Adaptive Measurement Research Articles

Analysis of the relation between facial asymmetry and users' preference between standard versus customized inset progressive addition lenses

Aims/Purpose: User adaptation to progressive addition lenses (PALs) wear requires accurate facial measurements, mainly naso or interpupillary distances, usually measured with a frame ruler. But facial asymmetries are usually ignored. Measurement of foveal fixation axis (FFA) ‐the line linking directly the fixation point and the fovea‐ allows precise facial asymmetry assessment. This study aimed to compare users' preference between standard versus customized inset PALs in patients with and without facial asymmetry according to their FFA measurement.Methods: A crossed, double blind, randomized study was conducted. Participants were classified according to previous experience with PALs (neophytes, PALs users, dropout, and uncomfortable PALs users) and with (>1.0 mm) or without (≤1.0 mm) facial asymmetry. After a complete eye test, two different PALs (LifeStyle 3i, Hoya) were prescribed in a randomized and masked order (2.5 mm standard inset and FFA customized inset PALs). PAL users' preference between both lenses was collected (subjective opinion) after 30 days of wear. Statistical analysis was performed using SPSS 26 (Chicago, USA). ANOVA was used to compare different groups and Chi‐square was used to analyse the frequency of choice of both PALs.Results: 71 participants (37 women and 34 men) were included. 49 with FFA asymmetry; 56% of them (95%CI 42–71%) preferred customized inset lens (Figure 1) (p = 0.05), in dropout group 67% (95%CI 33–100%). No differences (p > 0.05) in clinical parameters were found between patients with or without FFA asymmetry.Conclusions: Participants with FFA asymmetry preferred customized inset lens, especially dropout patients. Facial asymmetry could be a relevant factor in PALs adaptation and FFA measurement could improve users' satisfaction with customized PALs in patients with facial asymmetry.FIGURE 1 (Left). PALs choice according to the patients' facial asymmetry. (Right). PALs choice according to the patients previous use of PALs.imageFIGURE 1 (Left). PALs choice according to the patients' facial asymmetry. (Right). PALs choice according to the patients previous use of PALs.

Ecological selection of winter wheat as a measure of adaptation to climate change

Ecological selection of winter wheat as a measure of adaptation to climate change

Estimated effects of climate variability on agricultural production in Colombia

The objectives of this document are to assess the impact of climate variability on agricultural production in Colombiaand identify the effectiveness of irrigation districts as an adaptation measure. For the analysis, a panel ofmultidimensional data with random effects was used to estimate the effect on crops reported in 1,101 Colombianmunicipalities, between 2007 and 2017. Two variables were taken as climatic shocks: the sum of the absolute differencesin the monthly precipitation compared to its historical mean and the average of the differences in the monthlytemperature with respect to its historical average. The interaction between irrigation districts and rainfall levels was usedas an adaptability variable. The results indicate that the three-dimensional data panel model presented in this papershowed great applicability despite its low use and the small number of documents that exist on climate effects onagricultural production. The main conclusions are that temperature increases lead to decreases in agricultural productionand that irrigation districts as a measure of adaptation to climate variability do not appear to have a significant impact tocounteract it. We found that practices such as the use of shades could influence the reduction of temperatures locally.Similarly, it is necessary to analyses the impact of measures that mitigate the effects associated with changes intemperature rather than those related to the precipitation regime.

Сирийская экономика и санкции: ситуативная адаптация

War, loss of control over part of the territory, and economic sanctions have had a devastating effect on Syria’s economy. However, the country has managed to survive. This has been possible in part due to the measures of the Syrian government, private business, and the population to resist and adapt to economic sanctions. The adaptation strategy had not been planned, and the measures the state, private business, and the population have taken were not coordinated, unlike, for example, in Iran’s case, where strategies are developed and then announced based on future economic risks. Because of this, this strategy of counteraction and adaptation to economic sanctions may be termed as adaptive. The most serious economic sanctions on the Syrian economy have been imposed by the US, the EU, and the League of Arab States. They have restricted Syrian access to goods, technology, financial instruments and products, investments, and even in some cases humanitarian aid from the countries that initiated the sanctions. It is a very difficult task to identify the real Syrian losses caused by the economic sanctions, but it can be accurately asserted, based on the analysis in this article, that they do not allow the country to move forward to the recovery phase. State measures of adaptation to economic sanctions were supposed to become a buffer that would allow the national economy not only to survive, but also to move from stagnation to economic growth. However, it has to be stated that the situational strategy of adaptation to economic sanctions allowed the national economy to remain in a viable state, however, it does not allow it to move from recession to growth.

