Journal articles on the topic 'Process monitoring (PM)'
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Burr, Tom, Michael S. Hamada, John Howell, Misha Skurikhin, Larry Ticknor, and Brian Weaver. "Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism." Science and Technology of Nuclear Installations 2013 (2013): 1–18. http://dx.doi.org/10.1155/2013/705878.
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Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation dates to the 1920s with the Shewhart control chart; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual = data − prediction. This paper reviews alarm threshold estimation, introduces model selection options, and considers a range of assumptions regarding the data-generating mechanism for PM residuals. Two PM examples from nuclear safeguards are included to motivate the need for alarm threshold estimation. The first example involves mixtures of probability distributions that arise in solution monitoring, which is a common type of PM. The second example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals.
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Agbenyo, Fauster, Wisdom N-Yil-Yari, and Bernard Affiik Akanpabadai Akanbang. "Stakeholder Perspectives on Participatory Monitoring and Evaluation in Educational Projects in Upper West Region, Ghana." Journal of Planning and Land Management 2, no. 1 (September 11, 2021): 50–64. http://dx.doi.org/10.36005/jplm.v2i1.34.
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The paper set out to outline the differences between conventional M&E and PM&E from the perspectives of stakeholders and assess their involvement as well as the benefits associated with PM&E in two districts: Nadowli-Kaleo and Daffiama-Bussie-Issa in the Upper West Region, Ghana. The paper employed multi-stage, simple random and purposive sampling methods in identifying respondents for interviews. Key informant interviews were used to collect data. Thematic and qualitative content analysis of participants’ voices were used in analysing the data. Findings reveal that PM&E gives primary stakeholders power and control over project execution and taking actions on monitoring results. However, it emerged that the youth and women were not fully involved in the process, some beneficiaries have limited capacity and understanding of their roles in the PM&E process and their involvement is limited to ad hoc approaches due to resource constraints. The study concludes that despite its implementation challenges, PM&E has an edge over orthodox M&E in enhancing effective implementation of educational projects. The paper recommends education of and capacity building for beneficiaries on their roles in the PM&E process to enable them more actively and meaningfully participate in it. Policy decision-makers should make conscious efforts to timely free more resources to the monitoring teams to facilitate their work. The monitoring team should also make frantic efforts to engage the youth and women to achieve the right level of participation in the process.
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Morita, Maiko, Ikuo Arizono, Ippei Nakase, and Yasuhiko Takemoto. "Economical operation of the C pm control chart for monitoring process capability index." International Journal of Advanced Manufacturing Technology 43, no. 3-4 (September 16, 2008): 304–11. http://dx.doi.org/10.1007/s00170-008-1703-2.
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Benabbas, Aboubakr, Martin Geißelbrecht, Gabriel Martin Nikol, Lukas Mahr, Daniel Nähr, Simon Steuer, Gabriele Wiesemann, Thomas Müller, Daniela Nicklas, and Thomas Wieland. "Measure particulate matter by yourself: data-quality monitoring in a citizen science project." Journal of Sensors and Sensor Systems 8, no. 2 (November 5, 2019): 317–28. http://dx.doi.org/10.5194/jsss-8-317-2019.
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Abstract. The concern about air quality in urban areas and the impact of particulate matter (PM) on public health is turning into a big debate. A good solution to sensitize people to this issue is to involve them in the process of air quality monitoring. This paper presents contributions in the field of PM measurements using low-cost sensors. We show how a low-cost PM sensor can be extended to transfer data not only over Wi-Fi but also over the LoRa protocol. Then, we identify some of the correlations existing in the data through data analysis. Afterwards, we show how semantic technologies can help model and control sensor data quality in an increasing PM sensor network. We finally wrap up with a conclusion and plans for future work.
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Lou, Mengqi, Liguo Zhang, Feng Xie, Jianzhu Cao, Jiejuan Tong, Weirong Liu, and Yong Wang. "Design of the Online Gross γ Monitoring Instrument at the Exit of the Helium Purification System in HTR-PM." Science and Technology of Nuclear Installations 2018 (November 1, 2018): 1–12. http://dx.doi.org/10.1155/2018/5808352.
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After the successful construction and operation experience of the 10 MW high-temperature gas-cooled reactor (HTR-10), a high-temperature gas-cooled pebble-bed modular (HTR-PM) demonstration plant is under construction in Shidao Bay, Rongcheng City, Shandong province, China. An online gross γ monitoring instrument has been designed and placed at the exit of the helium purification system (HPS) of HTR-PM and is used to detect the activity concentration in the primary circuit after purification. The source terms in the primary loop of HTR-PM and the helium purification process were described. The detailed configuration of the gross γ monitoring instrument was presented in detail. The Monte Carlo method was used to simulate the detection efficiency of the monitoring system. Since the actual source terms in the primary loop of HTR-PM may be different than the current design values, a sensitivity analysis of the detection efficiency was implemented based on different relative proportions of the nuclides. The accuracy and resolution of the NaI(Tl) detector were discussed as well.
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Seo, SungChul, Choongki Min, Madeline Preston, Sanghoon Han, Sung-Hyuk Choi, So Young Kang, and Dohyeong Kim. "Ambient PM Concentrations as a Precursor of Emergency Visits for Respiratory Complaints: Roles of Deep Learning and Multi-Point Real-Time Monitoring." Sustainability 14, no. 5 (February 25, 2022): 2703. http://dx.doi.org/10.3390/su14052703.
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Despite ample evidence that high levels of particulate matter (PM) are associated with increased emergency visits related to respiratory diseases, little has been understood about how prediction processes could be improved by incorporating real-time data from multipoint monitoring stations. While previous studies use traditional statistical models, this study explored the feasibility of deep learning algorithms to improve the accuracy of predicting daily emergency hospital visits by tracking their spatiotemporal association with PM concentrations. We compared the predictive accuracy of the models based on PM datasets collected between 1 December 2019 and 31 December 2021 from a single but more accurate air monitoring station in each district (Air Korea) and multiple but less accurate monitoring sites (Korea Testing & Research Institute; KTR) within Guro District in Seoul, South Korea. We used MLP (multilayer perceptron) to integrate PM data from multiple locations and then LSTM (long short-term memory) models to incorporate the intrinsic temporal PM trends into the learning process. The results reveal evidence that predictive accuracy is improved from 1.67 to 0.79 in RMSE when spatial variations of air pollutants from multi-point stations are incorporated in the algorithm as a 9-day time window. The findings suggest guidelines on how environmental and health policymakers can arrange limited resources for emergency care and design ambient air monitoring and prevention strategies.
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Stefanovic, Nenad, and Dusan Stefanovic. "Supply chain performance measurement system based on scorecards and web portals." Computer Science and Information Systems 8, no. 1 (2011): 167–92. http://dx.doi.org/10.2298/csis090608018s.
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Successful supply chain management becomes essential for the ultimate success of corporations. Companies today seek an effective performance measurement (PM) system to maximize the bottom line. Unfortunately, performance measurement in the supply-chain field has not kept pace with today?s world of interdependent business relationships. What companies need is a new PM system that unifies different business elements, concepts, technologies and tools. In this paper, the architecture of such a pervasive PM system is introduced. The main system elements such as process model, metrics and data warehouse are described. Finally, a specialized PM web portal which enables proactive performance monitoring and fosters the improvement and optimization is presented.
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Elkhawaga, Ghada, Mervat Abuelkheir, Sherif I. Barakat, Alaa M. Riad, and Manfred Reichert. "CONDA-PM—A Systematic Review and Framework for Concept Drift Analysis in Process Mining." Algorithms 13, no. 7 (July 3, 2020): 161. http://dx.doi.org/10.3390/a13070161.
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Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts.
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Mei, Jiangyuan, Jian Hou, Hamid Reza Karimi, and Jiarao Huang. "A Novel Data-Driven Fault Diagnosis Algorithm Using Multivariate Dynamic Time Warping Measure." Abstract and Applied Analysis 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/625814.
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Process monitoring and fault diagnosis (PM-FD) has been an active research field since it plays important roles in many industrial applications. In this paper, we present a novel data-driven fault diagnosis algorithm which is based on the multivariate dynamic time warping measure. First of all, we propose a Mahalanobis distance based dynamic time warping measure which can compute the similarity of multivariate time series (MTS) efficiently and accurately. Then, a PM-FD framework which consists of data preprocessing, metric learning, MTS pieces building, and MTS classification is presented. After that, we conduct experiments on industrial benchmark of Tennessee Eastman (TE) process. The experimental results demonstrate the improved performance of the proposed algorithm when compared with other classical PM-FD classical methods.
