Low Intrusion Research Articles

Validation of computer vision-based ergonomic risk assessment tools for real manufacturing environments

This study contributes to understanding semi-automated ergonomic risk assessments in industrial manufacturing environments, proposing a practical tool for enhancing worker safety and operational efficiency. In the Industry 5.0 era, the human-centric approach in manufacturing is crucial, especially considering the aging workforce and the dynamic nature of the entire modern industrial sector, today integrating digital technology, automation, and sustainable practices to enhance productivity and environmental responsibility. This approach aims to adapt work conditions to individual capabilities, addressing the high incidence of work-related musculoskeletal disorders (MSDs). The traditional, subjective methods of ergonomic assessment are inadequate for dynamic settings, highlighting the need for affordable, automatic tools for continuous monitoring of workers’ postures to evaluate ergonomic risks effectively during tasks. To enable this perspective, 2D RGB Motion Capture (MoCap) systems based on computer vision currently seem the technologies of choice, given their low intrusiveness, cost, and implementation effort. However, the reliability and applicability of these systems in the dynamic and varied manufacturing environment remain uncertain. This research benchmarks various literature proposed MoCap tools and examines the viability of MoCap systems for ergonomic risk assessments in Industry 5.0 by exploiting one of the benchmarked semi-automated, low-cost and non-intrusive 2D RGB MoCap system, capable of continuously monitoring and analysing workers’ postures. By conducting experiments across varied manufacturing environments, this research evaluates the system’s effectiveness in assessing ergonomic risks and its adaptability to different production lines. Results reveal that the accuracy of risk assessments varies by specific environmental conditions and workstation setups. Although these systems are not yet optimized for expert-level risk certification, they offer significant potential for enhancing workplace safety and efficiency by providing continuous posture monitoring. Future improvements could explore advanced computational techniques like machine learning to refine ergonomic assessments further.

Estimating the Energy Expenditure of Grazing Farm Animals Based on Dynamic Body Acceleration.

Indirect methods of measuring the energy expenditure of grazing animals using heartbeat variation or accelerometers are very convenient due to their low cost and low intrusiveness, allowing animals to maintain their usual routine. In the case of accelerometers, it is possible to use them to measure activity, as well as to classify animal behavior, allowing their usage in other scenarios. Despite the obvious convenience of use, it is important to evaluate the measurement error and understand the validity of the measurement through a simplistic method. In this paper, data from accelerometers were used to classify behavior and measure animal activity, and an algorithm was developed to calculate the energy expended by sheep. The results of the energy expenditure calculations were subsequently compared with the values reported in the literature, and it was verified that the values obtained were within the reference ranges. Although it cannot be used as a real metering of energy expended, the method is promising, as it can be integrated with other complementary sources of information, such as the evolution of the animal's weight and ingestion time, thus providing assistance in animals' dietary management.

Natural noise management in collaborative recommender systems over time-related information

Recommender systems are currently a suitable alternative for providing easy and appropriate access to information for users in today’s digital information-overloaded world. However, an important drawback of these systems is the inconsistent behavior of users in providing item preferences. To address this issue, several natural noise management (NNM) approaches have been proposed, which positively influence recommendation accuracy. However, a major limitation of such previous works is the disregarding of the time-related information coupled to the rating data in RSs. Based on this motivation, this paper proposes two novel methods, named SeqNNM and SeqNNM-p for NNM focused on an incremental, time-aware recommender system scenario that has not yet been considered, by performing a classification-based NNM over specific preference sequences, driven by their associated timestamps. Such methods have been evaluated by simulating a real-time scenario and using metrics such as mean absolute error, root-mean-square error, precision, recall, NDCG, number of modified ratings, and running time. The obtained experimental results show that in the used settings, it is possible to achieve better recommendation accuracy with a low intrusion degree. Furthermore, the main innovation associated with the overall contribution is the screening of natural noise management approaches to be used on specific preferences subsets, and not over the whole dataset as discussed by previous authors. These proposed approaches allow the use of natural noise management in large datasets, in which it would be very difficult to correct the entire data.

