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تعداد مقالات یافته شده: 666
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1 Data Mining Strategies for Real-Time Control in New York City
استراتژی داده کاوی برای کنترل زمان واقعی در شهر نیویورک-2105
The Data Mining System (DMS) at New York City Department of Transportation (NYCDOT) mainly consists of four database systems for traffic and pedestrian/bicycle volumes, crash data, and signal timing plans as well as the Midtown in Motion (MIM) systems which are used as part of the NYCDOT Intelligent Transportation System (ITS) infrastructure. These database and control systems are operated by different units at NYCDOT as an independent database or operation system. New York City experiences heavy traffic volumes, pedestrians and cyclists in each Central Business District (CBD) area and along key arterial systems. There are consistent and urgent needs in New York City for real-time control to improve mobility and safety for all users of the street networks, and to provide a timely response and management of random incidents. Therefore, it is necessary to develop an integrated DMS for effective real-time control and active transportation management (ATM) in New York City. This paper will present new strategies for New York City suggesting the development of efficient and cost-effective DMS, involving: 1) use of new technology applications such as tablets and smartphone with Global Positioning System (GPS) and wireless communication features for data collection and reduction; 2) interface development among existing database and control systems; and 3) integrated DMS deployment with macroscopic and mesoscopic simulation models in Manhattan. This study paper also suggests a complete data mining process for real-time control with traditional static data, current real timing data from loop detectors, microwave sensors, and video cameras, and new real-time data using the GPS data. GPS data, including using taxi and bus GPS information, and smartphone applications can be obtained in all weather conditions and during anytime of the day. GPS data and smartphone application in NYCDOT DMS is discussed herein as a new concept. © 2014 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of Elhadi M. Shakshu Keywords: Data Mining System (DMS), New York City, real-time control, active transportation management (ATM), GPS data
مقاله انگلیسی
2 Tracking the northern seasonal cap retreat of mars using computer vision
ردیابی عقب نشینی کلاهک فصلی شمالی مریخ با استفاده از بینایی کامپیوتر-2022
Using polar stereographic images from the Mars Color Imager (MARCI), we use Python to autonomously track the Northern Polar Seasonal Cap (NPSC) recession from Mars Years (MY) 29 to MY 35 between Ls = 10° and Ls = 70°. We outline the cap and find an ellipse of best fit. We then compare our results to previously published recession rates, that were manually tracked, and find them to be consistent. Our process benefits from being automated, which increases the speed of tracking and allows us to monitor the recession with higher Ls fidelity than past studies. We find that most MYs have a local minimum recession rate at Ls = ~32° and a local maximum at Ls = ~51°. We also find that MY 30 experiences a rapid latitude increasing event that involves ~1° Ls of a rapid increase and ~5° Ls of slower recession, which then increases above the interannual average rate. We interpret this to be the result of a major sublimation driven by off-polar winds. We also discover divergent effects in the recession and size of the NPSC following the MY 28 and MY 35 global dust storms. MY 29’s cap is significantly smaller and retreats slower than the multi-year average, whereas MY 35’s cap is slighter larger and retreats very close to the average. We hypothesize that the diverging behavior of the caps in post-storm years can be a result of the differences in the date of onset and the duration of the storms.
مقاله انگلیسی
3 A computer vision-based method for bridge model updating using displacement influence lines
یک روش مبتنی بر بینایی کامپیوتری برای به‌روزرسانی مدل پل با استفاده از خطوط موثر جابجایی-2022
This paper presents a new computer vision-based method that simultaneously provides the moving vehicle’s tire loads, the location of the loads on a bridge, and the bridge’s response displacements, based on which the bridge’s influence lines can be constructed. The method employs computer vision techniques to measure the displacement influence lines of the bridge at different target positions, which is then later used to perform model updating of the finite element models of the monitored structural system.
The method is enabled by a novel computer vision-based vehicle weigh-in-motion method which the coauthors recently introduced. A correlation discriminating filter tracker is used to estimate the displacements at target points and the location of single or multiple moving loads, while a low-cost, non-contact weigh-in-motion technique evaluates the magnitude of the moving vehicle loads.