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Carrari, Elisa, Alessandra De Marco, Andrea Laschi, Ovidiu Badea, Laurence Dalstein-Richier, Silvano Fares, Stefan Leca, et al. "Economic and Life Cycle Analysis of Passive and Active Monitoring of Ozone for Forest Protection." Environments 8, no. 10 (October 9, 2021): 104. http://dx.doi.org/10.3390/environments8100104.
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At forest sites, phytotoxic tropospheric ozone (O3) can be monitored with continuously operating, active monitors (AM) or passive, cumulative samplers (PM). For the first time, we present evidence that the sustainability of active monitoring is better than that of passive sensors, as the environmental, economic, and social costs are usually lower in the former than in the latter. By using data collected in the field, environmental, social, and economic costs were analyzed. The study considered monitoring sites at three distances from a control station in Italy (30, 400, and 750 km), two forest types (deciduous and Mediterranean evergreen), and three time windows (5, 10, and 20 years of monitoring). AM resulted in more convenience than PM, even after 5 years, in terms of O3 depletion, global warming, and photochemical O3 creation potential, suggesting that passive monitoring of ozone is not environmentally sustainable, especially for long time periods. AM led to savings ranging from a minimum of EUR 9650 in 5 years up to EUR 94,796 in 20 years in evergreen forests. The resulting social cost of PM was always higher than that of AM. The present evaluation will help in the decision process for the set-up of long-term forest monitoring sites dedicated to the protection of forests from O3.
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Cruz Minguillón, María, Xavier Querol, Andrés Alastuey, Eliseo Monfort, and José Vicente Miró. "PM sources in a highly industrialised area in the process of implementing PM abatement technology. Quantification and evolution." Journal of Environmental Monitoring 9, no. 10 (2007): 1071. http://dx.doi.org/10.1039/b705474b.
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Park, Seohui, Minso Shin, Jungho Im, Chang-Keun Song, Myungje Choi, Jhoon Kim, Seungun Lee, et al. "Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea." Atmospheric Chemistry and Physics 19, no. 2 (January 28, 2019): 1097–113. http://dx.doi.org/10.5194/acp-19-1097-2019.
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Abstract. Long-term exposure to particulate matter (PM) with aerodynamic diameters < 10 (PM10) and 2.5 µm (PM2.5) has negative effects on human health. Although station-based PM monitoring has been conducted around the world, it is still challenging to provide spatially continuous PM information for vast areas at high spatial resolution. Satellite-derived aerosol information such as aerosol optical depth (AOD) has been frequently used to investigate ground-level PM concentrations. In this study, we combined multiple satellite-derived products including AOD with model-based meteorological parameters (i.e., dew-point temperature, wind speed, surface pressure, planetary boundary layer height, and relative humidity) and emission parameters (i.e., NO, NH3, SO2, primary organic aerosol (POA), and HCHO) to estimate surface PM concentrations over South Korea. Random forest (RF) machine learning was used to estimate both PM10 and PM2.5 concentrations with a total of 32 parameters for 2015–2016. The results show that the RF-based models produced good performance resulting in R2 values of 0.78 and 0.73 and root mean square errors (RMSEs) of 17.08 and 8.25 µg m−3 for PM10 and PM2.5, respectively. In particular, the proposed models successfully estimated high PM concentrations. AOD was identified as the most significant for estimating ground-level PM concentrations, followed by wind speed, solar radiation, and dew-point temperature. The use of aerosol information derived from a geostationary satellite sensor (i.e., Geostationary Ocean Color Imager, GOCI) resulted in slightly higher accuracy for estimating PM concentrations than that from a polar-orbiting sensor system (i.e., the Moderate Resolution Imaging Spectroradiometer, MODIS). The proposed RF models yielded better performance than the process-based approaches, particularly in improving on the underestimation of the process-based models (i.e., GEOS-Chem and the Community Multiscale Air Quality Modeling System, CMAQ).
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Poquette, Amelia J., David J. Moore, Ben Gouaux, Erin E. Morgan, Igor Grant, and Steven Paul Woods. "Prospective Memory and Antiretroviral Medication Non-Adherence in HIV: An Analysis of Ongoing Task Delay Length Using the Memory for Intentions Screening Test." Journal of the International Neuropsychological Society 19, no. 2 (October 25, 2012): 155–61. http://dx.doi.org/10.1017/s1355617712001051.
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AbstractUsing multi-process framework by McDaniel and Einstein (2000), the current study examined whether the length of prospective memory (PM) delay intervals as measured by the 2- and 15-min subscales of the Memory for Intentions Screening Test (MIST) have differential predictive value for antiretroviral (ARV) adherence. Participants included 74 HIV-infected individuals whose ARV adherence was tracked with an electronic monitoring system. Participants were classified as “adherent” (n = 49) or “non-adherent” (n = 25) based on recorded pill bottle openings of ≥90% of prescribed doses over 30 days. An adherence group by MIST delay interval interaction was observed, such that non-adherent participants had worse performance on the 15-min, but not 2-min delay PM MIST subscales. The observed MIST 15-min delay effects were significantly more pronounced on time- versus event-cued PM trials. Long-delay time-based PM was predictive of non-adherence independent of demographics, mood state, self-reported adherence, and general cognitive functioning. Findings from this clinical study indicate that ARV non-adherence may be particularly associated with deficits in strategic cue monitoring over longer PM delays, which may inform interventions to improve adherence among persons living with HIV infection. (JINS, 2012, 18, 1–7)
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Anderson, Francis T., and Mark A. McDaniel. "Retrieval in prospective memory: Multiple processes or just delay?" Quarterly Journal of Experimental Psychology 72, no. 9 (May 13, 2019): 2197–207. http://dx.doi.org/10.1177/1747021819845622.
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In prospective memory (PM) research, a common finding is that PM accuracy is greater using focal, rather than nonfocal, cues. Under the multiprocess framework, the high PM performance for focal cues (cues that facilitate noticing of the target), often in the absence of task interference, reflects people’s ability to rely on spontaneous retrieval processes. By contrast, nonfocal cues (cues that do not facilitate noticing) require monitoring. A competing explanation suggests that a single process underlies focal versus nonfocal PM: People adjust their delay in ongoing responding to allow enough time for PM information to reach awareness (delay theory). Participants’ lower nonfocal performance arises because they fail to delay responding to a sufficient degree; with focal cues, the PM information accumulation rate is fast enough that no delay is necessary (and thus most everyone performs well). We sought to improve nonfocal PM performance by pairing a PM task with fast information accumulation to an ongoing task for which the requisite information accumulated more slowly. Reasoning from delay theory, we expected PM accuracy levels in this nonfocal PM task to approximate that observed in a focal PM task (for which the PM tasks were identical). In contrast to this expectation, the focal condition displayed significantly higher PM accuracy (despite demonstrating a reliably shorter response delay). In light of these findings, we concluded that the multiprocess interpretation is favoured.
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Wang, Dja Shin, Hau Yu Yang, and Tong Yuan Koo. "Variable sample size control chart for monitoring process capability index Cpm." International Journal of Industrial and Systems Engineering 36, no. 1 (2020): 32. http://dx.doi.org/10.1504/ijise.2020.10031310.
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Wang, Dja Shin, Hau Yu Yang, and Tong Yuan Koo. "Variable sample size control chart for monitoring process capability index Cpm." International Journal of Industrial and Systems Engineering 36, no. 1 (2020): 32. http://dx.doi.org/10.1504/ijise.2020.109117.
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Ojo, Ochuko M., and Josiah O. Babatola. "Appraisal of Cumulative Volume of Biogas Produced from Water Hyacinth and Selected Animal Dungs Co-Digestion Mixes." Journal of Civil Engineering and Urbanism 11 (November 25, 2021): 58–64. http://dx.doi.org/10.54203/jceu.2021.8.
