Search results for: adaptable business models

Authors: N. G. Teik Hiang, Fathyah Hashim

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This is a case of how strategic management techniques can be used to help resolving problems faced by an ageing Small and Medium Enterprise (SME). Strategic way of resolving problems had been proven to be possible in this case despite general thought that strategic management is useful mostly for large corporations. Small and Medium Enterprises (SMEs) can also use strategic management in managing their business and determining their future cause of action and strategies in order to survive in this ever competent world. Strategic orientation is the key to survival and development of small and medium enterprises. In order to adapt to the fierce market competition, ageing SMEs should improve competitiveness and operational efficiency. They must therefore establish a sense of strategic management to improve the strategic management skills, combined with its own unique characteristics, and work out practical strategies to develop core competitiveness of enterprises in the fierce market competition in order to be sustainable. In this case, internal strengths and weaknesses of an SME had been identified. Strategic internal factors and external factors had been classified and further utilized to formulate potential strategies to encounter various problems faced by the SME. These strategies had been further match to take advantages of the opportunities and to overcome the weaknesses and minimize the threats it is facing. Tan, a consultant who was given the opportunity to formulate a plan for the business started with the environmental scanning (internal and external environmental analysis), assessing strengths and weaknesses for the company, strategies generation, analysis and evaluation. He had numerous discussions with the owner of the business and the senior management in order to match the key internal and external factors to formulate alternative strategies for solving the problems that the company facing. Some of the recommendations or solutions are generated from the inspiration of the owner of the business who is a very enterprising and experience businessman.

Keywords: strategic orientation, strategic management, SME, core competitiveness, sustainable

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Authors: Oluwole Victor Falobi, Lawrence Olusola Ige

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The cardinal drawing force of this study is to examine the influence of audio-visual resources in teaching business subjects in selected secondary schools in IfakoIjaiye Local Government Area of Lagos State, Nigeria. A descriptive survey research design was employed for the study. By using a quantitative research approach and a sample size of 120 students were randomly selected from four public schools. Three research questions with one hypothesis guided the study. Data collected were analysed using frequency, the mean and standard deviation for the research questions, and Pearson Product Moment Correlation PPMC were used to analysed the inferential statistic. Findings from the study revealed that the Influence of audio-visual resources in teaching business subjects in selected secondary schools in IfakoIjaiye Local Government Area of Lagos State is low. It further revealed data the knowledge of teachers on the use of audio-visual resources is high in Ifako Local Government Area. It was recommended that government should create a timely monitoring system in other to check secondary school laboratories and classrooms to replace outdated facilities and also purchase needed facilities for effective teaching and learning to take place.

Keywords: audio-visual resources, business subjects, school, teaching

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Authors: Dalia Suša Vugec

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Business process management (BPM) is widely used approach focused on designing, mapping, changing, managing and analyzing business processes of an organization, which eventually leads to better performance and derives many other benefits. Since every organization strives to improve its performance in order to be sustainable and to remain competitive on the market in long-term period, numerous organizations are nowadays adopting and implementing BPM. However, not all organizations are equally successful in that. One of the ways of measuring BPM success is by measuring its maturity by calculating Process Performance Index (PPI) using ten BPM success factors. Still, although BPM is a holistic concept, organizational culture is not taken into consideration in calculating PPI. Hence, aim of this paper is twofold; first, it aims to explore and analyze the current state of BPM success factors within the big organizations from Slovenia, Croatia, and Austria and second, it aims to analyze the structure of organizational culture within the observed companies, focusing on the link with BPM success factors as well. The presented study is based on the results of the questionnaire conducted as the part of the PROSPER project (IP-2014-09-3729) and financed by Croatian Science Foundation. The results of the questionnaire reveal differences in the achieved levels of BPM success factors and therefore BPM maturity in total between the three observed countries. Moreover, the structure of organizational culture across three countries also differs. This paper discusses the revealed differences between countries as well as the link between organizational culture and BPM success factors.

Keywords: business process management, BPM maturity, BPM success factors, organizational culture, process performance index

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Authors: Taieb Kherafa Noureddine

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The paper presents a new approach regarding the management in sports that is based on the principles of reengineering. Applying that modern and pure management system, called reengineering, in sports activity, we hope to get better and better results, in order to increase both the health state and the performances of trained athletes. The paper also presents the similarities between BPR (Business Process Reengineering) and sports managements, as well as the proposed solution for a proper implementation of such model of management. The five components of the basic BPR model are presented, together with their features for sports management.