Extent and survival of zoned pyroxene within intrusions hosting magmatic sulfides: Implications for zoned pyroxene as a prospectivity indicator

AbstractChromium-zoning patterns in pyroxene from the economically significant Ni-Cu sulfide deposits at Nova-Bollinger (Western Australia) and Kevitsa (Northern Finland) were investigated using XRF mapping, automated mineralogy, and EPMA analyses. At Nova-Bollinger, complex Cr-zoning patterns are found widely throughout the cumulus orthopyroxene and clinopyroxene within the Lower Intrusion, a small chonolith that hosts the vast extent of the sulfide mineralisation. Cumulus pyroxenes with visible sector and abrupt zonation patterns have been found up to 150 m vertically away from the massive sulfide ore. Complex zoning patterns are observed throughout the Kevitsa intrusion, in the form of strong oscillatory zoning in cumulus clinopyroxene and sector zoning in idiomorphic orthopyroxene oikocrysts. Kevitsa pyroxenes show varying degrees of hydration, leading to epitaxial replacement by amphibole. Cr zonation is visible through the early stages of this alteration, with preservation enabled by the presence of Cr-rich epitaxial amphibole; however, the remnant zoning is lost as the amphibole alteration progresses. Results suggest that Cr zonation in pyroxene may be an effective indicator of dynamic recharged conduits and therefore an indicator of favourable conditions for metal enriched magmatic sulfide ore formation. Such indicators have significant vertical extent from the ore body and can survive partial alteration, which makes them a useful tool for prospectivity assessment of drilled intrusions. Furthermore, our data show that there is potential for complexly zoned pyroxene to be used as an ex-situ prospectivity indicator in glacial till.

Assessment of the dynamic parameters of a 673-meter cable-stayed bridge with wireless three-component MEMS-based sensors

Dynamic structural monitoring of bridges under ambient vibrations is a method to assess dynamic parameters of structures with low intrusiveness, e.g. with Operational Modal Analysis (OMA) data processing. Yet, several barriers hinder its adoption for real world applications, such as a lack of adequate sensors or industrial sensor networks and more generally, a lack of integrated solutions. In this paper, we present a data collection campaign using a novel wireless sensing system for dynamic structural monitoring of civil engineering structures. The core enabler of this SHM product named S-lynks is the use of a novel ultra-low noise seismic MEMS accelerometer, QuietSeisTM, which makes possible to envision a true industrial wireless sensor network for OMA in civil engineering structures. We developed a bespoke wireless sensing system composed of Wireless Sensor Nodes (WSN) and Gateways (WSG) and combining Low Power Wide Area Network (LPWAN) and Wireless Local Area Network (WLAN) technologies to manage the WSN wake up, synchronization and data transmission to WSG. This product has been used on a 675-meter cable-stayed bridge to assess the dynamic parameters from ambient vibrations measurements. We successfully triggered 120 measure points on the deck and inside a tower in less than 10 hours. More than 20 modes are identified between 0 and 5 Hz, with well-defined mode shapes. Extra measurements on a few cables to identify the tension allow explaining the asymmetry observed in some mode shapes.

Spatial features of CO2 for occupancy detection in a naturally ventilated school building

Accurate occupancy information helps to improve building energy efficiency and occupant comfort. Occupancy detection methods based on CO2 sensors have received attention due to their low cost and low intrusiveness. In naturally ventilated buildings, the accuracy of CO2-based occupancy detection is generally low in related studies due to the complex ventilation behavior and the difficulty in measuring the actual air exchange through windows. In this study, we present two novel features for occupancy detection based on the spatial distribution of the CO2 concentration. After a quantitative analysis with Support Vector Machine (SVM) as classifier, it was found that the accuracy of occupancy state detection in naturally ventilated rooms could be improved by up to 14.8 percentage points compared to the baseline, reaching 83.2 % (F1 score 0.84) without any ventilation information. With ventilation information, the accuracy reached 87.6 % (F1 score 0.89). The performance of occupancy quantity detection was significantly improved by up to 25.3 percentage points versus baseline, reaching 56 %, with root mean square error (RMSE) of 11.44 occupants, using only CO2-related features. Additional ventilation information further enhanced the performance to 61.8 % (RMSE 9.02 occupants). By incorporating spatial features, the model using only CO2-related features revealed similar performance as the model containing additional ventilation information, resulting in a better low-cost occupancy detection method for naturally ventilated buildings.

Dimensionless numbers reveal distinct regimes in the structure and dynamics of pedestrian crowds.

In fluid mechanics, dimensionless numbers like the Reynolds number help classify flows. We argue that such a classification is also relevant for crowd flows by putting forward the dimensionless Intrusion and Avoidance numbers, which quantify the intrusions into the pedestrians' personal spaces and the imminency of the collisions that they face, respectively. Using an extensive dataset, we show that these numbers delineate regimes where distinct variables characterize the crowd's arrangement, namely, Euclidean distances at low Avoidance number and times-to-collision at low Intrusion number. On the basis of these findings, a perturbative expansion of the individual pedestrian dynamics is carried out around the noninteracting state, in quite general terms. Simulations confirm that this expansion performs well in its expected regime of applicability.

