 µg/Ncm and 22.54 µg/Ncm for PM₁₀, N0₂, and SO₂, respectively, all were within the DENR National Ambient Air Quality Guideline Values. Future emissions of PM₁₀, NOₓ, and SOₓ are estimated at different scenarios. Results show that in the year 2030, PM₁₀ emissions will be increased by 186.2%. NOₓ emissions and SOₓ emissions will also be increased by 38.9% and 5.5%, without the implementation of the scenarios.

Keywords: ambient air quality, emissions inventory, mobile air pollution, vehicular emissions

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Authors: Hailu Kebede Bekele

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Construction delays are suitable where project events occur at a certain time expected due to causes related to the client, consultant, and contractor. Delay is the major cause of the cost overrun that leads to the poor efficiency of the project. The cost difference between completion and the originally estimated is known as cost overrun. The common ways of cost overruns are not simple issues that can be neglected, but more attention should be given to prevent the organization from being devastated to be failed, and financial expenses to be extended. The reasons that may raised in different studies show that the problem may arise in construction projects due to errors in budgeting, lack of favorable weather conditions, inefficient machinery, and the availability of extravagance. The study is focused on the pace of mega projects that can have a significant change in the cost overrun calculation.15 mega projects are identified to study the problem of the cost overrun in the site. The contractor, consultant, and client are the principal stakeholders in the mega projects. 20 people from each sector were selected to participate in the investigation of the current mega construction project. The main objective of the study on the construction cost overrun is to prioritize the major causes of the cost overrun problem. The methodology that was employed in the construction cost overrun is the qualitative methodology that mostly rates the causes of construction project cost overrun. Interviews, open-ended and closed-ended questions group discussions, and rating qualitative methods are the best methodologies to study construction projects overrun. The result shows that design mistakes, lack of labor, payment delay, old equipment and scheduling, weather conditions, lack of skilled labor, payment delays, transportation, inflation, and order variations, market price fluctuation, and people's thoughts and philosophies, the prior cause of the cost overrun that fail the project performance. The institute shall follow the scheduled activities to bring a positive forward in the project life.

Keywords: cost overrun, delay, mega projects, design

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Authors: Odunayo S. Faluse, Roger Telfer

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Customer relationship management is a business strategy that is centred on the idea that ‘Customer is the driving force of any business’ i.e. Customer is placed in a central position in any business. However, this belief coupled with the advancement in information technology in the past twenty years has experienced a change. In any form of business today it can be concluded that customers are the modern dictators to whom the industry always adjusts its business operations due to the increase in availability of information, intense market competition and ever growing negotiating ideas of customers in the process of buying and selling. The most vital role of any organization is to satisfy or meet customer’s needs and demands, which eventually determines customer’s long-term value to the industry. Therefore, this paper analyses and describes the application of customer relationship management operational strategies in some of the major industries in business. Both developed and up-coming companies nowadays value the quality of customer services and client’s loyalty, they also recognize the customers that are not very sensitive when it comes to changes in price and thereby realize that attracting new customers is more tasking and expensive than retaining the existing customers. However, research shows that several factors have recently amounts to the sudden rise in the execution of CRM strategies in the marketplace, such as a diverted attention of some organization towards integrating ideas in retaining existing customers rather than attracting new one, gathering data about customers through the use of internal database system and acquiring of external syndicate data, also exponential increase in technological intelligence. Apparently, with this development in business operations, CRM research in Academia remain nascent; hence this paper gives detailed critical analysis of the recent advancement in the use of CRM and key research opportunities for future development in using the implementation of CRM as a determinant factor for successful business optimization.

