Search results for: decisions under uncertainty

Authors: Osama Terra, Hatem Hussein

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Calibration of Optical Time Domain Reflectometer (OTDR) is crucial for the accurate determination of loss budget for long optical fiber links. In this paper, the calibration of the attenuation scale of an OTDR using two different techniques is discussed and implemented. The first technique is the external modulation method (EM). A setup is proposed to calibrate an OTDR over a dynamic range of around 15 dB based on the EM method. Afterwards, the OTDR is calibrated using two standard reference fibers (SRF). Both SRF are calibrated using cut-back technique; one of them is calibrated at our home institute (the National Institute of Standards – NIS) while the other at the National Physical Laboratory (NPL) of the United Kingdom to confirm our results. In addition, the parameters contributing the calibration uncertainty are thoroughly investigated. Although the EM method has several advantages over the SRF method, the uncertainties in the SRF method is found to surpass that of the EM method.

Keywords: optical time domain reflectometer, fiber attenuation measurement, OTDR calibration, external source method

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Authors: Jentel Van Havermaet, Geert Van Hove, Elisabeth De Schauwer

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This study re-conceptualizes visual impairment in the interdependent context of James, his family, and allies. Living with a visual impairment is understood as an entanglement of assemblages, dynamics, disablism, systems… We narrated this diffractively into two meaningful events: decisions and processes on (inclusive) education and hinderances in connecting with others. We entangled and (un)raveled lived experiences in assemblages in which the contextualized meaning of visual impairment became more clearly. The contextualized narrative of James interwove complex intra-actions; showed the complexity and contextualization of entangled relationalities.

Keywords: disability studies, contextualization, visual impairment, assemblage, entanglement, lived experiences

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Alexandra Lipitakis, Evangelia A. E. C. Lipitakis

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In this article, a class of e-business strategy planning parameters are introduced and their effect on financial and non-financial performance of e-businesses and organizations is investigated. The relationships between these strategic planning parameters, i.e. Formality, Participation, Sophistication, Thoroughness, Synergy and Cooperation, Entropic Factor, Adaptivity, Uncertainty and Financial and Non-Financial Performance are examined and the directions of these relationships are given. A conceptual model has been constructed and quantitative research methods can be used to test the considered eight hypotheses. In the framework of e-business strategy planning this research study clearly demonstrates how strategic planning components have positive relationships with e-business strategy management and performance.

Keywords: e-business management, e-business model, e-business performance assessments, strategy management methodologies, strategy planning, quantitative methods

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Authors: Zuliziana Suif, Nordila Ahmad, Sengheng Hul

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This paper evaluates the impact of climate change on suspended sediment changes in the Mekong River Basin. In this study, the distributed process-based sediment transport model is used to examine the potential impact of future climate on suspended sediment dynamic changes in the Mekong River Basin. To this end, climate scenarios from two General Circulation Model (GCMs) were considered in the scenario analysis. The simulation results show that the sediment load and concentration shows 0.64% to 69% increase in the near future (2041-2050) and 2.5% to 95% in the far future (2090- 2099). As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in sediment management. Overall, the changes in sediment load and concentration can have a great implication for related sediment management.

Keywords: climate change, suspended sediment, Mekong River Basin, GCMs

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Authors: Kim Michelle Siegling, Thomas Spengler, Sebastian Herzog

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In personnel economics, the choice of a leadership style is about the question of how a supervisor should lead his or her employees in such a way that operational goals are achieved. In this paper, it is assumed that such leadership decisions are made according to the situation. Thus, the optimal or at least a permissible leadership style has to be selected from a set of several possible leadership styles. For this choice, a wide range of models has been developed in the scientific literature, from which the so-called normative decision model will be picked out and focused on. While the original model is based on univocal rules, this paper develops a fuzzy rule system.