Priority measures of adaptation to climate change in the viticulture sector in Serbia

Priority measures of adaptation to climate change in the viticulture sector in Serbia

INVESTIGATING THE DEPENDENCIES OF ROTARY GAS METERS ERROR ON FLOWRATE FOR DESIGNING THE ADAPTIVE MEASUREMENT SYSTEM

In this paper, the error of gas flowrate measured by rotary gas meters was investigated based on the results of experimental studies of the metrological characteristics of rotary gas meters obtained during their periodic metrological inspection. According to the results of statistical processing of rotary gas meters errors obtained during their metrological verification, the averaged errors for each verified flowrate were determined. In this way, the dependencies of the averaged meter error on the measured flowrate for various types of rotary gas meters were obtained. For each obtained dependence, the root mean square deviation of the averaged error was calculated, which confirms the adequacy of the obtained dependencies. To evaluate the integral systematic error of meters of each individual type over a long period of operation, the average weighted error was determined according to DSTU OIML R 137-1-2:2018, as well as theaverage measurement error of gas volume during the year according to the methodology proposed by the authors. The presence of the dependencies of gas meter error on the measured value of the flowrate makes it possible to isolate the unexcluded systematic error for every measured flowrate. The implementation of such a dependence in the flowrate computing software makes it possible to develop an adaptive system for measuring gas flowrate and volume, which corrects the measured value of the flowrate considering the unexcluded systematic error of the flowrate measurement. By integrating the systematic error of flowrate measurement in such a system, an archive of the systematic errors of gas volume is formed. The presence of gas volume systematic errors in the computer archive makes it possible to analyze this error and develop measures to eliminate it. Keywords: rotary gas meter, gas flowrate, systematic error, metrological verification, adaptive measurement system

Suwerenność narodu podczas pandemii COVID-19. Wnioski z doświadczeń państw Grupy Wyszehradzkiej. Wybory parlamentarne i samorządowe w cieniu koronawirusa

The coronavirus crisis led to severe restrictions of numerous fundamental rights almost globally, amongst which the right to vote was also concerned. Our research article aims to integrate the experience of the Visegrád region into the emerging strand of international legal scholarship from the long-term impact of the public health emergency on electoral frameworks. Based on a research collaboration funded by the International Visegrád Fund, the study presents the adaptative measures implemented by the four Visegrád countries to hold national or municipal elections in the shadow of the global pandemic, and contextualizes these interventions in the light of the global electoral tendencies. Finally, based on our research, the expected features of post-COVID electoral frameworks in the Visegrád region were also provided. Alternative electoral regimes are discussed for the promotion of flexibility and resilience, which are grounded on the combined elements of the traditional voting system, on additional public health requirements, and also on the extensive application of postal- and electronic voting.

A Covariance Matching-Based Adaptive Measurement Differencing Kalman Filter for INS’s Error Compensation

In this study, a covariance matching-based adaptive measurement differencing Kalman filter (AMDKF) for the case of time-correlated measurement errors is proposed. The solution to the state estimation problem involves deriving a filter that accounts for measurement differences. Specifically, the measurement noise in the generated measurements is assumed to be correlated with the process noise. To address this issue in the context of correlated process and measurement noise, we propose an adaptive measurement differencing Kalman filter that is robust to measurement faults. We also evaluate the robustness of the suggested AMDKF through an analysis. When noise increment type sensor faults are present in the time-correlated inertial navigation systems (INS) measurements, the states of a multi-input/output aircraft model were estimated using both the previously developed measurement differencing Kalman filter (MDKF) and the suggested AMDKF and the results were compared.

The Role of Big Data Analysis in Enterprise Transformation: Evidence from Taobao and Alibaba

In the context of information digitization, big data's ascendancy has profoundly impacted industries, especially e-commerce, ushering in a new era of data-driven transformation. The motivation for this research arises from understanding how pivotal big data analytics is in reshaping enterprise functionalities. Utilizing a ten-fold literature analysis, this study explores the interdependent relationship between the Taobao platform and the expansive Alibaba database. The investigation reveals that through big data, Taobao has fine-tuned its strategies, enabling large-scale personalization, accurate market forecasting, and the enhancement of supplier relationships. Such adaptative measures have not only solidified Taobao's market position but have also charted a course for enterprises seeking to harness the full potential of big data. The revelations from this study are seminal, emphasizing that in today's digital milieu, leveraging big data analytics is less of a luxury and more of a necessity for sustainable enterprise growth.

