Browse Topic: Customization

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Load Analysis of Flap and Slat Actuators in Aircraft High-Lift Systems2026-99-18027/17/2026
This study develops an end-to-end load analysis scheme for flap and slat actuators, which comprise the aircraft’s high-lift system, and the analysis results are directly integrated into hardware optimization. Because they shoulder heavy responsibilities during the takeoff and landing phases, whether they can remain rock-solid under complex aerodynamic conditions or even remain unmoved in emergencies is directly related to their overall safety performance. This work process is closely linked and includes three major links. First of all, according to the CCAR-25.301 standard, the load envelope under normal working conditions is sorted out, and the limit cases of abnormal faults are exhausted. Subsequently, ANSYS Workbench pulled silk and peeled off the cocoons to capture the peak stress at the engagement between the output shaft and the gear. In the end, the closed-loop verification of the customized test bench made the theoretical calculations and the hardware-measured data exactly the same. The entire package provides designers with hardcore data support, and always uses airworthiness, not convenience, as the criterion when improving actuator performance.
Xu, Yuanze
Evaluation of Civil Aircraft Options Based on Grey Analytic Hierarchy Process2026-99-18087/17/2026
Product options are an important means for civil aircraft manufacturers to meet market demand, increase revenue, and enhance competitiveness. How to achieve a customized configuration of civil aircraft options is the focus of attention for aircraft manufacturers. In order to reduce manufacturing costs and cover more target markets, it is necessary to pay attention to the customized detail design of aircraft products in the early stages of design. At present, academic research on product selection is relatively limited and lacks quantitative evaluation methods. This article selects four elements to form an evaluation indicator system, namely comfort, competitiveness, cost investment, and maintainability; establishes a civil aircraft option evaluation model based on grey correlation analysis, quantifies the degree of correlation between product options and customer needs, and uses the analytic hierarchy process to reflect the weight differences of evaluation indicators. Taking the option list of a wide-body aircraft as an example, the model was used to evaluate and rank the options, verifying the rationality of the model and providing a reference for aircraft manufacturers to make provisions in advance.
Lu, Meihua
Crowd Counting Network for Risk Early Warning in Exhibition Scenarios2026-99-07055/15/2026
As a densely populated public place, exhibitions feature spatial layouts with multi-area linkage and instantaneous crowd flow mutations. Thus, developing a crowd flow early warning system adapted to exhibition dynamics is a key focus at the public safety and smart exhibitions to avoid risks like local congestion-induced stampedes. In general, two core challenges in exhibition crowd counting: 1) Key dynamic gathering information is hidden in high frequency components, but no correlation mechanism between frequency components and scene has been established; 2) Instant crowd gatherings cause high-frequency local density mutations, leading to time delays and spatial ambiguity of dynamic signals. To solve these, we propose a novel Crowd Counting Network for Risk Early Warning in Exhibition Scenarios with two core modules: 1) A bidirectional feature filtering module optimizes frequency information through low-frequency suppression to reduce redundancy and high-frequency activation to enhancing dynamic signals. 2) A lightweight self-attention module captures long-range dependencies of high-frequency features via frequency-domain self-attention, enabling accurate identification of feature clusters from gatherings. Validated on datasets like ShanghaiTech and UCF-QNRF, this method provides an integrated solution for exhibition security monitoring, promoting crowd counting technology from general scenarios to industry customization.
Zhang, Jin, Zhang, Wanyue, Yuan, Jingjing, Chen, Zhen, Gu, Dazhi
A Shared Autonomy Architecture: Utilizing an Advanced Personalized Control System (APeCS) and Shared Autonomy Arbiter (SAB)2026-01-01474/7/2026
The shared autonomy framework has become an option with great potential in the field of autonomous vehicles. Human and machine control decisions typically demonstrate strengths in different scenarios. As a result, the robustness of systems can be enhanced by the collaboration between humans and autonomy. A shared autonomy architecture that takes into account both human and environmental factors was proposed in this work. The authority distribution between the human operator and the autonomy algorithm was determined by the Shared Autonomy Arbiter (SAB). Designed with a two-tier structure, the SAB incorporated a policy-level decision module, as well as a numerical-level arbitration tuning module. A fuzzy inference system (FIS) was incorporated to enhance the noise tolerance of the policy selection module. Furthermore, the human factor was taken into account by applying a projection to the users’ control input. The human operator’s control decision was projected by the Adaptive Personalized Control System (APeCS) to accommodate the skill levels and habits of various users. By incorporating a broad set of factors, this framework is suitable for diverse applications that require robustness in complex environments. Two case studies were included in this work to demonstrate its effectiveness. The first presented a concept design illustrating the application of the proposed architecture on autonomous vehicles operating in varied environments. The second showed that the proposed architecture can serve as a robust testbed by taking advantage of the authority modulating mechanism. By connecting a system under assessment and an established autonomy algorithm to the SAB, the new system can be tested robustly and safely through the flexible authority distribution.
Sang, I-Chen, Norris, William, Patterson, Albert, Sreenivas, Ramavarapu S., Soylemezoglu PhD, Ahmet, Nottage, Dustin S.
