Search results for: decision matrix

Authors: Xiaoqian Cheng, Jon Kleppe, Ole Torsaeter

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One objective of this work is to analyze the effects of surfactant properties (viscosity, concentration, and adsorption) on surfactant enhanced oil recovery at laboratory scale. The other objective is to obtain the functional relationships between surfactant properties and the ultimate oil recovery and oil recovery rate. A core is cut into two parts from the middle to imitate the matrix with a horizontal fracture. An injector and a producer are at the left and right sides of the fracture separately. The middle slice of the core is used as the model in this paper, whose size is 4cm x 0.1cm x 4.1cm, and the space of the fracture in the middle is 0.1 cm. The original properties of matrix, brine, oil in the base case are from Ekofisk Field. The properties of surfactant are from literature. Eclipse is used as the simulator. The results are followings: 1) The viscosity of surfactant solution has a positive linear relationship with surfactant oil recovery time. And the relationship between viscosity and oil production rate is an inverse function. The viscosity of surfactant solution has no obvious effect on ultimate oil recovery. Since most of the surfactant has no big effect on viscosity of brine, the viscosity of surfactant solution is not a key parameter of surfactant screening for surfactant flooding in fractured reservoirs. 2) The increase of surfactant concentration results a decrease of oil recovery rate and an increase of ultimate oil recovery. However, there are no functions could describe the relationships. Study on economy should be conducted because of the price of surfactant and oil. 3) In the study of surfactant adsorption, assume that the matrix wettability is changed to water-wet when the surfactant adsorption is to the maximum at all cases. And the ratio of surfactant adsorption and surfactant concentration (Cads/Csurf) is used to estimate the functional relationship. The results show that the relationship between ultimate oil recovery and Cads/Csurf is a logarithmic function. The oil production rate has a positive linear relationship with exp(Cads/Csurf). The work here could be used as a reference for the surfactant screening of surfactant enhanced oil recovery from fractured reservoirs. And the functional relationships between surfactant properties and the oil recovery rate and ultimate oil recovery help to improve upscaling methods.

Keywords: fractured reservoirs, surfactant adsorption, surfactant concentration, surfactant EOR, surfactant viscosity

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Nassim Bessaad, Qilian Bao, Zhao Jiangkang

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The fiber optics gyroscope in the strap-down inertial navigation system (FOG-SINS) suffers from precision degradation due to the influence of random errors. In this work, an enhanced Allan variance (AV) stochastic modeling method combined with discrete wavelet transform (DWT) for signal denoising is implemented to estimate the random process in the FOG signal. Furthermore, we devise a measurement-based iterative adaptive Sage-Husa nonlinear filter with augmented states to integrate a star tracker sensor with SINS. The proposed filter adapts the measurement noise covariance matrix based on the available data. Moreover, the enhanced stochastic modeling scheme is invested in tuning the process noise covariance matrix and the augmented state Gauss-Markov process parameters. Finally, the effectiveness of the proposed filter is investigated by employing the collected data in laboratory conditions. The result shows the filter's improved accuracy in comparison with the conventional Kalman filter (CKF).

Keywords: inertial navigation, adaptive filtering, star tracker, FOG

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

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In 1994, Korea experienced a national tragedy of Seongsu Bridge collapse. The accident was severe enough to alert governmental officers to the problem of existing management policy for national infrastructures. As a result, government legislated the ‘Guidelines for the safety inspection and test of infrastructure’ which have been utilized as the primary tool to make decision for the maintenance and rehabilitation of infrastructure for last twenty years. Although it is clear that the guideline established a basics how to evaluate and manage the condition of infrastructures in systematic manner, it is equally clear that the guideline needs improvements in order to obtain reasonable investment decisions for budget allocation. Because its inspection and evaluation procedures mainly focused on the structural condition of infrastructures, it was hard to make decision when the infrastructures were in same level of structural condition. In addition, it did not properly reflect various aspects of infrastructures such as performance, public demand, capacity, etc., which were more valuable to public. Regardless of the importance, these factors were commonly neglected in governmental decision-making process, because there factors were somewhat subjective and difficult to quantify in rational manner. Thus, this study proposes a framework to properly evaluate the serviceability indicators using AHP and Fuzzy approach. The framework is expected to assist governmental agency in establishing effective investment strategies for budget planning.

