Search results for: differential predictive coding

Authors: Hasan Basaran, Emre Unal

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Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

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Authors: Tran Gia Khanh, Dao Phuong Nam, Do Trong Tan, Nguyen Van Huong, Mai Xuan Sinh

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This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system.

Keywords: input state stability (ISS), tube-based robust MPC, continuous-time nonlinear systems, wheeled inverted pendulum

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

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

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

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Authors: Elmongi Elbellili, Ben Lauwens, Daan Huybrechs

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The increasing complexity of modern engineering systems presents a challenge to the digital simulation of these systems which usually can be represented by differential equations. The Linearly Implicit Quantized State System (LIQSS) offers an alternative approach to traditional numerical integration techniques for solving Ordinary Differential Equations (ODEs). This method proved effective for handling discontinuous and large stiff systems. However, the inherent discrete nature of LIQSS may introduce oscillations that result in unnecessary computational steps. The current oscillation detection mechanism relies on a condition that checks the significance of the derivatives, but it could be further improved. This paper describes a different cycle detection mechanism and presents the outcomes using LIQSS order one in simulating the Advection Diffusion problem. The efficiency of this new cycle detection mechanism is verified by comparing the performance of the current solver against the new version as well as a reference solution using a Runge-Kutta method of order14.

Keywords: numerical integration, quantized state systems, ordinary differential equations, stiffness, cycle detection, simulation

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Authors: Kushakov Kholmurodjon, Muhammadjonov Akbarshox

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This present paper is devoted to a system of second-order nonlinear differential equations with a special right-hand side, exactly, the linear part and a third-order polynomial of a special form. It is shown that for some relations between the parameters, there is a second-order curve in which trajectories leaving the points of this curve remain in the same place. Thus, the curve is invariant with respect to the given system. Moreover, this system is invariant under a non-degenerate linear transformation of variables. The form of this curve, depending on the relations between the parameters and the eigenvalues of the matrix, is proved. All solutions of this system of differential equations are shown analytically.

Keywords: dynamic system, ellipse, hyperbola, Hess system, polar coordinate system

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Authors: J. A. Gbadeyan, R. A. Kareem

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In this paper, we investigated the effects of unsteady internal heat generation of a two-step exothermic reactive hydromagnetic fluid flow under different chemical kinetics namely: Sensitized, Arrhenius and Bimolecular kinetics through an isothermal wall temperature channel. The resultant modeled nonlinear partial differential equations were simplified and solved using a combined Laplace-Differential Transform Method (LDTM). The solutions obtained were discussed and presented graphically to show the salient features of the fluid flow and heat transfer characteristics.

Keywords: unsteady, reactive, hydromagnetic, couette ow, exothermi creactio

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Authors: Mohamed El Horri, Amine Mouden, Reda Messaoudi, Mohamed Chekkal, Driss Benlaldj, Malika Baghdadi, Lahcene Benmahdi, Fatima Seghier

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Background/aim: Recently, the Von Willebrand factor antigen (vWF-Ag)has been identified as a new marker of portal hypertension (PH) and its complications. Few studies talked about its role in the prediction of esophageal varices. VWF-Ag is considered a non-invasive approach, In order to avoid the endoscopic burden, cost, drawbacks, unpleasant and repeated examinations to the patients. In our study, we aimed to evaluate the ability of this marker in the prediction of another complication of portal hypertension, which is portal hypertensive gastropathy (PHG), the one that is diagnosed also by endoscopic tools. Patients and methods: It is about a prospective study, which include 124 cirrhotic patients with no history of bleeding who underwent screening endoscopy for PH-related complications like esophageal varices (EVs) and PHG. Routine biological tests were performed as well as the VWF-Ag testing by both ELFA and Immunoturbidimetric techniques. The diagnostic performance of our marker was assessed using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic curves. Results: 124 patients were enrolled in this study, with a mean age of 58 years [CI: 55 – 60 years] and a sex ratio of 1.17. Viral etiologies were found in 50% of patients. Screening endoscopy revealed the presence of PHG in 20.2% of cases, while for EVsthey were found in 83.1% of cases. VWF-Ag levels, were significantly increased in patients with PHG compared to those who have not: 441% [CI: 375 – 506], versus 279% [CI: 253 – 304], respectively (p <0.0001). Using the area under the receiver operating characteristic curve (AUC), vWF-Ag was a good predictor for the presence of PHG. With a value higher than 320% and an AUC of 0.824, VWF-Ag had an 84% sensitivity, 74% specificity, 44.7% positive predictive value, 94.8% negative predictive value, and 75.8% diagnostic accuracy. Conclusion: VWF-Ag is a good non-invasive low coast marker for excluding the presence of PHG in patients with liver cirrhosis. Using this marker as part of a selective screening strategy might reduce the need for endoscopic screening and the coast of the management of these kinds of patients.