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Water Hyancinth (WH) was co-digested with different mix ratios of poultry manure (PM), cow dung (CD) and pig dung (PD). A comparative analysis of the cumulative volume of gas produced from the different co-digestion mixes was carried out. The monitoring of the digestion process was done on a daily basis for a retention period of 40 days. The efficacy of the digestion process as well as the best mix ratio of water hyacinth to the different animal dungs was also evaluated in terms of the volume of gas produced. A rotameter with a capacity of 0.1-1L/Min equipped with a measuring tube was used for the gas flow measurements. From the results obtained the best mix of the PD-aided WH digestion is 3 WH:7 PD while CD - aided WH digestion is 2 WH:8 CD and PM-aided WH digestion is 2 WH: 8 PM. The study also revealed that the PM-aided WH mix produced more biogas compared to the CD-aided and PD-aided WH digestion mix.
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Yang, Xufei, Chen Zhang, and Hong Li. "Field Comparison of TSI DustTrak versus TEOM in Two Poultry Houses." Transactions of the ASABE 61, no. 2 (2018): 653–60. http://dx.doi.org/10.13031/trans.12442.
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Abstract. The TSI DustTrak monitor has been used for particulate matter (PM) monitoring at various animal facilities. The instrument determines PM concentrations based on the principle of light scattering. Several assumptions (e.g., particle size, refractive index, and density) are imposed during the calibration process; however, they may not apply to PM emanating from agricultural settings. In this study, PM10 monitoring was conducted at a broiler house and a layer breeding house with four collocated instruments: three DustTrak monitors and one tapered element oscillating microbalance (TEOM). Being a federal equivalent method (FEM) for PM10 monitoring, TEOM was selected here as a transfer standard for assessing the field performance of DustTrak. Results revealed a good linearity between DustTrak and TEOM PM10 readings (R2 =0.92 and 0.85 in the broiler and layer breeding houses, respectively). However, DustTrak significantly underestimated PM10 concentrations in both houses. To correct for the monitoring bias by DustTrak, an average correction factor was derived from correlation analysis that characterized the ratio of DustTrak’s PM10 response to TEOM’s. The factor was calculated as 0.267 for the broiler house and 0.244 for the layer breeding house. Mie scattering simulation was performed to further verify the derived correction factors. A factor of 0.204 was estimated from the simulation, and it accorded well with experimental results. A dependence of the correction factor on PM10 concentration was noted in both poultry houses, indicating the feasibility of developing a concentration-dependent correction factor for future monitoring efforts. Such a relationship could also be explained by Mie scattering. This study is expected to facilitate a better understanding of the limitations and perspectives of the TSI DustTrak and other light scattering PM monitors for agricultural air quality research. Keywords: DustTrak, Mass concentration, Mie scattering, PM10, Poultry, TEOM.
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Kohler, Felix Christian, Philipp Schenk, Paul Koehler, Britt Wildemann, Gunther Olaf Hofmann, Steffen Derlien, Uta Biedermann, Isabel Graul, and Jakob Hallbauer. "How the Direction of Screws Affects the Primary Stability of a Posterior Malleolus Osteosynthesis under Torsional Loading: A Biomechanical Study." Applied Sciences 12, no. 8 (April 11, 2022): 3833. http://dx.doi.org/10.3390/app12083833.
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Insufficient fixation of a posterior malleolus fracture (PM) can lead to posttraumatic complications such as osteoarthritis and chronic pain. The purpose of this biomechanical study was to test the hypothesis of whether the direction of PM screw fixation has an impact on the primary stability of osteosynthesis of a PM under torsional loading. PM fractures of 7 pairs human cadaveric lower leg specimens were stabilized with posterior to anterior (p.a.) or anterior to posterior (a.p.) screw fixation. Stability of the osteosynthesis was biomechanically tested using cyclic external torsional loading levels, in 2 Nm steps from 2 Nm up to 12 Nm, under constant monitoring with 3D ultrasonic marker (Zebris). The primary stability does not differ between both stabilizations (p = 0.378) with a medium effect size (η2p = 0.065). The movement of the PM tends to be marginally greater for the osteosynthesis with a.p. screws than with p.a. screws. Whether a.p. screws or the alternative p.a. screw fixation is performed does not seem to have an influence on the primary stability of the osteosynthesis of the PM fixation under torsional loading. Although osteosynthesis from posterior seems to be more stable, the biomechanical results in the torsional test show quite equivalent stabilities. If there is no significant dislocation of the PM, a.p. screw fixation could be a minimally invasive but stable surgical strategy.
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Doubenskaia, Maria, Mikhail Pavlov, and Yuri Chivel. "Optical System for On-Line Monitoring and Temperature Control in Selective Laser Melting Technology." Key Engineering Materials 437 (May 2010): 458–61. http://dx.doi.org/10.4028/www.scientific.net/kem.437.458.
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A monitoring system is developed to visualize and to control the process of Selective Laser Melting (SLM) of metallic powder. The system is integrated with industrial PHENIX PM-100 machine. Visualization is carried out using LED illumination and CCD-camera; a home developed pyrometer is applied for monitoring of thermal phenomena in the zone of laser impact. Deviation of temperature from its optimal value is chosen as a criterion for the express method of quality control.
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You, Ming-Yi. "A predictive maintenance system for hybrid degradation processes." International Journal of Quality & Reliability Management 34, no. 7 (August 7, 2017): 1123–35. http://dx.doi.org/10.1108/ijqrm-08-2016-0141.
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Purpose The purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance effectiveness. Design/methodology/approach The PdM system updates the degradation model using partial condition monitoring information based on degradation type judgment. In addition, an extended multi-step-ahead updating stopping condition is adopted for performance enhancement of the PdM system. Findings An extensive numerical investigation compares the performance of the PdM system with the corresponding preventive maintenance (PM) policy. By carefully choosing the updating stopping condition, the PdM policy performs better than the corresponding PM policy. Research limitations/implications The proposed PdM system is applicable to single-unit systems. And the continuous degradation process should be well modeled by the stochastic linear degradation model (Gebraeel et al., 2009). Originality/value In literature, there are abundant studies on PdM policies for continuous degradation processes. However, research on hybrid degradation processes still focuses on condition-based maintenance policy and a PdM policy for a hybrid degradation process is still unreported. In this paper, a PdM system for hybrid degradation processes with continuous degradation and sudden damage is proposed. The PdM system decides PM schedules by fully utilizing the condition monitoring data of each specific product, and can hopefully improve maintenance effectiveness.
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Wang, Juan, Zhichao Liu, Jinhua Yang, and Zhentao Zhang. "Research on Networking Algorithm of Distributed FBG Sensor Network." Mobile Information Systems 2021 (October 11, 2021): 1–7. http://dx.doi.org/10.1155/2021/5250778.
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The status monitoring of industrial process equipment is of great significance to its production energy efficiency and safety. A state monitoring system for complex surface structures based on the distributed FBG sensor network is proposed. The system adopts the FBG network and realizes the calculation of the stress field of the complex surface through the FBG layout design at different positions in the three-dimensional space. A 32-channel FBG sensor network is designed, and the light source, demodulation module, and processing system are selected and analyzed. On the basis of building the FBG sensor network, the stress field test was carried out on the industrial process equipment. For complex three-dimensional surface structures, an optical scanner is used for position offset calibration. Experiments show that when force is applied to the center point, the slope of the FBG at the best sensitive position is 0.715 pm/N; when force is applied on both sides, the maximum slope in the positive direction is 0.348 pm/N and the maximum slope in the negative direction is −0.381 pm/N. After data fusion correction is used, the average error of the three-dimensional position offset of the test data is 6.85%. It can be seen that the FBG network has the ability to monitor the state of complex surface structures in the industrial engineering equipment.
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Kalgin, Alexander, Dmitry Podolskiy, Daria Parfenteva, and Jesse W. Campbell. "Performance management and job-goal alignment." International Journal of Public Sector Management 31, no. 1 (January 8, 2018): 65–80. http://dx.doi.org/10.1108/ijpsm-04-2016-0069.
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Purpose The use of performance management (PM) tools is a defining characteristic of public sector management. However, while research on PM is extensive, comparatively little focuses on how the practice shapes the attitudes and behavior of employees. The purpose of this paper is to address this question and develop a conditional process model that links PM to turnover intention. The model predicts that the PM-turnover relationship is mediated by job satisfaction and moderated by job-goal alignment. Design/methodology/approach The authors use a unique data set drawn from the Russian public sector to test the model empirically. Conditional process modeling is used to test for moderated mediation. The effects are further explored using bootstrapped bias-corrected confidence intervals. Findings The analysis suggests that PM has an indirect effect on turnover intention via job satisfaction in the average case. However, the indirect effect is stronger for employees who perceive that their work contributes directly to organizational goals. In contrast, for employees whose work lacks organizational goal alignment, PM has no significant effect. Originality/value Despite being an instrument to manage organizational (including human) resources, few studies have linked PM to employee-level outcomes. By doing so, this study implies promising research paths that can help generate a more complete picture of how PM shapes organizational processes in the public sector.