Keywords: infrastructure, evaluation, serviceability, fuzzy

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Wei Wang, Yuan Hu

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Epoxy resins (EP), one of the most important thermosetting polymers, is widely applied in various fields due to its desirable properties, such as excellent electrical insulation, low shrinkage, outstanding mechanical stiffness, satisfactory adhesion and solvent resistance. However, like most of the polymeric materials, EP has the fatal drawbacks including inherent flammability and high yield of toxic smoke, which restricts its application in the fields requiring fire safety. So, it is still a challenge and an interesting subject to develop new flame retardants which can not only remarkably improve the flame retardancy, but also render modified resins low toxic gases generation. In recent work, polymer nanocomposites based on nanohybrids that contain two or more kinds of nanofillers have drawn intensive interest, which can realize performance enhancements. The realization of previous hybrids of carbon nanotubes (CNTs) and molybdenum disulfide provides us a novel route to decorate layered double hydroxide (LDH) nanosheets on the surface of β-FeOOH nanorods; the deposited LDH nanosheets can fill the network and promote the work efficiency of β-FeOOH nanorods. Moreover, the synergistic effects between LDH and β-FeOOH can be anticipated to have potential applications in reducing fire hazards of EP composites for the combination of condense-phase and gas-phase mechanism. As reported, β-FeOOH nanorods can act as a core to prepare hybrid nanostructures combining with other nanoparticles through electrostatic attraction through layer-by-layer assembly technique. In this work, LDH nanosheets wrapped β-FeOOH nanorods (LDH-β-FeOOH) hybrids was synthesized by a facile method, with the purpose of combining the characteristics of one dimension (1D) and two dimension (2D), to improve the fire resistance of epoxy resin. The hybrids showed a well dispersion in EP matrix and had no obvious aggregation. Thermogravimetric analysis and cone calorimeter tests confirmed that LDH-β-FeOOH hybrids into EP matrix with a loading of 3% could obviously improve the fire safety of EP composites. The plausible flame retardancy mechanism was explored by thermogravimetric infrared (TG-IR) and X-ray photoelectron spectroscopy. The reasons were concluded: condense-phase and gas-phase. Nanofillers were transferred to the surface of matrix during combustion, which could not only shield EP matrix from external radiation and heat feedback from the fire zone, but also efficiently retard transport of oxygen and flammable pyrolysis.

Keywords: fire hazards, toxic gases, self-assembly, epoxy

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Authors: Kalandi Charan Pradhan

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In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

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Authors: Wenbo Yu, Zihao Yuan, Zhipeng Guo, Shoumei Xiong

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Under different slow shot speeds in vacuum assisted high pressure die casting (VHPDC) process, plate-shaped specimens of hypereutectic A390 aluminum alloy were produced. According to the results, the vacuum pressure inside the die cavity increased linearly with the increasing slow shot speed at the beginning of mold filling. Meanwhile, it was found that the tensile properties of vacuum die castings were deteriorated by the porosity content. In addition, the average primary Si size varies between 14µm to 23µm, which has a binary functional relationship with the slow shot speeds. Due to the vacuum effect, the castings were treated by T6 heat treatment. After heat treatment, microstructural morphologies revealed that needle-shaped and thin-flaked eutectic Si particles became rounded while Al2Cu dissolved into α-Al matrix. For the as-received sample in-situ tensile test, microcracks firstly initiate at the primary Si particles and propagated along Al matrix with a transgranular fracture mode. In contrast, for the treated sample, the crack initiated at the Al2Cu particles and propagated along Al grain boundaries with an intergranular fracture mode. In-situ three bending test, microcracks firstly formed in the primary Si particles for both samples. Subsequently, the cracks between primary Si linked along Al grain boundaries in as received sample. In contrast, the cracks in primary Si linked through the solid lines in Al matrix. Furthermore, the fractography revealed that the fracture mechanism has evolved from brittle transgranular fracture to a fracture mode with many dimples after heat treatment.

Keywords: A390 aluminum, vacuum assisted high pressure die casting, heat treatment, mechanical properties

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Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

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This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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Authors: Rakesh C. Mathad, G. Y. Lokesh, Basavegowda

