System Design Considerations Research Articles

Quantitative Measurements of Hazardous Gas Effluents from the Combustion of Crew Waste Simulant in Microgravity

Abstract In August 2021, Blue Origin launched their un-crewed NS-17 mission aboard their New Shepard launch vehicle. Among the scientific payloads was NASA’s Orbital Syngas Commodity Augmentation Reactor (OSCAR), a flight-capable test rig allowing the combustion of ~10 g of simulated astronaut trash. Developed at NASA’s Kennedy Space Center, OSCAR measured differences in the combustion of complex mixed waste materials between terrestrial gravity and microgravity conditions. OSCAR is self-contained and collects its own effluent gases, which were subsequently analyzed for trace volatile organic compounds (VOCs) with a modified EPA Method TO-15. It was found that combustion in microgravity produced higher levels of VOCs (2,883 mg measured VOCs per kg trash) than for analogous triplicate (terrestrial) laboratory experiments (1,237±286 mg measured VOCs per kg trash with 95% confidence interval), indicating significant differences that were consistent with previously reported combustion efficiencies. Also, the concentrations of the measured VOCs were compared to NASA’s Spacecraft Maximum Allowable Concentrations (SMAC) values. These results provide a basis for understanding important design considerations for spacecraft waste disposal systems as NASA and their commercial partners develop crewed vehicles for missions to the Moon and Mars.

Talk to the Wall: The Role of Speech Interaction in Collaborative Visual Analytics.

We present the results of an exploratory study on how pairs interact with speech commands and touch gestures on a wall-sized display during a collaborative sensemaking task. Previous work has shown that speech commands, alone or in combination with other input modalities, can support visual data exploration by individuals. However, it is still unknown whether and how speech commands can be used in collaboration, and for what tasks. To answer these questions, we developed a functioning prototype that we used as a technology probe. We conducted an in-depth exploratory study with 10 participant pairs to analyze their interaction choices, the interplay between the input modalities, and their collaboration. While touch was the most used modality, we found that participants preferred speech commands for global operations, used them for distant interaction, and that speech interaction contributed to the awareness of the partner's actions. Furthermore, the likelihood of using speech commands during collaboration was related to the personality trait of agreeableness. Regarding collaboration styles, participants interacted with speech equally often whether they were in loosely or closely coupled collaboration. While the partners stood closer to each other during close collaboration, they did not distance themselves to use speech commands. From our fndings, we derive and contribute a set of design considerations for collaborative and multimodal interactive data analysis systems. All supplemental materials are available at https://osf.io/8gpv2.

ELECTRO-MECHANICAL SYSTEM RELIABILITY AND FAIL-SAFE DESIGNS: EVALUATING THE BEST PRACTICES FOR ENSURING SYSTEM ROBUSTNESS AND LONGEVITY

This study provides a comprehensive analysis of the best practices for ensuring robustness, reliability, and longevity in electro-mechanical systems. The primary objectives were to evaluate the critical importance of fail-safe designs, explore the integration of advanced technologies such as AI and IoT, and develop effective strategies to enhance system performance and sustainability. Utilizing a systematic literature review methodology, the research involved a thorough examination of academic databases and digital libraries, adhering to strict inclusion and exclusion criteria. The search strategy focused on peer-reviewed articles published between 2000 and 2023, encompassing studies on electro-mechanical systems, reliability engineering, and advanced technological integrations. Key findings highlight the evolution of fail-safe designs and the significant role of smart sensors, AI, and IoT in enhancing system robustness and predictive maintenance capabilities. The study underscores the economic, environmental, and safety considerations in system design and operation, emphasizing the need for a holistic approach that includes technical, operational, and strategic aspects. Future challenges identified include managing complex integrated systems, adapting to rapid technological advancements, and addressing environmental and safety concerns. The study recommends that industry practitioners invest in R&D for advanced sensing technologies and predictive maintenance, while policymakers should focus on creating standards that encourage innovation and environmental sustainability. Future research directions include exploring the long-term impacts of emerging technologies on system reliability and longevity, and investigating sustainable materials and practices in system design. This comprehensive analysis offers valuable insights for researchers, industry practitioners, and policymakers in the field of electro-mechanical systems.
 Keywords: Electro-Mechanical Systems, System Reliability, Fail-Safe Design, System Longevity.

