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نتیجه جستجو - لجستیک

تعداد مقالات یافته شده: 68
ردیف عنوان نوع
1 Performance analysis of machine learning algorithm of detection and classification of brain tumor using computer vision
تحلیل عملکرد الگوریتم یادگیری ماشین تشخیص و طبقه بندی تومور مغزی با استفاده از بینایی کامپیوتر-2022
Brain tumor is one of the undesirables, uncontrolled growth of cells in all age groups. Classification of tumors depends no its origin and degree of its aggressiveness, it also helps the physician for proper diagnosis and treatment plan. This research demonstrates the analysis of various state-of-art techniques in Machine Learning such as Logistic, Multilayer Perceptron, Decision Tree, Naive Bayes classifier and Support Vector Machine for classification of tumors as Benign and Malignant and the Discreet wavelet transform for feature extraction on the synthetic data that is available data on the internet source OASIS and ADNI. The research also reveals that the Logistic Regression and the Multilayer Perceptron gives the highest accuracy of 90%. It mimics the human reasoning that learns, memorizes and is capable of reasoning and performing parallel computations. In future many more AI techniques can be trained to classify the multimodal MRI Brain scan to more than two classes of tumors.
keywords: هوش مصنوعی | ام آر آی | رگرسیون لجستیک | پرسپترون چند لایه | Artificial Intelligence | MRI | Logistic regression | OASIS | Multilayer Perceptron
مقاله انگلیسی
2 A detailed MILP formulation for the optimal design of advanced biofuel supply chains
یک فرمول دقیق MILP برای طراحی بهینه زنجیره های پیشرفته تأمین سوخت زیستی-2021
The optimal design of a biomass supply chain is a complex problem, which must take into account multiple interrelated factors (i.e the spatial distribution of the network nodes, the efficient planning of logistics activities, etc.). Mixed Integer Linear Programming has proven to be an effective mathematical tool for the optimization of the design and the management strategy of Advanced Biofuel Supply Chains (ABSC). This work presents a MILP formulation of the economical optimization of ABSC design, comprising the definition of the associated weekly management plan. A general modeling approach is proposed with a network structure comprising two intermediate echelons (storage and conversion facilities) and accounts for train and truck freight transport. The model is declined for the case of a multi- feedstock ABSC for green methanol production tested on the Italian case study. Residual biomass feed- stocks considered are woodchips from primary forestry residues, grape pomace, and exhausted olive pomace. The calculated cost of methanol is equal to 418.7 V/t with conversion facility cost accounting for 50% of the fuel cost share while transportation and storage costs for around 15%. When considering only woodchips the price of methanol increases to 433.4 V/t outlining the advantages of multi-feedstock approach.© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-NDlicense (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Residual biomass | Advanced biofuels | Supply chain design | Logistics network | MILP | Optimization
مقاله انگلیسی
3 Factors associated with knowledge towards postoperative nausea and vomiting management among health professionals in referral Hospitals of Northwest Ethiopia: A multi-center cross-sectional study
عوامل مرتبط با دانش به سوی تهوع پس از عمل و مدیریت استفراغ در میان متخصصان بهداشتی در بیمارستان های ارجاع شمال غربی اتیوپی:یک مطالعه چند منظوره مقطعی-2021
Background: Knowledge of health care professionals on postoperative nausea and vomiting (PONV) and anti- emetic prescription trends affects patient’s outcome after surgery and anesthesia and also patient and family satisfaction. Hence, knowing the knowledge status of health professionals towards PONV management is vital for the optimal care of surgical patients. Therefore, the study aimed to assess the knowledge and factors associated with PONV management among health professionals in referral hospitals of Northwest Ethiopia. Methods: An institutional based cross-sectional study was conducted on 407 health care professionals from March 1 to 30, 2019. A Simple random sampling technique was used to select the study participants. Both bivariable and multivariable logistic regression analysis were used to identify factors associated with the knowledge level of health professionals on PONV management. In the multivariable analysis, variables with a p-value <0.05 were considered statistically significant. Results: In this study, about 52.8% (95% CI: 47.9, 57.2) of the participants had good knowledge of PONV management. Being male (AOR = 1.95; 95% CI: 1.20, 3.17), Physician (AOR = 5.36; 95% CI: 2.20, 13.5), Anesthetist (AOR = 3.88; 95% CI: 1.66, 9.08), and taking training on PONV management (AOR = 5.32; 95%CI: 1.58, 17.89) were positively associated with good knowledgeable of health professionals about PONV management. Conclusion: and recommendation: More than half of health care professionals who are working in the periop- erative sites of the referral hospitals had good knowledge about the PONV management. Being male, Physician, Anesthetist and taking in-service training on PONV management were significantly affecting the knowledge level of health professionals on PONV management. Thus, providing regular in-service training on PONV manage- ment, especially for physician and anesthetist is highly recommended.
