با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
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
Bias reduction in the population size estimation of large data sets
کاهش تمایل در برآورد اندازه جمعیت مجموعه داده های بزرگ-2020
Estimation of the population size of large data sets and hard to reach populations can be a significant problem. For example, in the military, manpower is limited and the manual processing of large data sets can be time consuming. In addition, accessing the full population of data may be restricted by factors such as cost, time, and safety. Four new population size estimators are proposed, as extensions of existing methods, and their performances are compared in terms of bias with two existing methods in the big data literature. These would be particularly beneficial in the context of time-critical decisions or actions. The comparison is based on a simulation study and the application to five real network data sets (Twitter, LiveJournal, Pokec, Youtube, Wikipedia Talk). Whilst no single estimator (out of the four proposed) generates the most accurate estimates overall, the proposed estimators are shown to produce more accurate population size estimates for small sample sizes, but in some cases show more variability than existing estimators in the literature.
Keywords: Relative bias | Twitter | Size estimator | Youtube | Random walk sampling
The effects of Chile’s 2005 traffic law reform and in-country socioeconomic differences on road traffic deaths among children aged 0-14 years: A 12-year interrupted time series analysis
اثرات اصلاح قانون راهنمایی و رانندگی در سال 2005 شیلی و اختلافات اقتصادی و اجتماعی درون کشور در مورد مرگ و میر در جاده های کودکان در سن 0-14 سال: تجزیه و تحلیل قطع 12 ساله سری های زمانی -2020
Objectives: This study assessed the effect of Chile’s 2005 traffic law reform (TLR) on the rates of road traffic deaths (RTD) in children aged 0–14 years, adjusting for socioeconomic differences among the regions of the country. Methods: Free-access sources of official and national information provided the data for every year of the study period (2002–2013) and for each of the country’s 13 upper administrative divisions with respect to RTD in child pedestrians and RTD in child passengers (dependent variables), and the following control variables: the number of road traffic tickets processed, investment in road infrastructure, poverty, income inequality, insufficient education, unemployment, population aged 0–14 years, and prevalence of alcohol consumption in the general population. Interrupted time series analyses (level and slope change impact model), using generalized estimating equation methods, were conducted to assess the impact of the TLR (independent variable) on the dependents variables. Results: There was a significant interaction between time and Chile’s 2005 TLR for a reduction in child pedestrians (incidence rate ratio [IRR] 0.87, 95% confidence interval [CI] 0.79-0.96) and passengers RTD (IRR for interaction 0.80, 95% CI 0.67-0.96) trends. In addition, in child pedestrians, RTD rates were affected by poverty (IRR 1.04, 95% CI 1.02–1.05), income inequality (IRR 1.02, 95% CI 1.00–1.04), and unemployment (IRR 0.94, 95% CI 0.90-0.98), whereas in the case of child passengers, poverty (IRR 1.05, 95% CI 1.01–1.08) and income inequality (IRR 0.93, 95% CI 0.91-0.95) were significant. Conclusions: Large-scale legislative actions can be effective road safety measures if they are aimed at promoting behavioral change in developing countries, improving the safety of children on the road. Additionally, regional socioeconomic differences are associated with higher RTD rates in this population, making this an argument in favor of road safety policies that consider these inequalities. The number of road traffic tickets processed and the investment in road infrastructure were not significant.
Keywords: Safety management | Child | Traffic accidents | Mortality | Socioeconomic factors
Effectiveness of implementing the criminal administrative punishment law of drunk driving in China: An interrupted time series analysis, 2004-2017
اثربخشی اجرای قانون مجازات اداری کیفری رانندگی مست در چین: تجزیه و تحلیل سری های زمانی قطع شده ، 2004-2017-2020
In 2011, a more severe drunk driving law was implemented in China, which criminalized driving under the influence of alcohol for the first time and increased penalties for drunk driving. The present study aimed to assess effectiveness of the drunk driving law in China in reducing traffic crashes, injuries, and mortality. Data used in this study was obtained from the Traffic Management Bureau of the Ministry of Public Security of the People’s Republic of China. An interrupted time series analysis was conducted to analyze annual data from 2004 to 2017, including the number of road traffic crashes, deaths, and injuries caused by drunk driving in China. The average annual incidences of crashes, mortality, and injuries have decreased after the promulgation of drunk driving law in 2011. In the post-intervention period, the increased slope for crashes, mortality and injury rates were, respectively, -0.140 to -0.006, -0.052 to -0.005 and -0.150 to -0.008, indicating a weaker downward trend of dependent variables. The more stringent drunk driving law is not as effective as expected. Drunk driving is still a severe traffic safety problem to be addressed in China. Both legislation and other prevention programs should be adopted to reduce road traffic injuries caused by drunk driving in China.