A Review on Malicious URLs Detection Using Machine Learning Methods

Malicious URLs are a serious threat to cybersecurity because they can compromise user security and inflict large financial losses. The extensiveness and adaptability of traditional detection approaches which rely on blacklists are limited when it comes to rapidly emerging threats. In response, machine learning methods have become more popular as a means of improving the detection efficiency of malicious URLs. This paper provides a thorough analysis providing a structured understanding of all aspects and formal formulation of the machine learning job of malicious URL detection. It covers feature representation and algorithm design, classifying and reviewing contributions from literature studies. The survey aims to provide a state-of-the-art understanding and support future research and practical implementations. It targets a diverse audience, including experts, cybersecurity professionals and machine learning researchers. The article provides a comprehensive overview of the field discussing practical system design considerations, ongoing research challenges and future research directions.

Considerations for determining the performance of ultraviolet light emitting diode fluid disinfection systems.

The International Ultraviolet Association (IUVA) Task Force was formed to develop guidelines regarding testing and reporting on performance of UV LED water disinfection systems. The goal was to provide clarity in a guidance document on measuring system performance across the global UV LED water disinfection system market. A review of current performance measurement protocols for mercury lamp based systems shows that the common elements of UV LED system performance measurement protocols should be as follows: specified standard for the amount of pathogen reduction required, the requirement that the validation testing be conducted by a competent facility, and that the system be continually monitored by UV sensors while in use to verify system performance unless pathogen reduction is not claimed. UV LEDs have selectable peak wavelengths, as opposed to mercury lamps that have fixed emission wavelength values. As a result of this difference, the following changes to protocols used to test mercury lamp systems are recommended. First, the use of disinfection benchmarks other than 254 nm dose, such as direct inactivation values, dose benchmarks referenced to 254 nm, and/or dose benchmarks at the UV LED emission wavelength that give the same inactivation as the original 254 nm UV dose benchmark. Second, the use of 254 nm UV water transmittance values as a placeholder, rather than an assumed correct value, for systems under test with LED wavelengths >250 nm and water transmittance values ≥87%. More research is needed for lower wavelengths and UVTs. Third, the recommendation that germicidal response UV sensors be used in UV LED based systems to ensure that the validated disinfection is delivered. Finally, additional LED-specific considerations were also noted. UV LEDs are also instant-on devices, making them ideal light sources for systems operated intermittently. Performance testing of systems operated intermittently should include a test to insure that pathogens do not migrate past the UV LEDs while the LEDs are off. UV LED devices have recognized protocols for determining the lifetime of the devices, as well as for measuring other device properties. Caution should be exercised in using these lifetime values for devices in UV disinfection systems, since the thermal environment of the devices may be different for protocol testing and disinfection system operation. PRACTITIONER POINTS: Validation of UVC LED fluid disinfection is necessary for point of use, point of entry, and municipal applications. The emission spectrum properties, considerations and measurements for output over lifetime, and unique system design considerations of UVC LEDs as light sources are factors that must be considered when evaluating fluid disinfection performance. The instant-on operation, system geometry, validation benchmarks, system sensing, water transmittance, and fouling must also be considered for UVC LED devices when evaluating fluid disinfection performance.

Geographical challenges and inequity of healthcare access for high-risk paediatric heart disease.