keywords: تهوع و استفراغ پس از عمل | دانش | متخصصین سلامت | اتیوپی | Postoperative nausea and vomiting | Knowledge | Health professionals | Ethiopia
مقاله انگلیسی
4 Cybersecurity knowledge and skills for port facility security officers of international seaports_ Perspectives of IT and security personnel
دانش و مهارت های امنیتی سایبری برای افسران امنیتی تأسیسات پورت از دریاها بین المللی، دیدگاه های IT و پرسنل امنیتی-2021
Cyberattacks on worldwide port facilities have highlighted the urgent need for port facility security officers (PFSOs) to upgrade their cybersecurity knowledge and skills. This study used the survey data from all international container ports in Thailand and analyzed the results from two perspectives, i.e., IT and security officers. Based on 73 responses, cybersecurity knowledge and skill would become essential for PFSOs than ever before because the port digitalization and automation would shape the PFSOs career to a technically- oriented specialist rather than a multi-skilled generalist. Furthermore, the responsibilities of PFSOs would extend to cover cyber risk management, which enables them to prevent the digital port facilities from emerging cyber threats. Therefore, they should learn how to incorporate the existing risk management process with cyber risk management and cybersecurity knowledge because these would be the foundation for PFSOs to practice cybersecurity skills. At the end of the learning process, PFSOs could also gain cyber- security competence once they have mature knowledge and skill, which would be the vital element of port security hygiene. © 2021 The Authors. Production and hosting by Elsevier B.V. on behalf of The Korean Association of Shipping and Logistics, Inc. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). CC_BY_NC_ND_4.0
keywords: دانش سایبری | مهارت های سایبری | افسران امنیتی تسهیلات پورت | بنادر کانتینر بین المللی | Cybersecurity knowledge | Cybersecurity skills | Port facility security officers | International container ports
مقاله انگلیسی
5 ارتباط بین نوع زایمان و افسردگی پس از آن (PPD)
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 21
پیش زمینه : افسردگی پس از زایمان (PPD) با پیامدهای نامطلوب سلامتی از جمله خودکشی مادران همراه است. نوع زایمان از جمله ریسک فاکتورهای مربوط به افسردگی پس از زایمان (PPD) می باشد اما مطالعات گسترده ای در زمینه ارتباط بین نوع زایمان با افسردگی پس از زایمان صورت نگرفته است. هدف از این مطالعه بررسی ارتباط بین نوع زایمان با افسردگی پس از آن بین یک و شش ماه پس از زایمان می باشد.
روش ها : در یک مطالعه سراسری بر روی 89954 مادر با تولد تک قلو زنده، ما ارتباط بین نوع زایمان و خطرات افسردگی پس از زایمان ( PPD ) را بررسی کردیم. PPD با استفاده از مقیاس افسردگی پس از زایمان ادینبورگ (≥13) در 1 و 6 ماه پس از زایمان ارزیابی شد. نسبت احتمال ( Odds ratios (ORs) ) با فاصله اطمینان ( confidence intervals (CIs) ) 95% از افسردگی پس از زایمان ( PPD ) با استفاده از رگرسیون لجستیک (logistic regression ) چند متغیره پس از تعدیل عوامل فیزیکی، اجتماعی-اقتصادی و روانی قبل از تولد محاسبه شد.
نتایج : از میان 89954 زن , 3.7% در ماه اول پس از زایمان و 2.8% در ماه ششم پس از زایمان دارای افسردگی بودند. در مقایسه با زایمان طبیعی واژینال بدون کمک, زایمان به شکل سزارین به شکل بارزی با افسردگی در ماه اول همراه بود اما در ماه ششم به این شکل نبود و ORهای تعدیل شده به ترتیب 1.10 (95% CI، 1.00-1.21) و 1.01 (95% CI، 0.90-1.13) بودند.
افسردگی در ماه اول در زنانی که پریشانی روانی در دوران بارداری داشتند مشهود بود (OR تعدیل شده 1.15؛ 95% فاصله اطمینان (CI)، 1.03-1.28) اما ارتباط مشاهده شده پس از سازگار شدن مادر با موضوع با روش تغذیه نوزاد کاهش یافت.
