Search results for: stochastic uncertainty analysis

Authors: Ayedh Alqahtani

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Many construction firms in Saudi Arabia dedicated to building projects agree that the most important factor in the real estate market is the value that they can give to their customer. These firms understand the value of their client in different ways. Value can be defined as the size of the building project in relationship to the cost or the design quality of the materials utilized in finish work or any other features of building rooms such as the bathroom. Value can also be understood as something suitable for the money the client is investing for the new property. A quality tool is required to support companies to achieve a solution for the building project and to understand and manage the customer’s needs. Quality Function Development (QFD) method will be able to play this role since the main difference between QFD and other conventional quality management tools is QFD a valuable and very flexible tool for design and taking into the account the VOC. Currently, organizations and agencies are seeking suitable models able to deal better with uncertainty, and that is flexible and easy to use. The primary aim of this research project is to incorporate customer’s requirements in the conceptual design of construction projects. Towards this goal, QFD is selected due to its capability to integrate the design requirements to meet the customer’s needs. To develop QFD, this research focused upon the contribution of the different (significantly weighted) input factors that represent the main variables influencing QFD and subsequent analysis of the techniques used to measure them. First of all, this research will review the literature to determine the current practice of QFD in construction projects. Then, the researcher will review the literature to define the current customers of residential projects and gather information on customers’ requirements for the design of the residential building. After that, qualitative survey research will be conducted to rank customer’s needs and provide the views of stakeholder practitioners about how these needs can affect their satisfy. Moreover, a qualitative focus group with the members of the design team will be conducted to determine the improvements level and technical details for the design of residential buildings. Finally, the QFD will be developed to establish the degree of significance of the design’s solution.

Keywords: quality function development, construction projects, Saudi Arabia, quality tools

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Authors: Elio El Kahi, Michel Khouri, Olivier Deck, Pierre Rahme, Rasool Mehdizadeh

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Recent developments in civil engineering create multiple interaction problems between the soil and the structure. One of the major problems is the impact of ground movements on buildings. Consequently, managing risks associated with these movements, requires a determination of the different influencing factors and a specific knowledge of their variability/uncertainty. The main purpose of this research is to study the behavior of structures submitted to differential settlement, in order to assess their vulnerability, taking into consideration the different sources of uncertainties. Analytical approach is applied to investigate on one hand the influence of these uncertainties that are related to the soil, and on the other hand the structure stiffness variation with the presence of openings and the movement transmitted between them as related to the origin and shape of the free-field movement. Results reveal the effect of taking these uncertainties into consideration, and specify the dominant and most significant parameters that control the ground movement associated with the Soil-Structure Interaction (SSI) phenomenon.

Keywords: analytical approach, building, damage, differential settlement, soil-structure interaction, uncertainties

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Authors: Mohamad Saab, Sidi Souvi

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In a major nuclear accident, the released fission products (FPs) and the structural materials are likely to influence the transport of iodine in the reactor coolant system (RCS) of a pressurized water reactor (PWR). So far, the thermodynamic data on cesium and silver species used to estimate the magnitude of FP release show some discrepancies, data are scarce and not reliable. For this reason, it is crucial to review the thermodynamic values related to cesium and silver materials. To this end, we have used state-of-the-art quantum chemical methods to compute the formation enthalpies and entropies of AgHMoO₄, CsHMoO₄, and AgCsMoO₄ in the gas phase. Different quantum chemical methods have been investigated (DFT and CCSD(T)) in order to predict the geometrical parameters and the energetics including the correlation energy. The geometries were optimized with TPSSh-5%HF method, followed by a single point calculation of the total electronic energies using the CCSD(T) wave function method. We thus propose with a final uncertainty of about 2 kJmol⁻¹ standard enthalpies of formation of AgHMoO₄, CsHMoO₄, and AgCsMoO₄.

