Hasil untuk "Acoustics in engineering. Acoustical engineering"

Mandip Goswami

Room acoustics analysis plays a central role in architectural design, audio engineering, speech intelligibility assessment, and hearing research. Despite the availability of standardized metrics such as reverberation time, clarity, and speech transmission index, accessible tools that combine rigorous signal processing with intuitive visualization remain scarce. This paper presents AcoustiVision Pro, an open-source web-based platform for comprehensive room impulse response (RIR) analysis. The system computes twelve distinct acoustic parameters from uploaded or dataset-sourced RIRs, provides interactive 3D visualizations of early reflections, generates frequency-dependent decay characteristics through waterfall plots, and checks compliance against international standards including ANSI S12.60 and ISO 3382. We introduce the accompanying RIRMega and RIRMega Speech datasets hosted on Hugging Face, containing thousands of simulated room impulse responses with full metadata. The platform supports real-time auralization through FFT-based convolution, exports detailed PDF reports suitable for engineering documentation, and provides CSV data export for further analysis. We describe the mathematical foundations underlying each acoustic metric, detail the system architecture, and present preliminary case studies demonstrating the platform's utility across diverse application domains including classroom acoustics, healthcare facility design, and recording studio evaluation.

Fahim Hafiz, Md Jahidul Hoq Emon, Md Abid Hossain et al.

This paper proposes a novel curriculum for the microprocessors and microcontrollers laboratory course. The proposed curriculum blends structured laboratory experiments with an open-ended project phase, addressing complex engineering problems and activities. Microprocessors and microcontrollers are ubiquitous in modern technology, driving applications across diverse fields. To prepare future engineers for Industry 4.0, effective educational approaches are crucial. The proposed lab enables students to perform hands-on experiments using advanced microprocessors and microcontrollers while leveraging their acquired knowledge by working in teams to tackle self-defined complex engineering problems that utilize these devices and sensors, often used in the industry. Furthermore, this curriculum fosters multidisciplinary learning and equips students with problem-solving skills that can be applied in real-world scenarios. With recent technological advancements, traditional microprocessors and microcontrollers curricula often fail to capture the complexity of real-world applications. This curriculum addresses this critical gap by incorporating insights from experts in both industry and academia. It trains students with the necessary skills and knowledge to thrive in this rapidly evolving technological landscape, preparing them for success upon graduation. The curriculum integrates project-based learning, where students define complex engineering problems for themselves. This approach actively engages students, fostering a deeper understanding and enhancing their learning capabilities. Statistical analysis shows that the proposed curriculum significantly improves student learning outcomes, particularly in their ability to formulate and solve complex engineering problems, as well as engage in complex engineering activities.

Bertrand Meyer

Software engineering concepts and processes are worthy of formal study; and yet we seldom formalize them. This "research ideas" article explores what a theory of software engineering could and should look like. Software engineering research has developed formal techniques of specification and verification as an application of mathematics to specify and verify systems addressing needs of various application domains. These domains usually do not include the domain of software engineering itself. It is, however, a rich domain with many processes and properties that cry for formalization and potential verification. This article outlines the structure of a possible theory of software engineering in the form of an object-oriented model, isolating abstractions corresponding to fundamental software concepts of project, milestone, code module, test and other staples of our field, and their mutual relationships. While the presentation is only a sketch of the full theory, it provides a set of guidelines for how a comprehensive and practical Theory of Software Engineering should (through an open-source community effort) be developed.

Xiaowen Tao, Yinuo Wang, Jinzhao Zhou

End-to-end reinforcement learning (RL) for motion control trains policies directly from sensor inputs to motor commands, enabling unified controllers for different robots and tasks. However, most existing methods are either blind (proprioception-only) or rely on fusion backbones with unfavorable compute-memory trade-offs. Recurrent controllers struggle with long-horizon credit assignment, and Transformer-based fusion incurs quadratic cost in token length, limiting temporal and spatial context. We present a vision-driven cross-modal RL framework built on SSD-Mamba2, a selective state-space backbone that applies state-space duality (SSD) to enable both recurrent and convolutional scanning with hardware-aware streaming and near-linear scaling. Proprioceptive states and exteroceptive observations (e.g., depth tokens) are encoded into compact tokens and fused by stacked SSD-Mamba2 layers. The selective state-space updates retain long-range dependencies with markedly lower latency and memory use than quadratic self-attention, enabling longer look-ahead, higher token resolution, and stable training under limited compute. Policies are trained end-to-end under curricula that randomize terrain and appearance and progressively increase scene complexity. A compact, state-centric reward balances task progress, energy efficiency, and safety. Across diverse motion-control scenarios, our approach consistently surpasses strong state-of-the-art baselines in return, safety (collisions and falls), and sample efficiency, while converging faster at the same compute budget. These results suggest that SSD-Mamba2 provides a practical fusion backbone for resource-constrained robotic and autonomous systems in engineering informatics applications.