Keywords: agriculture, banking, business strategies, CRM, education, healthcare

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Authors: Sebastiana Viphindratin, Silvi Asna

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The under ground economy phenomenon is exist in Indonesia. There are some factors which affect the existence this underground economy activity. One of them is a hierarchy power structure that handles the underground economy existence. The example of the existence of underground economy is the occurring informal market in Indonesia. Malang city is one of the city which has this kind of market. Junk night market (JNM) as an underground economy activity is arising in that city. The JNM is located in Gatot Subroto Sidewalk Street. The JNM is a illegal market which sell thrift, antique, imitation and black market goods. The JNM is interesting topic to be discussed, because this market is running in long time without any policy from local government. The JNM activity has their own “power” that run the market rules. Thus, it is important to analyze how the existence and power structure of JNM actors community are in Malang city. This research using qualitative method with phenomenological approach where we try to understand the phenomenon and related actors deeply. The aim of this research is to know the existence and power structure of JNM actors community in Malang. In JNM, there is no any entry barriers and tax charge from Malang government itself. Price competition also occurs because the buyer can do a bargain with the seller. In maintaining buyer loyalty, the JNM actors also do pre-order system. Even though, this market is an illegal market but the JNM actors also give the goods guarantee (without legal contract) as a formal market. In JNM actor’s community, there is no hierarchy and formal power structure. The role in JNM is managed by informal leaders who come up from the trading activity problems that are sidewalk and parking area dividing. Therefore, can be concluded that even the JNM is illegal market but it can survive with natural market pattern. In JNM development, JNM has positive and negative impact for Malang city. The positive impact of JNM is this market can open a new employment but the negative impact is there is no tax income from that market. Therefore, suggested that the government of Malang city should manage and give appropriate policies in this case.

Keywords: junk night market (JNM), Malang city, underground economy, illegal

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Authors: Champika S. Kariyawasam

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The distribution of gorse (Ulex europaeus) plants in South Australia has been modelled using 126 presence-only location data as a function of seven climate parameters. The predicted range of U. europaeus is mainly along the Mount Lofty Ranges in the Adelaide Hills and on Kangaroo Island. Annual precipitation and yearly average aridity index appeared to be the highest contributing variables to the final model formulation. The Jackknife procedure was employed to identify the contribution of different variables to gorse model outputs and response curves were used to predict changes with changing environmental variables. Based on this analysis, it was revealed that the combined effect of one or more variables could make a completely different impact to the original variables on their own to the model prediction. This work also demonstrates the need for a careful approach when selecting environmental variables for projecting correlative models to climatically distinct area. Maxent acts as a robust model when projecting the fitted species distribution model to another area with changing climatic conditions, whereas the generalized linear model, bioclim, and domain models to be less robust in this regard. These findings are important not only for predicting and managing invasive alien gorse in South Australia and Sri Lanka but also in other countries of the invasive range.

Keywords: invasive species, Maxent, species distribution modelling, Ulex europaeus

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Authors: Amina Sultan, Mohamed Ghonim, Eman Oweida, Aya Abdelaziz

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Objective: To assess the diagnostic reliability of multi-detector CT in pre and post-operative evaluation of cochlear implant candidates. Material and Methods: The study includes 40 patients (18 males and 22 females); mean age 5.6 years. They were classified into two groups: Group A (20 patients): cochlear implant device was Nucleus-22 and Group B (20 patients): the device was MED-EL. Cochlear length (CL) and cochlear height (CH) were measured pre-operatively by 128-multidetector CT. Electrode length (EL) and insertion depth angle (α) were measured post-operatively by MDCT. Results: For Group A mean CL was 9.1 mm ± 0.4 SD; mean CH was 4.1 ± 0.3 SD; mean EL was 18 ± 2.7 SD; mean α angle was 299.05 ± 37 SD. Significant statistical correlation (P < 0.05) was found between preoperative CL and post-operative EL (r²=0.6); as well as EL and α angle (r²=0.7). Group B's mean CL was 9.1 mm ± 0.3 SD; mean CH was 4.1 ± 0.4 SD; mean EL was 27 ± 2.1 SD; mean α angle was 287.6 ± 41.7 SD. Significant statistical correlation was found between CL and EL (r²= 0.6) and α angle (r²=0.5). Also, a strong correlation was found between EL and α angle (r²=0.8). Significant statistical difference was detected between the two devices as regards to the electrode length. Conclusion: Multidetector CT is a reliable tool for preoperative planning and post-operative evaluation of the outcomes of cochlear implant operations. Cochlear length is a valuable prognostic parameter for prediction of the depth of electrode array insertion which can influence criteria of device selection.