Lightweight and compact smart walking cane.

Devices such as canes and wheelchairs, used to assist locomotion, have remained mostly unchanged for centuries. Recent advances in robotics have the potential to develop smart versions of these devices that can offer better support and living conditions to their users. This is the underlying objective of this project. The existing devices, used during recovery and rehabilitation phases where gait stability is key, are often bulky and cannot be easily migrated from hospital to domestic environments, where maneuvering space tends to be restricted. This article discusses a compact, lightweight and minimally invasive, robotic cane to assist locomotion. The device can assist users with mild locomotion disabilities, e.g., in the final stages of rehabilitation, to maintain and recover their balance in standing and walking situations. This extends previous experiments with alternative control strategies, merged with indicators (based on the Gini index) able to recognize differences between users. Several experiments, with a range of users possessing different mobility impairments, confirm the viability of the robotic cane, with users comfortably using the cane after three minutes, on average, proving its ease of use and low intrusiveness, and with constant support offered during the whole movement. Furthermore, the real-time tuning of the controller gains, via the Gini inequality index, enables adjustment to the user's movement.

Intrusion tip velocity controls the emplacement mechanism of sheet intrusions

Space for intruding magma is created by elastic, viscous, and/or plastic deformation of host rocks. Such deformation impacts the geometries of igneous intrusions, particularly sills and dikes. For example, tapered intrusion tips indicate linear-elastic fracturing during emplacement, whereas fluidization of host rocks has been linked to development of elongate magma fingers with rounded tips. Although host rock fluidization has only been observed at the lateral tips of magma fingers, it is assumed to occur at their leading edges (frontal tips) and thereby control their propagation and geometry. Here, we present macro- and microstructural evidence of fluidized sedimentary host rock at the lateral tips of magma fingers emanating from the Shonkin Sag laccolith (Montana, western United States), and we explore whether fluidization could have occurred at their frontal tips. Specifically, we combine heat diffusion modeling and fracture tip velocity estimates to show that: (1) low intrusion tip velocities (≤10−5 m s−1) allow pore fluids ahead of the intrusion to reach temperatures sufficient to cause fluidization, but (2) when tip velocities are high (∼0.01−1 m s−1), which is typical for many sheet intrusions, fluidization ahead of propagating tips is inhibited. Our results suggest that intrusion tip velocity (i.e., strain rate) is a first-order control on how rocks accommodate magma. Spatially and temporally varying velocities of lateral and frontal tips suggest that deformation mechanisms at these sites may be decoupled, meaning magma finger formation may not require host rock fluidization. It is thus critical to consider strain rate and three-dimensional intrusion geometry when inferring dominant magma emplacement mechanisms.

A stress-is-enhancing mindset is associated with lower traumatic stress symptoms during the COVID-19 pandemic

ABSTRACT Background A stress-is-enhancing mindset is associated with lower perceived stress and better coping. However, work examining the prospective associations of stress mindset on perceived traumatic stress symptoms during a stressful real-world life event is limited. The present prospective study explored whether stress-is-enhancing mindset measured before the onset of the COVID-19 global pandemic was associated with later traumatic stress symptoms in response to the COVID-19 global pandemic. Methods University students (N = 179; 68% female; Mage = 19.31, SD = 0.79 years) completed the Stress Mindset Measure (SMM) prior to COVID-19 pandemic onset as part of a larger study. The Impact of Event Scale-Revised (IES-R) with respect to the COVID-19 pandemic was completed 1 year into the pandemic. Results SMM negatively predicted the IES-R subscales intrusion, avoidance, and hyperarousal such that a more stress-is-enhancing mindset was associated with lower intrusion, avoidance, and hyperarousal following the onset of COVID-19. Conclusions Results suggest a more positive stress mindset is associated with fewer traumatic stress symptoms following a traumatic life event. Altering stress mindset may be an avenue for future interventions to cope with stress.

Bimetallic Zeolitic Imidazole Frameworks for Improved Stability and Performance of Intrusion-Extrusion Energy Applications.

Hydrophobic flexible zeolitic imidazole frameworks (ZIFs) represent reference microporous materials in the area of mechanical energy storage, conversion, and dissipation via non-wetting liquid intrusion-extrusion cycle. However, some of them exhibit drawbacks such as lack of stability, high intrusion pressure, or low intrusion volume that make them non-ideal materials to consider as candidates for real applications. In this work, we face these limitations by exploiting the hybrid ZIF concept. Concretely, a bimetallic SOD-like ZIF consisting of Co and Zn ions was synthesized and compared with Co-ZIF (ZIF-67) and Zn-ZIF (ZIF-8) showing for the first time that the hybrid ZIF combines the good stability of ZIF-8 with the higher water intrusion volume of ZIF-67. Moreover, it is shown that the hybrid-ZIF approach can be used to tune the intrusion/extrusion pressure, which is crucial for technological applications.

