Search results for: predictive models

Authors: Chayanika Rout, Debjani Chakraborty, Adrijit Goswami

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Our work presents an inventory model which illustrates imperfect production and imperfect inspection processes for deteriorating items. A cost-minimizing model is studied considering two types of inspection errors, namely, Type I error of falsely screening out a proportion of non-defects, thereby passing them on for rework and Type II error of falsely not screening out a proportion of defects, thus selling those to customers which incurs a penalty cost. The screened items are reworked; however, no returns are entertained due to deteriorating nature of the items. In more practical situations, certain parameters such as the demand rate and the deterioration rate of inventory cannot be accurately determined, and therefore, they are assumed to be triangular fuzzy numbers in our model. We calculate the optimal lot size that must be produced in order to minimize the total inventory cost for both the crisp and the fuzzy models. A numerical example is also considered to exemplify the procedure which is followed by the analysis of sensitivity of various parameters on the decision variable and the objective function.

Keywords: deteriorating items, EPQ, imperfect quality, rework, type I and type II inspection errors

Procedia PDF Downloads 183

Authors: Fahad Javed, Tasneem Akhter, Maria Zafar, Adnan Shafique

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Evaluation and quantification of techniques is critical element of research and development of technology. Simulations and models play an important role in providing the tools for such assessments. When we look at technologies which impact or is dependent on an average Joe consumer then modeling the socio-economic and psychological aspects of the consumer also gain an importance. For feed in tariff for home consumers which is being deployed for average consumer may force many consumers to be adapters of the technology. Understanding how consumers will adapt this technologies thus hold as much significance as evaluating how the techniques would work in consumer agnostic scenarios. In this paper we first build the case for simulators which accommodate socio-economic realities of the consumers to evaluate smart grid technologies, provide a glossary of data that can aid in this effort and present an abstract model to capture and simulate consumers' adaptation and behavioral response to smart grid technologies. We provide a case study to express the power of such simulators.

Keywords: smart grids, simulation, socio-economic parameters, feed in tariff (FiT), forecasting

Procedia PDF Downloads 359

Authors: Fuchun Li, Hong Xiao

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We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

Procedia PDF Downloads 437

Authors: Josua K. Junias, Fillemon N. Nangolo, Petrina T. Johaness

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The deterioration of pavement can lead to the formation of potholes, which cause the wheels of a vehicle to experience unusual and uneven movement. In addition, improper loading practices of heavy vehicles can result in dynamic loading of the pavement due to the vehicle's response to the irregular movement caused by the potholes. Previous studies have only focused on the effects of either the road's uneven surface or the asymmetrical loading of the vehicle, but not both. This study aimed to model the pavement's dynamic response to heavy vehicles under different loading configurations and wheel movements. A sample of 225 cases with symmetrical and asymmetrical loading and kinematic movements was used, and 27 validated 3D pavement-vehicle interactive models were developed using SIMWISE 4D. The study found that the type of kinematic movement experienced by the heavy vehicle affects the pavement's dynamic loading, with eccentrically loaded, asymmetrically kinematic heavy vehicles having a statistically significant impact. The study also suggests that the mass of the vehicle's suspension system plays a role in the pavement's dynamic loading.

Keywords: eccentricities, pavement dynamic loading, vertical displacement dynamic response, heavy vehicles

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Authors: J. Koiso-Kanttila, A. Soikkeli, A. Aapaoja

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Construction in Finland is focusing increasingly on renovation instead of conventional new construction, and this trend will continue to grow in the coming years and decades. Renovation of the large number of suburban residential apartment buildings built in the 1960s and 1970s poses a particular challenge. However, renovation projects are demanding for the residents of these buildings, since they usually are uninitiated in construction issues. On the other hand, renovation projects generally apply the operating models of new construction. Nevertheless, the residents of an existing residential apartment building are some of the best experts on the site. Thus, in this research project we applied a relational model in developing and testing at case sites a planning process that employs interactive planning methods. Current residents, housing company managers, the city zoning manager, the contractor’s and prefab element supplier’s representatives, professional designers and researchers all took part in the planning. The entire interactive planning process progressed phase by phase as the participants’ and designers’ concerted discussion and ideation process, so that the end result was a renovation plan desired by the residents.