Keywords: von willebrand factor, portal hypertensive gastropathy, prediction, liver cirrhosis

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Authors: Juliette Harper, Yu Yang

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

Keywords: NMPC, biodiesel, uncertainties, nonlinear, MATLAB

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Authors: Estephanie S. López Contreras, Vicente Aranda Palacios, Daniela Flores Silva, Felipe Oliveros Olivares, Romina Riquelme Escobedo, Iñaki Westerhout Usabiaga

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This research explored whether the context of online instruction has influenced the development of first-year English-teaching students' communication skills, being these speaking and listening. The theoretical basis finds its niche in the need to bridge the gap in knowledge about the Chilean online educational context and the development of English communicative skills. An interpretative paradigm and a phenomenological design were implemented in this study. Twenty- two first-year students and two teachers from an English teaching training program participated in the study. The students' ages ranged from 18 to 26 years of age, and the teachers' years of experience ranged from 5 to 13 years in the program. For data collection purposes, semi- structured interviews were applied to both students and teachers. Interview questions were based on the initial conceptualization of the central phenomenon. Observations, field notes, and focus groups with the students are also part of the data collection process. Data analysis considered two-cycle methods. The first included descriptive coding for field notes, initial coding for interviews, and creating a codebook. The second cycle included axial coding for both field notes and interviews. After data analysis, the findings show that students perceived online classes as instances in which active communication cannot always occur. In addition, changes made to the curricula as a consequence of the COVID-19 pandemic have affected students' speaking and listening skills.

Keywords: attitudes, communicative skills, EFL teaching training program, online instruction, and perceptions

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Authors: Francys Souza, Alberto Ohashi, Dorival Leao

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We present a general solution for finding the ε-optimal controls for non-Markovian stochastic systems as stochastic differential equations driven by Brownian motion, which is a problem recognized as a difficult solution. The contribution appears in the development of mathematical tools to deal with modeling and control of non-Markovian systems, whose applicability in different areas is well known. The methodology used consists to discretize the problem through a random discretization. In this way, we transform an infinite dimensional problem in a finite dimensional, thereafter we use measurable selection arguments, to find a control on an explicit form for the discretized problem. Then, we prove the control found for the discretized problem is a ε-optimal control for the original problem. Our theory provides a concrete description of a rather general class, among the principals, we can highlight financial problems such as portfolio control, hedging, super-hedging, pairs-trading and others. Therefore, our main contribution is the development of a tool to explicitly the ε-optimal control for non-Markovian stochastic systems. The pathwise analysis was made through a random discretization jointly with measurable selection arguments, has provided us with a structure to transform an infinite dimensional problem into a finite dimensional. The theory is applied to stochastic control problems based on path-dependent stochastic differential equations, where both drift and diffusion components are controlled. We are able to explicitly show optimal control with our method.

Keywords: dynamic programming equation, optimal control, stochastic control, stochastic differential equation

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Hamid Hamli Benzahar

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The main goal of this research is to study the deflection of a composite beam CB taking into account the effect of shear deformation. The structure is made up of two beams of different sections, joined together by thin adhesive, subjected to end moments and a distributed load. The fundamental differential equation of CB can be obtained from the total energy equation while considering the shear deformation. The differential equation found will be compared with those found in CB, where the shear deformation is zero. The CB system is numerically modeled by the finite element method, where the numerical results of deflection will be compared with those found theoretically.

