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1 |
Implementation and Calibration of an IoT Light Attenuation Turbidity Sensor
پیاده سازی و کالیبراسیون سنسور مه آلود تضعیف نور اینترنت اشیا-2022 Turbidity is an important characteristic of water quality that can indicate the presence of un-
desirable suspended particulate matter. Having access to an inexpensive and effective turbidity
sensor unlocks numerous Internet of Things (IoT) possibilities for remote environmental moni-
toring. Optical light attenuation turbidity sensors operate on the premise of detecting signal
degradation from a light source due to scattering from particles in a solution. This approach is
technologically unpretentious and only requires a handful of inexpensive electronic components
to construct. However, while this method is touted as “simple”, a significant challenge lies in
sensor calibration. That is, converting an analogue signal into a meaningful and accurate digital
reading in a known turbidity measurement standard (e.g., Nephelometric Turbidity Units (NTU)).
This paper presents an IoT light attenuation turbidity sensor design and explores the calibration
process to determine the sensor’s range and accuracy. Sensor calibration is undertaken using
Formazin turbidity standards and is cross-checked against a commercial turbidimeter. We provide
a step-by-step procedure for determining the correct signal strength to use and a functional form
for the sensor response to the Formazin standard. Finally, we specify an estimate of the accuracy
of the sensor and suggest the next steps in the proposed turbidity sensor’s development. Results
indicate that the sensor achieves within 2%-10% of accuracy at higher ranges (100–4000 NTU),
but its performance becomes significantly less reliable in low NTU ranges (< 100 NTU) where the
error rate increases to 26%. The turbidity sensor is used as part of an IoT remote aquatic envi-
ronmental monitoring platform. keywords: Internet of underwater things | Turbidity | Affordable sensors | Calibration | attenuation turbidimeter |
مقاله انگلیسی |
2 |
Life history, uses, trade and management of Diospyros crassiflora Hiern, the ebony tree of the Central African forests: A state of knowledge
تاریخچه زندگی، استفاده، تجارت و مدیریت Diospyros crassiflora Hiern، درخت آبنوس جنگل های آفریقای مرکزی: وضعیت دانش-2021 The Central African forest ebony, Diospyros crassiflora Hiern, is a small tree native to the moist forests of the
Congo Basin. Its appealing black heartwood was one of the first products to be exported from the Gulf of Guinea
in the 17th century and is today one of the main sources of ebony globally. Like for other ebony species, its
commercial exploitation raises serious questions about the long-term sustainability of its trade and the viability
of its populations, but the dots are yet to be joined. An examination of the interface between biology, trade, and
ecology is crucial to identify the interrelated factors that could influence the potential success of its conservation.
This paper reviews scientific and grey literature, forest inventories, herbarium and trade data to provide a critical
assessment of the main threats to D. crassiflora populations and gaps in the current state of knowledge. It is shown
here that the species is widespread but never abundant. In the longer term the species is threatened by forest
conversion to agriculture and widespread hunting of large mammals on which the species rely for seed dispersal.
It is currently selectively logged principally to make musical instruments and for the hongmu Chinese market, for
which only one alternative black wood, the near-threatened Dalbergia melanoxylon Guill. et Perr., is commercially
available. Trade statistics suggest that exports from source countries where the species is cut under the forest
concession system are relatively low compared to countries like Cameroon which has seen a recent increase in
exports, and where ebony is exploited without forest management plans. Logging remains a concern where the
exploitation and trade of D. crassiflora are managed in response to demand rather than informed by current stock
levels, growth rate and the particular reproductive biology of this species. The recent successes of private sector
initiatives to ensure the long-term supply of ebony in Cameroon are promising, but would require long-term and
large-scale commitments involving direct and indirect stakeholders to develop programs for the plantation and
policies for the sustainable management of the species. keywords: آبنوس | شکار | جنگل زدایی | تجارت | جنگل مرطوب آفریقا | گیتار | Ebony | Hunting | Deforestation | Trade | African moist forest | Guitar | CITES |
مقاله انگلیسی |
3 |
Accounting for Safety Barriers Degradation in the Risk Assessment of Oil and Gas Systems by Multistate Bayesian Networks
حسابداری برای تخریب موانع ایمنی در ارزیابی ریسک سیستم های نفت و گاز توسط شبکه های چندگانه بیزی-2021 In this paper, a multistate Bayesian Network (BN) is proposed to model and evaluate the functional performance
of safety barriers in Oil and Gas plants. The nodes of the BN represent the safety barriers Health States (HSs) and