Keywords: apartment building renovation, interactive planning, project alliance, user-orientedness

Procedia PDF Downloads 386

Authors: Parinaz Arashnia, Farzad Hatami, Saeed Ghaffarpour Jahromi

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Using steel in bridges’ construction because of their desired tensile and compressive strength and light weight especially in large spans was widely popular. Disadvantages of steel such as corrosion, buckling and weaknesses in high temperature and unsuitable weld could be solve with using Fibres Reinforced Polymer (FRP) profiles. The FRP is a remarkable class of composite polymers that can improve structural elements behaviour like corrosion resistance, fir resistance with good proofing and electricity and magnetic non-conductor. Nowadays except FRP reinforced bars and laminates, FRP I-beams are made and studied. The main reason for using FRP profiles is, prevent of corrosion and increase the load carrying capacity and durability, especially in large spans in bridges’ deck. In this paper, behaviour of I-section glass fibres reinforced polymer (GFRP) beam is discussed under point loads with numerical models and results has been compared and verified with experimental tests.

Keywords: glass fibres reinforced polymer, composite, I-section beam, durability, finite element method, numerical model

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

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Authors: Halima Adel Halim Shnishah, David Mulvaney

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Applying traditional symmetric cryptography algorithms while computing encryption and decryption provides immunity to secret keys against different attacks. One of the popular techniques generating automated secret keys is evolutionary computing by using Eureqa API tool, which got attention in 2013. In this paper, we are generating automated secret keys for image encryption and decryption using Eureqa API (tool which is used in evolutionary computing technique). Eureqa API models pseudo-random input data obtained from a suitable source to generate secret keys. The validation of generated secret keys is investigated by performing various statistical tests (histogram, chi-square, correlation of two adjacent pixels, correlation between original and encrypted images, entropy and key sensitivity). Experimental results obtained from methods including histogram analysis, correlation coefficient, entropy and key sensitivity, show that the proposed image encryption algorithms are secure and reliable, with the potential to be adapted for secure image communication applications.

Keywords: image encryption algorithms, Eureqa, statistical measurements, automated key generation

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Authors: Solomon Olusegun Olugbenro

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The purpose of this study is to ascertain the relationship of teachers' personalty and peer pressure on adolescents' personalty in mainland local government, Lagos State, Nigeria. The research design for this study was survey. A representative fraction of the population of mainland local government of lagos was used as sample. One hundred and fifty (150) teenagers whose age ranged from 11-19 from six randomly selected public and private secondary schools in mainland local government area of lagos were used. A four-point likert type questionnaire was constructed for eliciting data for this study. Data were analysed using t-test. The study revealed that there is a significant relationship between teachers' and adolescents' personality development. The study also revealed that there is significant relationship between peer pressure and adolescents' personality development. It was recommended that teachers should be role models to students as they manipulate environmental factors to assist adolescents in their personality development.

Keywords: adolescents, behavior, development, peer pressure, personality, relationship, significant, teachers

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Authors: Hamd Rezaeifar, Hamid Reza Sahriari

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Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.

Keywords: accident, data mining, neural network, GIS

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Authors: Xitong Liu, Yutong Huang, Shu-Ching Yang

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The phenomena of hypergamous and hypogamous marriages have become popular due to the imbalanced sex ratio caused by Chinese social preference for sons. Our research explores the spillover effect of husbands' lifestyles on their wives' marital satisfaction in China. Both personal and spouse lifestyle elements are utilized to develop regression models to study husbands' spillover effects on women's marital satisfaction. With data from China Family Panel Study and Stata for analysis, we tested our hypothesis that both smoking and substance use by a spouse will negatively impact women's marital satisfaction. Our empirical findings suggest that substance use has negative implications on marriage satisfaction. In particular, husbands' substance use is more critical to wives' marriage satisfaction than wives' behaviours. Conversely, another behavior indicating bad habits, the number of times the spouse drank alcohol, had no significant effect on the wife's marital satisfaction. We concluded our investigation and provided future implications for scholars in the family economics field.