Keywords: composite beam, shear deformation, moments, finites elements

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Authors: Di Luo, Maria Buchberger, Anja Pickhard

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Objectives: The purpose of this study was to assess and compare the diagnostic accuracy of four common morphological approaches, including sonography, computed tomography (CT), positron emission tomography/computed tomography (PET/CT), and magnetic resonance imaging (MRI) for the evaluation of cervical lymph node metastases in head and neck squamous cell carcinoma (HNSCC) patients. Material and Methods: Included in this retrospective study were 26 patients diagnosed with HNSCC between 2010 and 2011 who all underwent sonography, CT, PET/CT, and MRI imaging before neck dissection. Morphological data were compared to the corresponding histopathological results. Statistical analysis was performed with SPSS statistic software (version 26.0), calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for detection of cervical lymph node metastases. Results: The 5-year survival rate of the patient collective was 55.5%.Risk factors for survival included initial primary tumor stage, initial lymph node stage, initial metastasis status, and therapeutic approaches. Cox regression showed initial metastasis status(HR 8.671, 95%CI 1.316-57.123, p=0.025) and therapeutic approaches(HR 6.699, 95%CI 1.746-25.700, p=0.006)to be independent predictive risk factors for survival. Sensitivity was highest for MRI (96% compared to 85% for sonography and 89% for CT and PET/CT). Specificity was comparable with 95 % for CT and 98 % for sonography and PET/CT, but only 68% for MRI. While the MRI showed the least PPV (34%) compared to all other methods (85% for sonography,75% for CT, and 86% for PET/CT), the NPV was comparable in all methods(98-99%). The overall accuracy of cervical lymph node metastases detection was comparable for sonography, CT, and PET/CT with 96%,97%,94%, respectively, while MRI had only 72% accuracy. Conclusion: Since the initial status of metastasis is an independent predictive risk factor for patients’ survival, efficient detection is crucial to plan adequate therapeutic approaches. Sonography, CT, and PET/CT have better diagnostic accuracy than MRI for the evaluation of cervical lymph node metastases in HNSCC patients.

Keywords: cervical lymph node metastases, diagnostic accuracy, head and neck squamous carcinoma, risk factors, survival

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Authors: Markus Mazzola, Gunther Schaaf

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A vehicle driving with an Adaptive Cruise Control System (ACC) is usually controlled decentrally, based on the information of radar systems and in some publications based on C2X-Communication (CACC) to guarantee stable platoons. In this paper, we present a Model Predictive Control (MPC) design of a centralized, server-based ACC-System, whereby the vehicular platoon is modeled and controlled as a whole. It is then proven that the proposed MPC design guarantees asymptotic stability and hence string stability of the platoon. The Networked MPC design is chosen to be able to integrate system constraints optimally as well as to reduce the effects of communication delay and packet loss. The performance of the proposed controller is then simulated and analyzed in an LTE communication scenario using the LTE/EPC Network Simulator LENA, which is based on the ns-3 network simulator.

Keywords: adaptive cruise control, centralized server, networked model predictive control, string stability

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Authors: Ayaz Ahmad

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In this work, we present the effect of noise on the solution of a partial differential equation (PDE) in three different setting. We shall first consider random initial condition for two nonlinear dispersive PDE the non linear Schrodinger equation and the Kortteweg –de vries equation and analyse their effect on some special solution , the soliton solutions.The second case considered a linear partial differential equation , the wave equation with random initial conditions allow to substantially decrease the computational and data storage costs of an algorithm to solve the inverse problem based on the boundary measurements of the solution of this equation. Finally, the third example considered is that of the linear transport equation with a singular drift term, when we shall show that the addition of a multiplicative noise term forbids the blow up of solutions under a very weak hypothesis for which we have finite time blow up of a solution in the deterministic case. Here we consider the problem of wave propagation, which is modelled by a nonlinear dispersive equation with noisy initial condition .As observed noise can also be introduced directly in the equations.

Keywords: drift term, finite time blow up, inverse problem, soliton solution

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Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan

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This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Keywords: model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging

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Authors: Han Xue, Zhang Lanyue

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In order to seek more effective feature extraction technology, feature extraction method based on MFCC combined with vector hydrophone is exposed in the paper. The sound pressure signal and particle velocity signal of two kinds of ships are extracted by using MFCC and its evolution form, and the extracted features are fused by using fisher-ratio and correlated distance criterion. The features are then identified by BP neural network. The results showed that MFCC, First-Order Differential MFCC and Second-Order Differential MFCC features can be used as effective features for recognition of underwater targets, and the fusion feature can improve the recognition rate. Moreover, the results also showed that the recognition rate of the particle velocity signal is higher than that of the sound pressure signal, and it reflects the superiority of vector signal processing.