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Hsu, Clarissa, Sarah Evers, Benjamin H. Balderson, Karen J. Sherman, Nadine E. Foster, Katherin Estlin, Martin Levine, and Dan Cherkin. "Adaptation and Implementation of the STarT Back Risk Stratification Strategy in a US Health Care Organization: A Process Evaluation." Pain Medicine 20, no. 6 (September 28, 2018): 1105–19. http://dx.doi.org/10.1093/pm/pny170.
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Abstract Objective To support implementation of effective treatments for back pain that can be delivered to a range of people, we summarize learnings from our process evaluation of the MATCH trial’s implementation of an adaptation of the STarT Back risk-stratified care model. Design Our logic model–driven evaluation focused primarily on qualitative data sources. Setting This study took place in a US-based health care delivery system that had adapted and implemented the STarT Back stratified care approach. This was the first formal test of the strategy in a US setting. Methods Data collection included observation of implementation activities, staff/provider interviews, and post-training evaluation questionnaires. Data were analyzed using thematic analysis of qualitative data and descriptive statistics for questionnaire data. Results We found that both primary care teams and physical therapists at intervention clinics gave the training high scores on evaluation questionnaires and reported in the interviews that they found the training engaging and useful. However, there was significant variation in the extent to which the risk stratification strategy was incorporated into care. Some primary care providers reported that the intervention changed their conversations with patients and increased their confidence in working with patients with back pain. Providers using the STarT Back tool did not change referral rates for recommended matched treatments. Conclusions These insights provide guidance for future efforts to adapt and implement the STarT Back strategy and other complex practice change interventions. They emphasize the need for primary care–based interventions to minimize complexity and the need for ongoing monitoring and feedback.
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Hussain, Syed Ishtiaq, Huma Javed, Tehseen Khan, Sara Shazad, and Falak Naz Khalil. "Native Process Migration in Wireless Sensor Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/607143.
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This paper presents a novel architecture for native process migration (PM) in wireless sensor networks (WSNs) without the use of virtual execution environment. Resources in WSN are scarce; therefore creating virtual execution environment puts extra burden on already stringent resources. In addition, the proposed architecture is migrating with complete process instead of code only which also saves resources. The proposed architecture makes process migration decisions by continuously monitoring resources, such as remaining battery life and free memory space on a node. The architecture is suitable for networks with fewer expensive sensor nodes as it allows for better utilization of network resources. Transferring a live executing process from one node to another to meet processing demands dynamically improves fault tolerance, resource utilization, and network management in WSN. The architecture has been successfully tested and implemented on both COOJA simulator and a test bed of TelosB motes.
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Consul, Nikita, Xiaotao Guo, Courtney Coker, Sara Lopez-Pintado, Hanina Hibshoosh, Binsheng Zhao, Kevin Kalinsky, and Swarnali Acharyya. "Monitoring Metastasis and Cachexia in a Patient with Breast Cancer: A Case Study." Clinical Medicine Insights: Oncology 10 (January 2016): CMO.S40479. http://dx.doi.org/10.4137/cmo.s40479.
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Cachexia, a wasting syndrome associated with advanced cancer and metastasis, is rarely documented in breast cancer patients. However, the incidence of cachexia in breast cancer is now thought to be largely underestimated. In our case report of a breast cancer patient with bone metastasis monitored during the course of her treatment, we document the development of cachexia by image analysis in relation to her metastatic burden. Elucidation of the link between metastatic burden and cachexia could unveil a highly specific screening process for metastasis, by assessing true muscle mass loss. Our patient was a 49-year-old premenopausal woman, with metastatic invasive ductal breast carcinoma in the vertebral and iliac bones on presentation, which progressed with new metastases to her hips, thigh bones, and vertebrae. In the two-year period, that is between her diagnosis and death, she lost >10% of her baseline weight. During these two years, we retrospectively identified a decrease in paraspinal muscle (PM) at the third lumbar vertebra followed by a sharp decline in weight. The increased tumor burden over time in metastatic sites was accompanied by a decrease in abdominal muscle and visceral and subcutaneous fat and was followed by the patient's demise. The increasing tumor burden in the patient was correlated with the mass of other tissues to determine the tissue that could best serve as a surrogate marker to cachexia and tumor burden. We noted a strong negative correlation between PM area and metastatic tumor area at the third lumbar vertebral level, with PM loss correlating to increasing tumor burden. The monitoring of PM wasting may serve as a marker, and therefore a prognostic factor, for both cachexia and extent of metastatic disease, especially in breast cancer, where metastasis to bone is frequent. Based on our data and review of the literature in this case study, longitudinal monitoring of cachexia in the selected muscle groups can give clinicians early indications of the extent of cachexia in metastatic breast cancer patients.
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Falekas, Georgios, and Athanasios Karlis. "Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects." Energies 14, no. 18 (September 18, 2021): 5933. http://dx.doi.org/10.3390/en14185933.
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State-of-the-art Predictive Maintenance (PM) of Electrical Machines (EMs) focuses on employing Artificial Intelligence (AI) methods with well-established measurement and processing techniques while exploring new combinations, to further establish itself a profitable venture in industry. The latest trend in industrial manufacturing and monitoring is the Digital Twin (DT) which is just now being defined and explored, showing promising results in facilitating the realization of the Industry 4.0 concept. While PM efforts closely resemble suggested DT methodologies and would greatly benefit from improved data handling and availability, a lack of combination regarding the two concepts is detected in literature. In addition, the next-generation-Digital-Twin (nexDT) definition is yet ambiguous. Existing DT reviews discuss broader definitions and include citations often irrelevant to PM. This work aims to redefine the nexDT concept by reviewing latest descriptions in broader literature while establishing a specialized denotation for EM manufacturing, PM, and control, encapsulating most of the relevant work in the process, and providing a new definition specifically catered to PM, serving as a foundation for future endeavors. A brief review of both DT research and PM state-of-the-art spanning the last five years is presented, followed by the conjunction of core concepts into a definitive description. Finally, surmised benefits and future work prospects are reported, especially focused on enabling PM state-of-the-art in AI techniques.
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Magano, José, Cláudia Sousa Silva, and Micaela Martins. "Project Management in the Biotech Context: Exploring the Interrelation between Maturity and Sustainable Project Management." Sustainability 13, no. 21 (November 2, 2021): 12090. http://dx.doi.org/10.3390/su132112090.
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Biotechnology is an emerging and increasingly important sector in the current context. As the number of biotech projects grows, so does the need to establish processes to improve project management effectiveness and project success, including assessing their impacts (positive and negative) on the Sustainable Development Goal (SDGs). This broader approach opens the door to developing a new project management (PM) paradigm designated by sustainable project management (SPM). However, there is a need for more empirical studies to understand how sustainability can be integrated into project management. This research is based on the proposition that PM maturity could lead to incorporating sustainability in PM. No research studies are reported in the literature exploring this interrelationship between maturity and sustainable project management; such is this study’s purpose and originality. The study applies Kerzner’s Level 3 PM maturity model on a sample of 96 biotech companies in Portugal through a questionnaire that addressed project managers and team members. The findings suggest that the process of integrating sustainability into PM should follow these steps: (1) perform an early PM maturity diagnosis to identify the company’s most and least dominated areas; (2) identify the strengths and weaknesses that impact the integration of sustainability into project management practices; (3) develop a customized and adjusted action plan to integrate sustainability in PM. The study’s main contribution relies on understanding how sustainability can be integrated into project management, explaining the role of maturity assessment in this process. In addition, it characterizes the biotech industry projects concerning the linkage between PM maturity and sustainability and provides recommendations that may contribute to the companies’ development towards sustainable project management.
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Tzanis, Chris G., and Anastasios Alimissis. "Contributing towards Representative PM Data Coverage by Utilizing Artificial Neural Networks." Applied Sciences 11, no. 18 (September 11, 2021): 8431. http://dx.doi.org/10.3390/app11188431.