the corresponding conditional Failure Probability (FP) values are assigned. HSs are assessed on the basis of
specific Key Performance Indicators (KPIs) related to the barrier characteristics (i.e., technical, procedural or
organizational, continuously monitored or event-based characterized). FP values are estimated from failure
datasets (for technical barriers), evaluated by Human Reliability Analysis (HRA) (for operational and organi-
zational barriers) and assigned by expert elicitation (for barriers lacking data or information). For illustration,
the multistate BN model is developed for preventive barriers and applied to a case study related to the potential
release of flammable material in the slug catcher of a representative O&G Upstream plant which may lead to
major accident scenarios (fire, explosion, toxic dispersion). The results from the case study demonstrate that the
multistate BN model is able to account for the safety barriers HS and their associated functional performance. keywords: ارزیابی ریسک کمی | ارزیابی خطر زندگی | شبکه بیزی | مانع ایمنی | شاخص عملکرد کلیدی | حاشیه ایمنی احتمالی | Quantitative Risk Assessment | Living Risk Assessment | Bayesian Network | Safety Barrier | Key Performance Indicator | Probabilistic Safety Margins |
مقاله انگلیسی |
4 |
Comparison of the impacts of empirical power-law dispersion schemes on simulations of pollutant dispersion during different atmospheric conditions
مقایسه تأثیر برنامه های پراکندگی قانون تجربی قدرت در شبیه سازی پراکندگی آلاینده در شرایط جوی مختلف-2020 Accurate and rapid predictions of air pollutant dispersion are important for effective emergency responses after
sudden air pollution accidents (SAPA). Notably, dispersion parameters (σ) are the key variables that influence the
simulation accuracy of dispersion models. Empirical dispersion schemes based on power-law formulas are
probably appropriate choices for simulations in SAPA because of the requirement for only routine meteorological
data. However, performance comparisons of different schemes are lacking. In this study, the performances during
simulations of air pollutant dispersion of four typical empirical parameterised schemes, i.e. BRIGGS, SMITH,
Pasquill-Gifford, and Chinese National Standard (CNS), were investigated based on the GAUSSIAN plume model
with datasets for the classic Prairie Grass experiments, 1956. The performances when simulating peak and
overall concentrations in different Pasquill atmospheric stability classes (A, B, C, D, E, F) were quantitatively
analysed through different statistical approaches. Results showed that the performances of four schemes for peak
and overall concentrations were basically consistent. Scheme CNS in unstable atmospheric conditions (A, B, and
C) performed significantly better than the others according to performance criteria, which included the lowest
mean of absolute value of fractional biases, lowest normalised mean square errors, and largest mean values of the
fraction within a factor of two when predicting peak and overall concentrations, respectively. Schemes BRIGGS
and P-G exhibited slightly better performances during the neutral condition (D) followed by scheme CNS.
Schemes SMITH and CNS demonstrated slight merits in predicting concentrations compared to the other schemes
during stable conditions (E and F). As a whole, scheme CNS generally performed well for the different atmospheric
stability classes. These analysis results can help to fill in the data gaps and improve our understanding of
the influence of typical power-law function schemes on simulations of air pollutant dispersion. The results are
expected to provide scientific support for air pollution predictions, especially during emergency responses to
SAPA. Keywords: Empirical power-law dispersion schemes | Atmospheric stability | Performance evaluation | Statistical analysis | Emergency response | Sudden air pollution accidents |
مقاله انگلیسی |
5 |
Can the development of a patient’s condition be predicted through intelligent inquiry under the e-health business mode? Sequential feature map-based disease risk prediction upon features selected from cognitive diagnosis big dat
آیا می توان از طریق استعلام هوشمند تحت شرایط تجارت الکترونیکی ، وضعیت یک بیمار را پیش بینی کرد؟ پیش بینی خطر ابتلا به بیماری مبتنی بر ویژگی های توالی بر ویژگی های انتخاب شده از تشخیص شناختی داده های بزرگ-2020 The data-driven mode has promoted the researches of preventive medicine. In prediction of disease risks,
physicians’ clinical cognitive diagnosis data can be used for early prevention of diseases and, therefore, to reduce
medical cost, to improve accessibility of medical services and to lower medical risk. However, researches involved
no physicians’ cognition of patients’ conditions in intelligent inquiry under e-health business mode,
offered no diagnosis big data, neglected the values of the fused text information generated by joint activities of
online and offline medical data, and failed to thoroughly analyze the phenomenon of redundancy-complementarity
dispersion caused by high-order information shortage from the online inquiry data-driven perspective.