Keywords: vector information, MFCC, differential MFCC, fusion feature, BP neural network

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: Khadidja Bellifa, Sidi Mohamed Mekelleche

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Phenols and especially halogenated phenols represent a substantial part of the chemicals produced worldwide and are known as aquatic pollutants. Quantitative structure–toxicity relationship (QSTR) models are useful for understanding how chemical structure relates to the toxicity of chemicals. In the present study, the acute toxicities of 45 halogenated phenols to Tetrahymena Pyriformis are estimated using no cost semi-empirical quantum chemistry methods. QSTR models were established using the multiple linear regression technique and the predictive ability of the models was evaluated by the internal cross-validation, the Y-randomization and the external validation. Their structural chemical domain has been defined by the leverage approach. The results show that the best model is obtained with the AM1 method (R²= 0.91, R²CV= 0.90, SD= 0.20 for the training set and R²= 0.96, SD= 0.11 for the test set). Moreover, all the Tropsha’ criteria for a predictive QSTR model are verified.

Keywords: halogenated phenols, toxicity mechanism, hydrophobicity, electrophilicity index, quantitative stucture-toxicity relationships

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Authors: Dalia. G. Aseel, E. E. Hafez, S. M. Hammad

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Viral RNAs of both potato leaf roll virus (PLRV) and potato virus Y (PVY) were extracted from infected potato leaves collected from different Egyptian regions. Differential Display Polymerase Chain Reaction (DD-PCR) using (Endogluconase, β-1,3-glucanases, Chitinase, Peroxidase and Polyphenol oxidase) primers (forward strand) for was performed. The obtained data revealed different banding patterns depending on the viral type and the region of infection. Regarding PLRV, a 58 up regulated and 19 down regulated genes were detected, while, 31 up regulated and 14 down regulated genes were observed in case of PVY. Based on the nucleotide sequencing, variable phylogenetic relationships were reported for the three sequenced genes coding for: Induced stolen tip protein, Disease resistance RPP-like protein and non-specific lipid-transfer protein. In a complementary approach, using the quantitative Real-time PCR, the expressions of PRs genes understudy were estimated in the infected leaves by PLRV and PVY of three potato cultivars (Spunta, Diamont and Cara). The infection with both viruses inhibited the expressions of the five PRs genes. On the contrary, infected leaves by PLRV or PVY elevated the expression of some defense genes. This interaction also may be enhanced and/or inhibited the expression of some genes responsible for the plant defense mechanisms.

Keywords: PLRV, PVY, PR genes, DD-PCR, qRT-PCR, sequencing

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Authors: Johnson Oladele Fatokun, I. P. Akpan

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In this paper, the one-dimensional time dependent Schrödinger equation is discretized by the method of lines using a second order finite difference approximation to replace the second order spatial derivative. The evolving system of stiff ordinary differential equation (ODE) in time is solved numerically by an L-stable trapezoidal-like integrator. Results show accuracy of relative maximum error of order 10-4 in the interval of consideration. The performance of the method as compared to an existing scheme is considered favorable.

Keywords: Schrodinger’s equation, partial differential equations, method of lines (MOL), stiff ODE, trapezoidal-like integrator

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Authors: Shailaja Grover, Purvi Tiwari, Vigneshwaran S. R., U. Dinesh Kumar

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In India, grapes are one of the most important horticulture crops. Grapes are most vulnerable to downy mildew, which is one of the most devasting diseases. In the absence of a precise weather-based advisory system, farmers spray pesticides on their crops extensively. There are two main challenges associated with using these pesticides. Firstly, most of these sprays were panic sprays, which could have been avoided. Second, farmers use more expensive "Preventive and Eradicate" chemicals than "Systemic, Curative and Anti-sporulate" chemicals. When these chemicals are used indiscriminately, they can enter the fruit and cause health problems such as cancer. This paper utilizes decision trees and predictive modeling techniques to provide grape farmers with customized advice on grape disease management. This model is expected to reduce the overall use of chemicals by approximately 50% and the cost by around 70%. Most of the grapes produced will have relatively low residue levels of pesticides, i.e., below the permissible level.