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In agriculture using quality seeds of improved varieties is very important to ensure higher productivity thereby food security and sustainability. To ensure good productivity, seeds should have characters as described by the breeder. To know whether the characters as described by the breeder are expressing in a variety such as genuineness or genetic purity, field grow out test (GOT) is done. In pigeon pea which is long durational crop, conducting a GOT may take very long time and expensive also. Since in pigeon pea flower character is a most distinguishing character from the contaminants, conducting a field grow out test require 120-130 days or till flower emergence, which may increase cost of storage and seed production. This will also delay the distribution of seed inventory to the pigeon pea growing areas. In this view during 2014-15 with financial support of Govt. of Karnataka, India, a project to develop a molecular genetic test for newly developed variety of pigeon pea cv.TS3R was commissioned at Seed Unit, UAS, Raichur. A molecular test was developed with the help SSR markers to identify pure variety from possible off types in newly released pigeon pea variety TS3R. In the investigation, 44 primer pairs were screened to identify the specific marker associated with this variety. Pigeon pea cv. TS3R could be clearly identified by using the primer CCM 293 based on the banding pattern resolved on gel electrophoresis and PCR reactions. However some of the markers like AHSSR 46, CCM 82 and CCM 57 can be used to test other popular varieties in the region like Asha, GRG-811 and Maruti respectively. Further to develop this in to a lab test, the seed sample size was standardized to 200 seeds and a grow out matrix was developed. This matrix was used to sample 12 days old leaves to extract DNA. The lab test results were validated with actual field GOT test results and found variations within the acceptable limit of 1%. This molecular method can now be employed to test the genetic purity in pigeon pea cv TS3R which reduces the time and can be a cheaper alternative method for field GOT.

Keywords: genuineness, grow-out matrix, molecular genetic purity, SSR markers

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

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Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

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Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: decision support system, event-sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine

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Authors: Madhan Vinu, Yue-Chun Jiang, Yi-Feng Lin, Chia-Her Lin

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An effective approach to enhance the ethanol/water pervaporation of mixed matrix membranes prepared from three microporous aluminium based metal-organic frameworks (MOFs), [Al(OH)(BPDC)] (DUT-5), [Al(OH)(NDC)] (DUT-4) and [Al(OH)(BzPDC)] (CAU-8) have been synthesized by employing solvothermal reactions. Interestingly, all Al-MOFs showed attractive surface area with microporous 12.3, 10.2 and 8.0 Å for DUT-5, DUT-4 and CAU-8 MOFs which are confirmed through N₂ gas sorption measurements. All the microporous compounds are highly stable as confirmed by thermogravimetric analysis and temperature-dependent powder X-ray diffraction measurements. Furthermore, the synthesized microporous MOF particles of DUT-5, DUT-4, and CAU-8 were successfully incorporated into biological chitosan (CS) membranes to form DUT-5@CS, DUT-4@CS, and CAU-8@CS membranes. The different MOF loadings such as 0.1, 0.15, and 0.2 wt% in CS networks have been prepared, and the same were used to separate mixtures of water and ethanol at 25ºC in the pervaporation process. In particular, when 0.15 wt% of DUT-5 was loaded, MOF@CS membrane displayed excellent permeability and selectivity in ethanol/water separation than that of the previous literature. These CS based membranes separation through functionalized microporous MOFs reveals the key governing factors that are essential for designing novel MOF membranes for bioethanol purification.

Keywords: metal-organic framework, microporous materials, separation, chitosan membranes

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Authors: Ju-Hong Lee, Ching-Wei Liao

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An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

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Authors: Ghussoun Al-Jeiroudi

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Stochastic programming is one of the powerful technique which is used to solve real-life problems. Hence, the data of real-life problems is subject to significant uncertainty. Uncertainty is well studied and modeled by stochastic programming. Each day, problems become bigger and bigger and the need for a tool, which does deal with large scale problems, increase. Interior point method is a perfect tool to solve such problems. Interior point method is widely employed to solve the programs, which arise from stochastic programming. It is an iterative technique, so it is required a starting point. Well design starting point plays an important role in improving the convergence speed. In this paper, we propose a starting point for interior point method for multistage stochastic programming. Usually, the optimal solution of stage k+1 is used as starting point for the stage k. This point has the advantage of being close to the solution of the current program. However, it has a disadvantage; it is not in the feasible region of the current program. So, we suggest to take this point and modifying it. That is by adding to it a vector in the null space of the matrix of the unchanged constraints because the solution will change only in the null space of this matrix.

Keywords: interior point methods, stochastic programming, null space, starting points

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

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Authors: R. S. Sheu, H. Usman, M. S. Lawal

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Takagi-Sugeno (T-S) fuzzy model based control of a load frequency deviation in a single machine with limit nonlinearity on power coefficient is presented in the paper. Two T-S fuzzy rules with only rotor angle variable as input in the premise part, and linear state space models in the consequent part involving characteristic matrices determined from limits set on the power coefficient constant are formulated, state feedback control gains for closed loop control was determined from the formulated Linear Matrix Inequality (LMI) with eigenvalue optimization scheme for asymptotic and exponential stability (speed of esponse). Numerical evaluation of the closed loop object was carried out in Matlab. Simulation results generated of both the open and closed loop system showed the effectiveness of the control scheme in maintaining load frequency stability.