Alexandros Gazis, Ioannis Papadongonas, Athanasios Andriopoulos et al.

This article provides a comprehensive overview of sensors commonly used in low-cost, low-power systems, focusing on key concepts such as Internet of Things (IoT), Big Data, and smart sensor technologies. It outlines the evolving roles of sensors, emphasizing their characteristics, technological advancements, and the transition toward "smart sensors" with integrated processing capabilities. The article also explores the growing importance of mini-computing devices in educational environments. These devices provide cost-effective and energy-efficient solutions for system monitoring, prototype validation, and real-world application development. By interfacing with wireless sensor networks and IoT systems, mini-computers enable students and researchers to design, test, and deploy sensor-based systems with minimal resource requirements. Furthermore, this article examines the most widely used sensors, detailing their properties and modes of operation to help readers understand how sensor systems function. The aim of this study is to provide an overview of the most suitable sensors for various applications by explaining their uses and operations in simple terms. This clarity will assist researchers in selecting the appropriate sensors for educational and research purposes or understanding why specific sensors were chosen, along with their capabilities and possible limitations. Ultimately, this research seeks to equip future engineers with the knowledge and tools needed to integrate cutting-edge sensor networks, IoT, and Big Data technologies into scalable, real-world solutions.

Jianjun Zhao

Quantum computing has demonstrated the potential to solve computationally intensive problems more efficiently than classical methods. Many software engineering tasks, such as test case selection, static analysis, code clone detection, and defect prediction, involve complex optimization, search, or classification, making them candidates for quantum enhancement. In this paper, we introduce Quantum-Based Software Engineering (QBSE) as a new research direction for applying quantum computing to classical software engineering problems. We outline its scope, clarify its distinction from quantum software engineering (QSE), and identify key problem types that may benefit from quantum optimization, search, and learning techniques. We also summarize existing research efforts that remain fragmented. Finally, we outline a preliminary research agenda that may help guide the future development of QBSE, providing a structured and meaningful direction within software engineering.

Thomas J. Misa

The field of software engineering is embedded in both engineering and computer science, and may embody gender biases endemic to both. This paper surveys software engineering's origins and its long-running attention to engineering professionalism, profiling five leaders; it then examines the field's recent attention to gender issues and gender bias. It next quantitatively analyzes women's participation as research authors in the field's leading International Conference of Software Engineering (1976-2010), finding a dozen years with statistically significant gender exclusion. Policy dimensions of research on gender bias in computing are suggested.

Xiaopeng Kong, Yan Huang, Jingyi Wang

N owadays, underwater acoustic target recognition (UATR) is a core technology in underwater acoustics. Identifying the underwater target from the complex marine background noise is critical to gain an acoustic advantage in underwater confrontation. To tackle the problem at its source, this paper proposes a deep learning model to improve target recognition capability based on the convolutional neural network (CNN) model with a preemphasis filter (PEF) module (herein presented as PEF+CN $N$ model). This model learns the fluctuations and differences between ship targets and multiple marine background noises. It then enhances the time-frequency spectrum quality and the signal-to-noise ratio (SNR) in a data-driven way. Finally, comparative experiments were conducted to validate the improvements of the proposed model. The results showed that the spectral feature is more pronounced than the original condition. Moreover, the overall and the single-class recognition accuracy also increased compared with the same CNN model without PEF, confirming the intelligence of the proposed model and offering the feasibility for more practical engineering applications.

Joseph Daliwa Bainamndi, E. Siryabe, G. Ntamack et al.

This study deals with 3D printing multilayered micro-perforated panels (M-MPPs) coupled with buildings materials as compressed earth block for noise reduction applications. The sound absorption coefficient α is utilized as a metric to assess the sound insulation capabilities across a frequency range spanning from 10 to 3000 Hz, then evaluated and validated by numerical and experimental methods. The FEM model developed makes it possible to predict the acoustic absorption of M-MPPs by tuning the frequency range and varying optimized acoustics parameters, considering hole-hole interaction and taking into account visco-thermal effects that are present in compressed earth blocks. It is shown that the shape of perforations and material properties including the porosity rate, arrangement in the design of multilayer micro-perforated structures are identified to play a significant role in the sound performance of the entire structure. In addition, the application of MPP coupled with compressed earth blocks improve the sound absorption capacity of the composite structure. The developed FEM leads to accurate prediction of performance, efficient optimization, and cost effectiveness. Finally, the present study reveals the importance of M-MPPs combined with compressed earth blocks (CEBs) as viable noise reduction materials, particularly relevant for engineering applications and development initiatives in emerging economies.