Keywords: leadership, leadership styles, rule based systems, fuzzy logic

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Authors: Jiyoung Lee, Andrew D. Gershoff, Jerry Jisang Han

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Most extant research on consumer privacy concerns and their willingness to share personal data has focused on contextual factors (e.g., types of information collected, type of compensation) that lead to consumers’ personal information disclosure. Unfortunately, the literature lacks a clear understanding of how consumers’ incidental psychological needs may influence consumers’ decisions to share their personal information with companies or brands. In this research, we investigate how social exclusion, which is an increasing societal problem, especially since the onset of the COVID-19 pandemic, leads to increased information disclosure intentions for consumers. Specifically, we propose and find that when consumers become socially excluded, their desire for social connection increases, and this desire leads to a greater willingness to disclose their personal information with firms. The motivation to form and maintain interpersonal relationships is one of the most fundamental human needs, and many researchers have found that deprivation of belongingness has negative consequences. Given the negative effects of social exclusion and the universal need to affiliate with others, people respond to exclusion with a motivation for social reconnection, resulting in various cognitive and behavioral consequences, such as paying greater attention to social cues and conforming to others. Here, we propose personal information disclosure as another form of behavior that can satisfy such social connection needs. As self-disclosure can serve as a strategic tool in creating and developing social relationships, those who have been socially excluded and thus have greater social connection desires may be more willing to engage in self-disclosure behavior to satisfy such needs. We conducted four experiments to test how feelings of social exclusion can influence the extent to which consumers share their personal information with brands. Various manipulations and measures were used to demonstrate the robustness of our effects. Through the four studies, we confirmed that (1) consumers who have been socially excluded show greater willingness to share their personal information with brands and that (2) such an effect is driven by the excluded individuals’ desire for social connection. Our findings shed light on how the desire for social connection arising from exclusion influences consumers’ decisions to disclose their personal information to brands. We contribute to the consumer disclosure literature by uncovering a psychological need that influences consumers’ disclosure behavior. We also extend the social exclusion literature by demonstrating that exclusion influences not only consumers’ choice of products but also their decision to disclose personal information to brands.

Keywords: consumer-brand relationship, consumer information disclosure, consumer privacy, social exclusion

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: Ali Al-Zughaibi

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The purpose of this paper is to present a modeling and control of the quarter car active suspension system with unknown mass, unknown time-delay and road disturbance. The objective of designing the controller by deriving a control law to achieve stability of the system and convergence that can considerably improve the ride comfort and road disturbance handling. Thus is accomplished by using Routh-Herwitz criterion and based on some assumptions. A mathematical proof is given to show the ability of the designed controller to ensure stability and convergence of the active suspension system and dispersion oscillation of system with unknown mass, time-delay and road disturbances. Simulations were also performed for controlling quarter car suspension, where the results obtained from these simulations verify the validity of the proposed design.

Keywords: active suspension system, time-delay, disturbance rejection, dynamic uncertainty

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Authors: Jelena Radmanovic

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On 5 March 2020, the International Criminal Court has decided to authorize the investigation into the crimes allegedly committed on the territory of Afghanistan after 1 May 2003. The said determination has raised several controversies, including the recently imposed sanctions by the United States, furthering the United States' long-standing rejection of the authority of the International Criminal Court. The purpose of this research is to address the said investigation in light of its importance for the prevention of impunity in the cases where the perpetrators are nationals of Non-Party States to the Rome Statute. Difficulties that the International Criminal Court has been facing, concerning the establishment of its jurisdiction in those instances where an involved state is not a Party to the Rome Statute, have become the most significant stumbling block undermining the importance, integrity, and influence of the Court. The Situation in Afghanistan raises even further concern, bearing in mind that the Prosecutor’s Request for authorization of an investigation pursuant to article 15 from 20 November 2017 has initially been rejected with the ‘interests of justice’ as an applied rationale. The first method used for the present research is the description of the actual events regarding the aforementioned decisions and the following reactions in the international community, while with the second method – the method of conceptual analysis, the research will address the decisions pertaining to the International Criminal Court’s jurisdiction and will attempt to address the mentioned Decision of 5 March 2020 as an example of good practice and a precedent that should be followed in all similar situations. The research will attempt parsing the reasons used by the International Criminal Court, giving rather greater attention to the latter decision that has authorized the investigation and the points raised by the officials of the United States. It is a find of this research that the International Criminal Court, together with other similar judicial instances (Nuremberg and Tokyo Tribunals, The International Criminal Tribunal for the former Yugoslavia, The International Criminal Tribunal for Rwanda), has presented the world with the possibility of non-impunity, attempting to prosecute those responsible for the gravest of crimes known to the humanity and has shown that such persons should not enjoy the benefits of their immunities, with its focus primarily on the victims of such crimes. Whilst it is an issue that will most certainly be addressed further in the future, with the situations that will be brought before the International Criminal Court, the present research will make an attempt at pointing to the significance of the situation in Afghanistan, the International Criminal Court as such and the international criminal justice as a whole, for the purpose of putting an end to impunity.

