سیستم پشتیبانی از تصمیم برای خطرات و اقدامات متقابل ایمنی جاده ای اروپا
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 32
سیستم پشتیبانی از تصمیم درباره ایمنی جاده ای اروپا (roadsafety-dss.eu) یک سیستم نوآورانه است که شواهد و مدارک دسترس پذیری را درباره گستره وسیعی از خطرات جاده ای و اقدامات متقابل امکانپذیر فراهم می کند. این مقاله پایه و اساس علمی سیستم پشتیبانی از تصمیم را توصیف می کند. ساختار موجود در سیستم پشتیبانی از تصمیم شامل (1) یک طبقه بندی که به شناسایی عوامل خطر و اقدامات متقابل آن می پردازد و آنها را به همدیگر مرتبط می کند، (2) یک مجموعه ای از مطالعات، و (3) خلاصه هایی که تاثیرات تخمین زده شده در منابع علمی را برای هر عامل و سنجه خطر خلاصه بندی می کنند و (4) یک ابزار ارزیابی کارآمدی اقتصادی (محاسبه گر E3) می شود. سیستم پشتیبانی از تصمیم در یک ابزار نوین مبتنی بر وب با فصل مشترک بسیار انسانی اجرا می شود که به کاربران اجازه می دهد تا مرور اجمالی سریعی داشته باشند یا نتایج هر مطالعه را برطبق نیازهای مخصوص آنها عمیق تر بررسی کنند.
کلیدواژه ها: اقدامات متقابل ایمنی جاده | خطرات جاده ای | سودمندی | سیستم آنلاین | مرور | هزینه – سود
|مقاله ترجمه شده|
Fake pharmaceuticals: A review of current analytical approaches
داروهای تقلبی: مروری بر روش های تحلیلی در حال حاضر-2019
Poor quality pharmaceuticals may have serious consequences for human health because of treatment failure, development of antimicrobial resistance and dramatic adverse drug reactions. This can significantly undermine consumers confidence in healthcare systems and cause an increase in healthcare costs. The vast array of analytical approaches available nowadays makes an important contribution to distinguishing between genuine and fake medicines. The scientific literature published mostly over the last decade on this subject matter was searched and the support provided by modern analytical techniques in combating falsified drugs was discussed. This survey showed that chromatography–based techniques, often in combination with mass spectrometry, have the lions share. In turn, also colorimetry, infrared spectroscopy and Raman spectroscopy appear to be rather popular approaches.
Setting up standards: A methodological proposal for pediatric Triage machine learning model construction based on clinical outcomes
تنظیم استانداردها: یک پیشنهاد روش شناختی برای ساخت مدل یادگیری ماشین تراشی کودکان براساس نتایج بالینی-2019
Triage is a critical process in hospital emergency departments (ED). Specifically, we consider how to achieve fast and accurate patient Triage in the ED of a pediatric hospital. The goal of this paper is to establish methodological best practices for the application of machine learning (ML) to Triage in pediatric ED, providing a comprehensive comparison of the performance of ML techniques over a large dataset. Our work is among the first attempts in this direction. Following very recent works in the literature, we use the clinical outcome of a case as its label for supervised ML model training, instead of the more uncertain labels provided by experts. The experimental dataset contains the records along 3 years of operation of the hospital ED. It consists of 189,718 patients visits to the hospital. The clinical outcome of 9271 cases (4.98%) wa hospital admission, therefore our dataset is highly class imbalanced. Our reported performance comparison results focus on four ML models: Deep Learning (DL), Random Forest (RF), Naive Bayes (NB) and Support Vector Machines (SVM). Data preprocessing includes class imbalance correction, and case re-labeling. We use different well known metrics to evaluate performance of ML models in three different experimental settings: (a) classification of each case into the standard five Triage urgency levels, (b) discrimination of high versus low case severity according to its clinical outcome, and (c) comparison of the number of patients assigned to each standard Triage urgency level against the Triage rule based expert system currently in use at the hospital. RF achieved greater AUC, accuracy, PPV and specificity than the other models in the dychotomic classification experiments. On the implementation side, our study shows that ML predictive models trained according to clinical outcomes, provide better Triage performance than the current rule based expert system in operation at the hospital.