Keywords: T-S fuzzy model, state feedback control, linear matrix inequality (LMI), frequency deviation control

Procedia PDF Downloads 385

Authors: J. Niyitegeka, G. Nshimirimana, A. Silverstein, J. Odhiambo, Y. Lin, T. Nkurunziza, R. Riviello, S. Rulisa, P. Banguti, H. Magge, M. Macharia, J. P. Dushime, R. Habimana, B. Hedt-Gauthier

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In low-resource settings, women needing an emergency cesarean section experiences various delays in both reaching and receiving care that is often linked to poor neonatal outcomes. In this study, we quantified different measures of delays and assessed the association between these delays and neonatal outcomes at three rural district hospitals in Rwanda. This retrospective study included 441 neonates and their mothers who underwent emergency cesarean sections in 2015 at Butaro, Kirehe and Rwinkwavu District Hospitals. Four possible delays were measured: Time from start of labor to district hospital admission, travel time from a health center to the district hospital, time from admission to surgical incision, and time from the decision for the emergency cesarean section to surgical incision. Neonatal outcomes were categorized as unfavorable (APGAR < 7 or death) and favorable (APGAR ≥ 7). We assessed the relationship between each type of delay and neonatal outcomes using multivariate logistic regression. In our study, 38.7% (108 out of 279) of neonates’ mothers labored for 12 to 24 hours before hospital admission and 44.7% (159 of 356) of mothers were transferred from health centers that required 30 to 60 minutes of travel time to reach the district hospital. 48.1% (178 of 370) of caesarean sections started within five hours after admission and 85.2% (288 of 338) started more than thirty minutes after the decision for the emergency cesarean section was made. Neonatal outcomes were significantly worse among mothers with more than 90 minutes of travel time from the health center to the district hospital compared to health centers attached to the hospital (OR = 5.12, p = 0.02). Neonatal outcomes were also significantly different depending on decision to incision intervals; neonates with cesarean deliveries starting more than thirty minutes after decision had better outcomes than those started immediately (OR = 0.32, p = 0.04). Interventions that decrease barriers to access to maternal health care services can improve neonatal outcome after emergency cesarean section. Triaging could explain the inverse relationship between time from decision to incision and neonatal outcome; this must be studied more in the future.

Keywords: Africa, emergency obstetric care, rural health delivery, maternal and child health

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Authors: Ariane Plaisance, Holly O. Witteman, Patrick Michel Archambault

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Upon admission to an intensive care unit (ICU), all patients should discuss their wishes concerning life-sustaining interventions (e.g., cardiopulmonary resuscitation (CPR)). Without such discussions, interventions that prolong life at the cost of decreasing its quality may be used without appropriate guidance from patients. We employed user-centered design to adapt an existing decision aid (DA) about CPR to create a novel wiki-based DA adapted to the context of a single ICU and tailored to individual patient’s risk factors. During Phase 1, we conducted three weeks of ethnography of the decision-making context in our ICU to identify clinician and patient needs for a decision aid. During this time, we observed five dyads of intensivists and patients discussing their wishes concerning life-sustaining interventions. We also conducted semi-structured interviews with the attending intensivists in this ICU. During Phase 2, we conducted three rounds of rapid prototyping involving 15 patients and 11 other allied health professionals. We recorded discussions between intensivists and patients and used a standardized observation grid to collect patients’ comments and sociodemographic data. We applied content analysis to field notes, verbatim transcripts and the completed observation grids. Each round of observations and rapid prototyping iteratively informed the design of the next prototype. We also used the programming architecture of a wiki platform to embed the GO-FAR prediction rule programming code that we linked to a risk graphics software to better illustrate outcome risks calculated. During Phase I, we identified the need to add a section in our DA concerning invasive mechanical ventilation in addition to CPR because both life-sustaining interventions were often discussed together by physicians. During Phase II, we produced a context-adapted decision aid about CPR and mechanical ventilation that includes a values clarification section, questions about the patient’s functional autonomy prior to admission to the ICU and the functional decline that they would judge acceptable upon hospital discharge, risks and benefits of CPR and invasive mechanical ventilation, population-level statistics about CPR, a synthesis section to help patients come to a final decision and an online calculator based on the GO-FAR prediction rule. Even though the three rounds of rapid prototyping led to simplifying the information in our DA, 60% (n= 3/5) of the patients involved in the last cycle still did not understand the purpose of the DA. We also identified gaps in the discussion and documentation of patients’ preferences concerning life-sustaining interventions (e.g.,. CPR, invasive mechanical ventilation). The final version of our DA and our online wiki-based GO-FAR risk calculator using the IconArray.com risk graphics software are available online at www.wikidecision.org and are ready to be adapted to other contexts. Our results inform producers of decision aids on the use of wikis and user-centered design to develop DAs that are better adapted to users’ needs. Further work is needed on the creation of a video version of our DA. Physicians will also need the training to use our DA and to develop shared decision-making skills about goals of care.