Geographical context is an important consideration for health system design to promote equality in access to care for patients with childhood heart disease (CHD), particularly those living in regional, rural, and remote areas. To help inform future policy and practice recommendations, this study aimed to (i) describe the geographic distribution of high-risk CHD patients accessing an Australian state-wide specialist service and (ii) estimate travel time for accessing healthcare via general practitioners (primary), nearest paediatric centre (secondary) and specialist paediatric cardiac centre (tertiary). Participants included a cohort of children (0-18year) who accessed state-wide specialist CHD services over a 3-year period (2019-2021) in Queensland, Australia. Locations for patient residence, general practitioner, closest paediatric centre and tertiary cardiac centre were mapped using geographical information system (GIS) software (ArcGIS Online). Travel distance and times were estimated using a Google Maps Application Programming Interface (API). 1019 patients (median age 3.8 years) had cardiac intervention and were included in the sample. Of this cohort, 30.2% lived outside the heavily urbanised South East Queensland (SEQ) area where the tertiary centre is located. These patients travel substantially further and longer to access tertiary level care (but not secondary or primary level care) compared to those in SEQ. Median distance for patients residing outside SEQ to access tertiary care was 953km with a travel time of 10h 43min. This compares to 5.5km to the general practitioner and 20.6km to a paediatric service (8.9 and 54min respectively). This geographical mapping of CHD services has demonstrated a key challenge inherent in providing specialist cardiac care to children in a large state-based healthcare system. A significant proportion of high-risk patients live large distances from tertiary level care. The greater accessibility of primary care services highlights the importance of supporting primary care physicians outside metropolitan areas to acquire or build the ability and capacity to care for children with CHD. Strengthening local primary and secondary services not only has the potential to improve the outcomes of high-risk patients, but also to reduce costs and burden associated with potentially avoidable travel from regional, rural, or remote areas to access specialist CHD services.

Feasibility analysis of thermal storage defrosting method for air source heat pump: From energetic and economic viewpoints

Frosting issue of air source heat pump (ASHP) is a continuing concern. The conventional reverse cycle defrosting (RCD) method absorbs heat from indoor heat exchanger, thus greatly impacts the indoor thermal comfort. To solve the problem of insufficient defrosting heat supply for RCD method, thermal energy storage (TES) based defrosting method has gained increasing attention over the past years. Yet existing studies have only focused on specific prototype tests. There lacks general analysis on system characteristics and design considerations. To better address application concerns of TES-based defrosting method, this study carried out feasibility analysis for the TES-based ASHP system from both energetic and economic aspects. The energetic analysis reveals that the stable operation of TES-based ASHP relies on proper system design and control. Feasibility conditions concerned with key operating parameters are defined and deduced. Impact factors on average heating efficiency are also analyzed. Theoretical and numerical results indicate that energy saving potential of TES-based ASHP over conventional ASHP is conditional on the defrosting discount factor of conventional RCD method. TES-based ASHP enhances heating efficiency of conventional ASHP by 3.0% to 19.5% at ambient from −2°C to 2 °C due to relatively large defrosting discount factor of conventional RCD method. With respect to the economic aspects, the capital cost of TES-based ASHP is 26% higher than that of the conventional ASHP. But the total life cycle cost can be reduced by higher heating efficiency. The condensing heat storage ASHP exhibits cost advantages to the conventional ASHP when defrosting discount factor of conventional ASHP is higher than 1.13. Further prototype test with the TES-based ASHP could shed more light on the feasibility characteristics as revealed by the theoretical analysis.

Energy Performance and HVAC System Design Considerations for Indoor Agricultural Facilities

Energy Performance and HVAC System Design Considerations for Indoor Agricultural Facilities

Modeling and Analysis of Suspension-Based Electrolytes in Redox Flow Cells

Electrochemical systems with flowable suspension electrolytes (FSEs) have potential to help address growing demands for large-scale energy storage in order to bridge the gap between energy demand and renewable energy generation. Redox flow batteries with FSEs, for example, have several advantages in addition to long-duration energy storage and independent scaling of power and energy offered by the traditional flow batteries.1 FSEs containing solid energy storage materials enable higher charge storage capacities and hence higher energy densities, as well as new operating modes such as dissolution from and precipitation onto suspended particles.2-3 However, these emerging electrolyte compositions challenge cell design and operation as new performance trade-offs arising from the complex interplay of non-Newtonian rheology, flow-dependent transport properties, and electrochemical phenomena, must be considered.4 In this presentation, we will introduce a one-dimensional model to study the performance of a representative FSE-containing redox flow cell as a function of various material properties and operating conditions. The model integrates porous electrode theory with non-Newtonian suspension rheology and flow-dependent charge and species transport to investigate connections between rheological and electrochemical phenomena. We expound key dimensionless groups that arise from non-dimensionalizing the governing equations and describe the relative magnitudes of interrelated processes. We discuss model predictions of the cell performance in the multivariable space of the dimensionless groups using computed cell overpotentials and power relative to the pumping power, and identify specific operating regimes. Ultimately, the analysis will offer design considerations for electrochemical systems with FSEs, allowing more informed materials selection, cell engineering, and system architectures. Acknowledgments This work was funded by the Skoltech – MIT Next Generation Program. B.J.N gratefully acknowledge the NSF Graduate Research Fellowship Program under Grant Number 1122374. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. References M. L. Perry and A. Z. Weber, J. Electrochem. Soc., 163, A5064–A5067 (2016).H. Parant et al., Carbon, 119, 10–20 (2017).X. Wang, J. Chai, and J. “Jimmy” Jiang, Nano Materials Science, 3, 17–24 (2021).N. C. Hoyt, R. F. Savinell, and J. S. Wainright, Chemical Engineering Science, 144, 288–297 (2016).