Driver Personalized Lane Change Behavior Analysis Based on Attention Deep Embedding Clustering2025-01-734712/31/2025
The characteristic representation and in-depth understanding of driver personalized driving behavior are fundamental to achieving human-like autonomous driving, enhancing the rationality of autonomous driving decisions, and meeting passengers’ personalized needs. [ADDED]Personalized driving behavior refers to individual-specific patterns in vehicle operation that emerge from drivers’ unique combinations of skills, risk tolerance, and habitual responses.However, current research lacks consideration of cluster analysis in the feature representation stage and ignores the time-varying contribution degree of time series values to low-dimensional features, which inhibits further utilization and development. This study adopts deep embedding clustering method and introduces attention mechanism to investigate driver personalized high-speed lane change behavior.[ADDED] Using a comprehensive driving simulator platform, we collected 15-channel time series data from 12 drivers performing 216 lane changes across 18 controlled scenarios. The research establishes a joint optimization framework that simultaneously learns feature representation and cluster assignment through a variable joint objective function. Results show that compared with baseline methods, the features characterized by this method are closest to the original data after reconstruction. The clustering results demonstrate high intra-cluster compactness, large inter-cluster distances, and clear cluster shapes with significant differences among categories, facilitating personalized driving behavior classification. Model validation on multi-channel temporal classification datasets confirms the efficiency of the proposed model and effectiveness of attention mechanism integration with deep embedding clustering. This study reveals the superiority of attention deep embedding clustering method in the field of driver personalized driving behavior analysis and provides new directions for future research in intelligent vehicle development.
Dong, Haomin, Wang, Wei, Wang, Yue, Li, Lun, Yue, Yi, Tian, Jiaxiao, Han, Jiayi
TAILORING electrohydraulics for specialized scenarios25TOFHP12_0312/1/2025
Custom electrohydraulic solutions can address unique demands not satisfied by standard components. As mobile equipment is pushed to perform in increasingly demanding and challenging environments - ranging from frozen construction sites to harsh marine applications - some OEMs are discovering that customized solutions can provide significant advantages. Standard electronic controls and hydraulic components are carefully engineered to meet the requirements of a broad range of typical applications. For many OEMs, these components provide a dependable and cost-effective foundation, especially in environments and duties that don't push operational boundaries.
Cooper, Robin
Research on Light Transmission Technology of Wood Veneer for Automotive Interior Smart Surfaces15-19-01-000111/12/2025
Automotive wooden interiors are increasingly popular among consumers for their excellent appearance and texture. However, low light transmittance limits their application in automotive interior smart surfaces. This study explores light transmission technology for wood veneer in automotive interiors, proposing two solutions based on the properties of wood veneer: the light-transmitting veneer solution and the laser-engraved beacon solution. Both solutions were tested through production experiments to evaluate the light transmission effects and process feasibility. Experimental results show that the light-transmitting veneer solution significantly improves the light transmittance of wood veneers through material modification, but instability in structure and materials leads to the difficulty of presenting a better light transmission effect. In contrast, the laser-engraved beacon solution achieves clear and stable light transmission effects by directly processing light-transmitting beacons on the veneer, effectively avoiding interference from surface paint. To further address the issue of veneer fragility around the beacon areas, the solution was optimized, and the laser-engraved micro-perforated beacon solution was proposed. After testing, the optimal micro-perforation diameter (0.25 mm) and micro-perforation spacing (0.25 mm) were finally determined for the laser-engraved micro-perforated beacon solution. This research provides innovative solutions for the application of wood veneer in automotive interiors, promoting the personalization and intelligence of automotive interior design.
Yu, Yang, Dai, Xiaodong, Yu, Peng, He, Ping, Lin, Huangxu, Zhang, Xuechang
Customized Signalized Intersection Control for Pedestrian Safety Enhancement through Computer Vision Technologies09-13-02-00086/26/2025
The escalating complexity at intersections challenges the safety of the interaction between vehicles and pedestrians, especially for those with mobility impairments. Traditional traffic control systems detect pedestrians through costly technologies such as LiDAR and radar, limiting their adoption due to high costs and static programming. Therefore, the article proposes a customized signalized intersection control (CSIC) algorithm for pedestrian safety enhancement. This algorithm integrates advanced computer vision (CV) algorithms to detect, track, and predict pedestrian movements in real time, enhancing safety at a signalized intersection while remaining economically viable and easily integrated into existing infrastructure. Implemented at a key intersection in Bellevue, the CSIC system achieves a 100% pedestrian passing rate while simultaneously minimizing the average remaining walk time after crossings. The algorithm used in this study demonstrates the potential of combining CV with traditional traffic control mechanisms to create safer urban traffic environments for all road users.
Xia, Rongjing, Fang, Hongchao, Zhang, Chenyang
Manufacturing Technologies: A 2025 Medical Device Industry OutlookTBMG-532866/1/2025
The global medical device manufacturing industry is undergoing a rapid transformation driven by technological innovation, automation, and increasing demands for customized, high-quality care. For engineers at the heart of medtech manufacturing, understanding the latest technologies is crucial not only for maintaining competitiveness but also for ensuring regulatory compliance, improving time to market, and optimizing production workflows.