Keywords: angle of insertion (α angle), cochlear implant (CI), cochlear length (CL), Multidetector Computed Tomography (MDCT)

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Authors: Matza Gusto Andika, Malinda Sabrina, Syarie Fatunnisa

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Aerodynamic and aeroelastics studies on the hanger bridge profile are important to analyze the aerodynamic phenomenon and Aeroelastics stability of hanger. Wind tunnel tests were conducted on a model of H-beam profile from hanger bridge. The purpose of this study is to investigate steady aerodynamic characteristics such as lift coefficient (Cl), drag coefficient (Cd), and moment coefficient (Cm) under the different angle of attack for preliminary prediction of aeroelastics stability problems. After investigation the steady aerodynamics characteristics from the model, dynamic testing is also conducted in wind tunnel to know the aeroelastics phenomenon which occurs at the H-beam hanger bridge profile. The studies show that the torsional vortex induced vibration occur when the wind speed is 7.32 m/s until 9.19 m/s with maximum amplitude occur when the wind speed is 8.41 m/s. The result of wind tunnel testing is matching to hanger vibration where occur in the field, so wind tunnel studies has successful to model the problem. In order that the H-beam profile is not good enough for the hanger bridge and need to be modified to minimize the Aeroelastics problem. The modification can be done with structure dynamics modification or aerodynamics modification.

Keywords: aerodynamics, aeroelastic, hanger bridge, h-beam profile, vortex induced vibration, wind tunnel

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Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi

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Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.

Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol

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Authors: Adeola Adejumo, Oluwole David Adebayo, Muraina Kamilu Olanrewaju

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The purpose of this study was to investigate the influence of some psychological factors (i.e, school climate, parental involvement and classroom interaction) on the learning gains of university undergraduates in Mathematics in Ibadan, Nigeria. Three hundred undergraduates who are on open distance learning education programme in the University of Ibadan and thirty mathematics lecturers constituted the study’s sample. Both the independent and dependent variables were measured with relevant standardized instruments and the data obtained was analyzed using multiple regression statistical method. The instruments used were school climate scale, parental involvement scale and classroom interaction scale. Three research questions were answered in the study. The result showed that there was significant relationship between the three independent variables (school climate, parental involvement and classroom interaction) on the students’ learning gain in mathematics and that the independent variables both jointly and relatively contributed significantly to the prediction of students’ learning gain in mathematics. On the strength of these findings, the need to enhance the school climate, improve the parents’ involvement in the student’s education and encourage students’ classroom interaction were stressed and advocated.

Keywords: school climate, parental involvement, ODL, learning gains, mathematics

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Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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Authors: Nhi Ngoc Thien

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Franchising is a popular trend in Vietnam retail industry, especially in fast food industry. Several famous foreign fast food brands such as KFC, Lotteria, Jollibee or Pizza Hut invested on this potential market since the 1990s. Following this trend, in 2011, Burger King - the second largest fast food hamburger chain all over the world - entered Vietnam with its first store located in Tan Son Nhat International Airport, with the expectation to become the leading brand in the country. However, the business performance of Burger King was not going well in the first few years making it questioned about its strategy. The given assumption was that its business performance was affected negatively by its store location selection strategy. This research aims to investigate the current performance of Burger King Vietnam in terms of the controllable variables like store location as well as to explore the key factors influencing customer decision to choose Burger King. Therefore, a case study research method was conducted to approach deeply on the opinions and evaluations of 10 Burger King’s customers, Burger King's staffs and other fast food experts on Burger King’s performance through in-depth interview, direct observation and documentary analysis. Findings show that there are 8 determinants affecting the decision-making of Burger King’s customers, which are store location, quality of food, service quality, store atmosphere, price, promotion, menu and brand reputation. Moreover, findings present that Burger King’s staffs and fast food experts also mentioned the main problems of Burger King, which are about store location and food quality. As a result, there are some recommendations for Burger King Vietnam to improve its performance in the market and attract more Vietnamese target customers by giving suitable promotional activities among its customers and being differentiated itself from other fast food brands.