Keywords: Asian/Pacific Islander families, family economics, housework/division of labor, spillover

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Authors: Alex Contarino

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Professional sports leagues often have a “free agency” period, during which teams may sign players with expiring contracts.To promote parity, many leagues operate under a salary cap that limits the amount teams can spend on player’s salaries in a given year. Similarly, in fantasy sports leagues, salary cap drafts are a popular method for selecting players. In order to sign a free agent in either setting, teams must bid against one another to buy the player’s services while ensuring the sum of their player’s salaries is below the salary cap. This paper models the bidding process for a free agent as a constrained optimization problem that can be solved using linear programming. The objective is to determine the largest bid that a team should offer the player subject to the constraint that the value of signing the player must exceed the value of using the salary cap elsewhere. Iteratively solving this optimization problem for each available free agent provides teams with an effective framework for maximizing the talent on their rosters. The utility of this approach is demonstrated for team sport roster construction and fantasy sport drafts, using recent data sets from both settings.

Keywords: linear programming, optimization, roster management, salary cap

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Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin

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Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.

Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Ping Xu, Gregory T. Golm, Guanghan (Frank) Liu

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In the presence of competing events, traditional survival analysis may not be appropriate and can result in biased estimates, as it assumes independence between competing events and the event of interest. Instead, competing risk analysis should be considered to correctly estimate the survival probability of the event of interest and the hazard ratio between treatment groups. The COVID-19 pandemic has provided a potential source of competing risks in clinical trials, as participants in trials may experienceCOVID-related competing events before the occurrence of the event of interest, for instance, death due to COVID-19, which can affect the incidence rate of the event of interest. We have performed simulation studies to compare multiple competing risk analysis models, including the cumulative incidence function, the sub-distribution hazard function, and the cause-specific hazard function, to the traditional survival analysis model under various scenarios. We also provide a general recommendation on conducting competing risk analysis in randomized clinical trials during the era of the COVID-19 pandemic based on the extensive simulation results.

Keywords: competing risk, survival analysis, simulations, randomized clinical trial, COVID-19 pandemic

Procedia PDF Downloads 189

Authors: Jose A. C. Venancio, Alexandrino J. M. Goncalves, Anabela Marto, Nuno C. S. Rodrigues, Rita M. T. Ascenso

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Nowadays, it is common to find people who are concerned about getting away from the everyday life routine, looking forward to outcome well-being and pleasant emotions. Trying to disconnect themselves from the usual places of work and residence, they pursue different places, such as tourist destinations, aiming to have unexpected experiences. In order to make this exploration process easier, cities and tourism agencies seek new opportunities and solutions, creating routes with diverse cultural landmarks, including natural landscapes and historic buildings. These offers frequently aspire to the preservation of the local patrimony. In nature and wildlife, birdwatching is an activity that has been increasing, both in cities and in the countryside. This activity seeks to find, observe and identify the diversity of birds that live permanently or temporarily in these places, and it is usually supported by birdwatching guides. Leiria (Portugal) is a well-known city, presenting several historical and natural landmarks, like the Lis river and the castle where King D. Dinis lived in the 13th century. Along the Lis River, a conservation process was carried out and a pedestrian route was created (Polis project). This is considered an excellent spot for birdwatching, especially for the gray heron (Ardea cinerea) and for the kingfisher (Alcedo atthis). There is also a route through the city, from the riverside to the castle, which encloses a characterized variety of species, such as the barn swallow (Hirundo rustica), known for passing through different seasons of the year. Birdwatching is sometimes a difficult task since it is not always possible to see all bird species that inhabit a given place. For this reason, a need to create a technological solution was found to ease this activity. This project aims to encourage people to learn about the various species of birds that live along the Lis River and to promote the preservation of nature in a conscious way. This work is being conducted in collaboration with Leiria Municipal Council and with the Environmental Interpretation Centre. It intends to show the majesty of the Lis River, a place visited daily by several people, such as children and families, who use it for didactic and recreational activities. We are developing a mobile multi-platform application (Guard@Lis) that allows bird species to be observed along a given route, using representative digital 3D models through the integration of augmented reality technologies. Guard@Lis displays a route with points of interest for birdwatching and a list of species for each point of interest, along with scientific information, images and sounds for every species. For some birds, to ensure their observation, the user can watch them in loco, in their real and natural environment, with their mobile device by means of augmented reality, giving the sensation of presence of these birds, even if they cannot be seen in that place at that moment. The augmented reality feature is being developed with Vuforia SDK, using a hybrid approach to recognition and tracking processes, combining marks and geolocation techniques. This application proposes routes and notifies users with alerts for the possibility of viewing models of augmented reality birds. The final Guard@Lis prototype will be tested by volunteers in-situ.