The method described in this paper is tested and validated using a laboratory bridge model. The system was loaded with a vehicle with pressurized tires and equipped with a monitoring system consisting of laser displacement sensors, accelerometers, and cameras. Both artificial and natural targets were considered in the experimental tests to track the displacements with the cameras and yielded robust results consistent with the laser displacement measurements.
The extracted normalized displacement influence lines were then successfully used to perform model updating of the structure. The laser displacement sensors were used to validate the accuracy of the proposed computer vision-based approach in deriving the displacement measurements, while the accelerometers were used to derive the system’s modal properties employed to validate the updated finite element model. As a result, the updated finite element model correctly predicted the bridge’s displacements measured during the tests. Furthermore, the modal parameters estimated by the updated finite element model agreed well with those extracted from the experimental modal analysis carried out on the bridge model. The method described in this paper offers a low-cost non-contact monitoring tool that can be efficiently used without disrupting traffic for bridges in model updating analysis or long-term structural health monitoring.
keywords: Computer vision | Displacement influence line | Vehicle weigh-in-motion | Structural identification | Finite element method model | Model updating | Modal analysis | Bridge systems
مقاله انگلیسی
4 Barriers to computer vision applications in pig production facilities
موانع برنامه های بینایی کامپیوتری در تاسیسات تولید خوک-2022
Surveillance and analysis of behavior can be used to detect and characterize health disruption and welfare status in animals. The accurate identification of changes in behavior is a time-consuming task for caretakers in large, commercial pig production systems and requires strong observational skills and a working knowledge of animal husbandry and livestock systems operations. In recent years, many studies have explored the use of various technologies and sensors to assist animal caretakers in monitoring animal activity and behavior. Of these technologies, computer vision offers the most consistent promise as an effective aid in animal care, and yet, a systematic review of the state of application of this technology indicates that there are many significant barriers to its widespread adoption and successful utilization in commercial production system settings. One of the most important of these barriers is the recognition of the sources of errors from objective behavior labeling that are not measurable by current algorithm performance evaluations. Additionally, there is a significant disconnect between the remarkable advances in computer vision research interests and the integration of advances and practical needs being instituted by scientific experts working in commercial animal production partnerships. This lack of synergy between experts in the computer vision and animal health and production sectors means that existing and emerging datasets tend to have a very particular focus that cannot be easily pivoted or extended for use in other contexts, resulting in a generality versus particularity conundrum. This goal of this paper is to help catalogue and consider the major obstacles and impediments to the effective use of computer vision associated technologies in the swine industry by offering a systematic analysis of computer vision applications specific to commercial pig management by reviewing and summarizing the following: (i) the purpose and associated challenges of computer vision applications in pig behavior analysis; (ii) the use of computer vision algorithms and datasets for pig husbandry and management tasks; (iii) the process of dataset construction for computer vision algorithm development. In this appraisal, we outline common difficulties and challenges associated with each of these themes and suggest possible solutions. Finally, we highlight the opportunities for future research in computer vision applications that can build upon existing knowledge of pig management by extending our capability to interpret pig behaviors and thereby overcome the current barriers to applying computer vision technologies to pig production systems. In conclusion, we believe productive collaboration between animal-based scientists and computer-based scientists may accelerate animal behavior studies and lead the computer vision technologies to commercial applications in pig production facilities.
keywords: بینایی کامپیوتر | دامپروری دقیق | رفتار - اخلاق | یادگیری عمیق | مجموعه داده | گراز | Computer vision | Precision livestock farming | Behavior | Deep learning | Dataset | Swine
مقاله انگلیسی
5 Disintegration testing augmented by computer Vision technology
آزمایش تجزیه با فناوری Vision کامپیوتری تقویت شده است-2022
Oral solid dosage forms, specifically immediate release tablets, are prevalent in the pharmaceutical industry. Disintegration testing is often the first step of commercialization and large-scale production of these dosage forms. Current disintegration testing in the pharmaceutical industry, according to United States Pharmacopeia (USP) chapter 〈701〉, only gives information about the duration of the tablet disintegration process. This infor- mation is subjective, variable, and prone to human error due to manual or physical data collection methods via the human eye or contact disks. To lessen the data integrity risk associated with this process, efforts have been made to automate the analysis of the disintegration process using digital lens and other imaging technologies. This would provide a non-invasive method to quantitatively determine disintegration time through computer algorithms. The main challenges associated with developing such a system involve visualization of tablet pieces through cloudy and turbid liquid. The Computer Vision for Disintegration (CVD) system has been developed to be used along with traditional pharmaceutical disintegration testing devices to monitor tablet pieces and distinguish them from the surrounding liquid. The software written for CVD utilizes data captured by cameras or other lenses then uses mobile SSD and CNN, with an OpenCV and FRCNN machine learning model, to analyze and interpret the data. This technology is capable of consistently identifying tablets with ≥ 99.6% accuracy. Not only is the data produced by CVD more reliable, but it opens the possibility of a deeper understanding of disintegration rates and mechanisms in addition to duration.