A crowdsourced co-modality transportation system integrating passenger and freight

Co-modality transportation aims to integrate passenger and freight flows into a single system by sharing public transport between passengers and freight. This paper proposes a crowdsourced co-modality transportation system (CCTS) for enhancing the practical implementation of co-modality transportation in urban areas. Firstly, empirical investigations are conducted, including semi-structured interviews with industry practitioners and online surveys with passengers, to collect system design considerations. Secondly, an overview of the crowdsourced co-modality management platform (CCMP) is presented by highlighting three key components: co-modality services, information infrastructure, and decision support system. Thirdly, we formulate the parcel assignment problem in the CCTS and examine the factors that influence the performance of the CCTS. The empirical investigations suggest that crowdsourced passengers care about the potential risks and the degree of operation difficulty in crowdsourced activities but do not care about privacy issues. In addition, the experimental studies show that crowdsourced co-modality is more feasible and promising if more passengers are willing to provide crowdsourcing services.

Impact of Refrigerants Transition on HVAC System Performance and Environmental Sustainability

This study investigates the impact of refrigerant transitions on Heating, Ventilation, and Air Conditioning (HVAC) system performance and environmental sustainability. Through simulation-based analysis, the research evaluates the performance of three refrigerants: HFC-134a, R-410A, and HFO-1234yf. The study assesses cooling efficiency, energy consumption, and global warming potential (GWP) as key performance metrics. Results reveal that transitioning to low-GWP alternatives, particularly HFO-1234yf, enhances cooling efficiency and reduces energy consumption by 12% and 24% compared to R-410A and HFC-134a, respectively. HFO-1234yf also demonstrates a notable 98% reduction in GWP compared to HFC-134a. The discussion highlights the potential of low-GWP refrigerants to balance system performance gains with environmental concerns. Consideration of system design, operating conditions, and trade-offs further underscores the significance of responsible refrigerant choices in achieving sustainable HVAC practices. This research contributes to the ongoing discourse on sustainable technologies, offering practical insights for HVAC practitioners, designers, and policymakers striving to align efficiency with environmental responsibility in HVAC systems

A residual connection enabled deep neural network model for optic disk and optic cup segmentation for glaucoma diagnosis.

Glaucoma diagnosis at an early stage is vital for the timely initiation of its treatment for and preventing possible vision loss. For glaucoma diagnosis, an accurate estimation of the cup-to-disk ratio (CDR) is required. The current automatic CDR computation techniques attribute lower accuracy and higher complexity, which are important considerations for diagnostics system design to be used for such critical diagnoses. The current methods involve a deeper deep learning model, comprising a large number of parameters, which results in higher system complexity and training/testing time. To address these challenges, this paper proposes a Residual Connection (non-identity)-based Deep Neural Network (RC-DNN), which is based on non-identity residual connectivity for joint optic disk (OD) and optic cup (OC) detection. The proposed model is emboldened by efficient residual connectivity, which is beneficial in several ways. First, the model is efficient and can perform simultaneous segmentation of the OC and OD. Second, the efficient residual information flow permeates the vanishing gradient problem which results in faster converges of the model. Third, feature inspiration empowers the network to perform the segmentation with only a few network layers. We performed a comprehensive performance evaluation of the developed model based on its training in RIM-ONE and DRISHTIGS databases. For OC segmentation, for the images (test set) from {DRISHTI-GS and RIM-ONE} datasets, our proposed model achieves the dice coefficient, Jaccard coefficient, sensitivity, specificity, and balanced accuracy of {92.62, 86.52}, {86.87, 77.54}, {94.21, 95.36}, {99.83, 99.639}, and {94.2, 98.9}, respectively. These experimental results indicate that the developed model provides significant performance enhancement for joint OC and OD segmentation. Additionally, the reduced computational complexity based on reduced model parameters and higher segmentation accuracy provides the additional features of efficacy, robustness, and reliability of the developed model. These attributes of the developed model advocate for its deployment of population-scale glaucoma screening programs.