Keywords: Afghanistan, impunity, international criminal court, sanctions, United States

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Authors: Sabri Arik

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In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: M. Kamel El-Sayed

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The process of determining the degree of membership for an element to an uncertain concept has been found in many ways, using equivalence and symmetry relations in information systems. In the case of similarity, these methods did not take into account the degree of symmetry between elements. In this paper, we use a new definition for finding the membership based on the degree of symmetry. We provide an example to clarify the suggested methods and compare it with previous methods. This method opens the door to more accurate decisions in information systems.

Keywords: information system, uncertain concept, membership function, similarity relation, degree of similarity

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Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska

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Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.

Keywords: safety climate, occupational health, civil engineering, productivity

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Authors: Farzana Esmailkassam, Usakorn Kunanuvat, Zahraa Mohammed Ali

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Objective: The key barrier in Clozapine treatment of treatment-resistant schizophrenia (TRS) includes frequent bloods draws to monitor neutropenia, the main drug side effect. WBC and ANC monitoring must occur throughout treatment. Accurate WBC and ANC counts are necessary for clinical decisions to halt, modify or continue clozapine treatment. The CSAN Pronto point-of-care (POC) analyzer generates white blood cells (WBC) and absolute neutrophils (ANC) through image analysis of capillary blood. POC monitoring offers significant advantages over central laboratory testing. This study evaluated the performance of the CSAN Pronto against the Beckman DxH900 Hematology laboratory analyzer. Methods: Forty venous samples (EDTA whole blood) with varying concentrations of WBC and ANC as established on the DxH900 analyzer were tested in duplicates on three CSAN Pronto analyzers. Additionally, both venous and capillary samples were concomitantly collected from 20 volunteers and assessed on the CSAN Pronto and the DxH900 analyzer. The analytical performance including precision using liquid quality controls (QCs) as well as patient samples near the medical decision points, and linearity using a mix of high and low patient samples to create five concentrations was also evaluated. Results: In the precision study for QCs and whole blood, WBC and ANC showed CV inside the limits established according to manufacturer and laboratory acceptability standards. WBC and ANC were found to be linear across the measurement range with a correlation of 0.99. WBC and ANC from all analyzers correlated well in venous samples on the DxH900 across the tested sample ranges with a correlation of > 0.95. Mean bias in ANC obtained on the CSAN pronto versus the DxH900 was 0.07× 109 cells/L (95% L.O.A -0.25 to 0.49) for concentrations <4.0 × 109 cells/L, which includes decision-making cut-offs for continuing clozapine treatment. Mean bias in WBC obtained on the CSAN pronto versus the DxH900 was 0.34× 109 cells/L (95% L.O.A -0.13 to 0.72) for concentrations <5.0 × 109 cells/L. The mean bias was higher (-11% for ANC, 5% for WBC) at higher concentrations. The correlations between capillary and venous samples showed more variability with mean bias of 0.20 × 109 cells/L for the ANC. Conclusions: The CSAN pronto showed acceptable performance in WBC and ANC measurements from venous and capillary samples and was approved for clinical use. This testing will facilitate treatment decisions and improve clozapine uptake and compliance.

