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
IMPROVING PAIN REASSESSMENT AND DOCUMENTATION RATES: A QUALITY IMPROVEMENT PROJECT IN A TEACHING HOSPITAL’S EMERGENCY DEPARTMENT
بهبود نرخ مستند سازی و ارزیابی مجدد : یک طرح ارتقاء کیفی در بخش آمادگی دانشگاه علوم پزشکی-2020
ED pain score reassessment and documentation rates were drastically low according to sampled data from the St. Margaret Hospital Emergency Department leading to difficult pain management encounters for clinicians. The purpose of this project was to improve pain score reassessment rates in ED patients who were discharged with extremity pain. Methods: This project was an 8-month, prepostinterventional (preintervention: September-November 2018, intervention: December 2018-January 2019, and postintervention: February-April 2019) quality improvement project that took place in a community hospital emergency department. Emergency nurses participated in 6 focus groups, allowing for the creation of focus group-themed interventions at the request of the nursing staff. Daily audits of pain reassessment and documentation rates for individual nurses took place during the month of January 2019. In addition, a weekly newsletter was created and reported the ED pain reassessment and documentation rates. Results: All patient encounters (581) were reviewed over the 8-month period. Baseline pain score reassessment and documentation rates were 36.2% (confidence interval, 30.3%-42.3%) in the emergency department. Pain reassessment and documentation rates increased to 62.3% (confidence interval, 56.8%-67.6%) during the 3-month postintervention period. Discussion: Implementing daily audits and weekly newsletters that created transparency of individual and group performances increased pain score reassessment and documentation rates.
Key words: Pain reassessment | Pain documentation | Practice improvement | Quality improvement | Pain management
Energy costs information in manufacturing companies: A systematic literature review
اطلاعات مربوط به هزینه های انرژی در شرکت های تولیدی: بررسی منظم ادبیات-2020
Accurate, detailed, and up-to-date information on energy costs is crucial for energy management in manufacturing companies. Yet, to what extent is such energy costs information actually available and used? This study reviews empirical information provided in papers published in research journals about the availability and use of energy costs information in manufacturing companies. The study aims to focus both on energy-intensive companies as well as non-energy-intensive companies, and also to distinguish between the practices of small and medium-size enterprises (SMEs) vs. large companies. The literature review covers 23 journals in the fields of business, accounting, energy, and engineering, leading to the final sample that includes 51 papers for the analysis. Most studies in this sample concern energyintensive and large companies. The most striking result is that with only few exceptions, almost no studies provide a nuanced description of how measuring and allocating energy costs is being done. For example, almost no studies investigate specific cost allocation bases, the accuracy of cost allocations, or differentiation between first-stage allocation and second-stage allocation. Nevertheless, the overall impression is that many manufacturing companies resort to imprecise methods for measuring and allocating energy costs. They seem to lack much of the cost information necessary for energy management, such as information needed for improving energy efficiency, evaluating energy efficiency improvement investments, and holding managers accountable for energy efficiency.
Keywords: Energy cost information | Energy metering | Energy cost allocation | Manufacturing companies | Energy management | Systematic literature review
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
Qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions
ارزیابی ریسک کمی و کیفی پروژه با استفاده از یک مدل توسعه یافته PMBOK تحت شرایط غیر قطعی-2020
This study presented a qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions. Accordingly, an exploratory and applied research design was employed in this study. The research sample included 15 experienced staff working in main and related positions in Neyr Perse Company. After reviewing the literature and the Project Management Body of Knowledge (PMBOK), 32 risk factors were identified and their number reduced to 17 risks using the expert opinions via the fuzzy Delphi technique run through three stages. The results of the confirmatory factor analysis showed that all risks were confirmed by the members of the research sample. Then the identified risks were structured and ranked using fuzzy DEMATEL and fuzzy ANP techniques. The final results of the study showed that the political and economic sanctions had the highest weight followed by foreign investors’ attraction and the lack of regional infrastructure.
