Search Results (2,917)

Compared to commuting, grocery shopping trips, despite their profound implications for mixed land use and transportation planning, have received limited attention in travel behavior research. Drawing upon a travel diary survey conducted in a fast-growing metropolitan region of the United States, i.e., Salt Lake County, UT, this research investigated a variety of influential factors affecting mode choices associated with grocery shopping. We analyze how built environment (BE) characteristics, measured at seven spatial scales or different ways of aggregating spatial data—including straight-line buffers, network buffers, and census units—affect travel mode decisions. Key predictors of choosing walking, biking, or transit over driving include age, household size, vehicle ownership, income, land use mix, street density, and distance to the central business district (CBD). Notably, the influence of BE factors on mode choice is sensitive to different spatial aggregation methods and locations of origins and destinations. The straight-line buffer was a good indicator for the influence of store sales amount on mode choices; the network buffer was more suitable for the household built environment factors, whereas the measurement at the census block and block group levels was more effective for store-area characteristics. These findings underscore the importance of considering both the spatial analysis method and the location (home vs. store) when modeling non-work travel. A multi-scalar approach can enhance the accuracy of travel demand models and inform more effective land use and transportation planning strategies. Full article

This study examines how teacher–student relationships and school engagement change across online and in-school learning, based on the experiences of 105 cross-regional secondary vocational students in China. Using questionnaire surveys, the study explores students’ perceptions and learning needs in both settings. The findings confirm that teachers play a consistently positive role in promoting student engagement across both online and in-school learning modalities. While affective engagement was higher during online learning, driven by stronger teacher responsiveness and improved student–teacher relationships, students reported increased pride in their schools after returning home, reflecting a renewed appreciation. In-school learning was associated with higher behavioral engagement and greater motivation, despite tensions over intensified academic tasks. Online learning facilitated cognitive engagement through easier vocabulary searches; nevertheless, poor home environments reduced motivation. Enhancing engagement may require offering students autonomy, valuing their input, and clarifying the relevance of the learning content. Full article

This research focuses on designing polymer membranes as biocompatible materials using home-built electrospinning equipment, offering alternative solutions for tissue regeneration applications. This technological development supports cell growth on biomaterial substrates, including hepatocellular carcinoma (Hep-G2) cells. This work researches the compatibility of polymer membranes (fiber mats) made of polyvinylidene difluoride (PVDF) for possible use in cellular engineering. A standard culture medium was employed to support the proliferation of Hep-G2 cells under controlled conditions (37 °C, 4.8% CO₂, and 100% relative humidity). Subsequently, after the incubation period, electrochemical impedance spectroscopy (EIS) assays were conducted in a physiological environment to characterize the electrical cellular response, providing insights into the biocompatibility of the material. Scanning electron microscopy (SEM) was employed to evaluate cell adhesion, morphology, and growth on the PVDF polymer membranes. The results suggest that PVDF polymer membranes can be successfully produced through electrospinning technology, resulting in the formation of a dipole structure, including the possible presence of a polar β-phase, contributing to piezoelectric activity. EIS measurements, based on R_ct and C_dl values, are indicators of ion charge transfer and strong electrical interactions at the membrane interface. These findings suggest a favorable environment for cell proliferation, thereby enhancing cellular interactions at the fiber interface within the electrolyte. SEM observations displayed a consistent distribution of fibers with a distinctive spherical agglomeration on the entire PVDF surface. Finally, integrating piezoelectric properties into cell culture systems provides new opportunities for investigating the influence of electrical interactions on cellular behavior through electrochemical techniques. Based on the experimental results, this electrospun polymer demonstrates great potential as a promising candidate for next-generation biomaterials, with a probable application in tissue regeneration. Full article

