Preface Thi s textbook is about signals and systems, a discipline rooted in the intellectual tradition of electrical engineering (EE). This tradition, however, has evolved in unexpected ways. EE has lost its tight coupling with the " electrical. " Electricity provides the impetus, the potential, but not the body of the subject. How else could microelectromechanical systems (MEMS) become so important in EE? Is this not mechanical engineering? Or signal processing? Is this not mathe-matics? Or digital networking? Is this not computer science? How is it that control system techniques are profitably applied to aeronautical systems, structural mechanics , electrical systems, and options pricing? This book approaches signals and systems from a computational point of view. It is intended for students interested in the modern, highly digital problems of electrical engineering, computer science, and computer engineering. In particular , the approach is applicable to problems in computer networking, wireless communication systems, embedded control, audio and video signal processing, and, of course, circuits. A more traditional introduction to signals and systems would be biased toward the latter application, circuits. It would focus almost exclusively on linear time-invariant systems, and would develop continuous-time models first, with discrete-time models then treated as an advanced topic. The discipline, after all, grew out of the context of circuit analysis. But it has changed. Even pure EE xiii xiv Preface graduates are more likely to write software than to push electrons, and yet we still recognize them as electrical engineers. The approach in this book benefits students by showing from the start that the methods of signals and systems are applicable to software systems, and most interestingly, to systems that mix computers with physical devices such as circuits, mechanical control systems, and physical media. Such systems have become pervasive, and profoundly affect our daily lives. The shift away from circuits implies some changes in the way the methodology of signals and systems is presented. While it is still true that a voltage that varies over time is a signal, so is a packet sequence on a network. This text defines signals to cover both. While it is still true that an RLC circuit is a system, so is a computer program for decoding Internet audio. This text defines systems to cover both. While for some systems the state is still captured adequately by variables in a differential equation, for many it is now the values in …
Applications of quantum mechanics have led to many successful predictions and explanations of puzzling phenomena, and we now apply quantum mechanics to gain, process, and communicate information in novel ways. We can understand quantum mechanics by understanding how we have applied it. We should not seek agreement on the nature of the world it represents, because this theory does not itself represent the physical world (though its applications do help us to represent it better). When applied to a quantum state, quantum mechanics yields probabiities for physical events: both state and probability are objective--not because they represent elements of phyiscal reality, but because each exerts norrmative authority over the beliefs of anyone who accepts quantum mechanics and applies it relative to a physical situation they may (but need not) occupy. These events may be described by statements that are meaningful in an appropriate environmental context, and quantum mechanics can help one to say when that is. Measurement creates an appropriate context, so here the Born rule indirectly yields probabilities of measurement outcomes. The quantum state of a system does not "collapse" on measurement: a new state must be assigned relative to a physical situation in which information about the outcome is accessible. Understood this way, there is no measurement problem, and violations of Bell inequalities does not demonstrate "spooky" non-local action. Quantum field theories have no physical ontology of their own: a quantum field is a mathematical object in a model whose application helps us to improve and extend our descriptions of the world in other terms. We cannot realise the scenario of Wigner's friend and its recent extensions: but the data that provide overwhelming evidence for quantum mechanics are objective in the same sense as the relative measurement outcomes described in those scenarios.
Esteban Parra, Sonia Haiduc, Preetha Chatterjee
et al.
Peer review is the main mechanism by which the software engineering community assesses the quality of scientific results. However, the rapid growth of paper submissions in software engineering venues has outpaced the availability of qualified reviewers, creating a growing imbalance that risks constraining and negatively impacting the long-term growth of the Software Engineering (SE) research community. Our vision of the Future of the SE research landscape involves a more scalable, inclusive, and resilient peer review process that incorporates additional mechanisms for: 1) attracting and training newcomers to serve as high-quality reviewers, 2) incentivizing more community members to serve as peer reviewers, and 3) cautiously integrating AI tools to support a high-quality review process.
