Search results for: control problem

Authors: Hind Bouami

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Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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Authors: Y. Wang

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The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CN_maxn²) where C is the iterations, N_max is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.

Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Karen Odendaal

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Accounting transactions are becoming more complex, and more extensive accounting guidance is provided on a continuous basis. It is widely perceived that conceptual teaching of accounting contributes to lifelong learning. Such a conceptual teaching approach also contributes to effective accounting problem-solving. This framework-based approach is rooted in educational psychologies such as constructivism and Ausubel’s subsumption theory. This study aimed at investigating the ability of students to solve complex accounting problems by using only concepts underlying the Conceptual Framework. An assignment was administered to pre-graduate students at a South African university and this study made use of an interpretative research design which implemented multiple research instruments to investigate the ability of students to solve complex accounting problems using only concepts underlying the Conceptual Framework. Student perceptions were analysed and were aided by a related reflective questionnaire. The importance of the study indicates the necessity of Accounting educators to enhance a conceptual understanding among students as a mechanism for problem-solving of accounting issues. The results indicate that the ability of students to solve accounting problems effectively using only the Conceptual Framework depends on the complexity of the scenario and the students’ familiarity with the problem. The study promotes a balanced and more conceptual (rather than only technical) preference to the problem-solving of complex accounting problems. The study indubitably promotes considerable emphasis on the importance of the Conceptual Framework in accounting education and the promotion of life-long learning in the subject field.

Keywords: accounting education, conceptual teaching, constructivism, framework-based, problem-solving

Procedia PDF Downloads 233

Authors: Yunjia Yang, Peng Li, Gordon Xu, Timothy Mahony, Bing Zhang, Neena Mitter, Karishma Mody

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Sheep flystrike is one of the most economically important diseases affecting the Australian sheep and wool industry (>356M/annually). Currently, control of Lucillia cuprina relies almost exclusively on chemicals controls and the parasite has developed resistance to nearly all control chemicals used in the past. It is therefore critical to develop an alternative solution for the sustainable control and management of flystrike. RNA interference (RNAi) technologies have been successfully explored in multiple animal industries for developing parasites controls. This research project aims to develop a RNAi based biological control for sheep blowfly. Double-stranded RNA (dsRNA) has already proven successful against viruses, fungi and insects. However, the environmental instability of dsRNA is a major bottleneck for successful RNAi. Bentonite polymer (BenPol) technology can overcome this problem, as it can be tuned for the controlled release of dsRNA in the gut challenging pH environment of the blowfly larvae, prolonging its exposure time to and uptake by target cells. To investigate the potential of BenPol technology for dsRNA delivery, four different BenPol carriers were tested for their dsRNA loading capabilities, and three of them were found to be capable of affording dsRNA stability under multiple temperatures (4°C, 22°C, 40°C, 55°C) in sheep serum. Based on stability results, dsRNA from potential targeted genes was loaded onto BenPol carriers and tested in larvae feeding assays, three genes resulting in knockdowns. Meanwhile, a primary blowfly embryo cell line (BFEC) derived from L. cuprina embryos was successfully established, aim for an effective insect cell model for testing RNAi efficacy for preliminary assessments and screening. The results of this study establish that the dsRNA is stable when loaded on BenPol particles, unlike naked dsRNA rapidly degraded in sheep serum. The stable nanoparticle delivery system offered by BenPol technology can protect and increase the inherent stability of dsRNA molecules at higher temperatures in a complex biological fluid like serum, providing promise for its future use in enhancing animal protection.

Keywords: flystrike, RNA interference, bentonite polymer technology, Lucillia cuprina

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Authors: Sanchai Ratthanakwan

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This research aims to study situations and characteristics of the problems facing the urban poor. The data and information are collected by focus group and in-depth interview leader and members of Four Regions Slum Network, community representatives and the social welfare officer. The research can be concluded that the problems of the urban poor faced with three major problems: Firstly, the shortage of housing and stability issues in housing; secondly, the problem of substandard quality of life; and thirdly, the debt problem. The study found that a solution will be found in two ways: First way is the creation of housing for the urban poor in slums or community intrusion by the state. Second way is the stability in the housing and subsistence provided by the community center called “housing stability”.

Keywords: urban poor, social welfare, Bangkok metropolis, housing stability

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Authors: Shiuh-Jer Huang, Yun-Han Yeh

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A four-wheel drive electric vehicle was built with hub DC motors and FPGA embedded control structure. A 40 steps manual adjusting motorcycle shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. An intelligent fuzzy logic controller was proposed to real-time search appropriate damping ratio based on vehicle running condition. Then, a robust fuzzy sliding mode controller (FSMC) is employed to regulate the target damping ratio of each wheel axis semi-active suspension system. Finally, different road surface conditions are chosen to evaluate the control performance of this semi-active suspension and compare with that of passive system based on wheel axis acceleration signal.

