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This study introduces a novel approach for integrating a compact mechanism into the Marine Predator Algorithm (MPA), subsequently proposing innovative parallel and communication strategies. The synergistic combination of these methodologies substantially augments the global search efficiency and accelerates the convergence rate of the original MPA. The paper culminates in presenting an enhanced version of the Marine Predator Algorithm, termed PCMPA, which leverages compact parallel technology. The performance of PCMPA, alongside a range of comparative algorithms, is rigorously evaluated using the CEC2013 benchmark test functions. These comparative algorithms encompass recent variants of MPA, PSO, DE, and other newly developed algorithms. Evaluation results reveal that PCMPA outperforms its counterparts in a more extensive array of test functions. To corroborate PCMPA's efficacy in real-world scenarios, the algorithm is applied to parameter optimization in Backpropagation neural network (BNN) and targeted engineering optimization challenges. This application demonstrates that PCMPA consistently achieves enhanced performance in practical implementations. • The study presents a novel variant of the Marine Predators Algorithm, dubbed PCMPA. • The paper benchmarks PCMPA against other Marine Predators Algorithm variants and other Algorithms. • The research applies PCMPA to optimize parameters of BNNs and to tackle engineering optimization challenges. [ABSTRACT FROM AUTHOR]

Purpose: Numerous challenges in education emerge as our technology-driven society rapidly evolves and manifests more exigent requirements from engineering professionals. Higher education, nonetheless, seems to adapt to such requirements at an unequal speed, generating some tensions between industry and higher education institutions. The purpose of this paper is to share the experiences obtained through a process of assessment and redesign of a large enrollment course of programming from which the authors developed a systematic approach for course design/redesign. Design/methodology/approach: A mixed method approach was deployed for data gathering and evaluation, consisting of close-ended surveys, open-ended questionnaires, information matrices and state of the art compilation. Triangulation of the information offered clear data about the necessity of curriculum redesign; therefore, a new programming course curriculum encompassed with relevant necessities in engineering and science was developed. Findings: The authors produced a coherent and dynamic systematic path for assessment and design/redesign of course curriculum, which the authors find extremely helpful to improve negotiation processes inside higher education institutions, as it can be implemented to improve any large enrollment course curricula in engineering and science. Research limitations/implications: By following the systematic path for assessment and design/redesign of curricula the authors developed, higher education systems could embark more efficiently in the ever-challenging process of adapt their courses and programs to tackle the upcoming demands of our society. Originality/value: So far, a systematic path for assessment and design/redesign of course curriculum was not published, and it supports the improvement of pedagogical approaches in academic institutions. [ABSTRACT FROM AUTHOR]

The article discusses the role that necessity played in the invention of paperweights from the late 19th century through the 1950s in the U.S., including the electrical engineer Charles P. Steinmetz's use of ad-hoc paperweights throughout his career. An overview of various items used to hold down paper, including rounded stones and horseshoes, is provided.

The author reflects on the topics he's written about in the 25 years of writing for the journal. He states that nearly half of his articles focus either on bridges or on common and the design of often small items found in everyday life. He mentions how his father got him interested in design and engineering by his fascinating on details on where containers came from. He talks about his fascinating with bridges which started when writing his book "To Engineer is Human."

The nature of the real-world problem is multi-modal and multidimensional. This paper proposes a novel metaheuristic algorithm based on social behaviors of people acquiring favorable information, which is the society-based metaheuristic optimization mechanism, called the Information-Decision Search Algorithm (IDSE), aiming to provide a new optimization technology for solving real-world optimization problems. This optimization technology proposes special searching mechanisms of delivery behavior, approaching behavior, inheritance behavior, mutation behavior, interaction, and learning behavior, establishing corresponding mathematical models to develop an efficient optimization framework for solving constrained optimization. The performance of the proposed algorithm and 10 state-of-the-art optimizers is evaluated on 46 benchmarks, including convergence, solution accuracy, robustness, diversity, significance, and the dimensional-scalability on CEC 2017 benchmarks (50 Dim and 100 Dim). The statistical results suggest, with the dimensionality of the problem variable increasing, the computing efficiency of the proposed optimization technology keeps on the highest level at all times. The low-rank feature for IDSE on 46 benchmarks emphasizes the selective priority in solving the same optimization problem. In addition, IDSE also considers 7 real-world engineering problems. The comparison results suggest that IDSE is superior to competitive algorithms in improving solution accuracy and reducing optimization costs, indicating the significant performance for solving constraint optimization. [ABSTRACT FROM AUTHOR]

The article explores the issue of jamming in technology as of February 2018, highlighting paper jams that plague printer engineers. Topics include Xerox Corp.'s efforts to solve the paper jam issue, the invention of the printing press around 1440 by Johannes Gutenberg, and xerography invented by Chester Carlson.