Keywords: nuclear accident, ASTEC code, thermochemical database, quantum chemical methods

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Authors: J. R. Wang, W. Y. Cheng, J. S. Yeh, S. W. Chen, Y. M. Ferng, J. H. Yang, W. S. Hsu, C. Shih

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To understand the risk for dry storage concrete casks in the cask loading, transfer, and storage phase, the purpose of this research is to establish the probabilistic risk assessment (PRA) analysis methodology for dry storage concrete casks by using SAPHIRE 8 code. This analysis methodology is used to perform the study of Taiwan nuclear power plants (NPPs) dry storage system. The process of research has three steps. First, the data of the concrete casks and Taiwan NPPs are collected. Second, the PRA analysis methodology is developed by using SAPHIRE 8. Third, the PRA analysis is performed by using this methodology. According to the analysis results, the maximum risk is the multipurpose canister (MPC) drop case.

Keywords: PRA, dry storage, concrete cask, SAPHIRE

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Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: academic identity, digitized lecture, embodied learning, performance coaching

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Authors: Katharina Fellnhofer

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The more information and knowledge that technology provides, the more important are profoundly human skills like intuition, the skill of using nonconscious information. As our world becomes more complex, shaken by crises, and characterized by uncertainty, time pressure, ambiguity, and rapidly changing conditions, intuition is increasingly recognized as a key human asset. However, due to methodological limitations of sample size or time frame or a lack of real-world or cross-cultural scope, precisely how to measure intuition when facing risks on a nonconscious level remains unclear. In light of the measurement challenge related to intuition’s nonconscious nature, a technique is introduced to measure intuition via hidden images as nonconscious additional information to trigger intuition. This technique has been tested in a within-subject fully online design with 62,721 real-world investment decisions made by 657 subjects in Europe and the United States. Bayesian models highlight the technique’s potential to measure skill at using nonconscious information for conscious decision making. Over the long term, solving the mysteries of intuition and mastering its use could be of immense value in personal and organizational decision-making contexts.

Keywords: cognition, intuition, investment decisions, methodology

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Authors: Julieth Gudo

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The prevalence of corruption in African countries and persisting unsatisfactory distribution by governments of state resources among the citizens are clear indicators of a festering problem. Civil society organisations (CSOs) in Southern African countries, as citizen representatives, have been involved in challenging the ongoing corruption and poor governance in the public sector that have caused tensions between citizens and their governments. In doing so, civil society organisations demand accountability, transparency, and citizen participation in public governance. The problem is that CSOs’ role in challenging governments is not clearly defined in both law and literature. This uncertainty has resulted in an unsatisfying operating and legal environment for CSOs and a strained relationship between themselves and the governments. This paper examines civil society organisations' role in advancing good public governance in South Africa and Zimbabwe. The study will be conducted by means of a literature review and case studies. The state of public governance in Southern Africa will be discussed. The historical role of CSOs in the region of Southern Africa will be explored, followed by their role in public governance in contemporary South Africa and Zimbabwe. The relationship between state and civil society organisations will be examined. Furthermore, the legal frameworks that regulate and authoriseCSOs in their part in challenging poor governance in the public sector will be identified and discussed. Loopholes in such provisions will be identified, and measures that CSOs use to hold those responsible for poor governance accountable for their actions will be discussed, consequently closing the existing gap on the undefined role of CSOs in public governance in Southern Africa. The research demonstrates the need for an enabling operating environment through better cooperation, communication, and the relationship between governments and CSOs, the speedy and effective amendment of existing laws, and the introduction of legal provisions that give express authority to CSOs to challenge poor governance on the part of Southern African governments. Also critical is the enforcement of laws so that those responsible for poor governance and corruption in government are held accountable.