A Teacher’s Guide to Technology-Based Self-Monitoring Strategies for Student Behavior

Students with disabilities may demonstrate high rates of off-task behavior, resulting in poor academic achievement. To decrease students’ off-task behavior, teachers can identify student-guided supportive strategies to limit the amount of time they dedicate to behavior management. Moreover, when teachers use effective student-guided strategies that reflect high social validity, ease of use, and low intrusiveness, benefits are maximized and students will maintain their use of the strategy. This article provides step-by-step procedures for designing a technology-based self-monitoring (TBSM) strategy that increases the acceptability and continued use of standard self-monitoring procedures. Necessary adjustments to typical self-monitoring strategies considering technology-based delivery methods, including selecting and evaluating mobile applications, are introduced.

Triaxial accelerometer based azimuth estimator for horizontal axis wind turbines

One of the elements that receives the greatest stresses is the main shaft. Its damage is directly related to the cyclical nature of its rotational motion. However, the vast majority of horizontal axis wind turbines (HAWT) do not have sensors to measure the main-shaft angular position (azimuth), or they are not always easily accessible.Using a main-shaft placed single triaxial accelerometer for the estimation of the azimuth is proposed as a low intrusion approach that can be easily deployed in machines already in use. An approach using a tandem of two extended Kalman filters (calibration/prediction), aiming for a precise and robust estimation, is presented. The estimator is able to calibrate for accelerometer positional and orientation errors, as well as for bias drift. To simplify the burden of deployment, a simple procedure is proposed to determine the covariance matrices for a particular HAWT from those determined in a synthetic case.The proposed approach is analyzed using synthetic data, OpenFAST simulation of NREL-5MW HAWT. It outperforms the ATAN naive approach by an order of magnitude, showing errors smaller than 0.4o. The filter shows a good behavior, coherent with that of the synthetic setup, when tested on experimental data obtained from a 3MW HAWT.

Campus food service users' support for nudge strategies for fruit and vegetable-rich items: findings from a large Canadian national sample.

Although customer support is critical to the wider uptake of nudging strategies to promote fruits and vegetables (FV) in institutional food service (FS) settings, empirical research is sparse and typically based on small convenience samples. An online survey was conducted to assess support, perceived effectiveness and intrusiveness of nine nudge types drawn from Münscher et al.'s Taxonomy of Choice Architecture. We focused on the setting of campus FSs across Canada. A national sample of post-secondary students regularly using campus FSs was used (N 1057). Support for changing the range of options (B3) was the highest, closely followed by changing option-related effort (B2) and changing option-related consequences (B4). Facilitating commitment (C2), changing default (B1) and providing a social reference point (A3) received lowest support. Furthermore, we extracted three clusters of respondents based on perceived effectiveness and intrusiveness of nudge types. Characterised by a relatively low level of perceived effectiveness and moderately high level of intrusiveness, Cluster 1 (61⋅7 % of the sample) reported the lowest support for nudges. Cluster 2 (26⋅6 %), characterised by intermediate effectiveness and low intrusiveness of nudging, reported a high level of support for nudges. Lastly, Cluster 3 (11⋅7 %), characterised by high perceived effectiveness of as well as high perceived intrusiveness, reported the highest level of support for nudges. Findings confirm overall support for FV nudging, with significant differences across nudge types. Differences in customers' acceptance and perception across nudge types offer campus FS operators initial priors in selecting nudges to promote FV.

Polychrome majolica of Apulian domes: history, technique, pathology and conservation

The paper is focused on the historical-architectural evolution and material-technical qualification of polychrome majolica domes that were built between the 17th and 19th centuries in Apulian religious buildings. In particular, the cultural context in which this solution spread throughout the Mediterranean area is identified. Moreover, the case history of construction and decorative techniques that are distinctive of the regional territory is discussed in terms of underlying structure, installation of elements and surface colours. The study is then detailed on the Church of Santa Maria della Vetrana in Castellana Grotte (BA), for which the morpho-typological survey and mapping of the decay state are presented, based on the use of terrestrial and aerial digital photogrammetry. Finally, based on the identification of the main pathologies from both direct and indirect alteration factors, the most appropriate conservation and maintenance interventions are outlined, with specific focus on repair and integration of the majolica tiles, according to principles of high compatibility and low intrusiveness for a solution meeting artisan tradition and technical practice.