Keywords: ethnography, intensive care units, life-sustaining therapies, user-centered design

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

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Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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Authors: H. Alamri

Abstract:

Natural fiber reinforced composites have attracted researchers for their desirable properties of toughness, high modulus, low density, recyclability, and renewability. In fact, the use of natural fibers in polymer composites has the potential to produce materials with higher specific strength and specific modulus due of their low density. Likewise, polymer-nano-filler composites have been widely investigated for their unique and significant improvement in strength, modulus, impact strength, barrier properties, heat resistance and thermal stability. In this paper, The addition of halloysite nanotubes (HNTs) with three different weight percentages (1%, 3% and 5%) on enhancing barrier and flexural strength and modulus of cellulose-fiber (CF) /epoxy composites after water treatment for six months was studied. Results indicated that water uptake decreased as HNT content increased. The presence of HNT improved flexural strength and flexural modulus of CF/epoxy composites. SEM results showed damages in fiber-matrix interfacial bonding due to water absorption. The addition of HNTs was found to enhance to adhesion between fibers and matrix.

Keywords: mechanical properties, epoxy, nanocomposites, halloysite nanotubes

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Authors: Kevin Soubly, Kaysara Khatun

Abstract:

This study applies the existing Middle-Out Perspective (MOP) as a complementing analytical alternative to the customary dichotomous options of top-down vs. bottom-up strategies of international development and commons governance. It expands the framework by applying it to a new context of land management and environmental change, enabling fresh understandings of decision making around land use. Using a case study approach in Central Kalimantan, Indonesia among a village of indigenous Dayak, this study explores influences from both internal and external middle actors, utilizing qualitative empirical evidence and incorporating responses across 25 village households and 11 key stakeholders. Applying the factors of 'agency' and 'capacity' specific to the MOP, this study demonstrates middle actors’ unique capabilities and criticality to change due to their influence across various levels of decision-making. Study results indicate that middle actors play a large role, both passively and actively, both directly and indirectly, across various levels of decision-making, perception-shaping, and commons governance. In addition, the prominence of novel 'passive' middle actors, such as the internet, can provide communities themselves with a level of agency beyond that provided by other middle actors such as NGOs and palm oil industry entities – which often operate at the behest of the 'top' or out of self-interest. Further, the study posits that existing development and decision-making frameworks may misidentify the 'bottom' as the 'middle,' raising questions about traditional development and livelihood discourse, strategies, and support, from agricultural production to forest management. In conclusion, this study provides recommendations including that current policy preconceptions be reevaluated to engage middle actors in locally-adapted, integrative manners in order to improve governance and rural development efforts more broadly.

Keywords: environmental management, governance, Indonesia, land use, middle actors, middle-out perspective

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Authors: Jeon Chi-Ho, Lee Jae-Bin, Shim Chang-Su

Abstract:

National bridge inventory in Korea shows that the number of old prestressed concrete (PSC) bridgeover 30 years of service life is rapidly increasing. Recently tendon corrosion is one of the most critical issues in the maintenance of PSC bridges. In this paper, mechanical properties of corroded strands, which were removed from old bridges, were evaluated using tensile test. In the result, the equations to express the mechanical behavior of corroded strand were derived and compared to existing equation. For the decision of tendon replacement, it is necessary to evaluate the effect of corrosion level on strength and ductility of the structure. Considerations on analysis of PSC girders were introduced, and decision making on tendon replacement was also proposed.