Keywords: augmented reality, birdwatching route, mobile application, nature tourism, watch birds using augmented reality

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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Authors: Karolína Vozková, Matěj Kuc

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Net fee and commission income is one of the key elements of a bank’s core income. In the current low-interest rate environment, this type of income is gaining importance relative to net interest income. This paper analyses the effects of bank and country specific determinants of net fee and commission income on a set of cooperative banks from European countries in the 2007-2014 period. In order to do that, dynamic panel data methods (system Generalized Methods of Moments) were employed. Subsequently, alternative panel data methods were run as robustness checks of the analysis. Strong positive impact of bank concentration on the share of net fee and commission income was found, which proves that cooperative banks tend to display a higher share of fee income in less competitive markets. This is probably connected with the fact that they stick with their traditional deposit-taking and loan-providing model and fees on these services are driven down by the competitors. Moreover, compared to commercial banks, cooperatives do not expand heavily into non-traditional fee bearing services under competition and their overall fee income share is therefore decreasing with the increased competitiveness of the sector.

Keywords: cooperative banking, dynamic panel data models, net fee and commission income, system GMM

Procedia PDF Downloads 333

Authors: Aminu Fagge Muhammad

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The digital economy is fast becoming the most innovative and widest reaching economy in the world, especially in developing countries. The paper aimed at examining role of digital economy in the emerging countries like Nigeria. The methodology used in the study is Business Model Perspective: lying between the process and structural perspectives, bring in the idea of the new business models that are being enabled e.g. e-business or e-commerce. The paper concluded that, the policy objectives and measures, and processes and structures necessary to enhance digital economy growth and its contribution to socio-economic development. The finding reveals that, digital infrastructure is in part incomplete, costly and poorly-performing in emerging economies like Nigeria. The wider digital ecosystem suffers a shortfall in human capabilities, weak financing, and poor governance. It is also found that, Growth in the digital economy is exacerbating digital exclusion, inequality, adverse incorporation and other digital harms. It is recommended that, government in partnership with private sector should build strong local infrastructure to enable broadband availability and accessibility and to create an enabling environment for strong competition in the telecom and technology ecosystem.

Keywords: Digital Economy, Emerging Countries, Business Model , Nigeria

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Tauhidur Rahman, Arnab Kumar Sinha

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This paper presents a comparative study of Arch bridges based on their varying rise to span ratio. The comparison is done between different steel Arch bridges which have variable span length and rise to span ratio keeping the same support condition. The aim of our present study is to select the optimum value of rise to span ratio of Arch bridge as the cost of the Arch bridge increases with the increasing of the rise. In order to fulfill the objective, several rise to span ratio have been considered for same span of Arch bridge and various structural parameters such as Bending moment, shear force etc have been calculated for different model. A comparative study has been done for several Arch bridges finally to select the optimum rise to span ratio of the Arch bridges. In the present study, Finite Element model for medium to long span, with different rise to span ratio have been modeled and are analyzed with the help of a Computational Software named MIDAS Civil to evaluate the results such as Bending moments, Shear force, displacements, Stresses, influence line diagrams, critical loads. In the present study, 60 models of Arch bridges for 80 to 120 m span with different rise to span ratio has been thoroughly investigated.