keywords: از هم پاشیدگی | اشکال خوراکی جامد | تست تجزیه | یادگیری ماشین | شبکه های عصبی | Disintegration | Oral Solid Dosage Forms | Disintegration Test | Machine Learning | Neural Networks
مقاله انگلیسی
6 Towards automatic waste containers management in cities via computer vision: containers localization and geo-positioning in city maps
به سمت مدیریت خودکار ظروف زباله در شهرها از طریق بینایی کامپیوتری: محلی سازی ظروف و موقعیت جغرافیایی در نقشه های شهر-2022
This paper describes the scientific achievements of a collaboration between a research group and the waste management division of a company. While these results might be the basis for several practical or commercial developments, we here focus on a novel scientific contribution: a methodology to automatically generate geo- located waste container maps. It is based on the use of Computer Vision algorithms to detect waste containers and identify their geographic location and dimensions. Algorithms analyze a video sequence and provide an automatic discrimination between images with and without containers. More precisely, two state-of-the-art object detectors based on deep learning techniques have been selected for testing, according to their perfor- mance and to their adaptability to an on-board real-time environment: EfficientDet and YOLOv5. Experimental results indicate that the proposed visual model for waste container detection is able to effectively operate with consistent performance disregarding the container type (organic waste, plastic, glass and paper recycling,…) and the city layout, which has been assessed by evaluating it on eleven different Spanish cities that vary in terms of size, climate, urban layout and containers’ appearance.
keywords: Waste container localization | Deep Learning | Computer Vision | Object detection
مقاله انگلیسی
7 Accounting as a technology of neoliberalism: The accountability role of IPSAS in Nigeria
حسابداری به عنوان فناوری نئولیبرالیسم: نقش پاسخگویی IPSAS در نیجریه-2021
This paper critically examines the implications for Nigeria’s indebtedness of neoliberalism as a neo-colonial dependency concept and International Public Sector Accounting Standards (IPSAS) as a technology of a new form of economic imperialism. As Nigeria’s huge oil and gas revenues continue to be lost to corruption, the country relies on loans from Paris Club countries and International Financial Institutions (IFIs), notably the World Bank. In 1999, when the country changed from military to democratic governance, Nigeria’s debt to the Paris Club and the World Bank was $30bn. With pressure from the Paris Club and the World Bank to repay its debts, the new democratic Nigerian government sought debt forgiveness and rescheduling. Although the World Bank, representing the creditors in debt negotiation, does not go into specific accounting standards to be adopted by debtor nations, the Bank does require Nigeria to embrace neoliberal economic reforms (including public sector reporting framework that produces consistently relevant and reliable financial information – which denotes IPSAS). Despite the partial debt forgiveness, repayment of the balance of the debt and adoption of IPSAS, Nigeria remains endemically corrupt, relies on loans from powerful nations and IFIs, and has again become debt-laden. Contrary to neoliberal assumptions therefore, we provide the evidence that better accounting may not necessarily be a panacea for economic development.