Material Adapted Method for the Repair of Curved Thermoplastic Composite Structures by Induction Welding of Patches2025-01-01655/2/2025
Thermoplastic fiber-reinforced polymer composites (TPC) are gaining relevance in aviation due to their high specific strength, stiffness, potential recyclability and the ability to be repaired thanks to their meltability. To maximize their potential, efficient repair methods are needed to maintain aircraft safety and structural integrity. This article introduces a novel repair technique for damaged TPC structures, involving the joining of a repair patch with induction welding using a susceptor material. The susceptor consists of a material with high electrical conductivity and magnetic permeability and therefore reacts stronger to the electromagnetic field than the composite, even if the composite is carbon fiber based. I. e. the thermal energy is specifically concentrated in the repair area. In this study, the susceptor was placed on the patch and also in the welding zone. The repair process begins by identifying and preparing the damaged area, followed by precise scarfing. Care is taken to ensure that the surrounding material remains intact and that an exact stepped structure is created, which enables an optimal bonding with the patch to be used. The customized patch, which fits perfectly in terms of shape and material to the area to be augmented, is then inserted into the structure. Induction heating melts the thermoplastic matrix to join the patch with the structure using a flexible induction mat. The repair process is monitored using thermocouples to ensure even heat distribution, while pressure is maintained through a vacuum bag. The vacuum bag ensures a uniform pressure distribution even on complex curved structures. This adaptable repair method can handle individual damages. It was tested on flat carbon fiber-reinforced polyphenylene sulfide (CF-PPS) structures, showing repairs with nearly 70 % of the original performance for copper mesh susceptors. Optical tests of the specimens confirmed a bonding zone with minimal defects. Overall, this method offers a material-compatible solution for TPC repair in future aviation, advancing aerospace maintenance and offering significant potential for future industry use.
Geiger, Markus, Glaap, Anton, Schiebel, Patrick, May, David
Processing and Packaging MEMS to Maximize FunctionalityTBMG-530205/1/2025
MEMS is a more complex technology than traditional semiconductors. They are 3D structures with moving parts, making them much more difficult to fabricate. If you’re designing a semiconductor, you may be able to take advantage of an existing process development kit (PDK), which your foundry can provide to you. There is no equivalent approach in MEMS. It’s a “one process, one product” paradigm that requires a high level of customization. That takes time, money, and resources.
Matchit: A Domain-Adaptable Information Extraction and Categorization Tool for Enhanced Decision Making2025-01-81074/1/2025
This paper presents Matchit, a novel method for expediting issue investigation and generating actionable insights from textual data. Recognizing the challenges of extracting relevant information from large, unstructured datasets, we propose a domain-adaptable approach by integrating expert domain knowledge to guide Large Language models (LLMs) to automatically identify and categorize key information into distinct topics. This process offers two key functionalities: fully automatic topic extraction based solely on input data, providing a concise overview of the problem and potential solutions, and user-guided extraction, where domain experts can specify the type of information or pre-defined categories to target specific insights. This flexibility allows for both broad exploration and focused analysis of the data. Matchit's efficacy is demonstrated through its application in the automotive industry, where it successfully extracts repair diagnostics from diverse textual sources like repair records, surveys, and customer service logs. By identifying and categorizing information related to failure modes, symptoms, repair actions, and procedures, Matchit enables efficient identification of similar repairs in new datasets, significantly reducing manual review efforts. Case studies presented demonstrate the tool's effectiveness in achieving accurate matching results. Matchit's versatility extends beyond the automotive domain, offering a powerful solution for any application requiring customized information extraction, categorization, and matching from textual data.
Wang, Lijun, Arora, Karunesh
Near-Void-Free 3D PrintingTBMG-524502/1/2025
In recent years, metal additive manufacturing has emerged as a transformative technology, impacting traditional manufacturing processes across industries. Its ability to create complex geometries and customized parts with unprecedented precision has propelled it to the forefront of innovation in engineering and design. However, when compared to traditional manufacturing techniques, materials produced through 3D printing often exhibit inferior fatigue properties under cyclic loading conditions. This discrepancy significantly limits their widespread application as structural load-bearing components. The challenge lies in addressing the poor fatigue properties commonly attributed to the presence of micro voids induced during the current printing process procedures. Improving the fatigue performance of 3D printed materials and components has thus become a crucial research focus.
2025 Trends in Healthcare: Bridging Technology, Personalization, and AccessibilityTBMG-524602/1/2025
The emergence of data-driven healthcare promises predictive and preventive care through enhanced data integration and analytics. This trend means that medical device companies must navigate challenges related to data privacy and operational efficiency while transitioning to a data-centric approach. Artificial intelligence (AI) is spearheading this shift toward hyper-personalized medicine, enabling precision treatments based on genetic profiles and predictive analytics for early disease detection. Advancements in telemedicine, AI, wearable technology, and data analytics, are reshaping how care is delivered, making it more accessible, personalized, and efficient in 2025.