Keywords: business process reengineering, great sports events, sports management, training activities

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Safaa H. Sindi, Michael Roe

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This project divides supply chain (SC) models into seven Eras, according to the evolution of the market’s needs throughout time. The five earliest Eras describe the emergence of supply chains, while the last two Eras are to be created. Research objectives: The aim is to generate the two latest Eras with their respective models that focus on the consumable goods. Era Six contains the Optimal Multidimensional Matrix (OMM) that incorporates most characteristics of the SC and allocates them into four quarters (Agile, Lean, Leagile, and Basic SC). This will help companies, especially (SMEs) plan their optimal SC route. Era Seven creates an Automated Multidimensional Model (AMM) which upgrades the matrix of Era six, as it accounts for all the supply chain factors (i.e. Offshoring, sourcing, risk) into an interactive system with Heuristic Learning that helps larger companies and industries to select the best SC model for their market. Methodologies: The data collection is based on a Fuzzy-Delphi study that analyses statements using Fuzzy Logic. The first round of Delphi study will contain statements (fuzzy rules) about the matrix of Era six. The second round of Delphi contains the feedback given from the first round and so on. Preliminary findings: both models are applicable, Matrix of Era six reduces the complexity of choosing the best SC model for SMEs by helping them identify the best strategy of Basic SC, Lean, Agile and Leagile SC; that’s tailored to their needs. The interactive heuristic learning in the AMM of Era seven will help mitigate error and aid large companies to identify and re-strategize the best SC model and distribution system for their market and commodity, hence increasing efficiency. Potential contributions to the literature: The problematic issue facing many companies is to decide which SC model or strategy to incorporate, due to the many models and definitions developed over the years. This research simplifies this by putting most definition in a template and most models in the Matrix of era six. This research is original as the division of SC into Eras, the Matrix of Era six (OMM) with Fuzzy-Delphi and Heuristic Learning in the AMM of Era seven provides a synergy of tools that were not combined before in the area of SC. Additionally the OMM of Era six is unique as it combines most characteristics of the SC, which is an original concept in itself.

Keywords: Leagile, automation, heuristic learning, supply chain models

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Authors: Marlon P. Perez

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The study intended to determine the level of occupational stress that was experienced by faculty members of private and public business schools in Batangas City with the end in view of proposing organizational development interventions in managing occupational stressors. Stressors such as factors intrinsic to the job, role in the organization, relationships at work, career development and organizational structure and climate were used as determinants of occupational stress level. Descriptive method of research was used as its research design. There were only 64 full-time faculty members coming from private and public business schools in Batangas City – University of Batangas, Lyceum of the Philippines University-Batangas, Golden Gate Colleges, Batangas State University and Colegio ng Lungsod ng Batangas. Survey questionnaire was used as data gathering instrument. It was found out that all occupational stressors were assessed stressful when grouped according to its classification of tertiary schools while response of subject respondents differs on their assessment of occupational stressors. Age variable has become significantly related to respondents’ assessments on factors intrinsic to the job and career development; however, it was not significantly related to role in the organization, relationships at work and organizational structure and climate. On the other hand, gender, marital status, highest educational attainment, employment status, length of service, area of specialization and classification of tertiary school were revealed to be not significantly related to all occupational stressors. Various organizational development interventions have been proposed to manage the occupational stressors that are experienced by business faculty members in the institution.

Keywords: occupational stress, business school, organizational development, intervention, stressors, faculty members, assessment, manage

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Authors: Hannah Kolano, Paul Nadan, Jeremy Ryan, Sophia Nielsen

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The hooves of goats and other ruminants, or the family Ruminantia, are uniquely structured to adapt to rough terrain. Their hooves possess a hard outer shell and a soft interior that allow them to both conform to uneven surfaces and hook onto prominent features. In an effort to apply this unique mechanism to a robotics context, artificial feet for a hexapedal robot have been designed based on the hooves of ruminants to improve the robot’s ability to traverse unstructured environments such as those found on a rocky planet or asteroid, as well as in earth-based environments such as rubble, caves, and mountainous regions. The feet were manufactured using a combination of 3D printing and polyurethane casting techniques and attached to a commercially available hexapedal robot. The robot was programmed with a terrain-adaptive gait and proved capable of traversing a variety of uneven surfaces and inclines. This development of more adaptable robotic feet allows legged robots to operate in a wider range of environments and expands their possible applications.