This paper studies the exponential input-to-state stability under events (called as exponential ISS under events) for hybrid dynamical networks (HDNs) with coupling time-delays. Notions of input-to-state exponent, exponential ISS under events, and uniform exponential ISS under events are proposed. The exponential ISS under events and the uniform case are studied according to whether the flow gain is a small-gain or not. When the flow gain is a small-gain, Halanay-type ISS Lemmas are firstly established and used to derive criteria of exponential ISS under events and uniform exponential ISS under events. And the minimal dwell time between two consecutive events required for HDNs to achieve uniform exponential ISS under events is estimated. When the flow gain may be not a small-gain, by the method of Lyapunov–Krasovskii functional and M -matrix theory, criteria of exponential ISS under events and uniform exponential ISS under events are also established. And the maximal dwell time between two consecutive events is given for the uniform case. All conditions and results on the uniform case are easily checkable. Examples are given through the paper to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a new algebraic approach to the on-line signal derivatives estimation is proposed. The proposed approach is based on the conversion of the truncated Taylor series expansion to the set of linearly independent equations regarding the signal derivatives. The nonhomogeneous parts of the obtained set of equations are convolution integrals, which can be transformed to the stable linear state-space filter realization. The proposed algebraic estimator provides stable convergence without the need for periodic re-initialization, as in the case of the conventional algebraic estimators. In contrast to the Taylor series-based tracking differentiators, the proposed estimator also provides an estimation of the arbitrary number of the higher-order signal derivatives. In addition, the tuning of the estimator parameters does not depends on the filter dimension. The efficiency of the proposed estimator is illustrated by the simulation examples and experimental results related to the monitoring of the surgical drilling process. [ABSTRACT FROM AUTHOR]

Abstract This paper studies the global asymptotic stability of a class of interval fractional-order (FO) nonlinear systems with time-delay. First, a new lemma for the Caputo fractional derivative is presented. It extends the FO Lyapunov direct method allowing the stability analysis and synthesis of FO nonlinear systems with time-delay. Second, by employing FO Razumikhin theorem, a new delay-independent stability criterion, in the form of linear matrix inequality is established for ensuring that a system is globally asymptotically stable. It is shown that the new criterion is simple, easy to use and valid for the FO or integer-order interval neural networks with time-delay. Finally, the feasibility and effectiveness of the proposed scheme are tested with a numerical example. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we investigate the incremental H ∞ performance problem for a class of stochastic switched nonlinear systems by using a state-dependent switching law and the maximum and minimum dwell time approach. By resorting to the state-dependent switching law, some sufficient conditions are provided to cope with the incremental H ∞ performance problem, which can be applied even if all subsystems are unstable. Then, based on the maximum and minimum dwell time scheme, the incremental H ∞ performance problem to be solvable is derived for two cases: one is all subsystems are incrementally globally asymptotically stable in the mean(IGASiM), another is both IGASiM subsystems and unstable subsystems coexist. When all subsystems are IGASiM, the stochastic switched nonlinear system is IGASiM and possesses a incremental L 2 -gain under given conditions. When both IGASiM subsystems and unstable subsystems coexist, if the activation time ratio between IGASiM subsystems and unstable ones is not less than a specified constant, the sufficient conditions for the incremental H ∞ performance of the stochastic switched nonlinear system are given. Two numerical examples are given to illustrate the validity of methods proposed. [ABSTRACT FROM AUTHOR]