Keywords: acceleration, FPGA, Fuzzy sliding mode control, semi-active suspension

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Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

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Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

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Authors: Serhat Tüzün, Tufan Demirel

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The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

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Authors: L. Wilkening, G. Ackermann, T. T. Do

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This article presents an approach for stand-alone and grid-connected mode of a German low-voltage grid with high share of photovoltaic. For this purpose, suitable dynamic system models have been developed. This allows the simulation of dynamic events in very small time ranges and the operation management over longer periods of time. Using these simulations, suitable control parameters could be identified, and their effects on the grid can be analyzed. In order to validate the simulation results, a LV-grid test bench has been implemented at the University of Technology Hamburg. The developed control strategies are to be validated using real inverters, generators and different realistic loads. It is shown that a battery hybrid system installed next to a voltage transformer makes it possible to operate the LV-grid in stand-alone mode without using additional information and communication technology and without intervention in the existing grid units. By simulating critical days of the year, suitable control parameters for stable stand-alone operations are determined and set point specifications for different control strategies are defined.

Keywords: battery, e-mobility, photovoltaic, smart grid

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Authors: Pradeep A. G, Gorantla Giridhar, Vijay Turaga, Vinod Srinivasa

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The major problem in the flow control valve is of lower Cv, which will reduce the overall efficiency of the flow circuit. Designers are continuously working to improve the Cv of the valve, but they need to validate the design ideas they have regarding the improvement of Cv. The traditional method of prototyping and testing takes a lot of time. That is where CFD comes into the picture with very quick and accurate validation along with visualization, which is not possible with the traditional testing method. We have developed a method to predict Cv value using CFD analysis by iterating on various Boundary conditions, solver settings and by carrying out grid convergence studies to establish the correlation between the CFD model and Test data. The present study investigates 3 different ideas put forward by the designers for improving the flow capacity of the valves, like reducing the cage thickness, changing the port position, and using the parabolic plug to guide the flow. Using CFD, we analyzed all design changes using the established methodology that we developed. We were able to evaluate the effect of these design changes on the Valve Cv. We optimized the wetted surface of the valve further by suggesting the design modification to the lower part of the valve to make the flow more streamlined. We could find that changing cage thickness and port position has little impact on the valve Cv. The combination of optimized wetted surface and introduction of parabolic plug improved the Flow capacity (Cv) of the valve significantly.

Keywords: flow control valves, flow capacity (Cv), CFD simulations, design validation

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Authors: Blair D. Macdonald

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After nearly one hundred years of its origin, foundational quantum mechanics remains one of the greatest unexplained mysteries in physicists today. Within this time, chaos theory and its geometry, the fractal, has developed. In this paper, the propagation behaviour with an iteration of a simple fractal, the Koch Snowflake, was described and analysed. From an arbitrary observation point within the fractal set, the fractal propagates forward by oscillation—the focus of this study and retrospectively behind by exponential growth from a point beginning. It propagates a potentially infinite exponential oscillating sinusoidal wave of discrete triangle bits sharing many characteristics of light and quantum entities. The model's wave speed is potentially constant, offering insights into the perception and a direction of time where, to an observer, when travelling at the frontier of propagation, time may slow to a stop. In isolation, the fractal is a superposition of component bits where position and scale present a problem of location. In reality, this problem is experienced within fractal landscapes or fields where 'position' is only 'known' by the addition of information or markers. The quantum' measurement problem', 'uncertainty principle,' 'entanglement,' and the classical-quantum interface are addressed; these are a problem of scale invariance associated with isolated fractality. Dual forward and retrospective perspectives of the fractal model offer the opportunity for unification between quantum mechanics and cosmological mathematics, observations, and conjectures. Quantum and cosmological problems may be different aspects of the one fractal geometry.