Keywords: prestressed concrete bridge, tendon, corrosion, strength, ductility

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Authors: Logan Carmichael

Abstract:

As the world’s governments seek to increasingly digitize their service provisions, there exists a subsequent and fully valid concern about the security underpinning these digital governance provisions. Estonia, a small and innovative Baltic nation, has been refining both its digital governance structure and cybersecurity mechanisms for over three decades and has been praised as global ‘best practice’ in both fields. However, the security of the Estonian digital governance system has been ever-evolving and significantly shaped by cybersecurity crises. This paper examines said crises – 2007 cyberattacks on Estonian government, banks, and news media; the 2017 e-ID crisis; the ongoing COVID-19 pandemic; and the 2022 Russian invasion of Ukraine – and how governance decision-making following these crises has shaped the cybersecurity of the digital governance structure in Estonia. This paper employs a blended constructivist and historical institutionalist theoretical approach as a useful means to view governance and decision-making in the wake of cybersecurity incidents affecting the Estonian digital governance structure. Together, these theoretical groundings frame the topics of cybersecurity and digital governance in an Estonian context through a lens of ideation and experience, as well as institutional path dependencies over time and cybersecurity crises as critical junctures to study. Furthermore, this paper takes a qualitative approach, employing discourse analysis, policy analysis, and elite interviewing of Estonian officials involved in digital governance and cybersecurity in order to glean nuanced perspectives into the processes that followed these four crises. Ultimately, the results of this paper will offer insight into how governments undertake policy-driven change following cybersecurity crises to ensure sufficient security of their digitized service provisions. This paper’s findings are informative not only in continued decision-making in the Estonian system but also in other states currently implementing a digital governance structure, for which security mechanisms are of the utmost importance.

Keywords: cybersecurity, digital governance, Estonia, crisis management, governance in crisis

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

Abstract:

Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Shital Jhunjhunwala, Shweta Saraf

Abstract:

Research Question: The study, based on a survey, empirically tests the impact of the board’s engagement in the decision-making process on firm outcomes. It also examines the moderating effect of board leadership and board independence on the relationship. Research Findings: Boards’ engagement in the decision-making process is found to be vital for firm performance, wherein effective monitoring by the board outperforms their strategic guidance role in achieving desired outcomes. The separation of CEO and Chairman positively moderates the board’s engagement in protecting stakeholders’ interests, but lack of independence and passive behaviour of independent directors raises concern on the efficacy of independent directors. Theoretical Implications: The study provides the framework for process-oriented corporate governance research, where investigation of boards’ behaviour inside the boardroom develops a deeper understanding of board processes. Practitioner Implications: The study highlights the necessity of developing boards’ focus in a company on monitoring managerial actions. It suggests the need to separate the position of CEO and Chairman for addressing the interest of all stakeholders. It recommends policymakers review the existing mandate on board independence and create alternate monitoring mechanisms for addressing agency conflict.

Keywords: board, decision-making process, engagement, independence, leadership, innovation, stakeholders, firm performance, qualitative, India

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Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

Procedia PDF Downloads 428

Authors: Peter Olasupo Ogunjuyigbe, Sarafa Shittu

Abstract:

This paper emphasizes the relevance of conjugal relationship and spousal communication towards enhancing men’s involvement in contraceptive use among the Yorubas of South Western Nigeria. An understanding of males influence and the role they play in reproductive decision making can throw better light on mechanisms through which egalitarianness of husband/wife decision making influences contraceptive use. The objective of this study was to investigate how close conjugal relationships can be a good indicator of joint decision making among couples using data derived from a survey conducted in three states of South Western Nigeria. The study sample consisted of five hundred and twenty one (521) male respondents aged 15-59 years and five hundred and forty seven (547) female respondents aged 15-49 years. The study used both quantitative and qualitative approached to elicit information from the respondents. In order that the study would be truly representative of the towns, each of the study locations in the capital cities was divided into four strata: The traditional area, the migrant area, the mixed area (i.e. traditional and migrant), and the elite area. In the rural areas, selection of the respondents was by simple random sampling technique. However, the random selection was made in such a way that all the different parts of the locations were represented. Generally, the data collected were analysed at univariate, bivariate, and multivariate levels. Logistic regression models were employed to examine the interrelationships between male reproductive behaviour, conjugal relationship and contraceptive use. The study indicates that current use of contraceptive is high among this major ethnic group in Nigeria because of the improved level of communication among couples. The problem, however, is that men still have lower exposure rate when it comes to question of family planning information, education and counseling. This has serious implications on fertility regulation in Nigeria.

Keywords: behavior, conjugal, communication, counseling, spouse

Procedia PDF Downloads 127