Keywords: civil society organisations, public governance, southern Africa, South Africa, zimbabwe

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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Authors: Flutura Tahiraj, Emine Abdyli

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As a new alternative, mediation is integrated in the legislation of both developed and developing countries in Europe. Various researches in member states of the Council of Europe revealed obstacles, particularly related to the implementation of mediation in criminal matters. They are addressed through several recommendations and non-binding guidelines. However, there is limited empirical research on how the mediation in criminal matters is being implemented in the contexts of developing countries in South-Eastern Europe. Hence, the purpose of this qualitative study is to assess mediation in criminal matters in Kosovo by exploring how the main stakeholders describe the legal basis and implementation process and what it indicates for future practices. The data were gathered through 11 semi-structured interviews with judges, prosecutors, mediation clerks and mediators. Results show that laws and other guidelines that have been introduced since 2008 constitute a solid legal ground that facilitates mediation in criminal matters. The stakeholders are well aware of benefits mediation brings and express their willingness to advance its application to criminal matters. Results also indicate uncertainty among judges and prosecutors regarding the assessment and referral of certain criminal offences to mediation. To address it, specialized trainings, exchange programs and continuous monitoring and evaluation of the process could be supportive.

Keywords: mediation in criminal matters, legislation, implementation of mediation

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Authors: David Lall, Vikram Vishal, P. G. Ranjith

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Numerical modeling of gas production from hydrate-bearing reservoirs requires the solution of various thermal, hydrological, chemical, and mechanical phenomena in a coupled manner. Among the various reservoir properties that influence gas production estimates, the distribution of permeability across the domain is one of the most crucial parameters since it determines both heat transfer and mass transfer. The aspect of permeability in hydrate-bearing reservoirs is particularly complex compared to conventional reservoirs since it depends on the saturation of gas hydrates and hence, is dynamic during production. The dependence of permeability on hydrate saturation is mathematically represented using permeability-reduction models, which are specific to the expected morphology of hydrate accumulations (such as grain-coating or pore-filling hydrates). In this study, we demonstrate the impact of various permeability-reduction models, and consequently, different morphologies of hydrate deposits on the estimates of gas production using depressurization at the reservoir scale. We observe significant differences in produced water volumes and cumulative mass of produced gas between the models, thereby highlighting the uncertainty in production behavior arising from the ambiguity in the prevalent gas hydrate morphology.

Keywords: gas hydrate morphology, multi-scale modeling, THMC, fluid flow in porous media

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Authors: Jeong-Hyun Park, Young-Sik Park, Hyo-Teag Jung

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This paper presents static analysis deployment model for code quality on R&D Projects of SW Development. The proposed model includes the scope of R&D projects and index for static analysis of source code, operation model and execution process, environments and infrastructure system for R&D projects of SW development. There is the static analysis result of pilot project as case study based on the proposed deployment model and environment, and strategic considerations for success operation of the proposed static analysis deployment model for R&D Projects of SW Development. The proposed static analysis deployment model in this paper will be adapted and improved continuously for quality upgrade of R&D projects, and customer satisfaction of developed source codes and products.

Keywords: static analysis, code quality, coding rules, automation tool

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Authors: Tammeen Siraj, Wenxing Zhou, Terry Huang, Mohammad Al-Amin

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The high resolution inline inspection (ILI) tool is used extensively in the pipeline industry to identify, locate, and measure metal-loss corrosion anomalies on buried oil and gas steel pipelines. Corrosion anomalies may occur singly (i.e. individual anomalies) or as clusters (i.e. a colony of corrosion anomalies). Although the ILI technology has advanced immensely, there are measurement errors associated with the sizes of corrosion anomalies reported by ILI tools due limitations of the tools and associated sizing algorithms, and detection threshold of the tools (i.e. the minimum detectable feature dimension). Quantifying the measurement error in the ILI data is crucial for corrosion management and developing maintenance strategies that satisfy the safety and economic constraints. Studies on the measurement error associated with the length of the corrosion anomalies (in the longitudinal direction of the pipeline) has been scarcely reported in the literature and will be investigated in the present study. Limitations in the ILI tool and clustering process can sometimes cause clustering error, which is defined as the error introduced during the clustering process by including or excluding a single or group of anomalies in or from a cluster. Clustering error has been found to be one of the biggest contributory factors for relatively high uncertainties associated with ILI reported anomaly length. As such, this study focuses on developing a consistent and comprehensive framework to quantify the measurement errors in the ILI-reported anomaly length by comparing the ILI data and corresponding field measurements for individual and clustered corrosion anomalies. The analysis carried out in this study is based on the ILI and field measurement data for a set of anomalies collected from two segments of a buried natural gas pipeline currently in service in Alberta, Canada. Data analyses showed that the measurement error associated with the ILI-reported length of the anomalies without clustering error, denoted as Type I anomalies is markedly less than that for anomalies with clustering error, denoted as Type II anomalies. A methodology employing data mining techniques is further proposed to classify the Type I and Type II anomalies based on the ILI-reported corrosion anomaly information.