Keywords: measurement problem, observer, entanglement, unification

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Authors: Kiwon Yeom

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Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

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Authors: Diom Loreen Ndum, Omarine Njimanted

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With increasing automation in clinical laboratories, the requirements for quality control materials have greatly increased in order to monitor daily performance. The constant use of commercial control material is not economically feasible for many developing countries because of non-availability or the high-cost of the materials. Therefore, preparation and use of in-house quality control serum will be a very cost-effective measure with respect to laboratory needs.The objective of this study was to determine the efficacy of in-house prepared pooled sera with respect to commercially acquired control sample for routine internal quality control at the Nkwen District Hospital Laboratory. This was an analytical study, serum was taken from leftover serum samples of 5 healthy adult blood donors at the blood bank of Nkwen District Hospital, which had been screened negative for human immunodeficiency virus (HIV), hepatitis C virus (HCV) and Hepatitis B antigens (HBsAg), and were pooled together in a sterile container. From the pooled sera, sixty aliquots of 150µL each were prepared. Forty aliquots of 150µL each of commercially acquired samples were prepared after reconstitution and stored in a deep freezer at − 20°C until it was required for analysis. This study started from the 9th June to 12th August 2022. Every day, alongside with commercial control sample, one aliquot of pooled sera was removed from the deep freezer and allowed to thaw before analyzed for the following parameters: blood urea, serum creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), potassium and sodium. After getting the first 20 values for each parameter of pooled sera, the mean, standard deviation and coefficient of variation were calculated, and a Levey-Jennings (L-J) chart established. The mean and standard deviation for commercially acquired control sample was provided by the manufacturer. The following results were observed; pooled sera had lesser standard deviation for creatinine, urea and AST than commercially acquired control samples. There was statistically significant difference (p<0.05) between the mean values of creatinine, urea and AST for in-house quality control when compared with commercial control. The coefficient of variation for the parameters for both commercial control and in-house control samples were less than 30%, which is an acceptable difference. The L-J charts revealed shifts and trends (warning signs), so troubleshooting and corrective measures were taken. In conclusion, in-house quality control sample prepared from pooled serum can be a good control sample for routine internal quality control.

Keywords: internal quality control, levey-jennings chart, pooled sera, shifts, trends, westgard rules

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Authors: Riku Hayashida, Tomoaki Hashimoto

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This paper provides a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. Underwater robots are expected to be used for various work assignments. The large variety of applications of underwater robots motivates researchers to develop control systems and technologies for underwater robots. Several control methods have been proposed so far for the stabilization of nominal system model of underwater robots with no parameter uncertainty. Parameter uncertainties are considered to be obstacles in implementation of the such nominal control methods for underwater robots. The objective of this study is to establish a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: robust control, stabilization method, underwater robot, parameter uncertainty

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Authors: Hyunsik Park

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As the rate of cerebrovascular disease increases in old populations, the prevalence rate of vascular dementia would be expected. Therefore, authors designed this study to find out the possibility of somatosensory evoked potentials(SSEP) as a parameter for early diagnosis and prognosis prediction of vascular dementia in cortical vascular dementia patients. 21 patients who met the criteria for vascular dementia according to DSM-IV,ICD-10and NINDS-AIREN with the history of recent cognitive impairment, fluctuation progression, and neurologic deficit. We subdivided these patients into two groups; a mild dementia and a severe dementia groups by MMSE and CDR score; and analysed comparison between normal control group and patient control group who have been cerebrovascular attack(CVA) history without dementia by using N20 latency and amplitude of median nerve. In this study, mild dementia group showed significant differences on latency and amplitude with normal control group(p-value<0.05) except patient control group(p-value>0.05). Severe dementia group showed significant differences both normal control group and patient control group.(p-value<0.05, <001). Since no significant difference has founded between mild dementia group and patient control group, SSEP has limitation to use for early diagnosis test. However, the comparison between severe dementia group and others showed significant results which indicate SSEP can predict the prognosis of vascular dementia in cortical vascular dementia patients.

Keywords: SSEP, cortical vascular dementia, N20 latency, N20 amplitude

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: phase locked loop, voltage source inverter, single phase inverter, model predictive control, Matlab/Simulink