Air quality and health co-benefits of vehicle electrification and emission controls in the most populated United States urban hubs: Insights from New York, Los Angeles, Chicago, and Houston

Transitioning to electric vehicles (EVs) is a prominent strategy for reducing greenhouse gas emissions. However, given the complexity of atmospheric chemistry, the nuanced implications on air quality are yet to be fully understood. Our study delved into changes in PM2.5, ozone, and their associated precursors in major US urban areas, considering various electrification and mitigation scenarios. In the full electrification (FullE) scenario, PM2.5 reduction peaked at values between 0.34 and 2.29 μg.m−3 across distinct regions. Yet, certain areas in eastern Los Angeles exhibited a surprising uptick in PM2.5, reaching as much as 0.67 μg.m−3. This phenomenon was linked to a surge in secondary organic aerosols (SOAs), resulting from shifting NOx/VOCs (volatile organic compounds) dynamics and a spike in hydroxyl radical (OH) concentrations. The FullE scenario ushered in marked reductions in both NOx and maximum daily average 8-h (MDA8) ozone concentrations, with maximum levels ranging from 14.00 to 32.34 ppb and 2.58–9.58 ppb, respectively. However, certain instances revealed growths in MDA8 ozone concentrations, underscoring the intricacies of air quality management. From a health perspective, in the FullE scenario, New York, Chicago, and Houston stand to potentially avert 796, 328, and 157 premature deaths/month, respectively. Los Angeles could prevent 104 premature deaths/month in the HighE-BL scenario, representing a 29 % EV share for light-duty vehicles. However, the FullE scenario led to a rise in mortality in Los Angeles due to increased PM2.5 and MDA8 ozone levels. Economically, the FullE scenario projects health benefits amounting to 51–249 million $/day for New York, Chicago, and Houston. In contrast, Los Angeles may face economic downturns of up to 18 million $/day. In conclusion, while EV integration has the potential to improve urban air quality, offering substantial health and economic advantages, challenges persist. Our results emphasize the pivotal role of VOCs management, providing policymakers with insights for adaptable and efficient measures.

Priority areas for the development of field fodder production in view of the climate crisis

This article covers the topical issue of the general impact of climate change on Ukrainian agriculture and on the field fodder production industry specifically, as well as the problems of adapting agriculture to modern environmental conditions. The authors set out to substantiate promising ways of developing modern field fodder production considering climate change. For this, the study employed the abstract-logical method, system analysis, methods of systematisation and classification, and a range of economic and statistical research methods (comparison, series of dynamics, method of structural groupings). Both negative and positive manifestations of the climate crisis in crop production were highlighted, and possible measures to counteract risks and ways to use potential opportunities to develop field fodder production given the impact of climate change were systematised. Particular attention was paid to the global practices of agriculture in the face of climate change, namely, the components of a climate-smart crop production system. The study also described the main promising measures of adaptation of field fodder production to climate change: irrigation of agricultural land, arrangement of snow retention systems in the fields, rainwater harvesting, selection and introduction of new varieties of fodder crops, effective crop rotation, increase in sowing of drought-resistant fodder crops, optimisation of agricultural technologies to reduce losses of fodder crops at the stages of harvesting and storage, application of organic farming, the latest soil fertilisation technologies and the use of nanotechnology in soil cultivation. The findings of this study can be used by managers of specific agricultural enterprises, as well as by advisory services and government agencies in the field of agricultural policy implementation.

Naive Bayes Augmented with Genetic Algorithm: Feature Reduction Approach for Effective Cyber Attack Detection

This study examines the application of a Naive Bayes approach augmented with a genetic algorithm for the purpose of cyber intrusion detection. Being able to quickly adapt to the complex and variable nature of cyber-attacks, this approach offers an innovative solution, especially in feature reduction and data classification. The genetic algorithm is employed to identify the most optimal characteristics from the data sets, while the Naive Bayes classifier is utilised to detect cyber-attacks based on these features. Empirical examinations and evaluations have demonstrated that this comprehensive methodology yields superior precision rates and reduced rates of false positives compared to conventional techniques for detecting cyber intrusions. The findings of this study underscore the necessity of creating more efficient and adaptable measures in the realm of cyber security, particularly in light of the constantly evolving and unpredictable nature of threats.