Keywords: overall retail strategy, controllable variables, store location, quality of food

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Authors: Krassimir Todorov

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The purpose of the paper is to redefine the levels of structure of corporate, business and functional strategies that were established over the past several decades, to a conceptual model, consisting of corporate, business and operations strategies, that are reinforced by functional strategies. We will propose a conceptual framework of different perspectives in the role of strategic operations as a separate strategic place and reposition the remaining functional strategies as supporting tools, existing at all three levels. The proposed model is called ‘the strategic engine’, since the mutual relationships of its ingredients are identical with main elements and working principle of the internal combustion engine. Based on theoretical essence, related to every strategic level, we will prove that the strategic engine model is useful for managers seeking to safeguard the competitive advantage of their companies. Each strategy level is researched through its basic elements. At the corporate level we examine the scope of firm’s product, the vertical and geographical coverage. At the business level, the point of interest is limited to the SWOT analysis’ basic elements. While at operations level, the key research issue relates to the scope of the following performance indicators: cost, quality, speed, flexibility and dependability. In this relationship, the paper provides a different view for the role of operations strategy within the overall strategy concept. We will prove that the theoretical essence of operations goes far beyond the scope of traditionally accepted business functions. Exploring the applications of Resource-based theory and Market-based theory within the strategic levels framework, we will prove that there is a logical consequence of the theoretical impact in corporate, business and operations strategy – at every strategic level, the validity of one theory is substituted to the level of the other. Practical application of the conceptual model is tested in automotive industry. Actually, the proposed theoretical concept is inspired by a leading global automotive group – Inchcape PLC, listed on the London Stock Exchange, and constituent of the FTSE 250 Index.

Keywords: business strategy, corporate strategy, functional strategies, operations strategy

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Authors: M. Khalid, W. Rashmi, L. L. Kwan

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This work provides an overview on the experimental and numerical simulations of various nanofluids and their flow and heat transfer behavior. It was further extended to study the effect of nanoparticle concentration, fluid flow rates and thermo-physical properties on the heat transfer enhancement of Al2O3/water nanofluid in a turbulent flow circular conduit using ANSYS FLUENT™ 14.0. Single-phase approximation (homogeneous model) and two-phase (mixture and Eulerian) models were used to simulate the nanofluid flow behavior in the 3-D horizontal pipe. The numerical results were further validated with experimental correlations reported in the literature. It was found that heat transfer of nanofluids increases with increasing particle volume concentration and Reynolds number, respectively. Results showed good agreement (~9% deviation) with the experimental correlations, especially for a single-phase model with constant properties. Among two-phase models, mixture model (~14% deviation) showed better prediction compared to Eulerian-dispersed model (~18% deviation) when temperature independent properties were used. Non-drag forces were also employed in the Eulerian two-phase model. However, the two-phase mixture model with temperature dependent nanofluid properties gave slightly closer agreement (~12% deviation).

Keywords: nanofluid, CFD, heat transfer, forced convection, circular conduit

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Authors: Eric Wilson Santos Cabral, Marta Monteiro Da Costa Cruz, Rodrigo Pirola Pestana, Vivian Andréa Parreira

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In the transportation sector in Brazil, there is a great challenge that is the maintenance of profit in the face of the great variation in the price of diesel. This directly affects the variable cost of transport companies. Within the railways, part of the great challenges is to overcome the annual budget, cargo and ore transported, thus reducing costs compared to previous years, becoming more efficient each year. Within this scenario, the railway companies are looking for effective measures, aiming at reducing the ratio of liter of diesel consumed by KTKB (Kilometer Gross Ton multiplied by thousand). This ratio represents the indicator of energy efficiency of some railroads in Brazil and in other countries. In this study, we sought to analyze the behavior of the energy efficiency indicator on two parts: The first, with the application of technologies used in locomotives, such as the start-stop system of the diesel engine and the system of tracking and monitoring of fuel. The second, evaluation of the behavior of the variation of the type of cargo transported (loading mix). The study focused on locomotive technology will be carried out using statistical analysis, behavioral evaluation in different operating conditions, such as maneuvers for trains, service trains and freight trains. The analysis will also cover the evaluation of the loading mix made using statistical analysis of the existing railroad database, comparing the energy efficiency per loading mine and type of product. With the completion of this study, the railway undertakings should be able to better target decision-making in order to achieve substantial reductions in transport costs.