Le Liu, Long-Xiang Xie, Weichun Huang et al.

Sound absorption is important for room acoustics and remediation of noise. Acoustic metamaterials have recently emerged as one of the most promising platforms for sound absorption. However, the working bandwidth is severely limited because of the strong dispersion in the spectrum caused by local resonance. Utilizing the coupling effect among resonators can improve the absorbers' performance, but the requirement of collecting coupling effects among all resonators, not only the nearest-neighbor coupling, makes the system too complex to explore analytically. This Letter describes deep learning based acoustic metamaterials for achieving broadband sound absorption with no visible oscillation in a targeted frequency band. We numerically and experimentally achieve an average absorption coefficient larger than 97% within the ultra-broadband extending from 860 to 8000 Hz, proving the validity of the deep learning based acoustic metamaterials. The excellent ultra-broadband and near-perfect absorption performance allows the absorber for versatile applications in noise-control engineering and room acoustics. Our work also reveals the significance of modulating coupling effects among resonators, and the deep learning approach may blaze a trail in the design strategy of acoustic functional devices.

Xuedong Huang, Alex Acero, H. Hon et al.

Constantin Bîrțan, D. Popa, D. Selișteanu et al.

It is known that the acoustics of a performance hall are important for the performance of artistic events. The paper presents a methodology for determining and analysing the acoustic parameters for a performance hall under construction. First, the room was three-dimensionally scanned to obtain a geometric model in a virtual environment. The initial "points cloud" was processed using specific reverse engineering techniques and methods. Thus, irregularities of a geometric nature, such as non-conforming surfaces, spikes and self-intersections, were eliminated. Also, the "points cloud" was transformed into elementary triangular surfaces. These were unified and transformed into larger continuous surfaces. Then, this surface-based geometry was transformed into virtual solids. This geometry was compared with the initial plan of the performance hall. Finally, the geometric model was imported into a finite element analysis software. In this program, the materials were attached to the solid elements of the model, then the constraints and acoustic sources were defined. The model was divided into finite elements and the simulation was run. Results maps were obtained and further analysed and compared. Based on these results, significant conclusions were drawn.

E. Ghavanloo, Reza Lashani, Georgios I. Giannopoulos

Mohamad Fikri Datuela, Rahmayanti Rahmayanti, Wahyu Saputra et al.

This study aims to examine the comparison of room acoustics by using room engineering methods and testing zinc plate and GRC board materials in the same room. The results of the study show that the selection of materials for sound absorption in the room must be considered carefully and adjusted to the desired sound absorption needs. In testing using the room engineering method, it was seen that there was an increase in the effectiveness of sound absorption in both materials at various volume levels. However, in testing using the mandatory sound of the room acoustic tester, it can be seen that the sound frequency at the lower speaker position is more prominent in both materials at a lower volume. Meanwhile, in the test using the free sound of people giving speeches, it was seen that there was an increase in sound frequency at the top speaker position for both materials at a higher volume.

Yong Deng, Adrian Paskert, Zhiyuan Zhang et al.

As a next-generation toolkit, microrobots can transform a wide range of fields, including micromanufacturing, electronics, microfluidics, tissue engineering, and medicine. While still in their infancy, acoustically actuated wireless microrobots are becoming increasingly attractive, as acoustic control can generate large propulsive forces, requires relatively simple microrobot design, and does not entail complex manipulation systems. However, the interaction of acoustics with microstructure geometry is poorly understood to date, and its study is necessary for developing next-generation acoustically powered microrobots. We present here a mass-manufactured acoustically driven helical microrobot capable of locomotion using a fin-like double-helix microstructure. This microrobot responds to sound stimuli and mimics the spiral motion of natural microswimmers such as spirochetes. The asymmetric double helix interacts with the incident acoustic field, inducing a propulsion torque that causes the microrobot to rotate around its long axis. Moreover, our microrobot has the unique feature of its directionality being switchable by simply tuning the acoustic frequency. We demonstrate this locomotion in 2D and 3D artificial vasculatures using a single sound source. Since ultrasound is widely used as an imaging modality in clinical settings, our robotic system can integrate seamlessly into practice; thus, our findings could contribute to the development of next-generation smart microrobots. One-Sentence Summary We present an acoustically driven helical microrobot capable of corkscrew-like locomotion using a double-helix microstructure.

Michael Dorner, Maximilian Capraro, Oliver Treidler et al.