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Atmospheric aerosol particles have a significant impact on both the climatic conditions and human health, especially in densely populated urban areas, where the particle concentrations in several cases can be extremely threatening (increased anthropogenic emissions). Most large cities located in high-income countries have stations responsible for measuring particulate matter and various other parameters, collectively forming an operating monitoring network, which is essential for the purposes of environmental control. In the city of Athens, which is characterized by high population density and accumulates a large number of economic activities, the currently operating monitoring network is responsible, among others, for PM10 and PM2.5 measurements. The need for satisfactory data availability though can be supported by using machine learning methods, such as artificial neural networks. The methodology presented in this study uses a neural network model to provide spatiotemporal estimations of PM10 and PM2.5 concentrations by utilizing the existing PM data in combination with other climatic parameters that affect them. The overall performance of the predictive neural network models’ scheme is enhanced when meteorological parameters (wind speed and temperature) are included in the training process, lowering the error values of the predicted versus the observed time series’ concentrations. Furthermore, this work includes the calculation of the contribution of each predictor, in order to provide a clearer understanding of the relationship between the model’s output and input. The results of this procedure showcase that all PM input stations’ concentrations have an important impact on the estimations. Considering the meteorological variables, the results for PM2.5 seem to be affected more than those for PM10, although when examining PM10 and PM2.5 individually, the wind speed and temperature contribution is on a similar level with the corresponding contribution of the available PM concentrations of the neighbouring stations.
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Doubenskaia, Maria, Sergey Grigoriev, Ivan Zhirnov, and Igor Smurov. "Parametric analysis of SLM using comprehensive optical monitoring." Rapid Prototyping Journal 22, no. 1 (January 18, 2016): 40–50. http://dx.doi.org/10.1108/rpj-04-2014-0046.
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Purpose – This paper aims to propose methods for on-line monitoring and process quality assurance of Selective Laser Melting (SLM) technology as a competitive advantage to enhance its implementation into modern manufacturing industry. Design/methodology/approach – Monitoring of thermal emission from the laser impact zone was carried out by an originally developed pyrometer and a charge-coupled device (CCD) camera which were integrated with the optical system of the PHENIX PM-100 machine. Experiments are performed with variation of the basic process parameters such as powder layer thickness (0-120 μm), hatch distance (60-1,000 μm) and fabrication strategy (the so-called “one-zone” and “two-zone”). Findings – The pyrometer signal from the laser impact zone and the 2D temperature mapping from HAZ are rather sensible to variation of high-temperature phenomena during powder consolidation imposed by variation of the operational parameters. Research limitations/implications – Pyrometer measurements are in arbitrary units. This limitation is due to the difficulty to integrate diagnostic tools into the optical system of a commercial SLM machine. Practical implications – Enhancement of SLM process stability and efficiency through comprehensive optical diagnostics and on-line control. Originality/value – High-temperature phenomena in SLM were monitored coaxially with the laser beam for variation of several operational parameters.
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PREMITASARI, MARISA. "Analisis Jumlah Pengguna pada Traffic IP-based dengan Multi Criteria Decision Making." MIND Journal 5, no. 2 (July 4, 2021): 92–107. http://dx.doi.org/10.26760/mindjournal.v5i2.92-107.
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AbstrakTrafik telekomunikasi sudah bermigrasi ke IP-based Traffic. Salah satunya adalah Laboratorium TIK (Teknologi Informasi dan Komunikasi) ITENAS yang meng-generate invarian trafik. Pada penelitian ini, penulis melakukan monitoring pasif dan aktif untuk mendapatkan berbagai invarian trafik. Monitoring pasif didapatkan dari software ISP Moratel dan SOPHOS Firewall. Monitoring aktif dilakukan dengan capture data secara live pada waktu jam sibuk. Invarian trafik yang berhasil di-captured adalah incoming traffic, outgoing traffic, speed, volume, date dan downtime. Jam sibuk diambil berdasarkan dugaan sementara mulai pukul 10.00-16.00. Invarian ini menjadi input dari sistem untuk dijadikan kriteria dan jam sibuk dijadikan atribut. Kriteria dan atribut diolah dengan metoda Multi Criteria Decision Making yaitu SAW (Simple Additive Weighting) dan AHP(Analytical Hierarchy Process). Output dari sistem adalah prediksi jumlah pengguna di jam sibuk dengan skala fuzzy rules. Hasil penelitian menyimpulkan pukul 11.00 AM-12.00 PM adalah jam tersibuk dengan jumlah user terbanyak.Kata kunci: monitoring aktif, monitoring pasif, kriteria, atribut,bobotAbstractTelecommunication traffic has migrated to IP-based traffic .One of the industry is Laboratorium TIK ITENAS (Teknologi Informasi dan Komunikasi) which generates traffic invariant. In this study, the authors conducted passive and active monitoring to obtain various traffic invariance. Passive monitoring were obtained from ISP Moratel software and SOPHOS Firewall. Active monitoring were done by capturing live data during peak hours. Traffic invariance that have been captured consist incoming traffic, outgoing traffic, speed, volume, date and downtime. Busy hours were taken based on personal estimation start from 10.00-16.00. This invariance became the system’s input which has been used as criteria and peak hours are used as attributes. Criteria and attributes were processed using the Multi Criteria Decision Making method, namely SAW (Simple Additive Weighting and AHP (Analytical Hierarchy Process). The output of the system is user’s number prediction with fuzzy scale. The result concluded that 11.00 AM-12.00 PM is the busiest hours with the most number of usersKeywords: active monitoring, passive monitoring, criterion, attributes, weight
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Karnadi, Juan, Ibnu Roihan, Astha Ekadiyanto, and R. A. Koestoera. "Development of a Low-cost Arduino-based Patient Monitoring System for Heartrate, Oxygen Saturation and Body Temperature Parameters." Journal of Applied Science, Engineering and Technology 1, no. 1 (April 5, 2022): 26. http://dx.doi.org/10.47355/aset.v1i1.15.
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The implementation of Patient Monitor (PM) in ICU, ICCU, PICU and NICU currently imposes a significantly high cost of investment. According to studies conducted, there are three main parameters required to be measured, which are heartrate (BPM), oxygen saturation (SPO2) and body temperature (T). These are highly needed by the medical personnel to monitor in order to determine patient’s vital state. The low-cost patient monitor prototype (named Patient Monitor 3 Parameters or PM3P) was developed using Arduino platform. In order to measure the parameters, two types of sensor modules were chosen, namely MAX30100 for gathering heartrate and oxygen saturation data and DS18B20 for gathering the body temperature data. The prototyping process also included fixation and finalization of electrical circuit on a printed circuit board (PCB). The PM3P underwent extensive validation process by comparing it to the real industrial PM made by healthcare equipment industry. The comparison was done over data gathered by both system that were conducting the same measurement runs in parallel. Results of validation indicates that the low-cost patient monitor prototype has a slight error of 0,31% for heartrate and 1,59% for oxygen saturation compared to the industrial one. Further improvements for the Arduino based PM3P are also proposed in this paper in order to enhance its reading accuracy, namely calibration.
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Rest, Kathleen. "Silenced Science: Air Pollution Decision-Making at the EPA Threatens Public Health." NEW SOLUTIONS: A Journal of Environmental and Occupational Health Policy 17, no. 2 (August 2007): 13–16. http://dx.doi.org/10.1177/104829110701700203.
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The saga of the Environmental Protection Agency's new particulate matter (PM) rule is yet another example of this Administration's disregard for and disrespect of science and scientists—and may signal the beginning of a disturbing trend to reduce the role of science in protecting the quality of our air. Political interference in the PM case is clear. And more trouble may be in the wings when it comes to acceptable levels of ozone pollution and the process for setting the National Ambient Air Quality Standards (NAAQS). For several years, the Union of Concerned Scientists has been actively monitoring and documenting the misuse of science in public policy-making. Consider this a call to arms. Now is the time to engage your elected officials on these issues.
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Lovett, Christopher, Mohamad Baasiri, Khairallah Atwi, Mohammad H. Sowlat, Farimah Shirmohammadi, Alan L. Shihadeh, and Constantinos Sioutas. "Comparison of the oxidative potential of primary (POA) and secondary (SOA) organic aerosols derived from α-pinene and gasoline engine exhaust precursors." F1000Research 7 (July 9, 2018): 1031. http://dx.doi.org/10.12688/f1000research.15445.1.