Keywords: clustered corrosion anomaly, corrosion anomaly assessment, corrosion anomaly length, individual corrosion anomaly, metal-loss corrosion, oil and gas steel pipeline

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

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Authors: Mohammad Molavi, Mohsen Nourai

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The emancipation of the Muslim nation from the numerous problems and achieving to the decent position is one of the old desires of Muslim. Increasing efforts to realize this wish based on religious and rational teachings is the main goal for Muslim reformist. Almost all scholars relying on the Qur'an teaching emphasize on the significant role of Islamic Unity for the revival of Islamic civilization. But their methods for achieving to the Islamic Unity are not so clear. Generally speaking, failure to provide specific solutions, uncertainty in the face of universal literature in politics and governance, and etc. are some of the challenges facing the Islamic Unity.This paper via the descriptive-analytical method and by focusing on theoretical aspects of the subject has attempted to analyze Imam Khomeini points of view. Research findings show that there are several significant differences between Imam Khomeini's idea of Islamic Unity and ideas like 'Pan-Turkism', 'Pan-Arabism' and so on. Some of Imam Khomeini's principles in this regard are as follow: Strategic approach to unity, relying on juridical certain and systematic attitude, comprehensive approach, Holistic, rationality, and moderation. So, there is no any generality speaking or ambiguity in Khomeini's thought.

Keywords: Qur'an, Imam Khomeini, islamic unity, islamic nation, islamic political thought

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Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

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Authors: Mrigakshi Das

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The private sector investments and quantum of money required in this sector critically hinges on the financial risk and returns the sector offers to providers of capital. Therefore, it becomes important to understand financial performance of hospitals. Financial Analysis is useful for decision makers in a variety of settings. Consider the small proprietary hospitals, say, Physicians Clinic. The managers of such clinic need the information that financial statements provide. Attention to Financial Statements of healthcare Organizations can provide answers to questions like: How are they doing? What is their rate of profit? What is their solvency and liquidity position? What are their sources and application of funds? What is their Operational Efficiency? The researcher has studied Financial Statements of 5 Private Healthcare Organizations in Guwahati City.

Keywords: not-for-profit organizations, financial analysis, ratio analysis, profitability analysis, liquidity analysis, operational efficiency, capital structure analysis

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Authors: Chia-li Wang

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The surge of service and commerce platforms, such as e-commerce and internet-of-things, have rapidly changed our lives. How to avoid the congestion and get the job done in the platform is now a common problem that many people encounter every day. This requires platform users to make decisions about when to enter the platform. To that end, we investigate the strategic entering time of a simple platform containing random numbers of buyers and sellers of some item. Upon a trade, the buyer and the seller gain respective profits, yet they pay the cost of waiting in the platform. To maximize their expected payoffs from trading, both buyers and sellers can choose their entering times. This creates an interesting and practical framework of a game that is played among buyers, among sellers, and between them. That is, a strategy employed by a player is not only against players of its type but also a response to those of the other type, and, thus, a strategy profile is composed of strategies of buyers and sellers. The players' best response, the Nash equilibrium (NE) strategy profile, is derived by a pair of differential equations, which, in turn, are used to establish its existence and uniqueness. More importantly, its structure sheds valuable insights of how the entering strategy of one side (buyers or sellers) is affected by the entering behavior of the other side. These results provide a base for the study of dynamic pricing for stochastic demand-supply imbalances. Finally, comparisons between the social welfares (the sum of the payoffs incurred by individual participants) obtained by the optimal strategy and by the NE strategy are conducted for showing the efficiency loss relative to the socially optimal solution. That should help to manage the platform better.