Keywords: Machine learning | Emergency department | Triage | Data science | Clinical decision support systems
Perception, knowledge and attitudes of small animal practitioners regarding animal abuse and interpersonal violence in Brazil and Colombia
درک ، دانش و نگرش متخصصان حیوانات کوچک در مورد سوء استفاده از حیوانات و خشونت بین فردی در برزیل و کلمبیا-2019
Identification and report of animal abuse by veterinarians are fundamental to the promotion of animal welfare and the prosecution of this crime. Likewise, these professionals have an important responsibility to cope with the cycle of violence. This study aims to characterize the perception, knowledge, and attitudes of small animal practitioners regarding animal abuse and interpersonal violence in Brazil and Colombia. An online survey containing 27 questions was distributed to small animal practitioners of both countries. Multiple correspondence analysis (MCA) was employed to construct relationships among categorical variables and the chi-square statistic was used for testing these relationships. An important number of respondents had suspected that their patients could be victims of animal abuse (Brazil 48.1%; Colombia 64.5%). However, only a minority reported this situation to competent authorities (Brazil 32.7%; Colombia 10.8%). To receive training about veterinary forensics and/or animal welfare sciences in veterinary college was associated with identifying and denouncing animal abuse (p < .05). Deficiency in training received by veterinarians on veterinary forensic and animal welfare science in veterinary college was evident. Despite this, small animal practitioners recognize the existence of an association between animal abuse and interpersonal violence (Brazil 94.2%; Colombia 96.8%). The results highlight the need to strengthen education on animal abuse and promote the participation of veterinarians in the prosecution of this crime in Latin America.
Keywords: Veterinary education | Animal cruelty | Human-animal relationship | Companion animal maltreatment |Link theory
A systematic survey of computer-aided diagnosis in medicine: Past and present developments
مرور سیستماتیک تشخیص کمک به رایانه در پزشکی: تحولات گذشته و حال-2019
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diag- nostic decision-making process of medical experts, they can be considered as expert systems in medicine. Furthermore, CAD systems in medicine may process clinical data that can be complex and/or massive in size. They do so in order to infer new knowledge from data and use that knowledge to improve their diagnostic performance over time. Therefore, such systems can also be viewed as intelligent systems be- cause they use a feedback mechanism to improve their performance over time. The main aim of the literature survey described in this paper is to provide a comprehensive overview of past and current CAD developments. This survey/review can be of significant value to researchers and professionals in medicine and computer science. There are already some reviews about specific aspects of CAD in medicine. How- ever, this paper focuses on the entire spectrum of the capabilities of CAD systems in medicine. It also identifies the key developments that have led to today’s state-of-the-art in this area. It presents an ex- tensive and systematic literature review of CAD in medicine, based on 251 carefully selected publica- tions. While medicine and computer science have advanced dramatically in recent years, each area has also become profoundly more complex. This paper advocates that in order to further develop and im- prove CAD, it is required to have well-coordinated work among researchers and professionals in these two constituent fields. Finally, this survey helps to highlight areas where there are opportunities to make significant new contributions. This may profoundly impact future research in medicine and in select areas of computer science.
Keywords: Computer-aided diagnosis | Computer-aided detection | Expert and intelligent systems | Computerized signal analysis | Segmentation | Classification
Images of entrepreneurship: Using drawing to explore entrepreneurial experience
تصاویر کارآفرینی: استفاده از ترسیم برای کشف تجربه کارآفرینی-2019
Entrepreneurship is a generative and transformative process of altering convention where personal/ social history, assets, technologies, and trading activity are gathered in organizational form. How entrepreneurs frame this process, and are, in turn, organised by this process, constitutes the entrepreneurial experience. Typically this framing has been researched using narrative methods: how entrepreneurs tell their stories. In this paper we develop an emerging branch of inquiry challenging a sole focus on linguistic narrative in favour of accessing the experience of entrepreneurs by asking them to draw an image of their venture using pencils and paper. Drawing has long been recognised in other social science disciplines as an empirical method for eliciting indepth and latent information about complex or difficult experiences. In this paper we show some indicative drawings created by entrepreneurs, accompanied by their verbal explanations of what these drawings represent for them, and we highlight how the process was a generative exercise for the entrepreneurs. We focus on two aspects of drawing, which we refer to as “beginnings”, and “traces”, that we feel are particularly relevant to why this medium is valuable for exploring the experience of entrepreneurs.
