Search results for: Business Model

Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

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Authors: Abdel Hadi Ebraheim

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This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Due to its porous nature, karst terrains – geomorphologically developed from dissolved formations, is vulnerable to water shortage and deteriorated water quality. Therefore, a solid comprehension on sub-surface flow of karst landscape is essential to assess the long-term availability of groundwater resources. In this paper, a single-continuum model using a finite difference model, MODLFOW, was constructed to represent an unconfined carbonate aquifer in a tropical karst island of Rote in Indonesia. The model, spatially discretized in 20 x 20 m grid cells, was calibrated and validated using available groundwater level and atmospheric variables. In the calibration and validation steps, Parameter Estimation (PEST) and geostatistical pilot point methods were employed to estimate hydraulic conductivity and specific yield values. The results show that the model is able to represent the sub-surface flow indicated by good model performances both in calibration and validation steps. The final model can be used as a robust representation of the system for future study on climate and land use scenarios.

Keywords: carbonate aquifer, karst, sub-surface flow, groundwater model

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Authors: Julianne Cai, Weili Xue, Yibin Wu

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Social media retailing (SMR) platforms have become popular nowadays. It is characterized by a creative combination of content creation and product selling, which differs from traditional e-tailing (TE) with product selling alone. Motivated by real-world practices like social media platforms “TikTok” and douyin.com, we endeavor to study if the SMR model performs better than the TE model in a monopoly setting. By building a stylized economic model, we find that the SMR model does not always outperform the TE model. Specifically, when the SMR platform collects less commission from the seller than the TE platform, the seller, consumers, and social welfare all benefit more from the SMR model. In contrast, the platform benefits more from the SMR model if and only if the creator’s social influence is high enough or the cost of content creation is small enough. For the incentive structure of the content rewards in the SMR model, we found that a strong incentive mechanism (e.g., the quadratic form) is more powerful than a weak one (e.g., the linear form). The previous one will encourage the creator to choose a much higher quality level of content creation and meanwhile allowing the platform, consumers, and social welfare to become better off. Counterintuitively, providing more generous content rewards is not always helpful for the creator (seller), and it may reduce her profit. Our findings will guide the platform to effectively design incentive mechanisms to boost the content creation and retailing in the SMR model and help the influencers efficiently create content, engage their followers (fans), and price their products sold on the SMR platform.

Keywords: content creation, creator economy, incentive strategy, platform retailing

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Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: William Sigvardsson, Christoffer Alenius, Jenny Lindblom, Andreas Johansson, Marcus Sandberg

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This article covers a study focusing on a subarctic greenhouse located in Nikkala, Sweden. Through a visit and the creation of a CFD model, the study investigates the differences in energy demand with high pressure sodium (HPS) lights and light emitting diode (LED) lights in combination with an air-carried and water-carried heating system accordingly. Through an IDA ICE model, the impact of insulating the parts of the greenhouse without active cultivation was also investigated. This, with the purpose of comparing the current system in the greenhouse to state-of-the-art alternatives and evaluating if an investment in either a water-carried heating system in combination with LED lights and insulating the non-cultivating parts of the greenhouse could be considered profitable. Operating a greenhouse in the harsh subarctic climate found in the northern parts of Sweden is not an easy task and especially if the operation is year-round. With an average temperature of under -5 °C from November through January, efficient growing techniques are a must to ensure a profitable business. Today the most crucial parts of a greenhouse are the heating system, lighting system, dehumidifying measures, as well as thermal screen, and the impact of a poorly designed system in a sub-arctic could be devastating as the margins are slim. The greenhouse studied uses a pellet burner to power their air- carried heating system which is used. The simulations found the resulting savings amounted to just under 14 800 SEK monthly or 18 % of the total cost of energy by implementing the water-carrying heating system in combination with the LED lamps. Given this, a payback period of 3-9 years could be expected given different scenarios, including specific time periods, financial aids, and the resale price of the current system. The insulation of the non-cultivating parts of the greenhouse was found to have possible savings of 25 300 SEK annually or 46 % of the current heat demand resulting in a payback period of just over 1-2 years. Given the possible energy savings, a reduction in emitted CO2 equivalents of almost 1,9 tonnes could be achieved annually. It was concluded that relatively inexpensive investments in modern greenhouse equipment could make a significant contribution to reducing the energy consumption of the greenhouse resulting in a more competitive business environment for sub-arctic greenhouse owners. New parts of the greenhouse should be built with the water-carried heating system in combination with state-of-the-art LED lights, and all parts which are not housing active cultivation should be insulated. If the greenhouse in Nikkala is eligible for financial aid or finds a resale value in the current system, an investment should be made in a new water-carried heating system in combination with LED lights.