Keywords: arch bridge, analysis, comparative study, rise to span ratio

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Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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Authors: Zahid Ullah, Atlas Khan

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The presented research is dedicated to an extensive examination of the regularity properties associated with a specific class of equations, namely extremely degenerate elliptic equations. This study holds significance in unraveling the complexities inherent in these equations and understanding the smoothness of their solutions. The focus is on analyzing the regularity of results, aiming to contribute to the broader field of mathematical theory. By delving into the intricacies of extremely degenerate elliptic equations, the research seeks to advance our understanding beyond conventional analyses, addressing challenges posed by degeneracy and pushing the boundaries of classical analytical methods. The motivation for this exploration lies in the practical applicability of mathematical models, particularly in real-world scenarios where physical phenomena exhibit characteristics that challenge traditional mathematical modeling. The research aspires to fill gaps in the current understanding of regularity properties within solutions to extremely degenerate elliptic equations, ultimately contributing to both theoretical foundations and practical applications in diverse scientific fields.

Keywords: investigating smoothness, extremely degenerate elliptic equations, regularity properties, mathematical analysis, complexity solutions

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Authors: Noraishah Othman, Siti K. Kamarudin, Norinsan K. Othman, Mohd S. Takriff, Masli I. Rosli, Engku M. Fahmi, Mior A. Khusaini

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The present work describes hydrodynamics of mixing characteristics of two dual hybrid impeller consisting of, radial and axial impeller using radiotracer technique. Type A mixer, a Rushton turbine is mounted above a Pitched Blade Turbine (PBT) at common shaft and Type B mixer, a Rushton turbine is mounted below PBT. The objectives of this paper are to investigate the residence time distribution (RTD) of two hybrid mixers and to represent the respective mixers by RTD model. Each type of mixer will experience five radiotracer experiments using Tc99m as source of tracer and scintillation detectors NaI(Tl) are used for tracer detection. The results showed that mixer in parallel model and mixers in series with exchange can represent the flow model in mixer A whereas only mixer in parallel model can represent Type B mixer well than other models. In conclusion, Type A impeller, Rushton impeller above PBT, reduced the presence of dead zone in the mixer significantly rather than Type B.

Keywords: hybrid impeller, residence time distribution (RTD), radiotracer experiments, RTD model

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Authors: Redouane Tlemsani, Abdelkader Benyettou

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Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology. This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data. Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables. In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization. The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, computer vision

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

Abstract:

An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

Procedia PDF Downloads 97

Authors: Nady Farag Faragalla Hanna

Abstract:

In the car dealership industry in Japan, the sales specialist is a key factor in the success of the company. I hypothesize that when a company understands the characteristics of sales professionals in its industry, it is easier to recruit and train salespeople effectively. Lean human resources management ensures the economic success and performance of companies, especially small and medium-sized companies.The purpose of the article is to determine the characteristics of sales specialists for small and medium-sized car dealerships using the chi-square test and the proximate variable model. Accordingly, the results show that career change experience, learning ability and product knowledge are important, while university education, career building through internal transfer, leadership experience and people development are not important for becoming a sales professional. I also show that the characteristics of sales specialists are perseverance, humility, improvisation and passion for business.

Keywords: electronics engineering, marketing, sales, E-commerce digitalization, interactive systems, sales process ARIMA models, sales demand forecasting, time series, R codetraits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

Procedia PDF Downloads 53

Authors: Sunitha Thappa

Abstract:

Business environment is a set of complex interdependent dimensions that corporates have to always be vigil in identifying the influential waves. Over the year business environment has evolved into a basket of uncertainties. Every organization strives to counter this dynamic nature of business environment by recurrently evaluating the primary and support activities of its value chain. This has led to companies redesigning their business models, reinvent business processes and operating procedure on unremitting basis. A few specific issues that are placed before the present day managers are breaking down the functional interpretation of any challenge that organizations confronts, reduction in organizational hierarchy and tackling the components of the value chain to retain their competitive advantage. It is how effectively managers detect the changes and swiftly reorient themselves to these changes that define their success or failure. Given the complexity of decision making in this dynamic environment, two important question placed before the B-schools of today. Firstly, are they grooming and nurturing managerial talent proficient enough to thrive in this multifaceted business environment? Secondly, are the management graduates walking through their portals, able to view challenges from a cross-functional perspective with emphasis to customer and process rather than hierarchy and functions. This paper focuses on the need for a process oriented approach to management education.

Keywords: management education, pedagogy, functional, process

Procedia PDF Downloads 333