keywords: نئولیبرالیسم | موسسات مالی بین المللی (IFIS) | حسابداری بین المللی بخش دولتی | استانداردها (خود) | فساد | شفافیت و پاسخگویی | Neoliberalism | International Financial Institutions (IFIs) | International Public Sector Accounting | Standards (IPSAS) | Corruption | Transparency and Accountability
مقاله انگلیسی
8 Pain management for infants – Myths, misconceptions, barriers; knowledge and knowledge gaps
مدیریت درد برای نوزادان - افسانه ها، باورهای غلط، موانع؛ دانش و شکاف دانش-2021
Twelve years ago, the paper ‘Oral sucrose for pain management in infants: Myths and misconceptions’ was published in the Journal of Neonatal Nursing. At this time, eight myths or misconceptions were addressed. Since this time there has been more than 100 studies published reporting on analgesic effects of sweet solutions in newborns, which have been synthesised and included in systematic reviews. There has also been a growth of literature to support analgesic effects of breastfeeding and skin-to-skin care as well as concerning evidence of adverse long-term neurobehavioural outcomes associated with painful procedures. Yet, ongoing studies of pain management practices continue to report inconsistent use of these strategies during painful procedures. We are therefore at a cross-roads of evidence – there is knowledge of effective treatments, knowledge of harm of untreated pain, yet sick, premature as well as healthy infants are continuing to be exposed to painful procedures with no effective treatment. There are however ongoing myths, misconceptions, and practical barriers to using the evidence as well as ongoing knowledge gaps. This paper will therefore highlight existing myths, misconceptions, barriers and current knowledge gaps to using the three key evidence-based pain management strategies of breastfeeding, skin-to-skin care and sweet solutions, in the hope that this will bring to light newborn infant pain treatment practices that can be improved.
keywords: پرستاری | نوزاد تازه | درد | درمان درد | شیر دادن | ساکاروز | پوست به پوست | نوزاد | ترجمه دانش | پژوهش | Nursing | Newborn | Pain | Pain treatment | Breastfeeding | Sucrose | Skin-to-skin | Neonate | Knowledge translation | Research
مقاله انگلیسی
9 Sustainability at stake during COVID-19: Exploring the role of accounting in addressing environmental crises
پایداری در معرض خطر در Covid-19: بررسی نقش حسابداری در رسیدگی به بحران های زیست محیطی-2021
In this paper, we reflect and provide insights on the environmental implications of postCOVID-19 economic recoveries. More specifically, we highlight the connection(s) between the environment and the COVID-19 crisis, in particular the intertwined links between Mother Nature and the virus. We then raise some concerns about the ‘illusionary’ positive and negative effects of the crisis on the environment before evoking some past lessons about crisis management and recovery. We contend that the current accounting and accountability mechanisms employed in economic stimulus programs, as well as traditional environmental accounting approaches, are inadequate and limiting to achieve long-term sustainability change. The paper concludes by offering accounting practitioners and researchers some possibilities to take a step forward and develop new understandings of social and environmental value consistent with ecological principles and sustainable development—and hope that these reflections will contribute to a broader debate on the role of accounting for sustainable development in the Anthropocene
keywords: بحران زیست محیطی | کووید -19 | حسابداری اجتماعی و زیست محیطی | مسئوليت | Environmental crisis | COVID-19 | Social and environmental accounting | Accountability
مقاله انگلیسی
10 Three-month follow-up effects of a medication management program on nurses’ knowledge
اثرات پیگیری سه ماهه یک برنامه مدیریت دارو در دانش پرستاران-2021
This quasi-experimental study examined the effects of a medication management program on nurses knowledge of medication management, three months after program completion. Fifty-seven nurses took a multiple-choice test both immediately after the program and three months later. Changes in test performance were assessed using McNemar’s test and generalized estimating equations for binary outcomes. Test results were generally consistent from immediately post-program to three months later, though four items differed significantly. From immediately post-program to three months later, fewer nurses correctly answered the items: documenting no medication administration (98.2 vs 86.6, p = 0.04); documenting opioid administration (56.1 vs 33.3, p = 0.01); and observation after opioid administration (35.1 vs 19.3, p = 0.08. Significantly more nurses correctly answered the item concerning the pharmacology of medication administered with food (64.9 vs 77.2, p = 0.09). We recom- mend both continuous medication management training and focusing on the correspondence between theory- based knowledge and clinical practice routines.
keywords: پرستار بیمارستان | برنامه آموزشی | مدیریت دارو | دانش | Hospital nurse | Education program | Medication management | Knowledge
مقاله انگلیسی
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