Keywords: energy efficiency, sub-arctic greenhouses, energy measures, greenhouse climate control, greenhouse technology, CFD

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Authors: Wei-Neng Wang, Jhy-Yuan Shieh, Jhy-Hwa Chen, Juin-Jen Chang

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This paper incorporate tax evasion into a one-sector real business cycle (RBC) model to explores the quantitative interrelations between income tax rate and equilibrium (in)determinacy, and income tax rate is endogenously determined in order to balance the government budget. We find that the level of the effective income tax rate is key factor for equilibrium (in)determinacy, instead of the level of income tax rate in a tax evasion economy. Under an economy with tax evasion, the higher income tax rate is not sufficiently to lead to equilibrium indeterminate, it must combine with a necessary condition which is the lower fraction of tax evasion and that can result in agents' optimistic expectations to become self-fulfilling and sunspot fluctuation more likely to occur. On the other hand, an economy with tax evasion can see its macroeconomy become more stabilize, and a higher fraction of income tax evasion may has a stronger stabilizing effect.

Keywords: tax evasion, balanced-budget rule, equlibirium (in)determinacy, effective income tax rate

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Authors: Nareenad Panbun

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The objective is to study the knowledge utilization from the participants of the announcer training program by National Broadcasting and Telecommunications Commission (NBTC). This study is a quantitative research based on surveys and self-answering questionnaires. The population of this study is 100 participants randomly chosen by non-probability sampling method. The results have shown that most of the participants were satisfied with the topics of general knowledge about the broadcasting and television business for 37 people representing 37%, followed by the topics of broadcasting techniques. The legal issues, consumer rights, television business ethics, and credibility of the media are, in addition to the media's role and responsibilities in society, the use of language for successful communication. Therefore, the communication language skills are the most important for all of the trainees and will also build up the image of the broadcasting center.

Keywords: announcer training program, participant, requirements announced, theory of utilization

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Authors: L. E. Mphahama, A. Mushunje, A. Taruvinga

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Although broiler production does not generate any large incomes among the smallholder community, it represents the main source of livelihood and part of nutritional requirement. As a result, market for broiler meat is growing faster than that of any other meat products and is projected to continue growing in the coming decades. However, the implication is that a multitude of factors manipulates transformation of smallholder broiler farmers participating in the mainstream markets. From 217 smallholder broiler farmers, socio-economic and institutional factors in broiler farming were incorporated into Binary model to estimate the probability of broiler farmers’ participation in the mainstream markets within the Maseru district in Lesotho. Of the thirteen (13) predictor variables fitted into the model, six (6) variables (household size, number of years in broiler business, stock size, access to transport, access to extension services and access to market information) had significant coefficients while seven (7) variables (level of education, marital status, price of broilers, poultry association, access to contract, access to credit and access to storage) did not have a significant impact. It is recommended that smallholder broiler farmers organize themselves into cooperatives which will act as a vehicle through which they can access contracts and formal markets. These cooperatives will also enable easy training and workshops for broiler rearing and marketing/markets through extension visits.

Keywords: broiler chicken, mainstream market, Maseru district, participation, smallholder farmers

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Authors: Myungjin Lee, Daegun Han, Jongsung Kim, Soojun Kim, Hung Soo Kim

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Recently, the localized heavy rainfall and typhoons are frequently occurred due to the climate change and the damage is becoming bigger. Therefore, we may need a more accurate prediction of the rainfall and runoff. However, the gauge rainfall has the limited accuracy in space. Radar rainfall is better than gauge rainfall for the explanation of the spatial variability of rainfall but it is mostly underestimated with the uncertainty involved. Therefore, the ensemble of radar rainfall was simulated using error structure to overcome the uncertainty and gauge rainfall. The simulated ensemble was used as the input data of the rainfall-runoff models for obtaining the ensemble of runoff hydrographs. The previous studies discussed about the accuracy of the rainfall-runoff model. Even if the same input data such as rainfall is used for the runoff analysis using the models in the same basin, the models can have different results because of the uncertainty involved in the models. Therefore, we used two models of the SSARR model which is the lumped model, and the Vflo model which is a distributed model and tried to simulate the optimum runoff considering the uncertainty of each rainfall-runoff model. The study basin is located in Han river basin and we obtained one integrated runoff hydrograph which is an optimum runoff hydrograph using the blending methods such as Multi-Model Super Ensemble (MMSE), Simple Model Average (SMA), Mean Square Error (MSE). From this study, we could confirm the accuracy of rainfall and rainfall-runoff model using ensemble scenario and various rainfall-runoff model and we can use this result to study flood control measure due to climate change. Acknowledgements: This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05).