Abstract The paper is dedicated to solving the generalized periodic discrete-time coupled Sylvester matrix equation, which is frequently encountered in control theory and applied mathematics. The solvable condition and a iterative algorithm for this equation are presented. The proposed method is developed from a point of least squares method. The rationality of the method is testified by theoretical analysis, which shows that the algorithm can solve the problem within finite number of iterations. The presented approach is numerically reliable and requires less computation. A numerical example illustrates the effectiveness of the raised result. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a novel robust control strategy based on disturbance-compensation-gain (DCG) construction approach is proposed for small-scale unmanned helicopters in the presence of high-order mismatched disturbances. The overall control structure consists of two hierarchical layers. The inner-loop controller is to guarantee the stability of the unmanned helicopters subject to high-order mismatched disturbances. With the estimation of the disturbances and their successive derivatives via finite-time disturbance observer (FTDO), by properly designing some disturbance compensation gains, a novel robust controller is developed to remove the high-order mismatched disturbances from the output channels. The outer-loop controller is to produce flight commands for inner-loop system, as well as to track the reference trajectory, which is carried out with the dynamic inversion technique. The simulation results demonstrate that the unmanned helicopters are capable to perform flight missions autonomously with the proposed control strategy. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a practical technology or solution of quality-related fault diagnosis is provided for nonlinear and dynamic process. Unlike traditional data-based fault diagnosis methods, the alternative approach is focused more on identifying the propagation path that combines diagnostic information and process knowledge. The new method addresses the quality-related fault detection issue with developed nonlinear dynamic latent variable model for extracting nonlinear latent variables that exhibit dynamic correlations, then the advantage of relative reconstruction based contribution approach is followed to analyze the potential root-cause variables. Meanwhile, a new partitioned Bayesian network methodology is proposed for propagation path identification of quality-related faults. Finally, the whole proposed framework is applied to a real hot strip mill process, where the effectiveness is further demonstrated from real industrial data. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we investigate the asymptotic stability of fractional-order fuzzy neural networks with fixed-time impulse and time delay. According to the fractional Barbalat's lemma, Riemann–Liouville operator and Lyapunov stability theorem, some sufficient conditions are obtained to ensure the asymptotic stability of the fractional-order fuzzy neural networks. Two numerical examples are also given to illustrate the feasibility and effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Abstract This paper focuses on the parameter estimation problem of multivariate output-error autoregressive systems. Based on the decomposition technique and the auxiliary model identification idea, we derive a decomposition based auxiliary model recursive generalized least squares algorithm. The key is to divide the system into two fictitious subsystems, the one including a parameter vector and the other including a parameter matrix, and to estimate the two subsystems using the recursive least squares method, respectively. Compared with the auxiliary model based recursive generalized least squares algorithm, the proposed algorithm has less computational burden. Finally, an illustrative example is provided to verify the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Abstract In this paper, the problem of finite-horizon H ∞ state estimation is investigated for a class of discrete time-varying complex networks with multiplicative noises and random coupling strengths. The network nodes and estimators are connected via a constrained communication network which allows only one node to send measurement data at each transmission instant. The Round-Robin protocol is introduced to determine which node obtains the access to the network at certain transmission instant. The aim of the addressed problem is to design a set of time-varying estimator parameters such that the prescribed H ∞ performance is guaranteed over a finite horizon. By using the stochastic analysis approach and completing-the-square method, sufficient conditions are derived for the existence of the desired estimators in terms of the solution to backward recursive Riccati difference equations. Finally, a numerical example is provided to validate the feasibility and effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the positive filter design problem for a class of continuous-discrete Roesser model in Takagi-Sugeno fuzzy form. Both the observer-based and the general form of filters are designed with l 1 performance constraint. By utilizing the co-positive Lyapunov function approach, sufficient criteria are derived in the form of linear programming, which not only guarantee the existence of the positive lower-bounding/upper-bounding filters but also assure the resulting filtering error system to be asymptotically stable and having a prescribed l 1 -gain performance index. In addition, the explicit design schemes for the corresponding filter parameters are also presented. Finally, two numerical examples are provided to illustrate effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a new reaching law based sliding mode control strategy for discrete time systems is introduced. Contrary to most existing approaches, the new strategy uses a sliding variable with relative degree two. It is demonstrated that the new reaching law drives the sliding variable to a narrower quasi-sliding mode band than its relative degree one equivalent, while simultaneously ensuring the desired dynamic properties of the system. Furthermore, it is shown that the smaller quasi-sliding mode band width is reflected in reduced magnitude of all state variables in the sliding mode. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to study heat and mass transfer in copper-water and silver-water nanofluid flow over stretching sheet placed in saturated porous medium with internal heat generation or absorption. The authors further introduce a new algorithm for solving heat transfer problems in fluid mechanics. The model used for the nanofluid incorporates the nanoparticle volume fraction parameter and a consideration of the chemical reaction effects among other features. Design/methodology/approach – The partial differential equations for heat and mass transfer in copper-water and silver-water nanofluid flow over stretching sheet were transformed into a system of nonlinear ordinary differential equations. Exact solutions for the boundary layer equations were obtained in terms of a confluent hypergeometric series. A novel spectral relaxation method (SRM) is used to obtain numerical approximations of the governing differential equations. The exact solutions are used to test the convergence and accuracy of the SRM. Findings – Results were obtained for the fluid properties as well as the skin friction, and the heat and mass transfer rates. The results are compared with limiting cases from previous studies and they show that the proposed technique is an efficient numerical algorithm with assured convergence that serves as an alternative to numerical methods for solving nonlinear boundary value problems. Originality/value – A new algorithm is used for the first time in this paper. In addition, new exact solutions for the energy and mass transport equations have been obtained in terms of a confluent hypergeometric series. [ABSTRACT FROM AUTHOR]