Keywords: analytics in agriculture, downy mildew, weather based advisory, decision tree, predictive modelling

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Daniel Zaccariello

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Our study explores the usefulness of implementing facial expression recognition capabilities and using the Facial Action Coding System (FACS) in contexts where the other person is wearing a mask. In the communication process, the subjects use a plurality of distinct and autonomous reporting systems. Among them, the system of mimicking facial movements is worthy of attention. Basic emotion theorists have identified the existence of specific and universal patterns of facial expressions related to seven basic emotions -anger, disgust, contempt, fear, sadness, surprise, and happiness- that would distinguish one emotion from another. However, due to the COVID-19 pandemic, we have come up against the problem of having the lower half of the face covered and, therefore, not investigable due to the masks. Facial-emotional behavior is a good starting point for understanding: (1) the affective state (such as emotions), (2) cognitive activity (perplexity, concentration, boredom), (3) temperament and personality traits (hostility, sociability, shyness), (4) psychopathology (such as diagnostic information relevant to depression, mania, schizophrenia, and less severe disorders), (5) psychopathological processes that occur during social interactions patient and analyst. There are numerous methods to measure facial movements resulting from the action of muscles, see for example, the measurement of visible facial actions using coding systems (non-intrusive systems that require the presence of an observer who encodes and categorizes behaviors) and the measurement of electrical "discharges" of contracting muscles (facial electromyography; EMG). However, the measuring system invented by Ekman and Friesen (2002) - "Facial Action Coding System - FACS" is the most comprehensive, complete, and versatile. Our study, carried out on about 1,500 subjects over three years of work, allowed us to highlight how the movements of the hands and upper part of the face change depending on whether the subject wears a mask or not. We have been able to identify specific alterations to the subjects’ hand movement patterns and their upper face expressions while wearing masks compared to when not wearing them. We believe that finding correlations between how body language changes when our facial expressions are impaired can provide a better understanding of the link between the face and body non-verbal language.

Keywords: facial action coding system, COVID-19, masks, facial analysis

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Authors: N. Senu, I. A. Kasim, F. Ismail, N. Bachok

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In this paper zero-dissipative explicit Runge-Kutta method is derived for solving second-order ordinary differential equations with periodical solutions. The phase-lag and dissipation properties for Runge-Kutta (RK) method are also discussed. The new method has algebraic order three with dissipation of order infinity. The numerical results for the new method are compared with existing method when solving the second-order differential equations with periodic solutions using constant step size.

Keywords: dissipation, oscillatory solutions, phase-lag, Runge-Kutta methods

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Authors: Alaa Sheta

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Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.

Keywords: economic load dispatch, power systems, optimization, differential evolution

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Authors: Romaric Desbrousses, Lan Lin

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The objective of this study is to determine how Canadian seismic design provisions affect the column axial load resistance of moment-resisting frame reinforced concrete buildings subjected to the differential settlement of their foundation. To do so, two four-storey buildings are designed in accordance with the seismic design provisions of the Canadian Concrete Design Standards. One building is located in Toronto, which is situated in a moderate seismic hazard zone in Canada, and the other in Vancouver, which is in Canada’s highest seismic hazard zone. A finite element model of each building is developed using SAP 2000. A 100 mm settlement is assigned to the base of the building’s center column. The axial load resistance of the column is represented by the demand capacity ratio. The analysis results show that settlement-induced tensile axial forces have a particularly detrimental effect on the conventional settling columns of the Toronto buildings which fail at a much smaller settlement that those in the Vancouver buildings. The results also demonstrate that particular care should be taken in the design of columns in short-span buildings.

Keywords: Columns, Demand, Foundation differential settlement, Seismic design, Non-linear analysis

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Authors: Arash Jafari, Mehdi Taghaddosi, Azin Parvin

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In this study, a vibrational differential equation governing on swinging single-degree-of-freedom pendulum in a viscous fluid has been investigated. The damping process is characterized according to two different regimes: at first, damping in stationary viscous fluid, in the second, damping in flowing viscous fluid with constant velocity. Our purpose is to enhance the ability of solving the mentioned nonlinear differential equation with a simple and innovative approach. Comparisons are made between new method and Numerical Method (rkf45). The results show that this method is very effective and simple and can be applied for other nonlinear problems.