Evaluation of Superficial Damage of Mechanical Components through Digital Image Analysis Using Deep Learning Framework2024-36-003412/20/2024
Mechanical component failure often heralds superficial damage indicators such as color alteration due to overheating, texture degradation like rusting or false brinelling, spalling, and crack propagation. Conventional damage assessment relies heavily on visual inspections performed by technicians, a practice bogged down by time constraints and the subjective nature of human error. This research paper delves into the integration of deep learning methodologies to revolutionize surface damage evaluation, addressing significant bottlenecks in diagnostic precision and processing efficiency. We detail the end-to-end process of developing an intelligent inspection system: selecting appropriate deep learning architectures, annotating datasets, implementing data augmentation, optimizing hyperparameters, and deploying the model for widespread user accessibility. Specifically, the paper highlights the customization and assessment of state-of-the-art models, including EfficientNet B7 for multilabel classification and prominent object detection framework such as YOLO. Our results demonstrate the feasibility of automating damage detection, potentially transforming maintenance routines and reliability in mechanical settings. Follow-up research is planned to refine these methodologies, paving the way for a production-ready model that will further enhance the reliability and efficiency of mechanical component maintenance.
Cury, Rudoniel, Gioria, Gustavo, Chandrasekaran, Balaji
Bio-Ink for 3D PrintingTBMG-5218912/1/2024
Biomedical engineers have developed a “bio-ink” for 3D-printed materials that could serve as scaffolds for growing human tissues to repair or replace damaged ones in the body. Bioengineered tissues show promise in regenerative, precision, and personalized medicine; product development; and basic research, especially with the advent of 3D printing of biomaterials that could serve as scaffolds or temporary structures to grow tissues.
Personalized Medicine: The Role of Nanosensors in Disease DetectionTBMG-5170710/1/2024
Nanosensors are transforming the field of disease detection by offering unprecedented sensitivity, precision, and speed in identifying biomarkers associated with various health conditions. These tiny sensors, often built at the molecular or atomic scale, can detect minute changes in biological samples, enabling the early diagnosis of diseases such as cancer, infectious diseases, and neurological disorders.
Robotic Therapy Improves Tremor TreatmentTBMG-514869/1/2024
Researchers have developed SPINDLE, a pioneering robotic rehabilitation system. Combining virtual reality (VR) with customized resistance training, SPINDLE offers personalized therapy to enhance strength and dexterity for activities of daily living (ADLs). Its adaptability and potential for home use represent a major advancement in tremor rehabilitation, with broader healthcare implications.
SAE TOMORROW TODAY: What is the Future of the Car?134758/27/2024
From autonomy to software to customization, the future of the car is multifaceted. As one of the world's largest suppliers in the automotive space, Magna International uniquely understands this. The company's capabilities span the entire vehicle -- from design to manufacturing to technology -- thus optimizing vehicle performance and shaping the future of the car. To learn more, we sat down with we sat down with Joerg Grotendorst, Senior Vice President, Corporate R&D, Magna, to discuss advancements in electrification and autonomy, innovative design features, and sustainable technologies -- and why a holistic approach to mobility is necessary.
Hineman, Marcie
Model-Based State-of-Charge Estimation of 28 V LiFePO 4 Aircraft Battery14-14-01-00038/1/2024
This article introduces an advanced state-of-charge (SOC) estimation method customized for 28 V LiFePO4 (LFP) helicopter batteries. The battery usage profile is characterized by four consecutive current pulses, each corresponding to distinct operational phases on the helicopter: instrument check, key-on, recharge, and emergency power output stages. To establish a precise battery model for LFP cells, the parameters of a second-order equivalent-circuit model are identified as a function of C-rate, SOC, and temperature. Furthermore, the observability of the battery model is assessed using extended Lie derivatives. The signal-to-noise ratio (SNR) of the open-circuit voltage (OCV)–SOC relation is analyzed and employed to evaluate the estimator’s resilience against OCV flatness. The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are utilized for SOC estimation. The results emphasize the significance of meticulously choosing process and sensor noise covariance matrices to achieve a resilient SOC estimator for LFP cells. Furthermore, the UKF demonstrates superior robustness against OCV–SOC relationships compared to the EKF. Lastly, the UKF is selected for testing across various aircraft usage scenarios at 10°C, 25°C, and 45°C. The resultant root mean square errors for SOC estimation at these different temperatures are consistently below 2%, thereby validating the effectiveness of the UKF SOC estimation approach.
Gao, Yizhao, Nguyen, Trung, Onori, Simona
Researchers Demonstrate the First Chip-Based 3D PrinterTBMG-512488/1/2024
Imagine a portable 3D printer you could hold in the palm of your hand. The tiny device could enable a user to rapidly create customized, low-cost objects on the go, like a fastener to repair a wobbly bicycle wheel or a component for a critical medical operation.
Future Medications Could Be Personalized on a 3D PrinterTBMG-513098/1/2024
Chocolate-flavored pills for children who hate taking medicine. Several drugs combined into one daily pill for seniors who have trouble remembering to take their medications. Drugs printed at your local pharmacy at personalized dosages that best suit your health needs. These are just a few potential advantages of 3D drug printing, a new system for manufacturing drugs and treatments on-site at pharmacies, healthcare facilities, and other remote locations.