This review examines advancements in smart home security through the integration of home automation technologies. Various security systems, including surveillance cameras, smart locks, and motion sensors, are analyzed, highlighting their effectiveness in enhancing home security. These systems enable users to monitor and control their homes in real-time, providing an additional layer of security. The document also examines how these security systems can enhance the quality of life for users by providing greater convenience and control over their domestic environment. The ability to receive instant alerts and access video recordings from anywhere allows users to respond quickly to unexpected situations, thereby increasing their sense of security and well-being. Additionally, the challenges and future trends in this field are addressed, emphasizing the importance of designing solutions that are intuitive and easy to use. As technology continues to evolve, it is crucial for developers and manufacturers to focus on creating products that seamlessly integrate into users’ daily lives, facilitating their adoption and use. This comprehensive state-of-the-art review, based on the Scopus database, provides a detailed overview of the current status and future potential of smart home security systems. It highlights how ongoing innovation in this field can lead to the development of more advanced and efficient solutions that not only protect homes but also enhance the overall user experience. Full article

Solid propellant grain, as a typical polymer, are the thrust generation devices and core load-bearing components of solid rocket motor (SRM) and are also known as SRM grain. They are constantly exposed to extreme service environments such as high temperatures, high pressures, and dynamic shocks, and have a relatively high failure rate in the field use of SRM. Its life and reliability are the shortcomings that restrict the improvement of weapons and equipment capability in China at present. This paper summarizes the typical fault types of SRM grain at present, and compares and analyzes the research progress of reliability design and analysis technology, reliability optimization technology, life test technology and reliability evaluation technology of SRM grain at home and abroad; This paper analyzes the deficiencies and reasons in the research and application of SRM grain reliability technology in China, and points out the technical difficulties and challenges faced by the integrated design of performance and reliability of SRM independent innovation design according to the needs of the forward research and development system of SRM. Based on the existing design level and industrial foundation in China, the basic research suggestions that should be carried out to consolidate the design ability of SRM grain in China are given. Full article

The COVID-19 pandemic’s rapid shift to working from home has fundamentally challenged residential acoustic design, which traditionally prioritises rest and relaxation rather than sustained concentration. However, a clear gap exists in understanding how acoustic needs and the subjective evaluation of soundscape appropriateness (SA) differ between these conflicting activities within the same domestic space. Addressing this gap, this study reveals critical differences in how people experience and evaluate home soundscapes during work versus relaxation activities in the same residential spaces. Through an online survey of 247 Chinese participants during lockdown, we assessed soundscape perception attributes, the perceived saliencies of various sound types, and soundscape appropriateness (SA) ratings while working and relaxing at home. Our findings demonstrate that working at home creates a more demanding acoustic context: participants perceived indoor soundscapes as significantly less comfortable and less full of content when working compared to relaxing (p < 0.001), with natural sounds becoming less noticeable (−13.3%) and distracting household sounds more prominent (+7.5%). Structural equation modelling revealed distinct influence mechanisms: while comfort significantly mediates SA enhancement in both activities, the effect is stronger during relaxation (R² = 0.18). Critically, outdoor man-made noise, building-service noise, and neighbour sounds all negatively impact SA during work, with neighbour sounds showing the largest detrimental effect (total effect size = −0.17), whereas only neighbour sounds and outdoor man-made noise significantly disrupt relaxation activities. Additionally, natural sounds act as a positive factor during relaxation. These results expose a fundamental mismatch: existing residential acoustic environments, designed primarily for rest, fail to support the cognitive demands of work activities. This study provides evidence-based insights for acoustic design interventions, emphasising the need for activity-specific soundscape considerations in residential spaces. As hybrid work arrangements become the norm post-pandemic, our findings highlight the urgency of reimagining residential acoustic design to accommodate both focused work and restorative relaxation within the same home. Full article

This study examines the relationship between learning environments and learning outcomes in acquiring Korean as a language target. We compare two learner groups residing in the United States: English-speaking learners of Korean in foreign language contexts versus Korean heritage speakers. Both groups share English as their dominant language and receive similar tertiary-level instruction, yet differ in their language-learning profiles. We measure two groups’ comprehension behaviour involving Korean subject−predicate honorific agreement, focusing on two conditions manifesting a mismatch between the honorifiable status of a subject and the realisation of the honorific suffix in a predicate. Results from the acceptability judgement task revealed that (1) both learner groups rated the ungrammatical condition as more acceptable than native speakers did, (2) Korean heritage speakers rated the ungrammatical condition significantly lower than English-speaking learners, and (3) overall proficiency in Korean modulated learners’ evaluations of the ungrammatical condition in opposite directions between the groups. No between-group difference was found in the infelicitous-yet-grammatical condition. Results from reaction time measurement further showed that Korean heritage speakers responded considerably faster than English-speaking learners of Korean. These results underscore the critical role of broad usage experience—whether through home language exposure for heritage language speakers or formal instruction for foreign language learners—in shaping non-dominant language activities. Full article