Keywords: Entrepreneurial experience | Narratives | Drawing | Drawing methodology | Images
Evaluating solutions to the problem of false positives
ارزیابی راه حلهای مسئله مثبت کاذب-2019
A current challenge for the scientific community is the choice of appropriate policies to reduce the rate of false positives. Existing proposals differ in whether to prioritize tackling omission through transparency requirements, punishing more severe transgressions, or possibly both. We use a formal model to evaluate these possible solutions. We find that a policy that prohibitively increases the cost of ‘misdemeanor’ types of questionable research practices robustly decreases the overall rate of researcher misconduct, because the rate of ‘felonies’, such as fabrication, also decreases. Therefore proposals that aim to prevent lying by omission by enforcing reporting guidelines are likely to be effective in reducing researcher misconduct, but measures such as government audits (purported to counteract pure fraud) can backfire. Moreover, we find that an increase in the rewards of publication need not increase overall misconduct.
Keywords: Researcher misconduct | Reproducibility | False positives | Questionable research practices
Analytic network process: Academic insights and perspectives analysis
فرآیند شبکه تحلیلی: بینش دانشگاهی و تحلیل چشم اندازها-2019
Diversity multi-criteria decision-making methods have been developed to address different complex decision-making problems, and the analytic network process has been found to be one of the most effective techniques. There is an increase in the quality and quantity of publications related to the analytic network process. This detailed overview can provide the research status and development characteristics of analytic network process research and will be useful to researchers for future research directions. To achieve these goals, bibliometric techniques were used. In addition, past and present hotspots of analytic network process research were concluded, and future research trends were determined. The bibliometric analysis was carried out from various aspects including countries and regions, institutions, journals, authors, research areas, articles and author keywords based on data harvested from the Web of Science database. There were 1485 analytic network process-related publications retrieved from theWeb of Science. The results show that Expert Systems with Applications was the most productive journal publishing articles in analytic network process research (118); its number of publications has decreased dramatically since 2013, while Journal of Cleaner Production has shown an upward trend in recent years and ranks second with 47 publications. The most collaborative country is the United States. Taiwan takes a leading position in analytic network process research with 436 publications (29.36%), and National Chiao Tung University, which is located in Taiwan, produced the most articles and has gained the highest h-index (28). The major hot topics that employ analytic network process are sustainability, environmental management and supply chain management. These topics may continue to attract more attention in the future.
Keywords: Analytic Network Process | Web of science | Bibliometrics | Hot topics | Sustainability | Environmental management | Supply chain management
Conceptual structure and perspectives on entrepreneurship education research: A bibliometric review
ساختار مفهومی و دیدگاه های مربوط به تحقیقات آموزش کارآفرینی: یک مرور کتابشناختی-2019
This study aims to review the field of Entrepreneurship Education (EE). The review examines 325 scientific articles published in refereed scientific journals from 1987 to 2017. The SciMat software was used to conduct an analysis of performance indicators and science mapping visualizations. The performance analysis results identified some of the field’s most active and influential articles, journals, and authors. The science mapping visualization of co-word analysis results revealed EE research evolution. In general, we found that EE research has evolved from EE as part of an economic development strategy to the EE academic perspective. Furthermore, research themes showed that students, rather than teachers, have become the main agents of the educational process. The results of this bibliometric analysis enhance understanding of the evolution of EE research with a global overview of the relevant literature and its authors.
Keywords: Entrepreneurship education | Entrepreneurial intention | Entrepreneurial learning | Bibliometrics | SciMat
Reputational penalties for environmental violations: A pure and scientific replication study
مجازات اعتباری برای تخلفات زیست محیطی: مطالعه تکرار خالص و علمی-2019
Our pure replication of Karpoff et al. (2005) confirms their findings of negative abnormal returns andinsignificant reputational penalties following the announcement of environmental violations in the lasttwo decades of the twentieth century. A scientific replication using more recent data finds a decrease inthe magnitude of negative abnormal returns but similarly insignificant reputational penalties on average.While mean legal penalties for violations are higher in the more recent period, these penalties havedecreased relative to firms’ market valuations.
Keywords:Environmental violations | Reputational penalties | Enforcement