Cloud simulation assists active-safety development for electric refuse truck24TOFHP06_086/1/2024
North America's first electric, fully integrated custom cab and chassis refuse collection vehicle - slated for initial customer deliveries in mid-2024 - is equipped with a standard advanced driver-assistance system (ADAS). “A typical garbage truck uses commercial off-the-shelf active safety technologies, but the electrified McNeilus Volterra ZSL was purpose-built with active safety technologies to serve our refuse collection customer,” said Brendan Chan, chief engineer for autonomy and active safety at Oshkosh Corporation, McNeilus' parent company. “We wanted to make the safest and best refuse collection truck out there. And by using cloud-based simulation, we could accelerate the development of ADAS and other technologies,” Chan said in an interview with Truck & Off-Highway Engineering during the 2024 dSPACE User Conference in Plymouth, Michigan.
Buchholz, Kami
Aerospace Developments: Vol. 2EPRCOMPV3020235/10/2024
Aerospace is an industry where competition is high and the need to ensure safety and security while managing costs is foremost. Stakeholders, who gain the most by working together, do not necessarily trust each other. Changing backbone technologies that drive enterprise systems and secure historical records does not happen quickly (if at all). At best, businesses adapt incrementally, building customized applications on top of legacy systems. The complexity of these legacy systems leads to duplication of efforts and data storage, making them very inefficient. Technology that augments, rather than replaces, is needed to transform these complex systems into efficient, digital processes. Blockchain technology offers collaborative opportunities for solving some of the data problems that have long challenged the aerospace industry. The industry has been slow to adopt the technology even though experts agree that it has real potential to revolutionize the global supply chain—including maintenance, repair, and overhaul (MRO)—driving tremendous cost, excess inventory, and inefficiencies out of the system. This chapter discusses how the adoption of blockchain technology could have a significant impact on the aerospace industry and addresses some of the unsettled concerns surrounding the implementation of the technology.
Walthall, Rhonda, David, Aharon, Farell, James, Hann, Richard, Johansen, Tor A.
Effect of Aftermarket Modifications on ADAS Functionality – 2022 Chevrolet Silverado Light Vehicle2024-01-19614/9/2024
Advanced Driver Assistance Systems (ADAS) are becoming common on passenger cars and pickup trucks. Accordingly, the manufacturers and installers of aftermarket equipment for these vehicles have an interest in confirming the functionality of ADAS when their equipment is put in place. However, there is very little publicly available information on the effect of aftermarket components on original equipment ADAS. To address this deficiency, a research program was undertaken in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations, including stock as well as three modified conditions. Aftermarket modifications to the vehicle consisted of increased tire diameters, a level kit, and two different lift kits. A series of physical tests were carried out to evaluate the ADAS performance of the vehicle with modifications. Tests were designed to investigate differences in driver alerts including lane departure warnings, forward collision warnings, blind spot detections, and rear cross traffic alerts. These tests were also developed to assess the variation in vehicle responses when driver assistance technologies intervened. Intervention scenarios examined include lane keeping support, crash imminent braking, and traffic jam assistance. In general, results from the tests did not indicate significant ADAS performance differences when the vehicle was subject to modifications. Nevertheless, some tests showed a greater range in alert distances in certain modified configurations.
Bastiaan, Jennifer, Muller, Mike, Morales, Luis
Personalized Adhesives for Medical ImplantsTBMG-504524/1/2024
A team has developed medical adhesives that are not only safe for human use but also customizable for different organs. The researchers used mussel-derived adhesive proteins to develop customized underwater bio-adhesive patches (CUBAP).
Achieving Flexibility, Reliability, and Safety with Autonomous Mobile RobotsTBMG-503654/1/2024
With 40 years of experience to its name, Sunview Patio Doors Ltd. (acquired by Novatech Group in 2021), has solved one of the industry’s top challenges: meeting customers’ increased demands for faster and better services, while providing an option for product customization. Its ability to adopt digital technology allowed the company to satisfy its customers and compete globally in the marketplace.
Precision and Personalized Medicine: The Role of PhenotypesTBMG-501993/1/2024
SAE TOMORROW TODAY: Stellantis Talks Software Defined Vehicle Strategy134382/29/2024
How does a company like Stellantis decide what new technologies will go into each of its iconic brands? Whether its Chrysler, Dodge, Jeep, Fiat or Maserati, a common software platform differentiated by brand ensures Stellantis has a global approach alongside the ability to customize each vehicle and tailor its technology based on language, regional requirements, etc. Armed with lessons learned from the recent semiconductor shortage and direct engagement with the start-up community, Stellantis is enhancing the performance of its software defined vehicles with proven best practices and strategic partnerships. We sat down with Steve Rober, Senior Vice President, Global Head of Automotive Research and Advanced Engineering, to discuss how Stellantis is applying new technology across its legendary brand line-up.
Hineman, Marcie
Software: Optimized, Personalized Treatments for Movement ImpairmentsTBMG-4945411/1/2023
A team of Rice University engineers has launched a first-of-its-kind, open-source software that constructs and uses personalized computer models of how individual patients move to optimize treatments for neurologic and orthopedic mobility impairments.