Keywords: Drunk driving | Interrupted time series analysis | Road traffic law | Injury | Evaluation | China
Automatic underground space security monitoring based on BIM
نظارت بر امنیت خودکار فضای زیرزمینی بر اساس BIM-2020
Traditional underground space safety monitoring is ineffective as data continuity is weak, systematic and random errors are prominent, data quantification is difficult, data stability is scarce (especially in bad weather), and it is difficult to guarantee human safety. In this study, BIM technology and multi-data wireless sensor network transmission protocol, cloud computing platform are introduced into engineering monitoring, real-time online monitoring equipment, cloud computing platform and other hardware and software are developed, and corresponding online monitoring system for structural safety is developed to realize online monitoring and early diagnosis of underground space safety. First, the shape of the underground space, the surrounding environment, and various monitoring points are modeled using BIM. Then, the monitoring data collected from sensors at the engineering site are transmitted to the cloud via wireless transmission. Data information management is then realized via cloud computing, and an actual state-change trend and security assessment is provided. Finally, 4D technology (i.e., 3D model + time axis) that leverages a deformation chromatographic nephogram is used to facilitate managers to view deformation and safety of their underground spaces. To overcome past shortcomings, this system supports the management of basic engineering project data and storage of historical data. Furthermore, the system continuously reflects the fine response of each monitoring item under various working conditions all day, which has significant theoretical value and application.
Keywords: BIM technology | Deformation monitoring | Automation information | Management model
Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study
رانندگان ، موانع و ملاحظات اجتماعی برای پذیرش هوش مصنوعی در مشاغل و مدیریت: یک مطالعه عالی-2020
The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business and management domains has risen significantly in the last decade, and that rise has been followed by an increase in the number of systematic literature reviews. The aim of this study is to provide an overview of existing systematic reviews in this growing area of research and to synthesise their findings related to enablers, barriers and social implications of the AI adoption in business and management. The methodology used for this tertiary study is based on Kitchenham and Charter’s guidelines , resulting in a selection of 30 reviews published between 2005 and 2019 which are reporting results of 2,021 primary studies. These reviews cover the AI adoption across various business sectors (healthcare, information technology, energy, agriculture, apparel industry, engineering, smart cities, tourism and transport), management and business functions (HR, customer services, supply chain, health and safety, project management, decisionsupport, systems management and technology acceptance). While the drivers for the AI adoption in these areas are mainly economic, the barriers are related to the technical aspects (e.g. availability of data, reusability of models) as well as the social considerations such as, increased dependence on non-humans, job security, lack of knowledge, safety, trust and lack of multiple stakeholders’ perspectives. Very few reviews outside of the healthcare management domain consider human, organisational and wider societal factors and implications of the AI adoption. Most of the selected reviews are recommending an increased focus on social aspects of AI, in addition to more rigorous evaluation, use of hybrid approaches (AI and non-AI) and multidisciplinary approaches to AI design and evaluation. Furthermore, this study found that there is a lack of systematic reviews in some of the AI early adopter sectors such as financial industry and retail and that the existing systematic reviews are not focusing enough on human, organisational or societal implications of the AI adoption in their research objectives.
Keywords: artificial intelligence | business | machine learning | management | systematic literature review | tertiary study
Method for tracking and communicating aggregate risk through the use of model-based systems engineering (MBSE) tools
روش ردیابی و برقراری ارتباط ریسک با استفاده از ابزارهای مهندسی سیستم مبتنی بر مدل (MBSE)-2020
Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating ag- gregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5 ×5 risk matrix. Like earlier efforts, each box in the 5 ×5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with “Risk to ”relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system’s true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.