Dimensions of cultural sustainability—Local adaptation, adaptive capacity and social resilience

Cultural sustainability relates to sustainable development. According to UNESCO “culture provides the necessary transformative dimension that ensures the sustainability of development processes.” Originally sustainable development was defined through three dimensions-ecological, economic and social dimension. Further, the social dimension has been understood in multiple ways often accentuating socio-economic assets of development rather than socio-cultural capacities. Eventually, there has been an increasing interest in defining cultural sustainability as a fourth pillar of sustainable development. While becoming aware of the contemporary supranational risks such as climate change, COVID 19-pandemia or escalating military conflicts, sustainable development can hardly be envisioned in terms of linear progress but rather considered with anticipation of eventual shocks, interruptions, and vulnerabilities related to development. In this perspective, cultural sustainability can be increasingly associated with identifying vulnerabilities and with envisioning attainable measures of adaptation. This article addresses the complex issue of defining cultural sustainability through lenses of social resilience and adaptive capacity at local level.

Evaluation of a mobile app for dark adaptation measurement in individuals with age-related macular degeneration

We present clinical evaluation of a mobile app for dark adaptation (DA) measurement in age-related macular degeneration (AMD) patients and in older adults (age > 50 years) without AMD or other retinal disorders (NV). The outcome measures were the area under dark adaptation curve (AUDAC) and the time for visual sensitivity to recover by 3 log units (TR). Larger AUDAC and TR values indicated worse DA response. The association of AUDAC with AMD was analyzed using linear regression, while time-to-event analysis was used for TR. 32 AMD patients (mean ± SD; age:72 ± 6.3 years, VA:0.09 ± 0.08 logMAR) and 25 NV subjects (mean ± sd; age:65 ± 8.7 years, VA:0.049 ± 0.07 logMAR) were measured with the app. Controlling for age, VA, and cataract severity, the AMD presence was significantly associated with higher AUDAC (β = 0.41, 95% CI 0.18–0.64, p = 0.001) and with slower sensitivity recovery (β = 0.32, 95% CI 0.15–0.69, p = 0.004). DA measurements with the app were highly correlated with those obtained with AdaptDx—an established clinical device (n = 18, ρ = 0.87, p < 0.001). AMD classification accuracy using the app was 72%, which was comparable to the 71% accuracy of AdaptDx. Our findings indicate that the mobile app provided reliable and clinically meaningful DA measurements that were strongly correlated with the current standard of care in AMD.

Innovation in Adaptive Leadership Management Model through the Development of Digital Mindset in Activator School Programs

This research aims to design measurement instruments of digital mindset and adaptive leadershiphip, and also design of adaptive leadershiphip management model through the development of digital mindset in activator school program. The samples are 296 teachers of activator high school taken using proportional random sampling. Measurement of adaptive leadershiphip is carried out through the distribution of questionnaire instruments prepared based on 5 (five) dimensions of adaptive leadershiphip, including: 1) Emotional intelligence, 2) Organizational justice, 3) Development, 4) Character, and 5) Problem solving. Meanwhile, digital mindset measurement is carried out through the distribution of questionnaire instruments prepared based on 7 (seven) dimensions of digital mindset, namely: 1) Abundance mindset, 2) Growth mindset, 3) Agile approach, 4) Comfort with ambiguity,5) Explorer’s mind, 6) Collaborative approach, and 7) Embracing diversity. The results of the design of the digital mindset and adaptive leadershiphip measurement instrument for activator high school teachers in DKI Jakarta have proven to be valid and reliable, so that this instrument can be used to measure the digital mindset of all activator high school teachers in the DKI Jakarta. The results of the design of the adaptive leadershiphip management model through the development of the digital mindset of activator high school teachers in DKI Jakarta can be seen in detail in Figure 12, namely the structural model of the influence of digital mindset towards adaptive leadershiphip, where of the 7 (seven) digital mindset dimensions, only 4 (four) dimensions that show a significant influence on adaptive leadershiphip, namely dimensions: abundance mindset, growth mindset, explorer mindset, and embracing diversity.

Evaluation of the Use of Permeable Interlocking Concrete Pavement in Chile: Urban Infrastructure Solution for Adaptation and Mitigation against Climate Change