Keywords: biomimicry, legged locomotion, robotic foot design, ruminant feet, unstructured terrain navigation

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Authors: M. Guen

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A three-dimensional numerical study is used to analyze the behavior of the flow inside a vortex tube. The vortex tube or Ranque-Hilsch vortex tube is a simple device which is capable of dividing compressed air from the inlet nozzle tangentially into two flow with different temperatures warm and cold. This phenomenon is known from literature by temperature separation. The K ω-SST and K-ε turbulence models are used to predict the turbulent flow behaviour inside the tube. The vortex tube is an Exair 708 slpm (25 scfm) commercial tube. The cold and hot exits areas are 30.2 and 95 mm2 respectively. The vortex nozzle consists of 6 straight slots; the height and the width of each slot are 0.97 mm and 1.41 mm. The total area normal to the flow associated with six nozzles is therefore 8.15 mm 2. The present study focuses on a comparison between two turbulence models K ω-SST, K-ε by using a new configuration of vortex tube (Conical Vortex Tube). The performance curves of the temperature separation versus cold outlet mass fraction were calculated and compared with experimental and numerical study of other researchers.

Keywords: conical vortex tube, temperature separation, cold mass fraction, turbulence

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Authors: Olushola S. Ayanda, Olalekan S. Fatoki, Folahan A. Adekola, Bhekumusa J. Ximba, Cecilia O. Akintayo

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In the present study, the kinetics, equilibrium and thermodynamics of the adsorption of triphenyltin (TPT) from TPT-contaminated water onto nanoSiO2/fly ash/activated carbon composite was investigated in batch adsorption system. Equilibrium adsorption data were analyzed using Langmuir, Freundlich, Temkin and Dubinin–Radushkevich (D-R) isotherm models. Pseudo first- and second-order, Elovich and fractional power models were applied to test the kinetic data and in order to understand the mechanism of adsorption, thermodynamic parameters such as ΔG°, ΔSo and ΔH° were also calculated. The results showed a very good compliance with pseudo second-order equation while the Freundlich and D-R models fit the experiment data. Approximately 99.999 % TPT was removed from the initial concentration of 100 mg/L TPT at 80oC, contact time of 60 min, pH 8 and a stirring speed of 200 rpm. Thus, nanoSiO2/fly ash/activated carbon composite could be used as effective adsorbent for the removal of TPT from contaminated water and wastewater.

Keywords: isotherm, kinetics, nanoSiO₂/fly ash/activated carbon composite, tributyltin

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Authors: Elmamy Ahmedsalem

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The world has witnessed the collapse of many corporate giants as a result of unethical behavior in recent decades. This has induced a series of questions by the global community on why such occurrences could happen, even with corporate governance in place. This paper attempts to propose a philosophical approach from an Islamic perspective to be consolidated with current corporate governance in order to confront contemporary dilemmas. In this paper, ethical theories are presented as a discussion followed by their applications to modern cases of financial collapses. Virtue ethics by Aristotle, justice and fairness by John Rawls, deontology by Immanuel Kant, and utilitarianism by John Stuart Mill, are the four theories which can then be contrasted with the paradigm of Muslim scholars. Despite the differences between the fundamental principles of Islamic and Western worldviews, their ethical theories are aimed at making right decisions and solving ethical dilemmas based on what is good for society. Therefore, Islamic principles should be synthesized with Western philosophy to form a more coherent framework. The integration of Islamic and western ethical theories into business is important for sound corporate governance.

Keywords: business ethics, Islamic philosophy, western philosophy, Western and Islamic worldview of ethics

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Authors: Aminah Muchdar, Nuraeni, Eddy

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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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Authors: Dominik Halstrup, Marlene Schriever

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The industry, as one of the main energy consumer, is of critical importance along the way of transforming the energy system to Renewable Energies. The distributed character of the Energy Transition demands for further flexibility being introduced to the grid. In order to shed further light on the acceptance of Electric Energy Storage (ESS) from an industrial point of view, this study therefore examines the German manufacturing industry. The analysis in this paper uses data composed of a survey amongst 101 manufacturing companies in Germany. Being part of a two-stage research design, both qualitative and quantitative data was collected. Based on a literature review an acceptance concept was developed in the paper and four user-types identified: (Dedicated) User, Impeded User, Forced User and (Dedicated) Non-User and incorporated in the questionnaire. Both descriptive and bivariate analysis is deployed to identify the level of acceptance in the different organizations. After a factor analysis has been conducted, variables were grouped to form independent acceptance factors. Out of the 22 organizations that do show a positive attitude towards ESS, 5 have already implemented ESS and show a positive attitude towards ESS. They can be therefore considered ‘Dedicated Users’. The remaining 17 organizations have a positive attitude but have not implemented ESS yet. The results suggest that profitability plays an important role as well as load-management systems that are already in place. Surprisingly, 2 organizations have implemented ESS even though they have a negative attitude towards it. This is an example for a ‘Forced User’ where reasons of overriding importance or supporters with overriding authority might have forced the company to implement ESS. By far the biggest subset of the sample shows (critical) distance and can therefore be considered ‘(Dedicated) Non-Users’. The results indicate that the majority of the respondents have not thought ESS in their own organization through yet. For the majority of the sample one can therefore not speak of critical distance but rather a distance due to insufficient information and the perceived unprofitability. This paper identifies the relative state of acceptance of ESS in the manufacturing industry as well as current reasons for hindrance and perspectives for future growth of ESS in an industrial setting from a policy level. The interest that is currently generated by the media could be channeled and taken into a more substantial and individual discussion about ESS in an industrial setting. If the current perception of profitability could be addressed and communicated accordingly, ESS and their use in for instance cooperative business models could become a topic for more organizations in Germany and other parts of the world. As price mechanisms tend to favor existing technologies, policy makers need to further access the use of ESS and acknowledge the positive effects when integrated in an energy system. The subfields of generation, transmission and distribution become increasingly intertwined. New technologies and business models, such as ESS or cooperative arrangements entering the market, increase the number of stakeholders. Organizations need to find their place within this array of stakeholders.