Keywords: radar rainfall ensemble, rainfall-runoff models, blending method, optimum runoff hydrograph

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Authors: Idrissa Kayijuka

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The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

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The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

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Authors: P. Hajek, J. Stejskal

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The aim of this paper is to analyze the ability to identify and acquire knowledge from external sources at the regional level in the Czech Republic. The results show that the most important sources of knowledge for innovative activities are sources within the businesses themselves, followed by customers and suppliers. Furthermore, the analysis of relationships between the objective of the innovative activity and the ability to identify and acquire knowledge implies that knowledge obtained from a) customers aims at replacing outdated products and increasing product quality; b) suppliers aims at increasing capacity and flexibility of production; and c) competing businesses aims at growing market share and increasing the flexibility of production and services. Regions should therefore direct their support especially into development and strengthening of networks within the value chain.

Keywords: knowledge, acquisition, innovative business, Czech republic, region

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Authors: S. O. Oyamakin, A. U. Chukwu

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Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Zoran Barac, Maja Martinovic

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Higher Education Institutions (HEIs) are a special kind of organization, with its unique purpose and combination of actors. From the societal point of view, they are central institutions in the society that are involved in the activities of education, research, and innovation. At the same time, their societal function derives complex relationships between involved actors, ranging from students, faculty and administration, business community and corporate partners, government agencies, to the general public. HEIs are also particularly interesting as objects of governance research because of their unique public purpose and combination of stakeholders. Furthermore, they are the special type of institutions from an organizational viewpoint. HEIs are often described as “loosely coupled systems” or “organized anarchies“ that implies the challenging nature of their governance models. Governance models of HEIs describe roles, constellations, and modes of interaction of the involved actors in the process of strategic direction and holistic control of institutions, taking into account each particular context. Many governance models of the HEIs are primarily based on the balance of power among the involved actors. Besides the actors’ power and influence, leadership style and environmental contingency could impact the governance model of an HEI. Analyzing them through the frameworks of institutional and contingency theories, HEI governance models originate as outcomes of their institutional and contingency adaptation. HEIs tend to fit to institutional context comprised of formal and informal institutional rules. By fitting to institutional context, HEIs are converging to each other in terms of their structures, policies, and practices. On the other hand, contingency framework implies that there is no governance model that is suitable for all situations. Consequently, the contingency approach begins with identifying contingency variables that might impact a particular governance model. In order to be effective, the governance model should fit to contingency variables. While the institutional context creates converging forces on HEI governance actors and approaches, contingency variables are the causes of divergence of actors’ behavior and governance models. Finally, an HEI governance model is a balanced adaptation of the HEIs to the institutional context and contingency variables. It also encompasses roles, constellations, and modes of interaction of involved actors influenced by institutional and contingency pressures. Actors’ adaptation to the institutional context brings benefits of legitimacy and resources. On the other hand, the adaptation of the actors’ to the contingency variables brings high performance and effectiveness. HEI governance models outlined and analyzed in this paper are collegial, bureaucratic, entrepreneurial, network, professional, political, anarchical, cybernetic, trustee, stakeholder, and amalgam models.

Keywords: governance, governance models, higher education institutions, institutional context, situational context

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Authors: Lucky Farha, Martha L. Hall

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The current adaptive clothing brands are limited in numbers and specific categories. This study explores clothing challenges for children with Down syndrome and factors that influence their perception of adaptive clothing brands. Another aim of this study was to explore brands' challenges in the adaptive business and factors that influence their perceptions towards the adaptive market. In order to determine the market barriers affecting adaptive target market needs, the researcher applied Technology Acceptance Model. After interviewing and surveying parents/caregivers having children with Down syndrome and current adaptive brands, the results found education as the significant gap in the adaptive clothing market yet to be overcome. Based on the finding, several recommendations were suggested to improve the current barriers in the adaptive clothing market.

Keywords: adaptive fashion, disability, functional clothing, clothing needs assessment, down syndrome, clothing challenge

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Authors: Abdinasir Mohamed, Ashraf El-Hamalawi, Steven Yeomans, Matthew Frost, Andy Connell

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The evaluation and selection of appropriate software solutions to meet with an organisation’s inherent business requirements can be a problematic software engineering process that if done incorrectly can have a significant, costly and adverse effect on the business and its processes. The aim of this paper is to show the process and evaluation criteria followed to select the right engineering solution for the identified business requirement. The research adopted an action research method within an organisation in the oil and gas industry, which required a solution suitable for conducting stress analysis for soil-pipeline interaction analysis (SPIA). Through the use of the presented software selection and evaluation approach, to capture and measure key requirements, it was possible to determine a suitable software for the organisation. This paper investigates methodologies for selecting software packages, software evaluation techniques, and software evaluation criteria in evaluating software packages before providing an explanation of the developed methodology adopted. The key findings of the study are: (1) that there is a need to create a framework for software selection methodologies, (2) there are no universal selection criteria in the engineering industry, and (3) there is a need to validate the findings by creating an application based on the evaluation technique and evaluation criteria for selecting software packages for the engineering industry. The findings of the study are offered to support organisations in the oil and gas sector improve software selection methodologies for SPIA.