An Examination of Sensing Skins with Tailored Conductivity Distributions for Enhanced 2-D Surface Temperature Measurements Using Electrical Impedance Tomography (EIT)2023-01-168010/31/2023
For 2D surface temperature monitoring applications, a variant of Electrical Impedance Tomography (EIT) was evaluated computationally in this study. Literature examples of poor sensor performance in the center of the 2D domains away from the side electrodes motivated these efforts which seek to overcome some of the previously noted shortcomings. In particular, the use of ‘sensing skins’ with novel tailored baseline conductivities was examined using the EIDORS package for EIT. It was found that the best approach for detecting a temperature hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For well-performing combinations of these factors, customized baseline conductivities were assessed and compared to the baseline uniform conductivity. It was discovered that for some EIT applications, a tailored distribution needs to be smooth and that sudden changes in the conductivity gradients should be avoided to prevent the introduction of artifacts in the reconstructed conductivity field. Still, the benefits in terms of improved EIT performance were small for conditions for which the EIT measurements had been ‘optimized’ for the uniform baseline case. Within the limited scope of this study, only two specific cases showed benefits from customized distributions. For one case, a smooth tailored distribution with increased baseline conductivity in the center provided a better separation of two centrally located hot spots. For another case, a smooth tailored distribution with reduced conductivity in the center provided better estimates of the magnitudes of two hot spots near the center of the sensing skin. Overall, the results at hand suggest that improved 2D surface temperature measurement are best served by continued development of measurements and reconstruction algorithms rather than the use of sensing skins with tailored baseline conductivity distributions.
Sjöberg, Magnus
Sensor System Decreases Fall Risk for Older AdultsTBMG-489829/1/2023
A research team has designed a fall-risk assessment system that enables doctors to create personalized risk-management strategies for patients based on their individual movement patterns at home.
EVALUATION OF HASH-SEEDED PSEUDO-RANDOM NUMBER GENERATORS IN PARALLEL ENVIRONMENTS2024-01-40228/10/2023
ABSTRACT A customized approach to Pseudo Random Number Generation (PRNG) is developed specifically for the highly parallelizable sensor models in the ground vehicle autonomy application domain. The work considers three desirable attributes (namely quality, efficiency and determinism). Furthermore, the application demands high fanout (1:1Million+) seeding of traditional PRNGs. An approach using hash functions to generate the seeds for the PRNGs, each of which generates a small (i.e. 20) run of numbers, to handle determinism is investigated. Quality and efficiency are evaluated for multiple combinations of hash functions and PRNGs and a pareto front is created. Quality assessments were performed using industry standard testing suites (TestU01 and PractRand) and efficiency of various hash, PRNG, and batch size combinations was benchmarked on Windows/x64, ARM and NVIDIA/CUDA architectures. Citation: J. Kaniarz, M. Brudnak, “Evaluation of Hash-Seeded Pseudo-Random Number Generators in Parallel Environments,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023.
Kaniarz, John, Brudnak, Mark
Leveraging Customization to Decrease Device Complexity and Reduce CostsTBMG-488078/1/2023
The collaborative process can foster the kind of creativity and ingenuity that leads to the most innovative medical technology. In this Expert Insight, Nadia Hajjar, Category Manager for Life Sciences at Porex, provides perspective on the ins and outs of designing custom components, including leveraging customization to decrease device complexity and reduce component costs. Hajjar spoke with Medical Design Briefs about how the company focuses on innovation by identifying new materials even within their traditional material platforms and how deeper relationships with suppliers reduces the complexity and adds speed to the design process.
Highly Sensitive Biosensor Detects Extremely Small Changes in Tears, BloodTBMG-483166/1/2023
Wearable wireless biosensors are an integral part of digital healthcare and monitoring. Commonly used chipless resonant antenna-based biosensors are simple and affordable but have limited applicability due to their low sensitivity. Now, researchers from Japan have developed a novel, wireless, parity–time symmetry-based bioresonator that can detect minute concentrations of tear glucose and blood lactate. This highly sensitive, tunable, and robust bioresonator has the potential to have a great impact on personalized health monitoring and digitized healthcare systems.
Robots Tackle COVID by Automating Neutralizing Antibody TestTBMG-480355/1/2023
Imagine if one test could tell you whether you were protected from the latest COVID-19 variant. A partnership between state-of-the-art robotics and cutting-edge medical research will allow doctors at the University of Texas Medical Branch (UTMB) to give their patients more personalized and useful information.
Low-Cost, Customized Prosthesis Using 3D PrintingTBMG-473311/1/2023
Upper-limb forequarter amputations that involve the removal of the entire arm and scapula require highly customized prosthetic devices that are expensive but yet usually underutilized due to their high maintenance and low comfort levels. At the same time, while cosmetic prostheses — artificial limbs that provide patients the appearance of a pre-amputated body part — have a higher rate of continuous use, they have limitations in functional use.