Keywords: acceptance, energy storage solutions, German energy transition, manufacturing industry

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Authors: David de Oliveira Costa, Miguel Ângelo Lellis Moreira, Carlos Francisco Simões Gomes, Daniel Augusto de Moura Pereira, Marcos dos Santos

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Strategic management is a fundamental process for global companies that intend to remain competitive in an increasingly dynamic and complex market. To do so, it is necessary to maintain alignment with their principles and values. The Balanced Scorecard (BSC) proposes to ensure that the overall business performance is based on different perspectives (financial, customer, internal processes, and learning and growth). However, relying solely on the BSC may not be enough to ensure the success of strategic management. It is essential that companies also evaluate and prioritize strategic projects that need to be implemented to ensure they are aligned with the business vision and contribute to achieving established goals and objectives. In this context, the proposition involves the incorporation of the SAPEVO-M multicriteria method to indicate the degree of relevance between different perspectives. Thus, the strategic objectives linked to these perspectives have greater weight in the classification of structural projects. Additionally, it is proposed to apply the concept of the Impact & Probability Matrix (I&PM) to structure and ensure that strategic projects are evaluated according to their relevance and impact on the business. By structuring the business's strategic management in this way, alignment and prioritization of projects and actions related to strategic planning are ensured. This ensures that resources are directed towards the most relevant and impactful initiatives. Therefore, the objective of this article is to present the proposal for integrating the BSC methodology, the SAPEVO-M multicriteria method, and the prioritization matrix to establish a concrete weighting of strategic planning and obtain coherence in defining strategic projects aligned with the business vision. This ensures a robust decision-making support process.

Keywords: MCDA process, prioritization problematic, corporate strategy, multicriteria method

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Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

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This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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Authors: Abdullah E. Al-Mazrooei

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In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.

Keywords: bilinear systems, state space model, Kalman filter, application, models

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Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

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We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

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Authors: The Danh Phan

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House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Jose Juan Peña, J. Morales, J. García-Ravelo

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In the search of potential models applied in the theoretical treatment of diatomic molecules, some of them have been constructed by using standard hyperbolic functions as well as from the so-called q-deformed hyperbolic functions (sc q-dhf) for displacing and modifying the shape of the potential under study. In order to transcend the scope of hyperbolic functions, in this work, a kind of generalized q-deformed hyperbolic functions (g q-dhf) is presented. By a suitable transformation, through the q deformation parameter, it is shown that these g q-dhf can be expressed in terms of their corresponding standard ones besides they can be reduced to the sc q-dhf. As a useful application of the proposed approach, and considering a class of exactly solvable multi-parameter exponential-type potentials, some new q-deformed quantum interactions models that can be used as interesting alternative in quantum physics and quantum states are presented. Furthermore, due that quantum potential models are conditioned on the q-dependence of the parameters that characterize to the exponential-type potentials, it is shown that many specific cases of q-deformed potentials are obtained as particular cases from the proposal.

Keywords: diatomic molecules, exponential-type potentials, hyperbolic functions, q-deformed potentials

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Authors: David E. Culler, Noah D. Anderson

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Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together.