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Background: Primary (POA) and secondary (SOA) organic aerosols, deriving from both anthropogenic and biogenic sources, represent a major fraction of ambient particulate matter (PM) and play an important role in the etiology of respiratory and cardiovascular diseases, largely through systemic inflammation and cellular oxidative stress. The relative contributions of these species to the inhalation burden, however, are rather poorly characterized. In this study, we measured the in vitro oxidative stress response of alveolar macrophages exposed to primary and secondary PM derived from both anthropogenic and biogenic sources. Methods: POA and SOA were generated within an oxidation flow reactor (OFR) fed by pure, aerosolized α-pinene or gasoline engine exhaust, as representative emissions of biogenic and anthropogenic sources, respectively. The OFR utilized an ultraviolet (UV) lamp to achieve an equivalent atmospheric aging process of several days. Results: Anthropogenic SOA produced the greatest oxidative response (1900 ± 255 µg-Zymosan/mg-PM), followed by biogenic (α-pinene) SOA (1321 ± 542 µg-Zymosan/mg-PM), while anthropogenic POA produced the smallest response (51.4 ± 64.3 µg-Zymosan/mg-PM). Conclusions: These findings emphasize the importance of monitoring and controlling anthropogenic emissions in the urban atmosphere, while also taking into consideration spatial and seasonal differences in SOA composition. Local concentrations of biogenic and anthropogenic species contributing to the oxidative potential of ambient PM may vary widely, depending on the given region and time of year, due to factors such as surrounding vegetation, proximity to urban areas, and hours of daylight.
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Lovett, Christopher, Mohamad Baasiri, Khairallah Atwi, Mohammad H. Sowlat, Farimah Shirmohammadi, Alan L. Shihadeh, and Constantinos Sioutas. "Comparison of the oxidative potential of primary (POA) and secondary (SOA) organic aerosols derived from α-pinene and gasoline engine exhaust precursors." F1000Research 7 (March 11, 2019): 1031. http://dx.doi.org/10.12688/f1000research.15445.2.
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Background: Primary (POA) and secondary (SOA) organic aerosols, deriving from both anthropogenic and biogenic sources, represent a major fraction of ambient particulate matter (PM) and play an important role in the etiology of respiratory and cardiovascular diseases, largely through systemic inflammation and cellular oxidative stress. The relative contributions of these species to the inhalation burden, however, are rather poorly characterized. In this study, we measured the in vitro oxidative stress response of alveolar macrophages exposed to primary and secondary PM derived from both anthropogenic and biogenic sources. Methods: POA and SOA were generated within an oxidation flow reactor (OFR) fed by pure, aerosolized α-pinene or gasoline engine exhaust, as representative emissions of biogenic and anthropogenic sources, respectively. The OFR utilized an ultraviolet (UV) lamp to achieve an equivalent atmospheric aging process of several days. Results: Anthropogenic SOA produced the greatest oxidative response (1900 ± 255 µg-Zymosan/mg-PM), followed by biogenic (α-pinene) SOA (1321 ± 542 µg-Zymosan/mg-PM), while anthropogenic POA produced the smallest response (51.4 ± 64.3 µg-Zymosan/mg-PM). Conclusions: These findings emphasize the importance of monitoring and controlling anthropogenic emissions in the urban atmosphere, while also taking into consideration spatial and seasonal differences in SOA composition. Local concentrations of biogenic and anthropogenic species contributing to the oxidative potential of ambient PM may vary widely, depending on the given region and time of year, due to factors such as surrounding vegetation, proximity to urban areas, and hours of daylight.
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Popek, Robert, Beata Fornal-Pieniak, Filip Chyliński, Magdalena Pawełkowicz, Jan Bobrowicz, Dominika Chrzanowska, Natalia Piechota, and Arkadiusz Przybysz. "Not Only Trees Matter—Traffic-Related PM Accumulation by Vegetation of Urban Forests." Sustainability 14, no. 5 (March 3, 2022): 2973. http://dx.doi.org/10.3390/su14052973.
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In terms of the process of air purification, a lot of attention has been devoted to trees and shrubs. Little attention has been paid to herbaceous vegetation from the lower forest layers. Urban forests are often located on the outskirts of cities and surround exit roads where there is heavy traffic, generating particulate matter (PM) pollution. The aim of this study was to investigate the spread of PM from the road traffic in the air and to investigate how individual layers of urban forests accumulate PM. We conducted comparative analyses of PM accumulation on plants in five zones away from the road, into the forest, in the air, and in four vegetation layers: mosses, herbaceous plants, shrubs and trees. The results show that all forest layers accumulate PM. We show that PM is very efficiently accumulated by herbaceous plants growing along roadsides, and that the PM that was not deposited on herbaceous plants was accumulated by trees and shrubs. With increasing distance from the road into the forest, the PM content on herbaceous plants decreased and the accumulation on trees and shrubs increased. We estimated that PM concentration in the air dropped significantly in the front line of the trees, but it was still detectable up to 50 m into the forest. The results presented herein show that meadow vegetation and urban forests play a very important role in air purification. Our results provide a better understanding of the complexity of urban forest interactions and provide the basis for better planning of urban greenery.
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Zhou, Shijun, Guoxin Yan, Yanan Wu, Jiexiu Zhai, Ling Cong, and Zhenming Zhang. "The PM removal process of wetland plant leaves with different rainfall intensities and duration." Journal of Environmental Management 275 (December 2020): 111239. http://dx.doi.org/10.1016/j.jenvman.2020.111239.
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Khan, Muhammad, Numan Khan, Miroslaw J. Skibniewski, and Chansik Park. "Environmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique." Sustainability 13, no. 14 (July 13, 2021): 7797. http://dx.doi.org/10.3390/su13147797.
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Dust generation is generally considered a natural process in construction sites; ergo, workers are exposed to health issues due to fine dust exposure during construction work. The primary activities in the execution of construction work, such as indoor concrete and mortar mixing, are investigated to interrogate and understand the critical high particulate matter concentrations and thus health threats. Two low-cost dust sensors (Sharp GP2Y1014AU0F and Alphasense OPC N2) without implementing control measures to explicitly evaluate, compare and gauge them for these construction activities were utilized. The mean exposures to PM10, PM2.5 and PM1 during both activities were 3522.62, 236.46 and 47.62 µg/m3 and 6762.72, 471.30 and 59.09 µg/m3, respectively. The results show that PM10 and PM2.5 caused during the concrete mixing activity was approximately double compared to the mortar. The Latin Hypercube Sampling method is used to analyze the measurement results and to predict the exposure concentrations. The high dust emission and exposure from mixing activities fail to meet the World Health Organization and Health and Safety Commission standards for environmental exposure. These findings will leverage the integration of low-cost dust sensors with Building Information Modelling (BIM) to formulate a digital twin for automated dust control techniques in the construction site.
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Margrett, Jennifer A., Celinda Reese-Melancon, and Peter G. Rendell. "Examining Collaborative Dialogue Among Couples." Zeitschrift für Psychologie 219, no. 2 (January 2011): 100–107. http://dx.doi.org/10.1027/2151-2604/a000054.
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Prospective memory is a key ability required for independent living and consistent with Einstein and McDaniel (1990) , we hypothesized that social partners can serve as useful external memory aids, particularly in middle and late life when these abilities may wane. We employed the Virtual Week (Rendell & Craik, 2000) task in a novel way to investigate the contribution of social partners to the prospective memory process. We examined the collaborative interactions of 11 middle-aged (M = 52.15 years; n = 5) and older (M = 75.24 years; n = 6) married dyads. The dialogue of collaborating partners reflected important PM processes (e.g., encoding, monitoring, tutoring). Age group differences favored middle-aged adults, and preliminary evidence suggested a link between collaborative dialogue and PM performance. Further investigation can determine how social partners can be used strategically to improve prospective memory outcomes.
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Lee, Seung-Bok, Kyung Hwan Kim, Bo-Eun Park, and Gwi-Nam Bae. "A Fast Method for Estimating the Emission Factors of Air Pollutants from In-Use Vehicles Fleet." Applied Sciences 11, no. 16 (August 5, 2021): 7206. http://dx.doi.org/10.3390/app11167206.