Besides, the risk prediction simply based on offline clinical cognitive diagnosis data undoubtedly reduces
prediction precision. Importantly, relevant researches rarely considered temporal relationships of different
medical events, did not conduct detailed analysis on practical problems of pattern explosion, did not offer a
thought of intelligent portrayal map, and did not conduct relevant risk prediction based on the sub-maps obtained
from the map. In consequence, the paper presents a disease risk prediction method with the model for
redundancy-complementarity dispersion-based feature selection from physicians’ online cognitive diagnosis big
data to realize features selection from the cognitive diagnosis big data of online intelligent inquiry; the obtained
features were ranked intelligently for subsequent high-dimensional information shortage compensation; the
compensated key feature information of the cognitive diagnosis big data was fused with offline electronic
medical record (EMR) to form the virtual electronic medical record (VEMR). The formed VEMR was combined
with the method of the sequential feature map for modelling, and a sequential feature map-based model for
disease risk prediction was presented to obtain online users’ medical conditions. A neighborhood-based collaborative
prediction model was presented for prediction of an online intelligent medical inquiry user’s possible
diseases in the future and to intelligently rank the risk probabilities of the diseases. In the experiments, the online
intelligent medical inquiry users’ VEMRs were used as the foundation of the simulation experiments to predict
disease risks in chronic obstructive pulmonary disease (OCPD) population and rheumatic heart disease (RHD)
population. The experiments demonstrated that the presented method showed relatively good metric performances
in the VEMR and improved disease risk prediction. Keywords: Cognitive diagnosis big data | Online intelligent inquiry | Sequential feature map | Disease risk prediction | Redundancy and complementarity dispersion |
مقاله انگلیسی |
6 |
Research on BP network for retrieving extinction coefficient from Mie scattering signal of lidar
تحقیقات بر روی شبکه BP برای بازیابی ضریب خاموشی از سیگنال پراکندگی میای LIDAR-2020 Mie lidar is a powerful tool for detecting the optical properties of atmospheric aerosols. However, there
are two unknown parameters in the Mie lidar equation: the extinction coefficient and the backscattering
coefficient. In the common methods for solving the equation, it is necessary to make assumptions about
the relationship between the two unknown parameters. These assumptions will reduce the detection
precision of extinction coefficient. In view of this, the back propagation (BP) neural network is used to
retrieve extinction coefficient from the Mie scattering signal of lidar. Firstly, the structure and main
parameters of the BP network are designed according to the practical application. In order to improve
the convergence speed and prevent falling into local minima, the initial weights and thresholds of BP network
are optimized by genetic algorithm (GA). Then the GA-BP network is trained with Mie scattering
signal and the extinction coefficient retrieved by Raman method. Thus the mathematical relationship
between Mie scattering signal and the extinction coefficient is stored in the BP network. The trained
GA-BP network is then used to retrieve the extinction coefficient from Mie scattering signal in different
conditions and the applicability of the GA-BP network is researched. The research will promote the development
of Mie lidar retrieving algorithm. Keywords: Aerosol | Mie scattering | Lidar | Extinction coefficient | BP network | Genetic algorithm |
مقاله انگلیسی |
7 |
پیش بینی فواصل سوراخ کاری (بهره برداری نقطه ای) جدید در یک مخزن تخلیه شده به منظور دستیابی به حداکثر بهره وری: مطالعه موردی پیرامون بهره برداری PNN در یک چاه مخزن نفتی ایران
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 18 بهرهبرداری نوترون - نوترون پالس (PNN) برمبنای انتشار نوترون ها به داخل مناطق نزدیک چاه و محاسبه تاخیر تعداد نوترون به دلیل پراکندگی است. کاربرد اصلی این ابزار بهره برداری، تعیین نفت اشباع فعلی و تشخیص کانال در فواصل سوراخ شده و سوراخ نشده در پشت چاه است. تفسیر صحیح نتایج حاصل از بهره برداری PNN به مهندسان امکان پیش بینی فواصل سوراخ کاری جدید در مخازن تخلیه شده را می¬دهد. این مطالعه به بررسی کاربرد بهره برداری PNN در چاه واقع در یکی از مخازن نفتی ایران می پردازد. روش تفسیر به صورت گام به گام شرح داده شده است. در این مطالعه، به بحث پیرامون اصل بهره برداری PNN و مشخصات این ابزار پرداخته شده و کاربردهای بهره برداری PNN در ارزیابی نفت اشباع ، شناسایی مناطق دچار آب گرفتگی و پیش بینی پتانسیل مناطق سوراخ شده توصیف شده است. همچنین کانال بین همه لایه ها مورد بررسی قرار گرفته است ، مناطق نفتی خوب و ضعیف بر اساس اشباع نفت محاسباتی مشخص شده و فواصل سوراخ کاری جدید با هدف تقویت تولید نفت از مخازن پیشنهاد گردید. نتایج این مطالعه نشان دهنده تفسیر مناطق 1 تا 5 دارای نفت اشباع کم ، به عنوان مناطق نفت خیز است. مناطق 6 تا 8 نیز به عنوان مناطق نفتی خوبی که پتانسیل بالایی در تولید نفت دارند؛ و منطقه 9 به عنوان منطقه آب تفسیر می شود.