Design, fabrication and assembly considerations for electronic systems made of fibre devices

Design, fabrication and assembly considerations for electronic systems made of fibre devices

Single-shot extended field of view imaging using point spread function engineering.

We present a single-shot computational imaging system employing pupil phase engineering to extend the field of view (FOV) beyond the physical sensor limit. Our approach uses a point spread function in the form of a multiple-point impulse response (MPIR). Unlike the traditional point-to-point imaging model used by most traditional optical imaging systems, the proposed MPIR model can collect information from within and outside the sensor boundary. The detected raw image despite being scrambled can be decoded via a sparse optimization algorithm to get extended FOV imaging performance. We provide a thorough analysis of MPIR design regarding the number of impulses and their spatial extent. Increasing the number of impulses in MPIR of a given spatial extent leads to better information gathering within the detector region; however, it also reduces contrast in the raw data. Therefore, a trade-off between increasing the information and keeping adequate contrast in the detected data is necessary to achieve high-quality reconstruction. We first illustrate this trade-off with a simulation study and present experimental results on a suitably designed extended FOV imaging system. We demonstrate reconstructed images with a 4× gain in pixels over the native detection area without loss of spatial resolution. The proposed system design considerations are generic and can be applied to various imaging systems for extended FOV performance.

Holistic fleet optimization incorporating system design considerations

AbstractThe methodology described in this article enables a type of holistic fleet optimization that simultaneously considers the composition and activity of a fleet through time as well as the design of individual systems within the fleet. Often, real‐world system design optimization and fleet‐level acquisition optimization are treated separately due to the prohibitive scale and complexity of each problem. This means that fleet‐level schedules are typically limited to the inclusion of predefined system configurations and are blind to a rich spectrum of system design alternatives. Similarly, system design optimization often considers a system in isolation from the fleet and is blind to numerous, complex portfolio‐level considerations. In reality, these two problems are highly interconnected. To properly address this system‐fleet design interdependence, we present a general method for efficiently incorporating multi‐objective system design trade‐off information into a mixed‐integer linear programming (MILP) fleet‐level optimization. This work is motivated by the authors' experience with large‐scale DOD acquisition portfolios. However, the methodology is general to any application where the fleet‐level problem is a MILP and there exists at least one system having a design trade space in which two or more design objectives are parameters in the fleet‐level MILP.

Cyberattack Tracing System Operational Architecture

APT cyber attacks have been a problem for over a past decade, but still remain a challenge today as attackers use more sophisticated techniques and the number of objects to be protected increases. ‘Cyberattack Tracing System’ allows analysts to find undetected attack codes that penetrated and hid in enterprises, and to investigate their lateral movement propagation activities. The enterprise is characterized by multiple networks and mass hosts (PCs/servers). This paper presents a data processing procedure that collects event data, generates a temporally and spatially extended provenance graph and cyberattack tracing paths. In each data process procedure phases, system design considerations are suggested. With reflecting the data processing procedure and the characteristics of enterprise environment, an operational architecture for CyberAttack Tracing System is presented. The operational architecture will be lead to the detailed design of the system.

Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations.