In this paper, we present a distance-based framework for DL-Lite based on the notion of features. Within this framework, we propose a distance-based paraconsistent semantics for DL-Lite where meaningful conclusions can be rationally drawn even from an inconsistent knowledge base and we develop a distance-based inconsistency measurement for DL-Lite to provide more informative metrics which can tell the differences between axioms causing inconsistency and among inconsistent knowledge. Furthermore, we investigate several important logical properties (e.g., consistency preservation, closure consistency, splitting property etc.) of the entailment relation based on the new semantics and show its advantages in non-monotonic reasoning for DL-Lite. Finally, we show that our two distance-based inconsistency measures are basic inconsistency measures where some good properties hold such as Free Axiom Independence and Dominance of inconsistency etc. [ABSTRACT FROM AUTHOR]

Sport is one of the activities of human being where cooperative, competitive, self-learning and interactive environment helps in the overall improvement of the performance. These learning processes are very effective to regulate the players in a good direction as well as to enhance their capability of exploring the new techniques. Particle Swarm Optimization (PSO) is a popular stochastic optimization algorithm, used for solving real-world engineering problems. However, it usually suffers from local confinement and easily loses its diversity. In this paper, we have integrated the properties of sports with PSO algorithm and proposed an efficient player selection strategy based diversified PSO (EPS-dPSO), which improves the fitness and robustness of the technique without compromising the computational complexity of the algorithm. The properties of player selection is adopted to enhance the diversity within the search phase as well as to incorporate intense searching of the space. We have comprehensively evaluated the performance of proposed EPS-dPSO by applying it on standard benchmark problems. Experimental result shows that it not only tracks the global optimum within the small search interval but also able to obtain good result for large and asymmetrical search space and also insensitive to initialization of the problems. Further, tests are carried out on the benchmark functions from CEC2005, the large dimensional problems of CEC2008 and some real world problems from CEC2011. All the experimental results indicate the effectiveness and efficiency of the proposed EPS-dPSO compared to other traditional algorithms. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present a simple approach for calculation of the sensitivities in the free-form inverse design problems. The approach is based on the analogy with the similar tasks used in the signal-processing analysis. In the proposed case it is not required to solve an adjoint problem as in the most of the similar optimization tasks. The simulation engine used in the background is a Fast Boundary Element Method. The approach is validated on some known benchmark problems. Design/methodology/approach – Inverse design is recognized nowadays as a crucial scientific grand challenge. Contrary to the conventional approach (“Given the structure, find the properties”) it purses a new paradigm (“Given the desired property, find the structure”). Inverse class of problems has a broad application area, from the material-, medical-, bio- to the engineering-class of problems. When dealing with the inverse design in free-form optimization of the engineering problems the typical approach is to calculate the adjoint problem. Calculation of the adjoint problem mostly requires the costly calculation of the gradients, which makes the whole optimization procedure rather expensive due to the high computational burden required for their solution. Findings – In this paper it is proposed a novel Simple Sensitivity Approach to get in a fast way the response (sensitivity) function of the analyzed structure. The simulation engine used in the background is the Fast Boundary Element Method. Originality/value – Novel approach for inverse design when performing the free-form optimization of engineering problems. [ABSTRACT FROM AUTHOR]

Diagnosability is an important property that determines at the design stage how accurate any diagnosis algorithm can be on a partially observable system and thus has significant economic impact on the improvement of performance and reliability of complex systems. Very recently distributed approaches for diagnosability began to be investigated since centralized approaches are not realistic for large systems due to the combinatorial explosion of the search space. In this paper, we propose a new optimized algorithm for pattern diagnosability analysis of distributed systems with modular structure, where we obtain the original pattern diagnosability information from the relative components before abstracting the sufficient and necessary information to be propagated to other connected components. Then, the diagnosability decision can be made after global consistency checking at the proper level of the subsystem involved. Our experimental results and complexity analysis illustrate the correctness and efficiency of our approach both in a practical and theoretical way. Finally, we distinguish our work by presenting related works before the conclusion. [ABSTRACT FROM AUTHOR]