Keywords: absolute neutrophil counts, clozapine, point of care, white blood cells

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Authors: Saeed Mahjoub Moghadas, Farhad Asadi, Shahed Torkamandi, Hassan Moradi, Mahmood Purgamshidian

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In this paper, we present real-time obstacle avoidance approach for both autonomous and non-autonomous DS-based controllers and also based on dynamical systems (DS) method. In this approach, we can modulate the original dynamics of the controller and it allows us to determine safety margin and different types of DS to increase the robot’s reactiveness in the face of uncertainty in the localization of the obstacle and especially when robot moves very fast in changeable complex environments. The method is validated in simulation and influence of different autonomous and non-autonomous DS such as limit cycles, and unstable DS on this algorithm and also the position of different obstacles in complex environment is explained. Finally, we describe how the avoidance trajectories can be verified through different parameters such as safety factor.

Keywords: limit cycles, nonlinear dynamical system, real time obstacle avoidance, DS-based controllers

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Authors: Ilona Krone

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Maternal smoking during pregnancy increases the risk of perinatal/postnatal negative health outcomes; however, only 1 in 5 pregnant smokers quit smoking. That is a clinical and public health problem. Pregnant smokers have negative paternal support, and higher levels of perceived stress than non-smokers and quitters return to smoking in a stressful situation. A crisis like the COVID-19 outbreak causes significant uncertainty and stress. For pregnant women, additional stress may increase due to concerns for their fetus. Strategies targeting maternal stress and isolation may be particularly useful to prevent negative outcomes for women and their fetuses. Within the post-doctoral study, cooperating with leading specialists, an innovative program for pregnant smokers will be developed. Feasibility for reducing craving, distress intolerance, Covid 19 related stress, and fear in pregnant women in Latvia will be assessed.

Keywords: COVID 19, mindfulness, motivation, pregnancy, smoking cessation

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.

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The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.

Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism

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Authors: M. Zain, Thaung H. Aung, Naveed Anwar

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During the service life, a structure may experience extreme loading conditions. The current study proposes a new methodology that covers the effect of uncertainty involved in gravity loadings on key structural elements of new and complex structures by emphasizing on a very realistic assumption that allows the 'Performance-Based Assessment' to be executed on the structure against the gravity loadings. The methodology does not require the complete removal of an element, instead, it permits the incremental reduction in the capacity of key structural elements and preserves the same stiffness of the member in each case of capacity loss. To demonstrate the application of the proposed methodology, a 13 story complex structure is selected that comprises of a diverse structural configuration. The results ensure the structural integrity against the applied gravity loadings, as well as the effectiveness of the proposed methodology.

Keywords: force-deformation relationship, gravity loading, incremental capacity reduction, multi-linear plastic link element, SAP2000, stiffness

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Authors: Saurabh Agarwal

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This paper attempts to formalise the effect of demographic variables like marital status, gender, occupation and age on the source of investment advice which, in turn, affect the herd behaviour of investors and probability of investment in near future. Further, postulations have been made for most preferred investment option and purpose of saving and source of investment. Impact of theoretical analysis on choice among investment alternatives has also been investigated. The analysis contributes to understanding the different investment choices made by households in India. The insights offered in the paper indirectly contribute in uncovering the various unexplained asset pricing puzzles.

Keywords: portfolio choice, investment decisions, investor’s behaviour, Indian securities market

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Authors: Hyungmo Kim, Hwang Bae, Seok-Kyu Chang, Dong Won Lee, Yung Joo Ko, Sun Rock Choi, Hae Seob Choi, Hyeon Seok Woo, Dong-Jin Euh, Hyeong-Yeon Lee

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Flow mixing characteristics in the wire-wrapped 37-pin rod bundle were measured by using a wire-mesh sensing system for a sodium-cooled fast reactor (SFR). The subchannel flow mixing in SFR core subchannels was an essential characteristic for verification of a core thermal design and safety analysis. A dedicated test facility including the wire-mesh sensor system and tracing liquid injection system was developed, and the conductivity fields at the end of 37-pin rod bundle were visualized in several different flow conditions. These experimental results represented the reasonable agreements with the results of CFD, and the uncertainty of the mixing experiments has been conducted to evaluate the experimental results.