The engineering of complex software systems is often the result of a highly collaborative effort. However, collaboration within a multinational enterprise has an overlooked legal implication when developers collaborate across national borders: It is taxable. In this article, we discuss the unsolved problem of taxing collaborative software engineering across borders. We (1) introduce the reader to the basic principle of international taxation, (2) identify three main challenges for taxing collaborative software engineering making it a software engineering problem, and (3) estimate the industrial significance of cross-border collaboration in modern software engineering by measuring cross-border code reviews at a multinational software company.

Mr. Pritesh P. Rana, Dr. Shailesh Anand B. Goswami

Abstract - This review analyzes the use of polyurethane (PU) coatings in acoustical curtain fabrics to improve sound absorption. As noise pollution becomes a more serious public health concern, there is a rising need for long-term, effective, and aesthetically beautiful noise control solutions in architectural, automotive, and industrial settings. This study summarizes recent research on the acoustic performance of textile-based absorbers, with a special emphasis on the synergistic use of PU coatings to adjust airflow resistance, surface density, and structural porosity. Key mechanisms of sound attenuation in coated fabrics are investigated, including viscous-thermal dissipation, resonant absorption, and impedance matching. Experimental techniques and predictive modeling approaches—such as the Johnson-Champoux-Allard (JCA) model, Pieren's equivalent circuit model, and finite element simulations—are thoroughly examined. The effect of PU coating characteristics such as coating %, thickness, distribution, and formulation on acoustic absorption spectra is thoroughly investigated. This review also considers sustainability through the use of recovered PU materials and discusses future research directions, such as multifunctional coatings, smart acoustical fabrics, and scalable manufacturing processes. The findings demonstrate PU-coated fabrics' tremendous potential as high-performance, design-integrated acoustic materials for modern noise reduction. Benefits, including thermal insulation, privacy enhancement, energy efficiency, and hygiene considerations, are also discussed. The review concludes that acoustic curtains represent an effective passive noise-control solution when properly designed, installed, and maintained, and highlights emerging research directions for future development. Keywords: Acoustic curtains, noise pollution, sound absorption, polyurethane coating, airflow resistance, sustainable acoustics

Craig S. Carlson, Elina Nurkkala, M. Hannula et al.

Abstract The sound of food is of influence on how its flavour is perceived. Although rarely studied in psychoacoustics, cheese may have a resonating internal structure in the audible spectrum. It has been speculated that this structure or small bubbles that are formed as a result of fermentation are responsible for creating audible acoustic responses. The purpose of this study was to design a mechanical methodology to create audible acoustics from cheese samples and to quantify bubble presence in a sample. One hundred and two samples of mozzarella cheese with 1.5±0.4-cm3 volumes were subjected to shear from a wetted steel blade, whilst orthogonal force, blade acceleration, and acoustic response were continuously monitored. In addition, micro-computed tomography was performed. It was found that under our measurement conditions, mozzarella was forced to squeak in 10% of the experiments, at fundamental squeak frequencies up to 2 kHz, which indicates that the acoustics come from a resonating porous structure, rather than from resonating bubbles. The micro-computed tomography showed a bubble density of 51 cm−3. This low bubble density may account for the absence of a high-frequency component in the spectra analysed. Our results confirm the presence of small bubbles in squeaky mozzarella, but these generate frequencies much higher than those recorded.

Sijie Yang

The problem of transcribing data from an acoustic waveform has yielded multiple approaches over the last decades. The current preferred approach involves a three-stage model that breaks the problem into its constituent stages, each with an equivalent model. The first stage divides pure acoustics and language study using a Bayesian model. The second stage focuses on the acoustics model; this model makes the most sufficient and efficient division. The third stage focuses on the acoustics model; this model provides complete instruction on how to compute the probability required by the first stage, given the division specification declared within the second stage.

Ryan D. Clendening, Richard Dill, Brett J. Borghetti et al.

Small Unmanned Aircraft Systems (sUAS) are accessible platforms that pose a security threat. These threats warrant affordable and accurate methods for tracking sUAS. We apply neural network-based methods to predict sUAS range from cellphone acoustic recordings; the data comes from twenty-eight cellphones recording three different sUAS that fly over the devices. The timestamped acoustics data is transformed into 0.5s Mel-spectrograms frames and 0.5s raw audio frames. Truth values are calculated using euclidean distance from the sUAS to a cellphone and split into four range classes. The data is sequestered into an 80/20 training-test split and is used to train three different architectures. The 2DCNN architecture outperforms the other architectures (1DCNN and 2DCRNN). The 2DCNN is then re-trained to generalize sUAS range with various sUAS models and achieves an average Macro-F1 score of 0.758 across different sUAS models. The results show that deep-learning-based sUAS ranging with cellphones is an effective and low-cost method for accurately tracking sUAS.