Multi-objective optimization (MOO) is an important research topic in both science and engineering. This paper proposes a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA). We combine the memory of the best states of individual particles and their population in their evolution paths and the gravitational rules to construct a new search strategy. Under this strategy, the position and mass states of each particle are updated based on the memory associated with it and the current states of all particles in the current population in terms of their gravitational forces on it. A novel diversity-enhancement mechanism is also employed to control the velocity of each particle for traveling to a new position. Experiments were conducted on 12 well-known benchmark functions, and for each function the results of DMMOGSA were compared with those of SPEA2, NSGA-II and MOPSO. Our results show that DMMOGSA can reduce the effect of premature convergence and achieve more reliable performance on most of the tested cases. [ABSTRACT FROM AUTHOR]

In this paper we show that an enriched continuum model of the micromorphic type (Relaxed Micromorphic Model) can be used to model metamaterials' response in view of their use for meta-structural design. We focus on the fact that the reduced model's structure, coupled with the introduction of well-posed interface conditions, allows us to easily test different combinations of metamaterials' and classical-materials bricks, so that we can eventually end-up with the conception of a meta-structure acting as a mechanical diode for low/medium frequencies and as a total screen for higher frequencies. Thanks to the reduced model's structure, we are also able to optimize this meta-structure so that the diode-behaviour is enhanced for both "pressure" and "shear" incident waves and for all possible angles of incidence. • The importance of disposing of a reduced model to enable the effective use of metamaterials in meta-structural design. • An enriched continuum model of the micromorphic type can be effectively used to model metamaterials' response, even for specimens of finite size. • The reduced model's structure, coupled with the introduction of well-posed interface conditions allows us to unveil the response of meta-structures combining metamaterials and classical-materials bricks. • The conception of a simple metamaterial/classical-material structure that acts as a mechanical diode for low/medium frequencies and as a total screen for higher frequencies. [ABSTRACT FROM AUTHOR]

Bloch theorem is useful for analyzing wave propagation in periodic systems. It has been widely used to determine the energy bands of various translationally-periodic crystals and with the advent of nanoscale structures like nanotubes, it has been extended to account for additional symmetries using group theory. However, this extension is restricted to Hamiltonian systems with analytical potentials. For complex problems, as for engineering structures, the periodic unit cells are often discretized and the Bloch method is restricted to translational periodicity. The goal of this paper is to generalize the direct and transfer-matrix propagation Bloch method to structures with glide and screw symmetries by deriving appropriate boundary conditions. Dispersion relations for a set of reduced problems are compared to results from the classical method, when available. It is found that (i) the dispersion curves are easier to interpret, (ii) the computational cost and error are reduced, and (iii) revisited Bloch method is applicable to structures as the Boerdijk–Coxeter helix that do not possess purely-translational symmetries for which the classical method is not applicable. [ABSTRACT FROM AUTHOR]

System-of-systems (SoS) engineering involves a complex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems may possibly satisfy SoS capability objectives. The key issue is how to model such requirements to automate the process of analysis and assessment. This paper suggests a meta-model that defines both functional and nonfunctional features of SoS requirements for command and control, communication, computer, intelligence, surveillance reconnaissance (C4ISR) systems. A domain-specific modeling language is defined by extending unified modeling language (UML) constructed of class and association with fuzzy theory in order to model the fuzzy concepts of performance requirements. An efficiency evaluation function is introduced, based on Bezier curves, to predict the effectiveness of systems. An algorithm is presented to transform domain models in fuzzy UML into a requirements ontology in description logic (DL) so that requirements verification can be automated with a popular DL reasoner such as Pellet. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to validate the variational iteration method (VIM) is suitable for various nonlinear equations. Design/methodology/approach – The He’s VIM is applied to solve nonlinear equation which is derived from actual engineering problem. The result was compared with other method. Findings – The result obtained from VIM shows good agreement with Xu’s result which provide a solid evidence that VIM is convenient and effective for solving nonlinear equation in the engineering. Originality/value – The VIM can be extended to many academic and engineering fields for nonlinear equations solving. [ABSTRACT FROM AUTHOR]