Keywords: core thermal design, flow mixing, a wire-mesh sensor, a wire-wrap effect

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Authors: Keyvanl Yahya

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This paper aims to find a algorithmic structure that affords to predict and explain economic choice behaviour particularly under uncertainty (random policies) by manipulating the prevalent Actor-Critic learning method that complies with the requirements we have been entrusted ever since the field of neuroeconomics dawned on us. Whilst skimming some basics of neuroeconomics that might be relevant to our discussion, we will try to outline some of the important works which have so far been done to simulate choice making processes. Concerning neurological findings that suggest the existence of two specific functions that are executed through Basal Ganglia all the way down to sub-cortical areas, namely 'rewards' and 'beliefs', we will offer a modified version of actor/critic algorithm to shed a light on the relation between these functions and most importantly resolve what is referred to as a challenge for actor-critic algorithms, that is lack of inheritance or hierarchy which avoids the system being evolved in continuous time tasks whence the convergence might not emerge.

Keywords: neuroeconomics, choice behaviour, decision making, reinforcement learning, actor-critic algorithm

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Authors: Juliette Harper, Yu Yang

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Biofuels have gained significant attention recently due to the new regulations and agreements regarding fossil fuels and greenhouse gases being made by countries around the globe. One of the most common types of biofuels is biodiesel, primarily made via the transesterification reaction. We model this nonlinear process in MATLAB using the standard kinetic equations. Then, a nonlinear Model predictive control (NMPC) was developed to regulate this process due to its capability to handle process constraints. The feeding flow uncertainty and kinetic disturbances are further incorporated in the model to capture the real-world operating conditions. The simulation results will show that the proposed NMPC can guarantee the final composition of fatty acid methyl esters (FAME) above the target threshold with a high chance by adjusting the process temperature and flowrate. This research will allow further understanding of NMPC under uncertainties and how to design the computational strategy for larger process with more variables.

Keywords: NMPC, biodiesel, uncertainties, nonlinear, MATLAB

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Authors: Charles A. Khamala

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In 2003, constrained by an absent “rule of law culture” and negative economic growth, the new Kenyan government chose to pursue incremental judicial reforms rather than comprehensive constitutional reforms. President Mwai Kibaki’s first administration’s judicial reform strategy was two pronged. First, to implement unprecedented “radical surgery,” he appointed a new Chief Justice who instrumentally recommended that half the purportedly-corrupt judiciary should be removed by Presidential tribunals of inquiry. Second, the replacement High Court judges, initially, instrumentally-endorsed the “radical surgery’s” administrative decisions removing their corrupt predecessors. Meanwhile, retention of the welfare-reducing Constitution perpetuated declining public confidence in judicial institutions culminating in refusal by the dissatisfied opposition party to petition the disputed 2007 presidential election results, alleging biased and corrupt courts. Fatefully, widespread post-election violence ensued. Consequently, the international community prompted the second Kibaki administration to concede to a new Constitution. Suddenly, the High Court then adopted a non-instrumental interpretation to reject the 2003 “radical surgery.” This paper therefore critically analyzes whether the Kenyan court’s inconsistent interpretations–pertaining to the constitutionality of the 2003 “radical surgery” removing corruption from Kenya’s courts–was predicated on political expediency or human rights principles. If justice “must also seen to be done,” then pursuit of the CJ’s, Judicial Service Commission’s and president’s political or economic interests must be limited by respect for the suspected judges and magistrates’ due process rights. The separation of powers doctrine demands that the dismissed judges should have a right of appeal which entails impartial review by a special independent oversight mechanism. Instead, ignoring fundamental rights, Kenya’s new Supreme Court’s interpretation of another round of vetting under the new 2010 Constitution, ousts the High Court’s judicial review jurisdiction altogether, since removal of judicial corruption is “a constitutional imperative, akin to a national duty upon every judicial officer to pave way for judicial realignment and reformulation.”