Selective Mutism (SM) is a childhood anxiety disorder characterized by the persistent inability to speak in specific social settings while being able to speak freely in more comfortable environments, such as at home with family. This condition often leads to significant impairments in social, academic, and occupational functions. This article presents a novel treatment methodology that integrates the physiology of vocal production with pragmatic language instruction through teletherapy, administered to two adolescents diagnosed with selective mutism (SM). The frequency of speaking on the Selective Mutism Questionnaire increased from 35% to 86% and from 25% to 55% for the two children. Pragmatic language skills on the Social Communication Skills: Pragmatics Checklist improved from 47% to 96% and 13% to 40% after treatment. It is crucial to emphasize vocal control for speech initiation and pragmatic language for verbal expression. Detailed strategies, specific activities, and treatment outcomes are provided. Full article

Background/Objectives: Speech intelligibility (SI) is a key indicator of spoken language development, especially for children with hearing loss, as it directly impacts communication and social engagement. However, due to logistical and methodological challenges, SI assessment is often underutilised in clinical practice. This study aimed to evaluate the accuracy and consistency of an artificial intelligence (AI)-based transcription model in assessing SI in young children with cochlear implants (CI), hearing aids (HA), or normal hearing (NH), in comparison to naïve human listeners. Methods: A total of 580 speech samples from 58 five-year-old children were transcribed by three naïve listeners and the AI model. Word-level transcription accuracy was evaluated using Bland–Altman plots, intraclass correlation coefficients (ICCs), and word error rate (WER) metrics. Performance was compared across the CI, HA, and NH groups. Results: The AI model demonstrated high consistency with naïve listeners across all groups. Bland–Altman analyses revealed minimal bias, with fewer than 6% of sentences falling outside the 95% limits of agreement. ICC values exceeded 0.9 in all groups, with particularly strong agreement in the NH and CI groups (ICCs > 0.95). WER results further confirmed this alignment and indicated that children with CIs showed better SI performance than those using HAs. Conclusions: The AI-based method offers a reliable and objective solution for SI assessment in young children. Its agreement with human performance supports its integration into clinical and home environments for early intervention and ongoing monitoring of speech development in children with hearing loss. Full article

Objective: Given the critical workforce challenges in home care settings and the limited understanding of empowerment mechanisms in isolated work environments, this study aimed to examine how structural empowerment influences psychological empowerment among home care workers in South Korea through the mediating pathways of thriving at work and caregiver reciprocity. Based on Kanter’s empowerment theory, we specifically investigated the serial mediation effects to understand the complex processes through which organizational support structures translate into enhanced worker empowerment. Methods: A cross-sectional survey was conducted with 192 home care workers. Data were analyzed using descriptive statistics, correlation analysis, and serial multiple mediation analysis using SPSS Process Macro Model 6. Results: Structural empowerment demonstrated significant positive correlations with thriving at work (r = 0.445, p < 0.001), caregiver reciprocity (r = 0.490, p < 0.001), and psychological empowerment (r = 0.337, p < 0.001). Thriving at work significantly influenced both caregiver reciprocity (β = 0.3968, p < 0.001) and psychological empowerment (β = 0.1685, p < 0.001). The serial mediation analysis revealed that the indirect effect of structural empowerment on psychological empowerment through thriving at work and caregiver reciprocity was statistically significant (indirect effect = 0.1327, 95% CI [0.0713, 0.1929]), with the model explaining 58% of the variance in psychological empowerment. Conclusions: Structural empowerment significantly enhances psychological empowerment among home care workers through the sequential mediation of thriving at work and caregiver reciprocity. Healthcare organizations should prioritize strengthening structural empowerment through comprehensive support systems and conducive work environments to optimize care quality and worker well-being. Full article