واژههای کلیدی: گزارش سیستم نوترون-نوترون پالس (PNN) | مقدار سیگما | باقی مانده اشباع نفت | گزارش سیستم مرسوم | فواصل سوراخ کردن | مخزن تخلیه شده |
مقاله ترجمه شده |
8 |
مدیریت زباله های جامد شهری در طول شیوع SARS-COV-2 و سهولت قرنطینه: درس هایی از ایتالیا
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 19 ادبیات مربوط به زباله های جامد شهری در رابطه با COVID-19 کمیاب است. بر اساس تجربه ایتالیا، مقاله حاضر به استراتژی هایی با هدف جلوگیری از شیوع دوم ویروس کمک می کند. در واقع، سوء مدیریت زباله های جامد شهری می تواند استراتژی ها را در طول سهولت قرنطینه تضعیف کند. در طول شیوع SARS-COV-2 در ایتالیا، کاهش کلی در نرخ جمع آوری انتخابی وجود داشت (-15٪ در یک شهرداری با سیستم جمع آوری خانه به خانه به خوبی توسعه یافته). تأخیر در انتشار دستورالعملهای مدیریت پسماند بر ایمنی اپراتورهای جمعآوری زبالههای بالقوه آلوده تأثیر گذاشت. برخلاف انتظارات، ماسکها و دستکشهای یکبار مصرف تأثیر قابلتوجهی بر مدیریت پسماند. با این حال، پراکندگی ماسکها و دستکشهای رها شده در خارج از محیطهای داخلی باعث ایجاد مشکلات زیستمحیطی میشود. توصیه هایی در مورد مدیریت پسماند و حفاظت از اپراتورهای زباله مورد بحث قرار گرفته است. در نهایت، دستورالعمل هایی در مورد مناسب ترین تصفیه زباله از قبل ارسال و تجزیه و تحلیل شده است. نتایج ارائه شده در این مقاله نشان می دهد که بخش مدیریت MSW راه حل های مفیدی برای مقابله با COVID-19 پیدا کرده است. با این حال، این راه حل ها به اندازه کافی به اشتراک گذاشته نمی شوند. مطالعه موردی تحلیلشده در کار حاضر میتواند به تعریف استراتژیهایی برای پیشگیری یا کنترل اپیدمیهای مشابه یا دورههای همهگیر آینده کمک کند.
کلید واژه ها: کووید -19 | زباله جامد شهری | عفونت | امنیت شغلی | SARS-COV-2 | مجموعه انتخابی |
مقاله ترجمه شده |
9 |
How does urban expansion impact people’s exposure to green environments? A comparative study of 290 Chinese cities
توسعه شهری چه تأثیری در مواجهه افراد با محیط های سبز دارد؟ مطالعه تطبیقی 290 شهر چین-2020 Understanding the difference of greenspace in different urban areas is a critical requirement for maintaining
urban natural environment and lessening environmental inequality. However, how urban
expansion impacts on people’s exposure to ambient green environments has been limitedly addressed.
Here we integrated multi-source geospatial big data including mobile-phone location-based service
(LBS) data, Sentinel-2, and nighttime light satellite imageries to quantitatively estimate changes in
people’s exposure to green environments for 290 cities in China from 1992 to 2015. Results showed that
the urban expansion process directly led to differences in green environments between old and new
urban areas. These differences were not only observed by the green coverage rate but also captured using
a dynamic assessment of people’s exposure to greenspace. For most of China’s large cities, people could
enjoy more greenspace in new urban areas than the old ones. A significant day-to-night variation of
people’s exposure to greenspace was identified between old and new urban areas. Our results also
revealed that urbanization did bring some positive effects to improve green environments for cities
located in harsh natural conditions (e.g., semiarid/arid and desert regions). Keywords: Urban greenspace | Urban sprawl | Exposure assessment | Old and new urban area | Human mobility |
مقاله انگلیسی |
10 |
Magnetic permeability of inverse ferrofluid emulsion: Nonlinear ferrofluid magnetization law
نفوذپذیری مغناطیسی امولسیون فروس فلوئور معکوس: قانون مغناطیسی بصورت غیر خطی-2020 This paper is devoted to the mathematical modeling of the nonmonotonic and nonlinear behavior of the magnetic
permeability of inverse ferroemulsion under the influence of a uniform external magnetic field (Dikansky
et al., 2011). The presented model is an extension of the model developed for the case of weak external magnetic
field (Subbotin, 2018), in which the ferrofluid magnetization law is linear. The nonlinear ferrofluid magnetization
law is taken into account via the first-order modified mean-field theory (MMF1) (Ivanov et al., 2001). The
results show a good qualitative and quantitative agreement with the experimental data. Keywords: Ferrofluids | Inverse ferroemulsion | Magnetic permeability | Nonlinear ferrofluid magnetization law | Droplet polydispersity |
مقاله انگلیسی |