Keywords: railway transport, energy efficiency, railway technology, fuel consumption

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Authors: Valentina Di Maria, Anton Ianakiev

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The use of adhesive anchors for wooden constructions is an efficient technology to connect and design timber members in new timber structures and to rehabilitate the damaged structural members of historical buildings. Due to the lack of standard regulation in this specific area of structural design, designers’ choices are still supported by test analysis that enables knowledge, and the prediction, of the structural behavior of glued in rod joints. The paper outlines an experimental research activity aimed at identifying the tensile resistance capacity of several new adhesive joint prototypes made of epoxy resin, steel bar and timber, Oak and Douglas Fir species. The development of new adhesive connectors has been carried out by using epoxy to glue stainless steel bars into pre-drilled holes, characterized by smooth and rough internal surfaces, in timber samples. The realization of a threaded contact surface using a specific drill bit has led to an improved bond between wood and epoxy. The applied changes have also reduced the cost of the joints’ production. The paper presents the results of this parametric analysis and a Finite Element analysis that enables identification and study of the internal stress distribution in the proposed adhesive anchors.

Keywords: glued in rod joints, adhesive anchors, timber, epoxy, rough contact surface, threaded hole shape

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Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Heba Kamal, Ghada Saudi

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Due to The rapid expansion of energy and growing number of wind turbines construction in earthquake areas, a design method for simple and accurate evaluation of seismic load to ensure structural integrity is required. In Egypt, there are some appropriate places to build wind turbine towers lie in active seismically regions, so accurate analysis is necessary for prediction of seismic loads with consideration of intensity of the earthquake, soil and structural characteristics. In this research, seismic behavior of wind turbine towers Gamesa Type G52 in Zafarana Wind Farm Egypt is investigated using experimental work by ambient vibration test, and fully dynamic analysis based on time history from El Aqaba Earthquake 1995 using 3D by PLAXIS 3D software, including the soil structure interaction effect. The results obtained from dynamic analyses are discussed. From this study, it is concluded that, the fully dynamic seismic analysis based on used PLAXIS 3D with the aid of the full scale ambient vibration test gives almost good simulation for the seismic loads that can be applied to wind turbine tower design in Egypt.

Keywords: Wind turbine towers, Zafarana Wind Farm, Gamesa Type G52, ambient vibration test

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Authors: Tejeet Singh, Virat Khanna

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Composite materials have drawn considerable attention of engineers due to their light weight and application at high thermo-mechanical loads. With regard to the prediction of the life of high temperature structural components like rotating cylinders and the evaluation of their deterioration with time, it is essential to have a full knowledge of creep characteristics of these materials. Therefore, in the present study the secondary stage creep stresses and strain rates are estimated in thick-walled composite cylinders subjected to rotary inertia at different angular speeds. The composite cylinder is composed of aluminum matrix (Al) and reinforced with silicon carbide (SiC) particles which are uniformly mixed. The creep response of the material of the cylinder is described by threshold stress based creep law. The study indicates that with the increase in angular speed, the radial, tangential, axial and effective stress increases to a significant value. However, the radial stress remains zero at inner radius and outer radius due to imposed boundary conditions of zero pressure. Further, the stresses are tensile in nature throughout the entire radius of composite cylinder. The strain rates are also influenced in the same manner as that of creep stresses. The creep rates will increase significantly with the increase of centrifugal force on account of rotation.