Efficacy and safety of oral and inhalation commercial beta-glucan products: Systematic review of randomized controlled trials
اثربخشی و ایمنی محصولات بتا گلوکان تجاری و خوراکی استنشاق: مرور سیستماتیک کارآزمایی کنترل شده تصادفی-2020
Background & aims: Beta-glucans are advertised as biologically active compounds, with various health claims.We aimed to summarize results about efficacy and safety of commercial oral and inhalation betaglucan products on human health from randomized controlled trials (RCTs). Methods: We conducted systematic review of RCTs. We searched MEDLINE, CENTRAL and ClinicalTrials. gov. Any commercial product, any types of participants and any health-related outcomes were eligible. Two authors independently screened studies and extracted data. Cochrane risk of bias tool was used. This review did not have any extramural funding. Registration: PROSPERO record no. 42016043539. Results: We included 30 RCTs that were conducted on healthy or ill participants. Most of the trials reported beneficial effect of beta-glucan, but among the 105 different outcome domains and measures that were used, only three could be considered clinically relevant, while others were various biomarkers and surrogate outcomes such as complete blood count. Included studies on average had 33 participants per study arm, high or unclear risk of bias of at least one domain, and only half of them reported data for safety. More than half of trials that reported source of funding indicated commercial sponsorship from producers of beta-glucan. Only five RCTs reported trial registration. Conclusions: Commercial beta-glucan products were studied in a number of RCTs whose results can be considered only as preliminary, as they used small number of participants and surrogate outcomes. The quality of many studies was poor and further research and trials on bigger population should be performed before a final conclusion can be made.
Keywords: Beta-glucan | Systematic review | Evidence | Randomized controlled trial | Research waste
Intelligent decision-making of online shopping behavior based on internet of things
تصمیم گیری هوشمندانه از رفتار خرید آنلاین مبتنی بر اینترنت اشیا-2020
The development of big data and Internet of things (IoT) have brought big changes to e-commerce. Different kinds of information sources have improved the consumers’ online shopping performance and make it possible to realize the business intelligence. Grip force and eye-tracking sensors are applied to consumers online reviews search behavior by relating them to the research approaches in IoT. To begin with, public cognition of human contact degrees of recycled water reuses with grip force test was measured. According to the human contact degrees, 9 recycled water reuses presented by the experiment are classified into 4 categories. Based on the conclusion drawn from grip force test, purified recycled water and fresh vegetable irrigated with recycled water are regarded as the drinking for high-level human contact degree and the irrigation of food crops for low-level human contact degree respectively. Several pictures are designed for eye-tracking test by simulating an on-line shopping web page on Taobao (the most popular online shopping platform in China). By comparing the fixation time participants spent on the areas of interest (AOIs), we justify that consumers online reviews search behavior is substantially affected by human contact degrees of recycled products. It was found that consumers rely on safety perception reviews when buying high contact goods.
Keywords: Online reviews search behavior | Recycled products | Grip force sensor | Eye-tracking sensor | Internet of Things (IoT)
Modelling guidelines for safety analysis of Station Black Out sequences based on experiments at the PKL test facility
دستورالعمل های مدل سازی برای تجزیه و تحلیل ایمنی توالی خروجی ایستگاه سیاه براساس آزمایشات در مرکز آزمایش PKL-2020
After the Fukushima accident, ‘‘stress-test” activities carried out worldwide pointed out the need to study additional accident management measures to deal with prolonged Station Black Out (SBO) scenarios. Without any operator actions, a total loss of the secondary side heat sink leads to core uncovery, to core damage and ultimately to a melt-down scenario. The international NEA/OECD PKL-3 project has addressed the efficiency of possible accident management actions to re-establish core cooling by experiments at the PKL test facility. Since best estimate system codes were mainly developed to simulate LOCA scenarios, their performance and the general guidelines followed to simulate PWR power plants are called into question. In this paper, RELAP5 simulations of three SBO experiments are presented. An assessment of the code for the particular phenomenology in the experiments have been conducted. Specific guidelines on modelling and a list of the most important sources of uncertainties are provided.
Keywords: Integral test facility | PWR | Station black out | PKL