Keywords: PDM, PLM, collaboration, CAD/CAM, scalable systems

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Authors: Tsuu Faith Machingura, Daniel Madzanire, Doreen Nkala

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High employment opportunities in various towns in Zimbabwe attracted linguistically-diverse ethnic groups to settle therein. This movement, which largely was economically-induced, concocted diverse-populated communities in towns and in surrounding areas. Service provisions in such domains as education and business need to be diverse-sensitive. Prompted by the prevalence of diversity in present day business organisations, the study sought to suggest a cross-cultural strategy for managing an organisation located in a diverse-populated community. A case study research design was used. A sample of 10 participants consisting of five diverse business owners and five diverse clients was purposively drawn. Document analysis and key informant interviews were used to gather data. The study revealed that organisations that are located in diverse populated communities were shaped by the prevailing ethos. A diverse-sensitive managerial strategy was suggested as a pertinent cross-cultural managerial tool.

Keywords: cross-cultural strategy, linguistic diversity, diverse-populated community, ethnic groups

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Authors: Tobias Beyer, Christoph Friedrich

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Modern simulation methodology using finite element models is nowadays a recognized tool for product design/optimization. Likewise, manufacturing process design is increasingly becoming the focus of simulation methodology in order to enable sustainable results based on reduced real-life tests here as well. In this article, two process simulations -radial riveting and roller burnishing- used for mechanical joining of components are explained. In the first step, the required boundary conditions are developed and implemented in the respective simulation models. This is followed by process space validation. With the help of the validated models, the interdependencies of the input parameters are investigated and evaluated by means of sensitivity analyses. Limit case investigations are carried out and evaluated with the aid of the process simulations. Likewise, a comparison of the two joining methods to each other becomes possible.

Keywords: FEM, model-based process development, process simulation, radial riveting, roller burnishing, sensitivity analysis

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Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: asymptotic stability, Hartman-Grobman stability criterion, incubation period, Routh-Hurwitz criterion, Runge-Kutta method

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Authors: John Deely, Stephen Hynes, Mary Cawley, Sarah Hogan

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Domestic marine and coastal tourism have increased in importance over the last number of years due to the impacts of international travel, environmental concerns, associated health benefits and COVID-19 related travel restrictions. Consequently, this paper conceptualizes domestic marine and coastal tourism within an economic framework. Two logit models examine the factors that influence participation in the coastal day trips and overnight stays markets, respectively. Two truncated travel cost models are employed to explore trip duration, one analyzing the number of day trips taken and the other examining the number of nights spent in marine and coastal areas. Although a range of variables predicts participation, no one variable had a significant and consistent effect on every model. A division in access to domestic marine and coastal tourism is also observed based on variation in household income. The results also indicate a vibrant day trip market and large consumer surpluses.

Keywords: domestic marine and coastal tourism, day tripper, participation models, truncated travel cost model

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Michael C. Nwaohia

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Whereas anecdotal evidence supports the notion that increase in information technology (IT) know-how may enhance output of professionals in the accounting sector, this has not been systematically explored in the Nigerian context. Against this background, this paper examines the correlation between knowledgeability of IT and level of performance at everyday auditing and accounting tasks. It utilizes primary and secondary data from selected business organizations in Lagos, Nigeria. Accounting staff were administered structured questionnaires which, amongst other things, sought to examine knowledge and exposure to information technology prior to joining the firms and current level of performance based on self-reporting and supervisor comments. In addition, exposure to on-the-job IT training and current level of performance was examined. The statistical analysis of the data was done using the SPSS package. The results strongly suggest that prior exposure to IT skills enabled accounting professionals to better flexibly fit into the dynamic environment in which contemporary business takes place. Ultimately, the paper attempts to explicate some of the implications of these findings for individuals and business firms.

Keywords: accounting, firms, information technology, professional behavior

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram

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With the increase of prevailing non-traditional rivalry, mobile banking experiences an ever changing commercial backdrop. Substantial customer demands have established to be more intricate as customers request more expediency and superintend over their banking services. To enterprise advance and modernization in mobile banking applications, it is gradually obligatory to deeply leapfrog the scuffle using business model transformation. The dramaturgical vicissitudes taking place in mobile banking entail advanced traditions to exploit security. By reforming and transforming older back office into integrated mobile banking applications, banks can engender a supple and nimble banking environment that can rapidly respond to new business requirements over cloud computing. Cloud computing is transfiguring ecosystems in numerous industries, and mobile banking is no exemption providing services innovation, greater flexibility to respond to improved security and enhanced business intelligence with less cost. Cloud technology offer secure deployment possibilities that can provision banks in developing new customer experiences, empower operative relationship and advance speed to efficient banking transaction. Cloud adoption is escalating quickly since it can be made secured for commercial mobile banking transaction through backend as a service in scrutinizing the security strategies of the cloud service provider along with the antiquity of transaction details and their security related practices.

Keywords: cloud adoption, backend as a service, business intelligence, secured mobile banking

Procedia PDF Downloads 240