Identifying patients' social needs is a first critical step to address social determinants of health (SDoH)-the conditions in which people live, learn, work, and play that affect health. Addressing SDoH can improve health outcomes, population health, and health equity. Emerging SDoH reporting requirements call for health systems to implement efficient ways to identify and act on patients' social needs. Automatic extraction of SDoH from clinical notes within the electronic health record through natural language processing offers a promising approach. However, such automated SDoH systems could have unintended consequences for patients, related to stigma, privacy, confidentiality, and mistrust. Using Floridi et al's "AI4People" framework, we describe ethical considerations for system design and implementation that call attention to patient autonomy, beneficence, nonmaleficence, justice, and explicability. Based on our engagement of clinical and community champions in health equity work at University of Washington Medicine, we offer recommendations for integrating patient voices and needs into automated SDoH systems.

Investigation on the performance of an active noise control window system mounted on the top-hung window of a residential room

Urban noise mitigation experiment through active noise control window is not commonly carried out in in situ urban setting. This paper outlines our experimental settings of performing active noise control across the open aperture of the top-hung window frame in a dormitory room. A multi-channel adaptive filtered-x least mean square method is implemented in real-time. Experiments and analyses are carried out to investigate how the noise reduction performance of this active noise control window system is affected by the number of reference microphones, the distance between reference microphones and secondary sources, and the distributions of error microphones under practical restrictions of the real system implementation. Variation of the secondary path estimation is another important consideration in active noise control system design. Real-time experiments are carried out to investigate the sensitivity of the ANC window system over the secondary path variation caused by varying window opening status, and whether a generalised secondary path measured in one window opening setting can be applied to other window opening conditions.

Rapid Prototyping and Tooling Technology to Assist the Development of Low-Cost Dies

This case study aims toward the importance of the application of rapid prototyping and tooling technology in die design and manufacturing. Many conventional machining processes of die manufacturing, including computer numeric control (CNC) machining and electric discharge machining (EDM), are used by the local manufacturers of die, but these processes are time-consuming and expensive. There is a need to explore opportunities to reduce die manufacturing costs. This paper aims to assist the development of low-cost dies through the application of rapid prototyping and tooling technology. For this purpose, solid works software was used to design the die of a 4-hole Lego Block. 3D printing was incorporated in the existing capability of investment casting process for die manufacturing. A proper gating system design consideration was taken into account to ensure the accurate flow of casting material for achieving fine surface finish. From the results, it has been observed that gating system design with four ingates gives the optimum value of surface finish (~3.4156μm). The proposed rapid prototyping and tooling technology makes the practitioners (tool makers) capable of making dies with complex shapes, superior surface finishes, and dimensional accuracy in less or no time.

Thermo-electro-optical properties of seamless metallic nanowire networks for transparent conductor applications.

Rapid reaction time, high attainable temperatures, minimum operating voltage, excellent optical transmittance, and tunable sheet resistance are all desirable properties of transparent conductors, which are important thin-film components in numerous electronic devices. A seamless nanowire network (NWN) refers to a structure composed of nanowires that lack interwire contact junctions, resulting in a continuous and uninterrupted network arrangement. This seamless nature leads to unique properties, including high conductivity and surface area-to-volume ratios, which make it a promising candidate for a vast application range in nanotechnology. Here, we have conducted an in-depth computational investigation to study the thermo-electro-optical properties of seamless nanowire networks and understand their geometrical features using in-house computational implementations and a coupled electrothermal model built in COMSOL Multiphysics software. Sheet resistance calculations were performed using Ohm's law combined with Kirchhoff circuit laws for a random resistor network and compared with those obtained employing COMSOL. In this work, aluminium, gold, copper, and silver nanowires are the materials of choice for testing the transparent conduction performance of our systems. We have studied a wide range of tuning parameters, including the network area fraction, the width-to-depth aspect ratio, and the length of the nanowire segments. We obtained corresponding figures of merit (optical transmittance versus sheet resistance) and temperature distributions to provide a complete characterization of the performance of real-world transparent conductors idealized with seamless NWNs. Our analysis accounted for the thermo-electro-optical responses of the NWNs and the inspection of various controlling parameters depending on system design considerations to shed light on how the electrical transport, optical qualities, and thermal management of these systems can be optimized.