Classical Electrodynamics in ponderable media remains defined by a century-long debate over force and energy localization. While the prevailing view treats competing formulations (Minkowski, Abraham, etc.) as equivalent conventions, this monograph argues that global conservation is insufficient for physical validity. A formulation must be mechanically coherent: power transfer must strictly equal the work rate of the force acting on the mass target. We formalize this requirement as the Force--Energy Consistency Criterion (FECC) -- a ``Kinematic Lock'' ($ P = \mathbf{f} \cdot \mathbf{v} $) -- and use it to audit standard macroscopic tensors. The analysis demonstrates that only the Macroscopic Vacuum (Lorentz) Formulation offers a mechanically consistent description of total energy-momentum transfer. The internal distribution of this energy is shown to be macroscopically indeterminate. By reinterpreting spatial averaging as spectral filtering, we reconstruct the theory from the microscopic baseline. This perspective identifies a universal host interface that routes electromagnetic energy into mechanical work, heat, and reversible storage, revealing a structural isomorphism where thermodynamics, mechanics, and electrodynamics emerge as coupled spectral projections.
This special issue introduces emerging intelligent healthcare technologies that incorporate big medical data, artificial intelligence, scientific computing, federated learning, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases, etc. Health monitoring and diagnosis for the target structure of interest are achieved through the interpretation of collected data. Advances in sensor technologies and data acquisition tools have led to a new era of big data, where massive amounts of medical data are collected by different sensors. This special issue offers valuable insights to researchers and engineers on designing intelligent bio-inspired Health 4.0 technologies and improving remote patient information delivery and care. By intelligently investigating and collecting large amounts of healthcare data (i.e., big data), sensors can enhance the decision-making process and help in early disease diagnosis. Hence, scalable machine learning, deep learning, and intelligent algorithms are needed to develop more interoperable solutions and make effective decisions in emerging sensor technologies. Optimization algorithms can be applied to acquire sensor data from multiple sources for fast and accurate health monitoring. In this special issue, seven manuscripts are published. The papers are directly or indirectly related to advanced clustering, imaging, and computing for bio-signal acquisition systems with intelligent computing.
Computer engineering. Computer hardware, Mechanics of engineering. Applied mechanics
Rehan Khan, Michał Wieczorowski, Abdel-Hamid I. Mourad
et al.
Erosion behavior of AISI 1045 carbon steel was investigated using slurry solutions with different viscosities (1 cP, 3 cP, and 8 cP) containing 5 wt% silica sand as erodent particles. Tests were carried out using a slurry pot apparatus with various rotational velocities and at three mounting angles (30°, 60°, and 90°). The qualitative and quantitative analysis was performed using the Taguchi design method, paint modeling, image processing, and microscopic imaging techniques. The results indicate that the erosion process in the slurry flow is significantly influenced by fluid viscosity. There is a notable decrease in erosion wear rate as fluid viscosity increases. An analysis of variance (ANOVA) test was conducted, concluding that viscosity and rotational speed are the significant factors influencing the weight loss of carbon steel. The results demonstrate that each factor has a major impact on the response; velocity (47.20 %) is the primary factor contributing to R, followed by viscosity (38.20 %). The erosive wear mechanism changed considerably with the variation in fluid viscosity and impact angles. As viscosity increases, the cutting and pitting erosion wear mechanism shift to sliding wear with the development of micro-perforation sites.
This study aims to investigate how the load, the intensity, and the polarity of electric current influence the frictional behavior and electrical resistance between a graphite pin loaded against a rotating copper disc. A pin-on-cylinder tribometer was utilized to achieve this. A gray relational grade obtained from gray relational analysis was employed to assess the performance characteristic in the Taguchi mixed L18 (2 1 x 3 2) method. The Taguchi design method determined the optimal control factors that affect the friction coefficient and electrical resistance. Analysis of variance (ANOVA) was employed to analyze the effects of the control parameters on the friction coefficient and electrical resistance of the contact. The experiment parameters included applied normal load (3, 5.5, and 8.5 N), electrical current (10, 25, and 30 A), and polarity (cathode and anode). The analysis results indicated that the polarity was the primary factor influencing the friction coefficient, while the electrical current was the most effective factor in the electrical resistance of the contact. The optimal control parameters for achieving the lowest friction coefficient values were X1Y3Z1, while for the lowest electrical resistance values were X2Y3Z3. Based on the gray relational analysis results, the optimal parameters for minimizing both the friction coefficient and electrical resistance were X1Y3Z1.