FUTURE-TECH FLAGSHIP22AUTP11_0112/1/2022
2024 Cadillac Celestiq spearheads GM's path to next-gen architectures, processes and propulsion. Restoring the Cadillac brand to its golden-age pinnacle, when it stood equal among Europe's ultra-luxury greats, has long been an intermittent dream within GM. The grandiose ‘Sixteen’ concept in 2003 earned praise, raised hopes, and narrowly missed production approval. Next year, however, another no-compromises Cadillac - electric, of course - returns to take on Rolls-Royce and Maybach in the battle of unbridled luxury. Each Ultium-powered 2024 Celestiq will be bespoke - hand-built in a dedicated $81-million facility located within GM's Warren, Mich., Technical Center and personalized to its “client's” request. With an MSRP expected to begin at more than $300,000, Celestiq can be a prestigious profit-earner for GM. Strategically, the dramatic-proportioned EV spearheads technologies that are expected to cascade across GM's product portfolio. They include an architecture dominated by large aluminum castings; mass adoption of additive/3D printed components; sophisticated next-generation propulsion, advanced chassis control and interior systems, and GM's UltraCruise automated-driving tech.
Brooke, Lindsay
Catering to CustomizationTBMG-466677/1/2022
Made-to-order footwear, clothing, and jewelry. Patient-specific replacement joints and medication tailored to their age and weight. Bespoke bicycles, and office chairs that fit like the proverbial glove. These are just a few examples of the customized or personalized products that consumers have come to demand in recent years. How are manufacturers able to fulfill these expectations? In addition, how can they keep the final price from being driven upward by the immense complexity and supply chain disruption that product customization should cause?
SAE TOMORROW TODAY: Pursuing AV Micro-Transit on a Global Scale132265/13/2022
May Mobility's self-driving shuttles have provided more than 300,000 autonomous rides in nine cities in the US and Japan. And CEO Edwin Olson is just getting started. He has a recipe for transforming transportation - and quality of life - worldwide: - A policy of listening to people to understand the unique transit challenges they face in their communities - inaccessible public transit, for example, or a long trudge from the bus stop to the dining district. - A strategy to work with cities, state agencies, and private enterprises to customize autonomous vehicle (AV) services that fill mobility gaps. - A powerhouse partnership with Toyota capable of providing vehicles, services, and resources on a global scale. - A game-changing approach to AV software development, known as multi-policy decision-making. The underlying technology is critical to ensure safety and build trust, of course, but Olson argues that success starts with a human touch and understanding each community's unique needs. "Autonomous cars are hard, and every city brings new challenges for us to solve," he says. "There is nothing quite so motivating . . . as a real-world point of contact with riders and cities to determine where to focus and what to fix."
Hineman, Marcie
Co-Simulation Platform for Modeling and Evaluating Connected and Automated Vehicles and Human Behavior in Mixed Traffic12-05-04-00254/21/2022
Modeling, prediction, and evaluation of personalized driving behaviors are crucial to emerging advanced driver-assistance systems (ADAS) that require a large amount of customized driving data. However, collecting such type of data from the real world could be very costly and sometimes unrealistic. To address this need, several high-definition game engine-based simulators have been developed. Furthermore, the computational load for cooperative automated driving systems (CADS) with a decent size may be much beyond the capability of a standalone (edge) computer. To address all these concerns, in this study we develop a co-simulation platform integrating Unity, Simulation of Urban MObility (SUMO), and Amazon Web Services (AWS), where Unity provides realistic driving experience and simulates on-board sensors; SUMO models realistic traffic dynamics; and AWS provides serverless cloud computing power and personalized data storage. To evaluate this platform, we select cooperative on-ramp merging in mixed traffic as a study case, and establish human-in-the-loop (HuiL) simulations. The results show that our proposed platform can facilitate data collection and performance assessment for modeling personalized behaviors and interactions in CADS under various traffic scenarios.
Zhao, Xuanpeng, Liao, Xishun, Wang, Ziran, Wu, Guoyuan, Barth, Matthew, Han, Kyungtae, Tiwari, Prashant
Machine Learning Advances Personalized MedicineTBMG-407452/1/2022
A new study shows that machine learning techniques can offer powerful new tools for advancing personalized medicine. The research tackles long-unsolvable problems in biological systems at the cellular level. The new research is one of the first examples of using machine learning to address issues with modeling nonlinear systems and understanding complex processes that might occur in human tissues.
Making UX easy on THE EYES21AUTP10_0210/1/2021
Faurecia IRYStec combined physiology and image processing to create uniquely personalized high-fidelity screen displays, as pioneered by Mercedes' MBUX. The company's founder explains. The vital concept of personalized vision has been around since the 13th century, allegedly when the first eyeglasses appeared in Italy. It took nearly another 500 years for American inventor Benjamin Franklin to create bifocal lenses. If he'd had a glimpse into the future, the forward-thinking Franklin may have wondered why, with electronic display screens dominating 21st century life, the ability to deliver eye-friendly displays customized to the user's own vision had been largely neglected. That development came in 2015 when Tara Akhavan, an entrepreneurial Montreal-based computer engineer, completed her initial proof-of-concept for what became the world's first software platform using perception and physiology to optimize the user experience (UX) of display systems. Akhavan founded a company, IRYStec Software, to take her idea to market. Mobility applications soon became a focus, and with the help of fore-sighted investors and Tier-1 supplier Faurecia (whose Faurecia Clarion Electronics group acquired IRYStec in 2020), Akhavan's pioneering technology entered production in the MBUX Hyperscreen fitted in the 2021 Mercedes-Benz E-Class convertible.