Polychrome majolica of Apulian domes: history, technique, pathology and conservation

The paper is focused on the historical-architectural evolution and material-technical qualification of polychrome majolica domes that were built between the 17th and 19th centuries in Apulian religious buildings. In particular, the cultural context in which this solution spread throughout the Mediterranean area is identified. Moreover, the case history of construction and decorative techniques that are distinctive of the regional territory is discussed in terms of underlying structure, installation of elements and surface colours. The study is then detailed on the Church of Santa Maria della Vetrana in Castellana Grotte (BA), for which the morpho-typological survey and mapping of the decay state are presented, based on the use of terrestrial and aerial digital photogrammetry. Finally, based on the identification of the main pathologies from both direct and indirect alteration factors, the most appropriate conservation and maintenance interventions are outlined, with specific focus on repair and integration of the majolica tiles, according to principles of high compatibility and low intrusiveness for a solution meeting artisan tradition and technical practice.

Review of Optical Thermometry Techniques for Flows at the Microscale towards Their Applicability to Gas Microflows.

Thermometry techniques have been widely developed during the last decades to analyze thermal properties of various fluid flows. Following the increasing interest for microfluidic applications, most of these techniques have been adapted to the microscale and some new experimental approaches have emerged. In the last years, the need for a detailed experimental analysis of gaseous microflows has drastically grown due to a variety of exciting new applications. Unfortunately, thermometry is not yet well developed for analyzing gas flows at the microscale. Thus, the present review aims at analyzing the main currently available thermometry techniques adapted to microflows. Following a rapid presentation and classification of these techniques, the review is focused on optical techniques, which are the most suited for application at microscale. Their presentation is followed by a discussion about their applicability to gas microflows, especially in confined conditions, and the current challenges to be overcome are presented. A special place is dedicated to Raman and molecular tagging thermometry techniques due to their high potential and low intrusiveness.

Fiber Bragg Grating Sensors ice detection: Methodologies and performance

New Researches have been done recently in order to create and adapt new systems to the recent Appendix O FAR 25 Aeronautical aircraft icing regulations. One important issue are the Supercooled Large Droplets (SLD) that are an important hazard in many cases. Novel sensor technologies for aircraft are being developed in order to assess the ice severity and to discriminate between large size droplets and small size droplets ice accretions. The European SENS4ICE project gives founding for the research and development of several aeronautical ice detection systems that can discriminate between Appendix C and Appendix O conditions. In the present paper, the strengths and weaknesses of the Fiber Optic ice Detector (FOD) developed by INTA are discussed using a test matrix from the Canadian National Research Council (NRC). The FOD has presented good performance at the NRC ice wind tunnel tests in the ice detection time, detecting ice in most cases earlier than required by the actual standard (ED-103). Its lightness, low intrusiveness and small size, makes the FOD ideal for aeronautical applications. It measures indirectly the icing cloud characteristics, such as the liquid water content (LWC) and the ice accretion rate, so only an approximate severity assessment could be done. • FBG sensors are useful for fast detection. • The Optic Fiber sensors can estimate the icing conditions in rime conditions • The optic fiber sensor can provide of information about the type of ice and its location

An Intrusion Detection Algorithm for DDoS Attacks Based on DBN and Three-way Decisions

To solve the problems of few DDoS attack detection methods and low intrusion detection rate of existing methods in software defined network (SDN), an intrusion detection algorithm DBN-TWD based on deep belief network (DBN) and Three-way decisions was proposed. Firstly, DBN was used to extract features of SDN flow entries, then directly classifying data in the positive and negative domains, and the data in the boundary domain is reclassified by the K-nearest neighbor algorithm. Simulation results show that compared with other intrusion detection models, the detection rate of this method is higher, and the false alarm rate is lower.

Research on intrusion detection method based on 1D-ICNN-BiGRU

Intrusion detection is one of the effective ways to secure the network. Based the unbalanced network traffic data between different attacks, the intrusion detection algorithm turns out to be low intrusion detection accuracy and low identification rate of minority attacks. To solve the problems, an improved intrusion detection model combined with one-dimensional convolutional neural network and bidirectional gated recurrent unit(1D-ICNN-BiGRU) is proposed. First, the dataset is balanced by the SMOTE-Tomek algorithm, then 1D-ICNN-BiGRU is performed for feature extraction, and the final fully connected layer of the model is replaced by global average pooling. The results show that based on the balanced data, the proposed model achieves higher intrusion detection accuracy for R2L and U2R attack than other classic intrusion detection models. The proposed model also improved the identification rate of minority attacks, making the model accuracy rate reach 95.53%, and the false positive rate is only 2.98%.