The rapid expansion of 5G-enabled Internet of Things (IoT) devices in smart homes has heightened the need for robust, privacy-preserving, and real-time cybersecurity mechanisms. Traditional cloud-based security systems often face latency and privacy bottlenecks, making them unsuitable for edge-constrained environments. In this work, we propose Edge-FLGuard+, a federated and lightweight anomaly detection framework specifically designed for 5G-enabled smart home ecosystems. The framework integrates edge AI with federated learning to detect network and device anomalies while preserving user privacy and reducing cloud dependency. A lightweight autoencoder-based model is trained across distributed edge nodes using privacy-preserving federated averaging. We evaluate our framework using the TON_IoT and CIC-IDS2018 datasets under realistic smart home attack scenarios. Experimental results show that Edge-FLGuard+ achieves high detection accuracy (≥95%) with minimal communication and computational overhead, outperforming traditional centralized and local-only baselines. Our results demonstrate the viability of federated AI models for real-time security in next-generation smart home networks. Full article

Wi-Fi sensing leverages variations in CSI (channel state information) to infer human activities in a contactless and low-cost manner, with growing applications in smart homes, healthcare, and security. While deep learning has advanced macro-motion sensing tasks, micro-motion sensing such as keypad stroke recognition remains underexplored due to subtle inter-class CSI variations and significant intra-class variance. These challenges make it difficult for existing deep learning models typically relying on fully connected MLPs to accurately recognize keypad inputs. To address the issue, we propose a novel approach that combines a discriminative feature extractor with a Kolmogorov–Arnold Network (KAN)-based classifier. The combined model is trained to reduce intra-class variability by clustering features around class-specific centers. The KAN classifier learns nonlinear spline functions to efficiently delineate the complex decision boundaries between different keypad inputs with fewer parameters. To validate our method, we collect a CSI dataset with low-cost Wi-Fi devices (ESP8266 and Raspberry Pi 4) in a real-world keypad sensing environment. Experimental results verify the effectiveness and practicality of our method for keypad input sensing applications in that it outperforms existing approaches in sensing accuracy while requiring fewer parameters. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

As the demand for energy-efficient homes continues to rise, the importance of advanced mechanical ventilation systems in maintaining indoor air quality (IAQ) has become increasingly evident. However, challenges related to energy balance, IAQ, and occupant thermal comfort persist. This review examines the performance of mechanical ventilation systems in regulating indoor climate, improving air quality, and minimising energy consumption. The findings indicate that demand-controlled ventilation (DCV) can enhance energy efficiency by up to 88% while maintaining CO₂ concentrations below 1000 ppm during 76% of the occupancy period. Heat recovery systems achieve efficiencies of nearly 90%, leading to a reduction in heating energy consumption by approximately 19%. Studies also show that employing mechanical rather than natural ventilation in schools lowers CO₂ levels by 20–30%. Nevertheless, occupant misuse or poorly designed systems can result in CO₂ concentrations exceeding 1600 ppm in residential environments. Hybrid ventilation systems have demonstrated improved thermal comfort, with predicted mean vote (PMV) values ranging from –0.41 to 0.37 when radiant heating is utilized. Despite ongoing technological advancements, issues such as system durability, user acceptance, and adaptability across climate zones remain. Smart, personalized ventilation strategies supported by modern control algorithms and continuous monitoring are essential for the development of resilient and health-promoting buildings. Future research should prioritize the integration of renewable energy sources and adaptive ventilation controls to further optimise system performance. Full article

Smart home technology enhances the quality of life, particularly with respect to in-home care and health monitoring. While video-based methods provide accurate behavior analysis, privacy concerns drive interest in non-visual alternatives. This study proposes a Bluetooth Low Energy (BLE)-enabled indoor positioning and behavior recognition system, integrating machine learning techniques to support sustainable and privacy-preserving health monitoring. Key optimizations include: (1) a vertically mounted Data Collection Unit (DCU) for improved height positioning, (2) synchronized data collection to reduce discrepancies, (3) Kalman filtering to smooth RSSI signals, and (4) AI-based RSSI analysis for enhanced behavior recognition. Experiments in a real home environment used a smart wristband to assess BLE signal variations across different activities (standing, sitting, lying down). The results show that the proposed system reliably tracks user locations and identifies behavior patterns. This research supports elderly care, remote health monitoring, and non-invasive behavior analysis, providing a privacy-preserving solution for smart healthcare applications. Full article