Keywords: double-sided queue, non-cooperative game, nash equilibrium, price of anarchy

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control

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Authors: Giovanni Masala, Stefania Marica

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Forecasting electricity load plays a crucial role regards decision making and planning for economical purposes. Besides, in the light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Empirical data about electricity load highlights a clear seasonal behavior (higher load during the winter season), which is partly due to climatic effects. We also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires non-linear regression and Fourier series while we will investigate the stochastic component through econometrical tools. The calibration of the parameters’ model will be performed by using data coming from the Italian market in a 6 year period (2007- 2012). Then, we will perform a Monte Carlo simulation in order to compare the simulated data respect to the real data (both in-sample and out-of-sample inspection). The reliability of the model will be deduced thanks to standard tests which highlight a good fitting of the simulated values.

Keywords: ARMA-GARCH process, electricity load, fitting tests, Fourier series, Monte Carlo simulation, non-linear regression

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: D. Beziakina, E. Bulgakova

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This study continues the research on Tuvinian intonation and presents a general cross-dialect analysis of intonation of Tuvinian declarative utterances, specifically the character of the tone movement in order to test the hypothesis about the prevalence of level tone in some Tuvinian dialects. The results of the analysis of basic pitch characteristics of Tuvinian speech (in general and in comparison with two other Turkic languages - Uzbek and Azerbaijani) are also given in this paper. The goal of our work was to obtain the ranges of pitch parameter values typical for Tuvinian speech. Such language-specific values can be used in speaker identification systems in order to get more accurate results of ethnic speech analysis. We also present the results of a cross-dialect analysis of declarative intonation in the poorly studied Tuvinian language.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

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Authors: Maya Jaber

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In today's ever-changing world, organizational leaders will need to transform their organizations to meet the demands they face from employees, consumers, local and federal governments, and the global market. Change agents and leaders will need a new paradigm of thinking for creative problem solving and innovation in a time of uncertainty. A new framework that is developed from Design Science Research foundations with holistic design thinking methodologies (HTDM) and action research approaches has been developed through Dr. Jaber’s research. It combines these philosophies into a three-step process that can be utilized in practice for any sustainability, change, or project management applications. This framework was developed to assist in the pedagogy for the implementation of her holistic strategy formalized framework Integral Design Thinking (IDT). Her work focuses on real world application for the streamlining and adoption of initiatives into organizational culture transformation. This paper will discuss the foundations of this philosophy and the methods for utilization in practice developed in Dr. Jaber's research.

Keywords: design science research, action research, critical thinking, design thinking, organizational transformation, sustainability management, organizational culture change

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Authors: Abderafi Charki, David Bigaud

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The aim of this oral speach is to present the PVMODREL© (PhotoVoltaic MODule RELiability) new software developed in the University of Angers. This new tool permits us to evaluate the lifetime and reliability of a PV module whatever its geographical location and environmental conditions. The electrical power output of a PV module decreases with time mainly as a result of the effects of corrosion, encapsulation discoloration, and solder bond failure. The failure of a PV module is defined as the point where the electrical power degradation reaches a given threshold value. Accelerated life tests (ALTs) are commonly used to assess the reliability of a PV module. However, ALTs provide limited data on the failure of a module and these tests are expensive to carry out. One possible solution is to conduct accelerated degradation tests. The Wiener process in conjunction with the accelerated failure time model makes it possible to carry out numerous simulations and thus to determine the failure time distribution based on the aforementioned threshold value. By this means, the failure time distribution and the lifetime (mean and uncertainty) can be evaluated. An example using the damp heat test is shown to demonstrate the usefulness PVMODREL.