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The real-world emission factors of gaseous and particulate air pollutants emitted from in-use vehicles, can be rapidly estimated using monitoring data of their concentration profiles from inside roadway tunnels using a mobile laboratory equipped with fast monitoring instruments. The concentrations of CO2 and particle-bound polycyclic aromatic hydrocarbons (PM-PAHs) and NOx, were observed to increase linearly with traveling distance inside two successive roadway tunnels: the Hongjimun Tunnel and the Jeongneung Tunnel on the Naebu Express Way in Seoul, Korea, except for a small region of decrease. In the decreasing regions, within a few hundred meters of the entrance and before the exit, outside background air with low concentrations of air pollutants was thought to have intruded. From the slopes of the linear regression between distance and concentrations, a fleet-averaged (light-, medium-, and heavy-duty vehicles with 54%, 36%, and 10%, respectively) emission factor of CO2, PM-PAHs, and NOx at an average speed of ~60 km h−1 could be calculated as 197 ± 38 g km−1, 4.2 ± 0.8 × 10−4 g km−1, and 0.530 ± 0.230 g km−1, respectively, which are within the ranges of values reported in the literature. For each tunnel, the emission factors of CO2, PM-PAHs, and NOx estimated on days with higher-than-normal fractions of heavy-duty vehicles, were higher than those on other days. From these results, the new fast method proposed in this study is considered useful for estimating real-world emission factors of air pollutants by using a mobile laboratory as a complementary tool to traditional tunnel studies. This method can be used to rapidly make emission maps at roadway tunnels in mega-cities like Seoul, Korea, for urban air-quality management.
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P., Bächler, Löschner V., Meyer J., and Dittler A. "Process integrated monitoring of spatially resolved particle emissions of a baghouse filter using a network of low-cost PM-sensors." Process Safety and Environmental Protection 160 (April 2022): 411–23. http://dx.doi.org/10.1016/j.psep.2022.02.005.
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Zerbino, Pierluigi, Davide Aloini, Riccardo Dulmin, and Valeria Mininno. "Towards Analytics-Enabled Efficiency Improvements in Maritime Transportation: A Case Study in a Mediterranean Port." Sustainability 11, no. 16 (August 18, 2019): 4473. http://dx.doi.org/10.3390/su11164473.
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The current digitalization trend, the increased attention towards sustainability, and the spread of the business analytics call for higher efficiency in port operations and for investigating the quantitative approaches for maritime logistics and freight transport systems. Thus, this manuscript aims at enabling analytics-driven improvements in the port transportation processes efficiency by streamlining the related information flow, i.e., by attaining shorter time frames of the information and document sharing among the export stakeholders. We developed a case study in a mid-sized European port, in which we applied Process Mining (PM)—an emerging type of business analytics—to a seven-month dataset from the freight export process. Four process inefficiencies and an issue that can jeopardize the reliability of the time performance measurements were detected, and we proposed a draft of solutions to cope with them. PM enabled enhancements in the overall export time length, which might improve the vessels’ turnover and reduce the corresponding operational costs, and supported the potential re-design of performance indicators in process control and monitoring. The results answer the above-mentioned calls and they offer a valuable, analytics-based alternative to the extant approaches for improving port performance, because it focuses on the port information flow, which is often related to sustainability issues, rather than the physical one.
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Matsiliza, Noluthando. "Participatory Monitoring and Evaluation: Reviewing an Inclusive Approach in the South Africa's Government Wide Monitoring and Evaluation." Africa’s Public Service Delivery and Performance Review 1, no. 2 (September 1, 2012): 67. http://dx.doi.org/10.4102/apsdpr.v1i2.31.
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The premise of this paper is to canvass for the inclusion of stakeholders in participating in the Government Wide Monitoring and Evaluation (GWM&E) using the participatory monitoring and evaluation (PM&E) approach. The focus is mainly on the practicality of using participatory methods as part of the agenda to cascade the implement the M&E into different stake-holders using various methods in South Africa. A variety of public participation methods should be recognised to benchmark for the inclusion of stakeholders at the local level in the evaluation and monitoring of public programmes and projects in order to allow more space for civil society engagement in development policies and social accountability. Participation is increasingly recognised by countries as an integral part of M&E process while it offers environment for civic participation in a more inclusive and responsive approach towards service delivery and budget allocation in South Africa. Using a qualitative approach, conclusions and recommendations from this study contribute towards monitoring and evaluation of policies, programmes and projects in the field of Public Management. This study intends to address the paucity of literature on Participatory Monitoring and Evaluation in South Africa.
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Ohemeng, Frank Louis Kwaku, Emelia Amoako Asiedu, and Theresa Obuobisa-Darko. "Giving sense and changing perceptions in the implementation of the performance management system in public sector organisations in developing countries." International Journal of Public Sector Management 31, no. 3 (April 9, 2018): 372–92. http://dx.doi.org/10.1108/ijpsm-05-2017-0136.
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Purpose Change in public organisations has become inevitable in modern times. Yet, implementing change continues to be problematic, especially the attempt to introduce performance management (PM) in the sector. The purpose of this paper is to examine how HR managers are using sensegiving processes to attempt to institutionalise PM in public organisations in Ghana PM in public organisations in Ghana. Design/methodology/approach The paper utilises the mixed methods approach to examine the process of sensegiving. In using this method, the authors used focus group, as well as individual interview techniques and a quantitative survey of some selected organisations in the public sector. Findings The results of the study show that, four main activities, i.e. workshops, seminars and training, one-on-one communication, and unit meetings are employed in the process. The analysis indicates that these activities have become quite effective in the quest to change perceptions about PM in the sector. Research limitations/implications The research was limited to a few organisations. Hence, it will be necessary to expand it, if possible to the entire public sector to see if the same results will be obtained. Practical implications It shows that reformers must be cognisant of the views of employees in developing and implementing reforms that focus on changing both individual orientations and organisational and culture. Originality/value This is the first time such a study has been done in Ghana. Furthermore, studies on PM institutionalisation and implementation have either been qualitative or quantitative in nature. Studies using the mixed methods approach are rare, with those we know coming mostly from the Western World. Thus, this paper is one of the few to examine this issue using the mixed methods approach and more so from a developing country’s perspective.
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Veeramanikandasamy*, T., Gokul Raj. S, A. Balamurugan, A. P. Ramesh, and Y. A. Syed Khadar. "IoT based Real-time Air Quality Monitoring and Control System to Improve the Health and Safety of Industrial Workers." International Journal of Innovative Technology and Exploring Engineering 9, no. 4 (February 28, 2020): 1889–84. http://dx.doi.org/10.35940/ijrte.d1604.018520.
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Pollution is adding contaminants into the nature that causes an adverse change in the environment. Air pollution is one of the highest mortality risk factors globally. The sources of air pollution in the industries are power plants, chamber process, cleaning, burning of materials, etc. A variety of pollutants emitted into the air such as sulfur dioxide, carbon monoxide, carbon dioxide, ammonia and volatile organic compounds. Particulate Matter (PM) is an air pollutant that is the mixture of solid dust or pollen and liquid droplets with air. Air pollution in industrial workplaces is a major concern and monitoring and management of it to be addressed to protect the industrial workers health from the air pollution effects. The people are suffering from several respiratory and heart issues along with cancer due to increasing air pollution. This device is composed of ESP32 MCU, MQ135 gas sensor, SDS011 optical dust particle sensor, and BME280 humidity and temperature sensor for monitoring the air quality. The gas sensor MQ135 senses the harmful gases present in the environment. SDS011 optical dust sensor senses the PM levels (PM10 and PM2.5) in the atmosphere. The sensor values are evaluated for the Air Quality Index (AQI) and display it on the ThingSpeak IoT platform. Vrituino app has used for a virtual screen with widgets on the mobile phone to monitor the system using the web. In order to improve the real-time performance of the system, an IoT and a cloud computing technology are being used. The ESP32 turns on the fan units to maintain the pollutants within the safe limit when the presence of harmful gases and PM levels exceeds a certain threshold level. This system is essential for industrial work places to adopt measures and control air pollution which increase industrial workers safety.
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Meirovitz, A., H. S. Rennert, T. Peretz, A. Salmon, and G. Rennert. "The margins effect: Residual tumor after breast conserving surgery." Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 11045. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.11045.