Keywords: composite, creep, rotating cylinder, angular speed

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Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

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The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Teng Zhang, Xuelin Zhang, Shouxiang Lu, Changhai Li

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The existence of animal groups and collective migration are common in nature, and collective behavior is attracting more and more attention of researchers. Previous results have shown that architectural design had an important effect on the process of crowd evacuation. In this paper, collective behavior of mice passing through a middle-exit or corner-exit under panic was investigated. Selfish behavior and herd behavior were easily observed in our video, which caused the congregation with high density near the exit. Triangle structure of congregation formed near the middle-exit while arch structure formed near the corner-exit. It is noteworthy that the exit located at the middle of the wall was more effective for evacuation than at the corner. Meanwhile, the escape sequence of mouse passing through the exit was investigated, and the result showed that the priority depends largely on its location in the congregation. With the level of stimulus increasing, these phenomena still exist. The frequency distributions of time intervals and the burst sizes were also analyzed in this study to explore the secret of collective behavior of mice. These results could provide evidence for the hypothesis or prediction about human behavior in crowd evacuation. However, it is not clear whether the simulated results from different species can correspond to reality or not. Broader comparison among different species about this topic will be eager to be conducted to deepen our understanding of collective behavior in nature.

Keywords: collective behavior, mice, evacuation, exit location

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Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Raphael Tuor, Denis Lalanne

Abstract:

The ATM research community is missing suitable tools to design, test, and validate new UI prototypes. Important stakes underline the implementation of both DSS and XAI methods into current systems. ML-based DSS are gaining in relevance as ATFM becomes increasingly complex. However, these systems only prove useful if a human can understand them, and thus new XAI methods are needed. The human-machine dyad should work as a team and should understand each other. We present xSky, a configurable benchmark tool that allows us to compare different versions of an ATC interface in conflict detection tasks. Our main contributions to the ATC research community are (1) a conflict detection task simulator (xSky) that allows to test the applicability of visual prototypes on scenarios of varying difficulty and outputting relevant operational metrics (2) a theoretical approach to the explanations of AI-driven trajectory predictions. xSky addresses several issues that were identified within available research tools. Researchers can configure the dimensions affecting scenario difficulty with a simple CSV file. Both the content and appearance of the XAI elements can be customized in a few steps. As a proof-of-concept, we implemented an XAI prototype inspired by the maritime field.

Keywords: air traffic control, air traffic simulation, conflict detection, explainable artificial intelligence, explainability, human-automation collaboration, human factors, information visualization, interpretability, trajectory prediction

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Authors: Bikash Kumar Malick

Abstract:

Labour reform is a most celebrated theme for policy makers, at the same time it is also a most misunderstood and skeptical concept even for the educated masses in India. One of the widely focused and discussed topics which needs an in-depth examination is India’s labour laws. It may actually help to reach points to understand the exact requirements in labour reforms by making the labour laws more simple and concise in form and its implementation. It is also a requirement to guide states in India in terms of making laws on it as Indian Constitution itself is federal in form and unitary in spirit. Recently, Codes of Wages Bill has been introduced in Indian Parliament while other three codes are waiting to come in the same line and those codes actually highlight the simplified features of labour laws to enable labour reform in a succinct manner. However, it still brings more confusion in minds of people. To wipe out the confusion and to bring a note and to put it for correlation among the labour reforms of both centre and states which both generates employment and make growth sustainable in India providing clear public understanding. This time is also ripe minimizing the apprehension about all the coming labour laws simplified in different codes in India. This article attempts to highlight the need of labour reform and its possible impact. It also examines the higher rates of minimum wages and its links with its coverage agriculture and nonagricultural sectors (including mines) over the period time. It also takes into consideration of central sphere and in states sphere minimum wage which are linked with Consumer Price Index to bring into account the living standard of workers and to examine the cause and effect between minimum wage and output in both agriculture and non agricultural sector with regression analysis. Increase in minimum wage has actually strengthened the sustainable output.