Keywords: lifetime, reliability, PV Module, accelerated life testing, accelerated degradation testing

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Authors: Francesca Nardi, Kashish Aneja, Katherine Ginsbach

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The COVID-19 pandemic has demonstrated both a need for evidence-based and rights-based public health policy and how challenging it can be to make effective decisions with limited information, evidence, and data. The O’Neill Institute, in conjunction with several partners, has been working since the beginning of the pandemic to collect, analyze, and distribute critical data on public health policies enacted in response to COVID-19 around the world in the COVID-19 Law Lab. Well-designed laws and policies can help build strong health systems, implement necessary measures to combat viral transmission, enforce actions that promote public health and safety for everyone, and on the individual level have a direct impact on health outcomes. Poorly designed laws and policies, on the other hand, can fail to achieve the intended results and/or obstruct the realization of fundamental human rights, further disease spread, or cause unintended collateral harms. When done properly, laws can provide the foundation that brings clarity to complexity, embrace nuance, and identifies gaps of uncertainty. However, laws can also shape the societal factors that make disease possible. Law is inseparable from the rest of society, and COVID-19 has exposed just how much laws and policies intersects all facets of society. In the COVID-19 context, evidence-based and well-informed law and policy decisions—made at the right time and in the right place—can and have meant the difference between life or death for many. Having a solid evidentiary base of legal information can promote the understanding of what works well and where, and it can drive resources and action to where they are needed most. We know that legal mechanisms can enable nations to reduce inequities and prepare for emerging threats, like novel pathogens that result in deadly disease outbreaks or antibiotic resistance. The collection and analysis of data on these legal mechanisms is a critical step towards ensuring that legal interventions and legal landscapes are effectively incorporated into more traditional kinds of health science data analyses. The COVID-19 Law Labs see a unique opportunity to collect and analyze this kind of non-traditional data to inform policy using laws and policies from across the globe and across diseases. This global view is critical to assessing the efficacy of policies in a wide range of cultural, economic, and demographic circumstances. The COVID-19 Law Lab is not just a collection of legal texts relating to COVID-19; it is a dataset of concise and actionable legal information that can be used by health researchers, social scientists, academics, human rights advocates, law and policymakers, government decision-makers, and others for cross-disciplinary quantitative and qualitative analysis to identify best practices from this outbreak, and previous ones, to be better prepared for potential future public health events.

Keywords: public health law, surveillance, policy, legal, data

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Truong Nguyen Luan Vu, Le Hieu Giang, Le Linh

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The FOPI controller is proposed based on the main properties of the decoupling control scheme, as well as the fractional calculus. By using the simplified decoupling technique, the transfer function of decoupled apparent process is firstly separated into a set of n equivalent independent processes in terms of a ratio of the diagonal elements of original open-loop transfer function to those of dynamic relative gain array and the fraction – order PI controller is then developed for each control loops due to the Bode’s ideal transfer function that gives the desired fractional closed-loop response in the frequency domain. The simulation studies were carried out to evaluate the proposed design approach in a fair compared with the other existing methods in accordance with the structured singular value (SSV) theory that used to measure the robust stability of control systems under multiplicative output uncertainty. The simulation results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.

Keywords: ideal transfer function of bode, fractional calculus, fractional order proportional integral (FOPI) controller, decoupling control system

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Authors: Leander Van Neste, Kirk Wojno

Abstract:

The innate immune system reacts to foreign insult in several unique ways, one of which is phagocytosis of perceived threats such as cancer, bacteria, and viruses. The goal of this study was to look for evidence of phagocytosed RNA from tumor cells in circulating monocytes. While all monocytes possess phagocytic capabilities, the non-classical CD14+/FCGR3A+ monocytes and the intermediate CD14++/FCGR3A+ monocytes most actively remove threatening ‘external’ cellular materials. Purified CD14-positive monocyte samples from fourteen patients recently diagnosed with clinically localized prostate cancer (PCa) were investigated by single-cell RNA sequencing using the 10X Genomics protocol followed by paired-end sequencing on Illumina’s NovaSeq. Similarly, samples were processed and used as controls, i.e., one patient underwent biopsy but was found not to harbor prostate cancer (benign), three young, healthy men, and three men previously diagnosed with prostate cancer that recently underwent (curative) radical prostatectomy (post-RP). Sequencing data were mapped using 10X Genomics’ CellRanger software and viable cells were subsequently identified using CellBender, removing technical artifacts such as doublets and non-cellular RNA. Next, data analysis was performed in R, using the Seurat package. Because the main goal was to identify differences between PCa patients and ‘control’ patients, rather than exploring differences between individual subjects, the individual Seurat objects of all 21 patients were merged into one Seurat object per Seurat’s recommendation. Finally, the single-cell dataset was normalized as a whole prior to further analysis. Cell identity was assessed using the SingleR and cell dex packages. The Monaco Immune Data was selected as the reference dataset, consisting of bulk RNA-seq data of sorted human immune cells. The Monaco classification was supplemented with normalized PCa data obtained from The Cancer Genome Atlas (TCGA), which consists of bulk RNA sequencing data from 499 prostate tumor tissues (including 1 metastatic) and 52 (adjacent) normal prostate tissues. SingleR was subsequently run on the combined immune cell and PCa datasets. As expected, the vast majority of cells were labeled as having a monocytic origin (~90%), with the most noticeable difference being the larger number of intermediate monocytes in the PCa patients (13.6% versus 7.1%; p<.001). In men harboring PCa, 0.60% of all purified monocytes were classified as harboring PCa signals when the TCGA data were included. This was 3-fold, 7.5-fold, and 4-fold higher compared to post-RP, benign, and young men, respectively (all p<.001). In addition, with 7.91%, the number of unclassified cells, i.e., cells with pruned labels due to high uncertainty of the assigned label, was also highest in men with PCa, compared to 3.51%, 2.67%, and 5.51% of cells in post-RP, benign, and young men, respectively (all p<.001). It can be postulated that actively phagocytosing cells are hardest to classify due to their dual immune cell and foreign cell nature. Hence, the higher number of unclassified cells and intermediate monocytes in PCa patients might reflect higher phagocytic activity due to tumor burden. This also illustrates that small numbers (~1%) of circulating peripheral blood monocytes that have interacted with tumor cells might still possess detectable phagocytosed tumor RNA.

Keywords: circulating monocytes, phagocytic cells, prostate cancer, tumor immune response

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Authors: Eliane Abdo

Abstract:

Small and medium sized firms “SMEs” play essential role in the countries’ economic development mainly in terms of production, employment and equitable distribution of income. For innovative SMEs, the investment in the human capital and in research and development are crucial to survive in a competitive environment. In this paper we perform a literature review to underline the financing difficulties and constraints which innovative SMEs face while investing in intangible assets: not only when defining amount of the investments but also while choosing its financing methods. Literature review revealed that in order to finance their intangible assets, SMEs rely in first on their internal financing: the availability of internal cash flows can then determine their investment’s decision. Moreover SMEs face difficulties to finance their intangibles by financial debts due to the uncertainty of future cash flow and the absence of physical guarantees; they will therefore go for the issuance of new shares as a second choice, since innovative companies have high opportunity of growth that attract new shareholders.

Keywords: small and medium sized firms, capital structure, intangible investment, financial constraints

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Authors: Wajeehah Aayeshah, Joy Higgs

Abstract:

The term “transcending pedagogies” has been created to refer to teaching and learning strategies that transcend the mode of student enrolment, the needs of different students, and different learning spaces. The value of such pedagogies in the current arena when learning spaces, technologies and preferences are more volatile than ever before, is a key focus of this paper. The paper will examine current and emerging pedagogies that transcend the learning spaces and enrollment modes of on campus, distance, virtual and workplace learning contexts. A further point of interest is how academics in professional and higher education settings interpret and implement pedagogies in the current global conversation space and re-creation of higher education. This study questioned how the notion and practice of transcending pedagogies enables us to re-imagine and reshape university curricula. It explored the nature of teaching and learning spaces and those professional and higher education (current and emerging) pedagogies that can be implemented across these spaces. We set out to identify how transcending pedagogies can assist students in learning to deal with complexity, uncertainty and change in the practice worlds and better appeal to students who are making decisions on where to enrol. The data for this study was collected through in-depth interviews and focus groups with academics and policy makers within academia.

Keywords: Transcending Pedagogies, teaching and learning strategies, learning spaces, pedagogies

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