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11045 Background: Resection of breast cancer with good surgical margins is one of the fundamental aspects of breast conserving surgery. Most studies have shown that women with positive margins after breast conserving surgery (BCS) fared worse compared to those with negative margins, regardless of chemotherapy or radiation therapy. Nowadays, when partial breast irradiation is gaining popularity, understanding the natural history of positive or close margins is particularly important. We studied the surgical process in a large cohort of Israeli women with breast cancer to estimate the frequency of tumor margin involvement in the primary and subsequent surgical procedure. Methods: The National Israeli Breast Cancer Detection Programs has been monitoring the detection process of all new cases of breast cancer in Israel since 1996. Full data on tumor histology and surgical procedures, including indication of margins in the pathology report were available for 16,925 malignant breast tumors. Margins were classified as positive margins (PM), close (= 2mm) (CM) or negative margins (greater then 2mm)(NM). Results: BCS was identified in 14,815 women with invasive cancer and 2,110 with pure ductal carcinoma in situ (DCIS). Only 7,751 (52.3%) of the 14,815 women with invasive cancer had NM, while 2,868 (19.4%) had CM and 4,196 (28.3%) had PM. Among those with PM, 2,276 (54.6%) had a re-operation within 6 months from the index surgery and 1,265 (55.6%) of them were found to be malignant; 58% of them were invasive cancers and 42% DCIS. Among the invasives on re-operation, 24.4% still had PM and another 12.1% had CM while among the DCIS 14.4% had PM and 17.6% had CM. Of the 717 women with DCIS and positive margins at first surgery, 67.9% had a second operation. Of them, 59.8% had malignancy, 8.8% of them invasive. Overall 10.6% of all invasive cancers and 3.7% of all DCIS had PM on relumpectomy within 6 month regardless of initial margin status. Conclusions: A relatively high proportion of all women undergoing BCS were found to have positive or close margins, even after re-operations. If a failure to reach clean margins is a reflection of an aggressive tumor phenotype, special attention should be given to these patients and treatment should be adjusted accordingly. No significant financial relationships to disclose.
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Kim, Jong Choon, Sung Wook Jung, Jae Boong Choi, Yoon Suk Chang, Young Jin Kim, and In-Ju Hwang. "Development of a Neural Network-Based Real-Time Fatigue Monitoring System for the Heavy Load Carrying Facility." Solid State Phenomena 110 (March 2006): 201–12. http://dx.doi.org/10.4028/www.scientific.net/ssp.110.201.
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The heavy load carrying facility, such as ladle crane, is operating under severe working environment. It usually carries melted iron to the furnace, and thus, the accident due to crane failure may cause detrimental damage to the entire steel making factory. While the ladle crane is designed for 20 years of safe operation in a steel making company, several critical cracks due to fatigue loading have been reported during the maintenance process. In order to prevent fatal failure due to crack growth, ladle crane has been periodically inspected and maintained. However, the inspection and maintenance including repair and replacement cause the whole manufacturing line to stop, it is critical to set the appropriate inspection interval and replacement criteria. For this reason, the importance of plant maintenance (PM) has been highly raised to provide efficient plant operation. Recently, a number of engineering methodologies, such as fitness for service guidelines (FFS) and plant lifecycle management (PLM) system, have been applied to improve the plant operation efficiency. Also, a network-based business operation system, which is called ERP (Enterprise Resource Planning), has been introduced in the field of plant maintenance. However, there hasn’t been any attempt to connect engineering methodologies to the ERP PM(Plant Maintenance) system. In this paper, an engineering methodology which provides life time evaluation under fatigue loading has been implemented to the web-based ERP PM system along with real-time fatigue monitoring system. In order to monitor the real time loading, a web-based fatigue monitoring system for ladle crane has been developed and installed inside the ladle crane. For the estimation of fatigue life, 3-dimensional finite element (FE) analyses were conducted for actual transients. Finally, the fatigue life time estimation program is developed by integrating FE analysis results and real-time monitoring data. For the direct calculation of remained fatigue life, an artificial neural network (ANN) algorithm has been applied. The proposed system is expected to play a great role in determining appropriate inspection and maintenance schedule which has become critical issue for the efficient plant maintenance.
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Chandra, Goutam, Davi A. G. Mázala, and Jyoti K. Jaiswal. "Coping with the calcium overload caused by cell injury: ER to the rescue." Cell Stress 5, no. 5 (May 10, 2021): 73–75. http://dx.doi.org/10.15698/cst2021.05.249.
Full textAbstract:
Cells maintain their cytosolic calcium (Ca2+) in nanomolar range and use controlled increase in Ca2+ for intracellular signaling. With the extracellular Ca2+ in the millimolar range, there is a steep Ca2+ gradient across the plasma membrane (PM). Thus, injury that damages PM, leads to a cytosolic Ca2+ overload, which helps activate PM repair (PMR) response. However, in order to survive, the cells must cope with the Ca2+ overload. In a recent study (Chandra et al. J Cell Biol,doi: 10.1083/jcb.202006035) we have examined how cells cope with injury-induced cytosolic Ca2+ overload. By monitoring Ca2+ dynamics in the cytosol and endoplasmic reticulum (ER), we found that PM injury-triggered increase in cytosolic Ca2+ is taken up by the ER. Pharmacological inhibition of ER Ca2+ uptake interferes with this process and compromises the repair ability of the injured cells. Muscle cells from patients and mouse model for the muscular dystrophy showed that lack of Anoctamin 5 (ANO5)/Transmembrane protein 16E (TMEM16E), an ER-resident putative Ca2+-activated chloride channel (CaCC), are poor at coping with cytosolic Ca2+ overload. Pharmacological inhibition of CaCC and lack of ANO5, both prevent Ca2+ uptake into ER. These studies identify a requirement of Cl– uptake by the ER in sequestering injury-triggered cytosolic Ca2+ increase in the ER. Further, these studies show that ER helps injured cells cope with Ca2+ overload during PMR, lack of which contributes to muscular dystrophy due to mutations in the ANO5 protein.
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Tang, Dong, Li Wang, Yang Liu, Ning Liu, Yuzhe Wu, and Lie Chen. "Installation strategy and optimization of PM sensor for diesel engine." Sensor Review 40, no. 1 (January 24, 2020): 89–96. http://dx.doi.org/10.1108/sr-04-2019-0088.
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Purpose This paper aims to design and optimize the threaded fastener of leakage current particulate matter (PM) sensor. The corresponding air-tight test is conducted to ensure the reliability of the installation strategy with screw connection. Design/methodology/approach Research on the pressure-deformation curve of seal gasket was conducted and the vibration load of engine was considered for the calculation of the minimum installation pre-tightening force. Simultaneously, the danger threaded section area was calculated, and the carrying capacity was verified. The height of the welding line was studied to ensure the reliability of the application. FEA was carried out to acquire the relationship between local structure size and local stress for continuous improvement of thread connection. The installation torque range was acquired from the torque control principle for the pre-tightening force. The sealing reliability of the connector was proved with leakage. Findings The air tightness of the thread connector is proved to be fine. When the pre-tightening force is over 8,000 N, and its length reaches 2 mm, the connector has good reliability at ambient temperature. The tightening torque of 60-74 Nm can guarantee the reliable fixing ability of thread connector, and its plastic non-deformation ability in the process of repeated tearing down. Originality/value This paper provides an installation strategy and an optimization of PM sensor, which has a positive effect on the study and the manufacture of PM sensor. It is helpful to further develop PM sensor and after-treatment technology. This kind of real-time monitoring PM sensor needs to be studied further to achieve its commercial application.
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Konstantaki, Maria, Georgios Violakis, Georgios A. Pappas, Thomas Geernaert, Nikos Korakas, Nikos Tiriakidis, Thomai Tiriakidi, et al. "Monitoring of Torque Induced Strain in Composite Shafts with Embedded and Surface-Mounted Optical Fiber Bragg Gratings." Sensors 21, no. 7 (March 31, 2021): 2403. http://dx.doi.org/10.3390/s21072403.
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In this study, silica glass, optical fiber Bragg gratings (FBGs) are used for torque-induced strain monitoring in carbon fiber reinforced polymer (CFRP) hollow shafts toward the development of a methodology for structural load monitoring. Optical fibers with gratings are embedded during shaft manufacturing, by an industrial filament winding process, along different orientations with respect to its central axis and surface mounted after production. Experimental results are supported by numerical modeling of the shaft with appropriate boundary conditions and homogenized material properties. For an applied torque up to 800 Nm, the strain sensitivity of an embedded grating positioned along the reinforcing fibers’ direction winded under 55° is in the order of 3.6 pm/Nm, while this value is more than 4× times higher than the other examined orientations. The study also shows that surface-mounted optical fiber Bragg gratings along the reinforcing carbon fibers’ direction perform equally well in monitoring strains in composite shafts under torque.