Engineering (General). Civil engineering (General), Mechanics of engineering. Applied mechanics
The paper gathers and unifies mechanical stability conditions for all symmetry classes of 3D and 2D materials under arbitrary load. The methodology is based on the spectral decomposition of the fourth-order stiffness tensors mapped to second-order tensors using orthonormal (Mandel) notation, and the verification of the positivity of the so-called Kelvin moduli. An explicit set of stability conditions for 3D and 2D crystals of higher symmetry is also included, as well as a Mathematica notebook that allows mechanical stability analysis for crystals, stress-free and stressed, of arbitrary symmetry under arbitrary loads.
Ulrich Römer, Stefan Hartmann, Jendrik-Alexander Tröger
et al.
In the framework of solid mechanics, the task of deriving material parameters from experimental data has recently re-emerged with the progress in full-field measurement capabilities and the renewed advances of machine learning. In this context, new methods such as the virtual fields method and physics-informed neural networks have been developed as alternatives to the already established least-squares and finite element-based approaches. Moreover, model discovery problems are starting to emerge and can also be addressed in a parameter estimation framework. These developments call for a new unified perspective, which is able to cover both traditional parameter estimation methods and novel approaches in which the state variables or the model structure itself are inferred as well. Adopting concepts discussed in the inverse problems community, we distinguish between all-at-once and reduced approaches. With this general framework, we are able to structure a large portion of the literature on parameter estimation in computational mechanics - and we can identify combinations that have not yet been addressed, two of which are proposed in this paper. We also discuss statistical approaches to quantify the uncertainty related to the estimated parameters, and we propose a novel two-step procedure for identification of complex material models based on both frequentist and Bayesian principles. Finally, we illustrate and compare several of the aforementioned methods with mechanical benchmarks based on synthetic and real data.
The fracture process of tungsten is dominated by the competition mechanism between the plastic deformation and the crack propagation near the crack tip. The non-Schmid (NS) effect, which considers the contribution of non-planar shear stress on the screw dislocation motion, is known to significantly influence the plastic deformation of tungsten at low and medium temperatures. However, how the NS effect influences the crack-tip plasticity and the fracture behavior of tungsten remains to be answered. In this work, the coupled crystal-plasticity and phase-field model (CP-PFM) was adopted to study the influence of the NS effect on the plastic deformation of un-notched tungsten and the fracture process of pre-notched tungsten at different temperatures. It was found that the lower the temperature, the more significant the NS effect on tungsten plasticity, which manifests in the lower yield stress and more unsymmetrical plastic deformation when the NS effect is considered. In contrast, the NS effect displayed the most obvious effect on the fracture behavior of pre-notched tungsten in the medium temperature regime, which manifested as higher fracture stress, a more significant crack-tip shielding effect, different fracture morphology, and lower crack propagation speed. The brittle fracture response at low temperature was not affected too much by the existence of the NS effect.
Aous Abd Al-jabar Hashim, Abdul Mun’em Abbas , Layth Abed
et al.
Ocean energy represented by waves is considered as a one of the renewable energy sources. This study aims to evaluate the methods that enhancing the ocean wave energy convertor performance. The mechanism of wave energy convertor is by converting mechanical energy to an electricity energy using DC generator and running by the pulling of wire due to ocean wave movement. Moreover, the test and analyze of converting the wave energy to electricity are conducted. Firstly, the role of numerical modeling lies in fabricating the tested rig in addition to study and analyze the buoyancy and stability in fluid mechanics as results of converting the kinetic energy derived from sea waves into rotational energy. The experimental tests were achieved locally at the Arabic gulf-South of Iraq/Basra (Khor Alzubayr). the tests were performed in two cases named: after happening the tidal (tested in one direction) and at the increasing of the sea water (tested in bidirectional). The results of local tests (at the sea) show that the maximum power of test was recorded value about 68 W in case of happening the tidal with an increase percentage of 92.6% over the case of bidirectional. These findings encouraging for more investigation in the methods that could increase energy harvesting from ocean waves since it is an enormous amount of energy.
Engineering machinery, tools, and implements, Mechanics of engineering. Applied mechanics