Keywords: software evaluation, end user programs, soil pipeline analysis, software selection

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Authors: Ana Rahma Yuniarti, Ki Moo Lim

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Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

Procedia PDF Downloads 204

Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

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Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

Procedia PDF Downloads 361

Authors: Yungtai Lo

Abstract:

The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

Procedia PDF Downloads 287

Authors: K. Djellabi, M. E. H. Latreche

Abstract:

Induction heating computer simulation is a powerful tool for process design and optimization, induction coil design, equipment selection, as well as education and business presentations. The authors share their vast experience in the practical use of computer simulation for different induction heating and heat treating processes. In this paper deals with mathematical modeling and numerical simulation of induction heating furnaces with axisymmetric geometries. For the numerical solution, we propose finite element methods combined with boundary (FEM) for the electromagnetic model using COMSOL® Multiphysics Software. Some numerical results for an industrial furnace are shown with high frequency.

Keywords: numerical methods, induction furnaces, induction heating, finite element method, Comsol multiphysics software

Procedia PDF Downloads 449

Authors: Anthony Townley

Abstract:

Contract negotiation is fundamental to commercial law practice. For this study, genre and discourse analytical methodology was used to examine the legal negotiation of a Merger & Acquisition (M&A) deal undertaken by legal and business professionals in English across different jurisdictions in Europe. While some of the most delicate negotiations involved in this process were carried on face-to-face or over the telephone, these were generally progressed more systematically – and on the record – in the form of emails, email attachments, and as comments and amendments recorded in successive ‘marked-up’ versions of the contracts under negotiation. This large corpus of textual data was originally obtained by the author, in 2012, for the purpose of doctoral research. For this study, the analysis is particularly concerned with the use of emails and covering letters to exchange legal advice about the negotiations. These two genres help to stabilize and progress the negotiation process and account for negotiation activities. Swalesian analysis of functional Moves and Steps was able to identify structural similarities and differences between these text types and to identify certain salient discursive features within them. The analytical findings also indicate how particular linguistic strategies are more appropriately and more effectively associated with one legal genre rather than another. The concept of intertextuality is an important dimension of contract negotiation discourse and this study also examined how the discursive relationships between the different texts influence the way that texts are constructed. In terms of materials development, the research findings can contribute to more authentic English for Legal & Business Purposes pedagogies for students and novice lawyers and business professionals. The findings can first be used to design discursive maps that provide learners with a coherent account of the intertextual nature of the contract negotiation process. These discursive maps can then function as a framework in which to present detailed findings about the textual and structural features of the text types by applying the Swalesian genre analysis. Based on this acquired knowledge of the textual nature of contract negotiation, the authentic discourse materials can then be used to provide learners with practical opportunities to role-play negotiation activities and experience professional ways of thinking and using language in preparation for the written discourse challenges they will face in this important area of legal and business practice.

Keywords: English for legal and business purposes, discourse analysis, genre analysis, intertextuality, pedagogical materials

Procedia PDF Downloads 149

Authors: Muhammedamin Hussen Saad, Geoffrey Haagler, Onno Omta, Gerben Van Der Velde

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Unfolding chaos and persistent disruptions pose threats to companies’ performance especially in vulnerable settings of SME’s particularly in developing countries. Attention for resilience research in the academic world has increased considerably during the last decade looking at the number of papers published. As we are interested in adding to the understanding of the foundation and development of the concept of resilience, we focus especially on structuring the literature of business resilience in those vulnerable settings. A well-structured systematic search & review procedure was deployed. First, we defined key search terms and applied these to multiple databases (Scopus, Web of Science, Google Scholar, Emerald, and Science Direct). To make our literature search more encompassing, we augmented with co-citation, reference checking including hand searching techniques. The paper offers (1) an overview of SMEs resilience literature from 2000 up to March 2017 comprising 88 articles, and (2) special attention, within that overview, to developing countries. This review concludes that resilience literature is very much diverse in definitions and its measurements, and is inconclusive about its influencing factors. Furthermore, resilience literature is based predominantly on research in the developed world. On the bases of how the concept resilience emerges from the literature we describe distinct features of resilience, give options to extend the theoretical bases of research into resilience and describe concrete ideas for further research.

Keywords: business resilience, systematic review, SMEs, developing countries

Procedia PDF Downloads 172