Keywords: oscillating systems, angular frequency and damping ratio, pendulum at fluid, locus of maximum

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Authors: Chi-Hsuan Cheng

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This research aims to evaluate public-private partnerships against cyberattacks by comparing the UK and Taiwan. First, the study analyses major cyberattacks and factors influencing cybersecurity in both countries. Second, it assesses the effectiveness of current cyber defence strategies in combating cyberattacks by comparing the approaches taken in the UK and Taiwan, while also evaluating the cyber resilience of both nations. Lastly, the research evaluates existing public-private partnerships by comparing those in the UK and Taiwan, and proposes recommendations for enhancing cooperation and collaboration mechanisms in tackling cyberattacks. Grounded theory serves as the core research method. Theoretical sampling is used to recruit participants in both the UK and Taiwan, including investigators, police officers, and professionals from cybersecurity firms. Semi-structured interviews are conducted in English in the UK and Mandarin in Taiwan, recorded with consent, and pseudonymised for privacy. Data analysis involves open coding, grouping excerpts into codes, and categorising codes. Axial coding connects codes into categories, leading to the development of a codebook. The process continues iteratively until theoretical saturation is reached. Finally, selective coding identifies the core topic, evaluating public-private cooperation against cyberattacks and its implications for social and policing strategies in the UK and Taiwan, which highlights the current status of the cybersecurity industry, governmental plans for cybersecurity, and contributions to cybersecurity from both government sectors and cybersecurity firms, with a particular focus on public-private partnerships. In summary, this research aims to offer practical recommendations to law enforcement, private sectors, and academia for reflecting on current strategies and tailoring future approaches in cybersecurity

Keywords: cybersecurity, cybercrime, public private partnerships, cyberattack

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Authors: Megan E. Davies

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With the intention of identifying cognitive processes uniquely involved in the dark triad personality traits of psychopathy, Machiavellianism, and narcissism, this study aimed to determine further potential differences and parameters of individual traits by explaining a statistically significant amount of variance between the constructs of manipulativeness, impulsiveness, grit, and need for cognition within the dark triad. Applying a cross-sectional design, N = 96 participants self-reported using the MACH-IV, SRP-III, NFC-S, and Grit Scale for Perseverance and Passion for Long-Term Goals. Hierarchical regression analyses showed that only manipulativeness predicted Machiavellianism, whereas manipulativeness and impulsiveness were found to have predictive qualities for psychopathy. Overall, these results found areas of discrepancy and overlap between manipulation and impulsivity regarding psychopathy and Machiavellianism. Additionally, this study serves to preliminarily eliminate the Need for Cognition and grit as predictive variables for Machiavellianism and psychopathy.

Keywords: Machiavellianism, psychopathy, manipulation, impulsiveness, need for cognition, grit, dark triad

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Authors: Alaina Caulkett, Audra Selkowitz, Lauren Harter, Aimee DeFoe

Abstract:

Educational robotics is an effective tool for teaching and learning STEM curricula. Yet, most traditional professional development programs do not cover engineering, coding, or robotics. This paper will give an overview of how and why the VEX Professional Development Plus Introductory Training courses were developed to provide guided, simple professional development in the area of robotics and computer science instruction. These training courses guide educators through learning the basics of VEX robotics platforms, including VEX 123, GO, IQ, and EXP. Because many educators do not have experience teaching robotics or computer science, this course is meant to simulate one on one training or tutoring through video-based instruction. These videos, led by education professionals, can be watched at any time, which allows educators to watch at their own pace and create their own personalized professional development timeline. This personalization expands beyond the course itself into an online community where educators at different points in the self-paced course can converse with one another or with instructors from the videos and learn from a growing community of practice. By the end of each course, educators are armed with the skills to introduce robotics or computer science in their classroom or educational setting. The design of the course was guided by a variation of the Understanding by Design (UbD) framework and included hands-on activities and challenges to keep educators engaged and excited about robotics. Some of the concepts covered include, but are not limited to, following build instructions, building a robot, updating firmware, coding the robot to drive and turn autonomously, coding a robot using multiple methods, and considerations for teaching robotics and computer science in the classroom, and more. A secondary goal of this research is to discuss how this professional development approach can serve as an example in the larger educational community and explore ways that it could be further researched or used in the future.

Keywords: computer science education, online professional development, professional development, robotics education, video-based instruction

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