Keywords: administrative decisions, corruption, fair hearing, judicial review, (non) instrumental

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Authors: Mirna Diab

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Mobile learning, or M-learning, drives the development of new teaching, learning, and assessment strategies in schools and colleges. With initiatives across states, districts, and institutions, the United States leads mobile learning, significantly impacting education. Since 2010, over 2,3 million American pupils have received their education via mobile devices, demonstrating its rapid expansion. Nonetheless, mobile learning lacks a consistent and explicit definition that helps educators, students, and stakeholders grasp its essence and implement it effectively. This article addresses the need for a revised definition by introducing readers to various mobile learning concepts and understandings. It seeks to raise awareness, clarify, and encourage making well-informed decisions regarding its incorporation as a potent learning tool.

Keywords: mobile learning, mobile pedagogy, mobile technological devices, learner mobility

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Authors: Asma Bentaifa

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This paper investigates the effect of ownership concentration and especially the presence of controlling shareholders on the firm’s payout decisions. Using a sample of 870 French companies during 2007 to 2012, we find that the share of dividends in total payout is negatively correlated with the size of cash flow held by controlling shareholder, and positively related to the divergence between voting rights and cash flow rights of largest shareholders. We also document that controlled firms tend to prefer dividends over repurchases to mitigate conflicts between controlling shareholders and minority shareholders related to the presence of control enhancing devices.

Keywords: ownership, payout policy, dividend, minority expropriation

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Zichun Chu

Abstract:

The issue of tribal poverty has always attracted attentions. Due to social and economic difficulties, the indigenous people's personal development and tribal development have been greatly restricted. Past studies have pointed out that poverty may come from a lack of education. The United Nations Sustainable Development Goals (SDGs) also stated that if we are to solve the poverty problem, providing education widely is an important key. According to the theory of intellectual capital adaptation, “being capable” and “willing to do” are the keys of development. Therefore, we can say that the "ability" and "will" of tribal residents for their tribal development is the core concern of the tribal development. This research was designed to investigate the career choice development model of indigenous tribe people by investigating the current status of human capital, social capital, and cultural capital of tribal residents. This study collected 327 questionnaires (70% of total households) from Truku tribe to answer the research question: Did education help them for job choosing decisions from the aspects of human capital, social capital, and cultural capital in tribal status. This project highlighted the ‘single tribal research approach’ to gain an in-depth understanding of the human capital formed under the unique culture of the tribe (Truku tribe). The results show that the education level of most research participants was high school, very few high school graduates chose to further their education to college level; due to the lack of education of their parents, the social capital was limited to support them for jobs choice, most of them work for labor and service industries; however, their culture capital was comparably rich for works, the sharing culture of Taiwanese indigenous people made their work status stable. The results suggested that we should emphasize more on the development of vocational education based on the tribe’s location and resources. The self-advocacy of indigenous people should be developed so that they would gain more power on making career decisions. This research project is part of a pilot project called “INDIGENOUS PEOPLES, POVERTY, AND DEVELOPMENT,” sponsored by the National Science and Technology Council of Taiwan. If this paper were accepted to present in the 2023 ICIP, it would be lovely if a panel is formed for me and other co-researchers (Chuanju Cheng, Chih-Yuan Weng, and YiXuan Chen), for the audience will be able to get a full picture of this pilot project.

Keywords: career choices, career model, indegenous career development, indigenous education, tribe

Procedia PDF Downloads 66

Authors: Mike Tsionas

Abstract:

The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

Procedia PDF Downloads 332