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Authors: Neringa Bagdonaite

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Study Aims: The current study aimed to systematically analyse various research done in the area of female post-traumatic stress disorder (PTSD) and alcohol abuse, and to critically review these results on the basis of theoretical models as well as answer following questions: (I) What is the reciprocal relationship between PTSD and problem alcohol use among females; (II) What are the moderating/mediating factors of this relationship? Methods: The computer bibliographic databases Ebsco, Scopus, Springer, Web of Science, Medline, Science Direct were used to search for scientific articles. Systematic analyses sample consisted of peer-reviewed, English written articles addressing mixed gender and female PTSD and alcohol abuse issues from Jan 2012 to May 2017. Results: Total of 1011 articles were found in scientific databases related to searched keywords of which 29 met the selection criteria and were analysed. The results of longitudinal studies indicate that (I) various trauma, especially interpersonal trauma exposure in childhood is linked with increased risk of revictimization in later life and problem alcohol use; (II) revictimization in adolescence or adulthood, rather than victimization in childhood has a greater impact on the onset and progression of problematic alcohol use in adulthood. Cross-sectional and epidemiological studies also support significant relationships between female PTSD and problem alcohol use. Regards to the negative impact of alcohol use on PTSD symptoms results are yet controversial; some evidence suggests that alcohol does not exacerbate symptoms of PTSD over time, while others argue that problem alcohol use worsens PTSD symptoms and is linked to chronicity of both disorders, especially among women with previous alcohol use problems. Analysis of moderating/mediating factors of PTSD and problem alcohol use revealed, that higher motives/expectancies, specifically distress coping motives for alcohol use significantly moderates the relationship between PTSD and problematic alcohol use. Whereas negative affective states mediate relationship between symptoms of PTSD and alcohol use, but only among woman with alcohol use problems already developed. Conclusions: Interpersonal trauma experience, especially in childhood and its reappearance in lifetime is linked with PTSD symptoms and problem drinking among women. Moreover, problem alcohol use can be both a cause and a consequence of trauma and PTSD, and if used for coping it, increases the likelihood of chronicity of both disorders. In order to effectively treat both disorders, it’s worthwhile taking into account this dynamic interplay of women's PTSD symptoms and problem drinking.

Keywords: female, trauma, post-traumatic stress disorder, problem alcohol use, systemic analysis

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Authors: Muhammad M. A. S. Mahmoud

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Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H₂S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. The new design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance.

Keywords: gas separator, gas sweetening, intelligent controller, fuzzy control

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Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

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The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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Authors: Jean Felix Tuyisingize

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Speeding or inappropriate speed is a major problem worldwide, contributing to 10-15% of road crashes and 30% of fatal injury crashes. The consequences of speeding put the driver's life at risk and the lives of other road users like motorists, cyclists, and pedestrians. To control vehicle speeds, governments, and traffic authorities enforced speed regulations through speed cameras and speed section control, which monitor all vehicle speeds and detect plate numbers to levy penalties. However, speed limit violations are prevalent, even on motorways with speed cameras. The problem with speed cameras is that they alter driver behaviors, and their effect declines with increasing distance from the speed camera location. Drivers decelerate short distances before the camera and vigorously accelerate above the speed limit just after passing by the camera. The sudden decelerating near cameras causes the drivers to try to make up for lost time after passing it, and they do this by speeding up, resulting in a phenomenon known as the "Kangaroo jump" or "V-profile" around camera/ASSC areas. This study investigated the impact of speed enforcement devices, specifically Average Speed Section Control (ASSCs) and fixed cameras, on acceleration and deceleration events within their vicinity. The research employed advanced statistical and Geographic Information System (GIS) analysis on naturalistic driving data, to uncover speeding patterns near the speed enforcement systems. The study revealed a notable concentration of events within a 600-meter radius of enforcement devices, suggesting their influence on driver behaviors within a specific range. However, most of these events are of low severity, suggesting that drivers may not significantly alter their speed upon encountering these devices. This behavior could be attributed to several reasons, such as consistently maintaining safe speeds or using real-time in-vehicle intervention systems. The complexity of driver behavior is also highlighted, indicating the potential influence of factors like traffic density, road conditions, weather, time of day, and driver characteristics. Further, the study highlighted that high-severity events often occurred outside speed enforcement zones, particularly around intersections, indicating these as potential hotspots for drastic speed changes. These findings call for a broader perspective on traffic safety interventions beyond reliance on speed enforcement devices. However, the study acknowledges certain limitations, such as its reliance on a specific geographical focus, which may impact the broad applicability of the findings. Additionally, the severity of speed modification events was categorized into low, medium, and high, which could oversimplify the continuum of speed changes and potentially mask trends within each category. This research contributes valuable insights to traffic safety and driver behavior literature, illuminating the complexity of driver behavior and the potential influence of factors beyond the presence of speed enforcement devices. Future research directions may employ various categories of event severity. They may also explore the role of in-vehicle technologies, driver characteristics, and a broader set of environmental variables in driving behavior and traffic safety.