Brooke, Lindsay
Moving One Step Closer to Personalized AnesthesiaTBMG-394747/1/2021
Anesthesia may be an exact science, but it’s not yet fully personalized. Anesthesiologists use a variety of methods to calculate the right dose for a given patient: clinical studies, medical databases and laboratory measurements, for example. However, every individual responds to anesthetics in a different way, and there’s no way of knowing what that response will be until the anesthetic is administered.
Device Combines Optics and Image Analysis to Count BiomoleculesTBMG-392806/1/2021
The promise of personalized medicine involves a simple device that keeps each person apprised of their level of health, identifies even trace amounts of undesirable biomarkers in blood or saliva, and serves as an early warning system for diseases.
Variations in User Implementation of the CORA Rating Metric2020-22-00014/2/2021
The CORA rating metric is frequently used in the field of injury biomechanics to compare the similarity of response time histories. However, subjectivity exists within the CORA metric in the form of user-customizable parameters that give the metric the flexibility to be used for a variety of applications. How these parameters are customized is not always reported in the literature, and it is unknown how these customizations affect the CORA scores. Therefore, the purpose of this study was to evaluate how variations in the CORA parameters affect the resulting similarity scores. A literature review was conducted to determine how the CORA parameters are commonly customized within the literature. Then, CORA scores for two datasets were calculated using the most common parameter customizations and the default parameters. Differences between the CORA scores using customized and default parameters were statistically significant for all customizations. Furthermore, most customizations produced score increases relative to the default settings. The use of standard deviation corridors and exclusion of the corridor component were found to produce the largest score differences. The observed differences demonstrated the need for researchers to exercise transparency when using customized parameters in CORA analyses.
Albert, Devon L
Expert Roundtable: Connected Mobility 2020: Faster, Smarter and Cooler?129251/25/2021
Panelists: John Waraniak, SEMA, Kelly Funkhouser, Consumer Reports, Kristin Slanina, True Car, Brian Cabell, FCA Group Connected, automated, and electric vehicles must connect with consumer lifestyles and experiences. For many, cars are works of art, access, power, fashion, and fun. They represent freedom and mobility, as well as passion and style. Consumers are demanding greater vehicle personalization and unique ride experiences from their vehicles while reshaping traditional mobility trends of capability, efficiency, and performance and fusing them with new and emerging models of convenience and lifestyle connectivity. Leading automakers and suppliers are designing and packaging their connected, automated, and electric technologies and product content around consumer branding and social context to set themselves from their competition with faster, smarter, and cooler vehicles.
by, Moderated
Low-Cost, Customized Prosthesis Using 3D PrintingTBMG-383071/1/2021
Upper limb forequarter amputations that involve the removal of the entire arm and scapula require highly customized prosthetic devices that are expensive but yet usually underutilized due to their high maintenance and low comfort levels. At the same time, while cosmetic prostheses — artificial limbs that provide patients the appearance of a pre-amputated body part — have a higher rate of continuous use, they have limitations in functional use.
Route Planning of Customizable and Cruising Autonomous Bus in CAV Environment2020-01-513512/30/2020
In order to improve the public service attributes and the utilization efficiency of CAV, the paper proposes a customizable and cruising autonomous bus (CCAB) route planning model. This model makes CCAB as customizable and fast as a taxi, and at the same time as a bus to meet multiple demands. Considering that CCAB needs to meet personalized customized riding demand, the paper combines allocation strategy of customized demands to establish a real-time optimization method for customizable and cruising routes based on the elliptical feasible area. This enable CCAB to have the ability of autonomous cruising and autonomous planning of customized routes. In CAV environment, the driver will be replaced by on-board computer of CCAB, the driver’s empirical route selection method will be replaced by the route planning model proposed in this paper. CCAB use historical ride data from each stop to predict future demand. Based on prediction results, the potential passenger rate of route is calculated, and the route is optimized at the same time, so as to determine the final cruising route of the unloaded/loaded bus. By route optimizing, the load rate of CCAB can be improved and the empty mileage can be reduced. The stability of route planning model proposed in this paper is verified by simulation. Meanwhile, sensitivity analysis is carried out by changing demand density and CCAB number in simulation. The conclusion is drawn that determining the optimal number of CCAB corresponding to different demand densities is of great significance for improving efficiency, reducing empty CCAB driving time and passenger waiting time.
Haijian, Bai, Jun, Wang, Liyang, Wei
Research on Self Driving Customized Bus Lines Based on Users’ Real-Time Needs2020-01-514012/30/2020
In order to solve the problem that the existing customized bus can only select transfer points on the static line, and cannot dynamically plan the route according to the user's real-time demand, this paper establishes a route planning model of unmanned customized bus with the total cost minimization as the optimization goal. The model comprehensively considers the operating cost, passenger satisfaction and charging demand of driverless public transport to ensure efficient transportation and excellent user experience. Dijkstra algorithm is applied to solve the shortest path selection problem involved in the model, and genetic algorithm is used to solve the model. The route selection schemes of vehicle transportation plan, driving route and charging plan are obtained to achieve the goal of minimizing the total cost. The validity and practicability of the model and method are verified by the example of Sioux Falls network.
Zhang, Xiaofeng, Zhao, Xiaomei, Xie, Dongfan, Bi, Jun
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