Probabilistic causal interaction models have become quite popular among Bayesian-network engineers as elicitation of all probabilities required often proves the main bottleneck in building a real-world network with domain experts. The best-known interaction models are the noisy-OR model and its generalisations. These models in essence are parameterised conditional probability tables for which just a limited number of parameter probabilities are required. The models assume specific properties of intercausal interaction and cannot be applied uncritically. Given their clear engineering advantages however, they are subject to ill-considered use. This paper demonstrates that such ill-considered use can result in poorly calibrated output probabilities from a Bayesian network. By studying, in an analytical way, the propagation effects of noisy-OR calculated probability values, we identify conditions under which use of the model can be harmful for a network's performance. These conditions demonstrate that use of the noisy-OR model for mere pragmatic reasons is sometimes warranted, even when the model's underlying assumptions are not met in reality. [ABSTRACT FROM AUTHOR]

Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current–voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamics of two models of jerk equations: The first one which is very simple and driven by an external constant signal, and the second one more complicated with an external periodic excitation. These particular equations are very important mathematical models of physical systems, with broad range applications in engineering, namely in electronic and telecommunication to generate the trains of regular and chaotic pulses. Although regular pulses are useful for the modulation of signals, the chaotic one can be used for the signal masking and modulations. The simplest jerk equation is chosen in the literature, while the periodic driven one is derived from Kirchhoff laws applied on a real electronic circuit conveniently built. The existence and uniqueness of their solutions are verified from the fixed- point theorem. Particularly by using the two parameters perturbation methods usually applied to find solitons, the periodic solutions are found, and proved to be sensitive to nonlinearity parameter and the external signal voltage's amplitudes. The numerical investigations are next performed proving the existence of some interesting results such as the bubble bifurcation and the generation of chaotic pulses. Pspice and real experiments are performed on the periodic driven version of jerk equation in order to verify theoretical investigations. [ABSTRACT FROM AUTHOR]

• Research highlights the influence of AM over PANI memristive device conductance. • Research highlights the influence of FM over PANI memristive device conductance. • Research highlights the influence of PWM over PANI memristive device conductance. This paper is dedicated to the experimental study of learning properties of systems, based on polyaniline (PANI) memristive devices. Signals with different forms, amplitudes, frequencies have been used as external stimuli and it has been demonstrated their different influence over memristive device conductance. According to the obtained results, pulse width modulation seems the most adequate method for the implementation of neuromorphic circuits. [ABSTRACT FROM AUTHOR]

The article focuses on investigating potential misconduct regarding changes in the papers' author lists and other information. Topics discussed include guidelines under Fundamental Canon 5 of the American Society of Civil Engineers (ASCE) Code of Ethics; providing credit for engineering work; and need for engineers to be objective and truthful in professional reports, statements, or testimony.

An interview with Special Libraries Association (SLA) member, Sarah Shujah is presented. When asked about what inspired her to write her paper on Library Hackfest she said that the topic would help in computer science, engineering librarians, and integration of information literacy. Shujah spoke about her interest in libraries from childhood and how she realized her long term goal of becoming a librarian. She discussed about her plans for 2015 and her interests in information literacy.

The article offers information on the Engineering Festival (E-fest) program of American Society of Mechanical Engineers (ASME) which features more than 500 students to the campus of the University of Nevada, Las Vegas, in March 2017. It mentions student competitions held during E-Fest West included the Student Design Competition and the ASME Old Guard competitions, plus an informal team-building competition with CDs, cardboard and rubber bands as core components.

The aticle discusses COVID-19 has introduced a number of hardships on bulk material handlers, including limiting options for critical training to improve conveyor safety and productivity. Topics include the views of Todd Swinderman, Chief Execuitive Officier Emeritus of Martin Engineering, on industry; and upon completion, attendees have eligible to receive either Professional Development Unit or Continuing Education Unit credits.

The article reflects on the changes in the heating, ventilating, and air conditioning (HVAC) industry since the 1960s. Topics covered include the use of drafting paper to design plastic templates and lay out sheet metal and pipe design. Also mentioned is the importance of technological advancements to seamlessly integrate design with operation, construction and maintenance of HVAC systems.

The article discusses papers published within the issue, including an article by Matthew Franchek on the technologies used in subsea engineering, another by Egidio Marotta on a design process that uses predictive tools for the design of undersea components and one by Phaneendra Kondapi on engineering solutions for flow assurance.