Keywords: acceleration, deceleration, speeding, inappropriate speed, speed enforcement cameras

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Authors: Venkateswar Pujari

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This study tries to investigate the complex interplay between control, awareness, and attention in human cognitive processes. The fundamental elements of cognitive functioning that play a significant role in influencing perception, decision-making, and behavior are attention, awareness, and control. Understanding how they interact can help us better understand how our minds work and may even increase our understanding of cognitive science and its therapeutic applications. The study uses an empirical methodology to examine the relationships between attention, awareness, and control by integrating different experimental paradigms and neuropsychological tests. To ensure the generalizability of findings, a wide sample of participants is chosen, including people with various cognitive profiles and ages. The study is structured into four primary parts, each of which focuses on one component of how attention, awareness, and control interact: 1. Evaluation of Attentional Capacity and Selectivity: In this stage, participants complete established attention tests, including the Stroop task and visual search tasks. 2. Evaluation of Awareness Degrees: In the second stage, participants' degrees of conscious and unconscious awareness are assessed using perceptual awareness tasks such as masked priming and binocular rivalry tasks. 3. Investigation of Cognitive Control Mechanisms: In the third phase, reaction inhibition, cognitive flexibility, and working memory capacity are investigated using exercises like the Wisconsin Card Sorting Test and the Go/No-Go paradigm. 4. Results Integration and Analysis: Data from all phases are integrated and analyzed in the final phase. To investigate potential links and prediction correlations between attention, awareness, and control, correlational and regression analyses are carried out. The study's conclusions shed light on the intricate relationships that exist between control, awareness, and attention throughout cognitive function. The findings may have consequences for cognitive psychology, neuroscience, and clinical psychology by providing new understandings of cognitive dysfunctions linked to deficiencies in attention, awareness, and control systems.

Keywords: attention, awareness, control, cognitive functioning, neuropsychological assessment

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Authors: Rayleigh Dada Abu, Halilu Ahmad Shaba

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Siltation is a serious problem that affects public water supply infrastructures such as dams and reservoirs. It is a major problem which threatens the performance and sustainability of dams and reservoirs. It reduces the dam capacity for flood control, potable water supply, changes water stage, reduces water quality and recreational benefits. The focus of this study is the Lower Usuma reservoir. At completion the reservoir had a gross storage capacity of 100 × 106 m3 (100 million cubic metres), a maximum operational level of 587.440 m a.s.l., with a maximum depth of 49 m and a catchment area of 241 km2 at dam site with a daily designed production capacity of 10,000 cubic metres per hour. The reservoir is 1,300 m long and feeds the treatment plant mainly by gravity. The reservoir became operational in 1986 and no survey has been conducted to determine its current storage capacity and rate of siltation. Hydrographic survey of the reservoir by integrated acoustic echo-sounding technique was conducted in November 2012 to determine the level and rate of siltation. The result obtained shows that the reservoir has lost 12.0 meters depth to siltation in 26 years of its operation; indicating 24.5% loss in installed storage capacity. The present bathymetric survey provides baseline information for future work on siltation depth and annual rates of storage capacity loss for the Lower Usuma reservoir.

Keywords: sedimentation, lower Usuma reservoir, acoustic echo sounder, bathymetric survey

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Authors: Ali Afaghi, Sehraneh Ghaemi

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The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.

Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs

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Authors: Michael Okeke, Andrew Blyth

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Supervisory Control And Data Acquisition (SCADA) as the state of the art Industrial Control Systems (ICS) are used in many different critical infrastructures, from smart home to energy systems and from locomotives train system to planes. Security of SCADA systems is vital since many lives depend on it for daily activities and deviation from normal operation could be disastrous to the environment as well as lives. This paper describes how No-Trust-Zone (NTZ) architecture could be incorporated into SCADA Systems in order to reduce the chances of malicious intent. The architecture is made up of two distinctive parts which are; the field devices such as; sensors, PLCs pumps, and actuators. The second part of the architecture is designed following lambda architecture, which is made up of a detection algorithm based on Particle Swarm Optimization (PSO) and Hadoop framework for data processing and storage. Apache Spark will be a part of the lambda architecture for real-time analysis of packets for anomalies detection.

Keywords: industrial control system (ics, no-trust-zone (ntz), particle swarm optimisation (pso), supervisory control and data acquisition (scada), swarm intelligence (SI)

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Authors: Christine K. Fulmer

Abstract:

Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: social work education, problem-based learning, pedagogy, experiential learning, constructivist theoretical approach

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Authors: Dalvinder Kaur Mangal

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For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out.

Keywords: errors-in-variable (EIV), false EIV, equation error, output error, iterative prefiltering, Gaussian noise

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Authors: Homa Ghave, Parmis Shahmaleki

Abstract:

This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

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Authors: Abdeljalil Beniiche

Abstract:

The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

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