There is currently a context of climate change due to the way modern cities are developed, and they are made up mainly of impermeable surfaces and concrete buildings that change the hydrological cycle, causing (i) an increase in temperatures, (ii) the accumulation of stormwater on different surfaces, (iii) overflow in drainage systems, and (iv) the alteration of ventilation patterns, among others. This article presents a case study on the implementation of a permeable interlocking concrete paving (PICP) system, and it develops physical–mathematical modeling using software for the design of a parking lot that currently does not have adequate paving and urban drainage, resulting in sporadic flooding due to heavy rainfall in the city of Temuco, La Araucanía region, Chile. This article’s contribution highlights the application of new technology in Chile, discussing road infrastructure solutions based on sustainable urban drainage systems (SUDSs), which seek to implement feasible alternatives in urban sectors to improve human livelihood. The factors studied include structural and hydrological properties, along with the infiltration analysis of the system according to historical rainfall records in the area. This research concludes that the permeable pavement system with a drainage pipe and smooth roughness coefficient performs satisfactorily for an extreme hydrometeorological event corresponding to 140 mm considering 24 h of rainfall with a return period of 100 years equivalent to an inflow of 673 m3/day. Finally, the results indicate that, at least in the conditions of the city of Temuco, the use of permeable interlocking concrete pavement (PICP) proves to be a sustainable and feasible alternative to implementing measures of adaptation and mitigation against climate change, reducing the city’s flooding zones and allowing the irrigation of urban green areas.

Change Point Detection with Adaptive Measurement Schedules for Network Performance Verification

When verifying that a communications network fulfills its specified performance, it is critical to note sudden shifts in network behavior as quickly as possible. Change point detection methods can be useful in this endeavor, but classical methods rely on measuring with a fixed measurement period, which can often be suboptimal in terms of measurement costs. In this paper, we extend the existing framework of change point detection with a notion of physical time. Instead of merely deciding when to stop, agents must now also decide at which future time to take the next measurement. Agents must now minimize the necessary number of measurements pre- and post-change, while maintaining a trade-off between post-change delay and false alarm rate. We establish, through this framework, the suboptimality of typical periodic measurements and propose a simple alternative, called crisis mode agents. We show analytically that crisis mode agents significantly outperform periodic measurements schemes. We further verify this in numerical evaluation, both on an array of synthetic change point detection problems as well as on the problem of detecting traffic load changes in a 5G test bed through end-to-end RTT measurements.

Frequency adaptive conductivity measurement based on reverse approximation

Accurately measuring the solution conductivity is important both for environmental assessment and process monitoring. A reverse approximation frequency adaptive conductivity test method is proposed in this paper. This method avoids the complex calculation of the time constant τ of the first-order resistance-capacitance network and eliminates the influence of the accessory capacitance on the measurement results to the greatest extent. Through 9 groups of optimal frequency selection experiments, the optimal measurement frequency of R1 and Rx fixed ratio in a certain range is obtained. The optimal measurement frequency and dimensionless relationship model constitute a complete frequency adaptive solution conductivity measurement method.Through comparative analysis, the mean absolute percentage error of the measurement results is 2.65%, which not only improves the measurement accuracy of the existing self-developed equipment but also provides a new solution to solve the influence of additional capacitance in the conductivity measurement process.

Risk‐based thinking for extreme events: What do terrorism and climate change have in common?

AbstractTerrorism and climate change debates are often characterized by worst‐case thinking, cost neglect, probability neglect, and avoidance of the notion of acceptable risk. This is not unexpected when dealing with extreme events. However, it can result in a frightened public, costly policy outcomes, and wasteful expenditures. The paper will describe how risk‐based approaches are well suited to infrastructure decision‐making for extreme events. Risk management concepts will be illustrated with current research of risk‐based assessment of climate adaptation engineering strategies including designing new houses in Australia subject to cyclones and extreme wind events. It will be shown that small improvements to house designs at a one‐off cost of several thousand dollars per house can reduce damage risks by 70%–80% and achieve billions of dollars of net benefit for community resilience—this helps offset some the predicted adverse effects of climate change for a modest cost. The effect of risk perceptions, insurance, and economic incentives is explored for another climate adaption measure. The paper will also highlight that there is much to be optimistic about the future, and in the ability of risk‐based thinking to meet many challenges.

A Siamese CNN-BiLSTM-based method for unbalance few-shot fault diagnosis of rolling bearings

Small and imbalanced fault samples have a profound impact on the diagnostic performance of a model in the process of locating and quantifying the rolling bearing damage of aeroengines in practice. Therefore, a Siamese Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) model was proposed in this paper. Random selection and cross combination methods were used to augment and balance sample sizes at first. Then, two weight-sharing CNN-BiLSTM models were used for adaptive extraction and distance measurement of weak fault features. Finally, the fault classification was performed based on feature distance. Model performance was verified using simulated fault test data of rolling bearings. The results showed that the Siamese CNN-BiLSTM model could achieve an accuracy of up to 96.0% for quantitative diagnosis and 98.0% for location diagnosis. This model was also capable of solving the imbalanced classification of samples and made it possible to transfer between different rotating speeds and working conditions.