Keywords: codes of wages, indian constitution, minimum wage, labour laws, labour reforms

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Authors: Rajat Mittal, Harshal Raut, Jung Hee Seo

Abstract:

Wave-assisted propulsion (WAP) systems convert wave energy into thrust using elastically mounted hydrofoils. We employ sharp-interface immersed boundary simulations to examine the effect of two key parameters on the flow physics, the fluid-structure interaction, as well as thrust performance of these systems - the stiffness of the torsional spring and the location of the rotational center. The variation in spring stiffness leads to different amplitude of pitch motion, phase difference with respect to heaving motion and thrust coefficient and we show the utility of ‘maps’ of energy exchange between the flow and the hydrofoil system, as a way to understand and predict this behavior. The Force Partitioning Method (FPM) is used to decompose the pressure forces into individual components and understand the mechanism behind increase in thrust. Next, a scaling law is presented for the thrust coefficient generated by heaving and pitching foil. The parameters within the scaling law are calculated based on direct-numerical simulations based parametric study utilized to generate the energy maps. The predictions of the proposed scaling law are then compared with those of a similar model from the literature, showing a noticeable improvement in the prediction of the thrust coefficient.

Keywords: propulsion, flapping foils, hydrodynamics, wave power

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Authors: Sujoy Das, M. M. Ghosh

Abstract:

The thermal conductivity of a fluid can be significantly enhanced by dispersing nano-sized particles in it, and the resultant fluid is termed as "nanofluid". A theoretical model for estimating the thermal conductivity of a nanofluid has been proposed here. It is based on the mechanism that evenly dispersed nanoparticles within a nanofluid undergo Brownian motion in course of which the nanoparticles repeatedly collide with the heat source. During each collision a rapid heat transfer occurs owing to the solid-solid contact. Molecular dynamics (MD) simulation of the collision of nanoparticles with the heat source has shown that there is a pulse-like pick up of heat by the nanoparticles within 20-100 ps, the extent of which depends not only on thermal conductivity of the nanoparticles, but also on the elastic and other physical properties of the nanoparticle. After the collision the nanoparticles undergo Brownian motion in the base fluid and release the excess heat to the surrounding base fluid within 2-10 ms. The Brownian motion and associated temperature variation of the nanoparticles have been modeled by stochastic analysis. Repeated occurrence of these events by the suspended nanoparticles significantly contributes to the characteristic thermal conductivity of the nanofluids, which has been estimated by the present model for a ethylene glycol based nanofluid containing Cu-nanoparticles of size ranging from 8 to 20 nm, with Gaussian size distribution. The prediction of the present model has shown a reasonable agreement with the experimental data available in literature.

Keywords: brownian dynamics, molecular dynamics, nanofluid, thermal conductivity

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Authors: Yina A. Cifuentes Triana, Andrés M. Pinzón Velásco, Marío E. Velásquez Lozano

Abstract:

In this work the sequencing and genome characterization of a natural isolate of Saccharomyces cerevisiae yeast (strain 202-3), identified with potential for the production of second generation ethanol from sugarcane bagasse hydrolysates is presented. This strain was selected because its capability to consume xylose during the fermentation of sugarcane bagasse hydrolysates, taking into account that many strains of S. cerevisiae are incapable of processing this sugar. This advantage and other prominent positive aspects during fermentation profiles evaluated in bagasse hydrolysates made the strain 202-3 a candidate strain to improve the production of second-generation ethanol, which was proposed as a first step to study the strain at the genomic level. The molecular characterization was carried out by genome sequencing with the Illumina HiSeq 2000 platform paired end; the assembly was performed with different programs, finally choosing the assembler ABYSS with kmer 89. Gene prediction was developed with the approach of hidden Markov models with Augustus. The genes identified were scored based on similarity with public databases of nucleotide and protein. Records were organized from ontological functions at different hierarchical levels, which identified central metabolic functions and roles of the S. cerevisiae strain 202-3, highlighting the presence of four possible new proteins, two of them probably associated with the positive consumption of xylose.

Keywords: cellulosic ethanol, Saccharomyces cerevisiae, genome sequencing, xylose consumption

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