Keywords: Project risks | Project management body of knowledge (PMBOK) | Uncertainty | Mixed qualitative and quantitative risk assessment approach | Mathematics | Probability theory | Engineering | Industrial engineering | Business
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.
Recent changes in UK medical law: implications for radiologists
تغییرات اخیر در پزشک قانونی انگلستان: پیامدهای برای رادیولوژیستها-2020
Since Lord Woolf declared in 2001 that the courts have been excessively deferential to the medical profession, there has been an incremental series of changes to the law concerning medical negligence. The most substantial changes concern consent, but significant change has also appeared regarding the concept of causation. This article reviews these changes, and points out areas of direct relevance to diagnostic and interventional radiology.
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
Challenges and recommended technologies for the industrial internet of things: A comprehensive review
چالش ها و فن آوری های پیشنهادی برای اینترنت اشیا صنعتی: مرور جامع-2020
Physical world integration with cyber world opens the opportunity of creating smart environments; this new paradigm is called the Internet of Things (IoT). Communication between humans and objects has been extended into those between objects and objects. Industrial IoT (IIoT) takes benefits of IoT communications in business applications focusing in interoperability between machines (i.e., IIoT is a subset from the IoT). Number of daily life things and objects connected to the Internet has been in increasing fashion, which makes the IoT be the dynamic network of networks. Challenges such as heterogeneity, dynamicity, velocity, and volume of data, make IoT services produce inconsistent, inaccurate, incomplete, and incorrect results, which are critical for many applications especially in IIoT (e.g., health-care, smart transportation, wearable, finance, industry, etc.). Discovering, searching, and sharing data and resources reveal 40% of IoT benefits to cover almost industrial applications. Enabling real-time data analysis, knowledge extraction, and search techniques based on Information Communication Technologies (ICT), such as data fusion, machine learning, big data, cloud computing, blockchain, etc., can reduce and control IoT and leverage its value. This research presents a comprehensive review to study state-of-the-art challenges and recommended technologies for enabling data analysis and search in the future IoT presenting a framework for ICT integration in IoT layers. This paper surveys current IoT search engines (IoTSEs) and presents two case studies to reflect promising enhancements on intelligence and smartness of IoT applications due to ICT integration.
Keywords: Industrial IoT (IIoT) | Searching and indexing | Blockchain | Big data | Data fusion Machine learning | Cloud and fog computing
Inherent laws between tetrahedral arrangement pattern and optical performance in tetrahedron-based mid-infrared nonlinear optical materials
قوانین ذاتی بین الگوی چیدمان چهار ضلعی و عملکرد نوری در مواد نوری غیر خطی مادون قرمز مبتنی بر تتراهدرن-2020
Mid-infrared (MIR) nonlinear optical (NLO) crystals are commonly used as the core devices for all-solidstate MIR lasers which play a key role in many military and civilian areas. The discovery of new MIR NLO crystals with great performance is vital for the development of relevant scientific and technology fields. In this work, we focus on the tetrahedron-based MIR NLO compounds with the chemical formula of AM- Q (A = alkali or alkaline earth metal cations except Li; M = tetra-coordinated cations; Q = S, Se, Te, P, F, Cl, Br, I), whose structural frameworks are constructed by [MQ4] tetrahedral units. These materials have attracted great attention since almost all existing MIR NLO materials with the practical application prospects belong to this category. Systematic understanding of these tetrahedron-based compounds will contribute a lot to the design and preparation of novel well-performed MIR NLO crystals. We comprehensively reviewed the reported tetrahedron-based compounds A-M-Q for the first time and revealed the inherent laws among A/M ratio, arrangement pattern of tetrahedral units and NLO performance in these compounds.
Keywords: Mid-infrared NLO materials | Tetrahedron-based compounds | Tetrahedral arrangement pattern | Structure-property relationship | Optical performance