نتیجه گیری : مادرانی که در دوران بارداری مشکلات روانی داشته اند و مادرانی که با روش سزارین زایمان کرده اند در معرض ابتلا به به افسردگی پس از زایمان می باشند.
کلمات کلیدی: سزارین | افسردگی پس از زایمان | پریشانی روانی | شیردهی | مطالعه آینده نگر
مقاله ترجمه شده
6 Resilient regional food supply chains and rethinking the way forward: Key takeaways from the COVID-19 pandemic
زنجیره های تأمین مواد غذایی منطقه ای انعطاف پذیر و بازنگری در مسیر پیش رو: اقداماتی اساسی از بیماری همه گیر COVID-19-2021
Context: The U.S. food supply system relies heavily on vertically-integrated food supply chains (FSCs), which leverage large-scale production, streamlined operations, and centralized planning and control to provide consumers with a consistent supply of food. However, these FSCs were seriously disrupted upon the outbreak of the COVID-19 pandemic in spring 2020. During the height of the crisis, they were slow to respond to production system failures and sudden and widespread changes in consumer demand. By contrast, many regionalized food supply chains (RFSCs) proved to be adaptive and responsive to changes in demand and delivery requirements, quickly pivoting to distribute products directly to consumers safely.
Objective: The objective of this research is to explore how RFSCs can improve the resilience of the U.S. food supply system in the face of large-scale disruptions like the COVID-19 crisis. In particular, this research seeks to gain a greater understanding of how RFSCs can leverage logistics best practices for efficient and reliable distribution to consumers in normal times and during disasters.
Methods: This study presents seven case studies of RFSCs in Texas and Iowa that adopted logistics best practices to enable them to provide their customers with convenient and safe purchasing mechanisms during the COVID- 19 emergency. A description of how the strategies adopted by each participant promote the achievement of the United Nations Sustainable Development goals is provided.
Results and conclusions: The successes experienced by these farmers and distributors at the height of the COVID-19 pandemic were a consequence of their willingness to adopt new distribution and logistics strategies. Collaboration among RFSC actors was a particularly effective strategy, as well as the adoption of scale- appropriate information and communication technologies, which helped to facilitate collaboration. Further, these case studies demonstrate how improved logistics performance allowed RFSCs to contribute to the health and well-being of their communities in a time of need.
Significance: These case studies demonstrate the potential of RFSCs to support a resilient and socially-sustainable food system that communities can rely on, even in the face of a major disruption like COVID-19. The adoption of logistics best practices helped these RFSCs to develop new organizational strengths that will likely support sustainable development in their communities after the crisis ends.
Keywords: UN Sustainable Development Goals | Regional food supply chains | Resilience | COVID-19 | Logistics best practices | Case studies
مقاله انگلیسی
7 An integrated production-logistics-crop rotation planning model for sugar beet supply chains
یک مدل برنامه ریزی تولید-لجستیک و چرخش محصول برای زنجیره های تامین چغندر قند-2021
This paper presents an integrated strategic-tactical planning model for the sugar beet supply chain problem. The model includes the critical agricultural and industrial decisions coupled with the transportation of crops by capacitated vehicles from farms to the processing facilities. In the agricultural stage, the proposed model is used to analyze both agronomic and operational constraints for achieving a sustainable farming system through feasible strategic crop rotation plans. These plans integrate crop sequences with temporal and spatial variations while considering the known seasonal demand. The agricultural decisions involve crops planting and harvesting decisions to fulfill both fresh produce crops and processing demands. In the industrial stage, the key decisions include aggregate production plans for processing the harvested beet, as well as managing the shipping and storage of these agro-materials in the production facility. In this paper, a binary integer programming model is formulated with the objective of minimizing the overall operational cost including transportation and inventory of processed and non-processed beets. A unique time dimension was added to the planning horizon to allow crop rotation planning between different cropping seasons. A realistic case is used to test the formulated model and elaborate its complexity.
Keywords: Agro-food supply chain | Agricultural planning | Crop rotation planning | Linear programming
مقاله انگلیسی
8 Supply Chain Network Design Considering Customer Psychological Behavior-A 4PL Perspective
طراحی شبکه زنجیره تأمین با در نظر گرفتن رفتار روانشناختی مشتری-دیدگاه 4PL-2021
From the perspective of Fourth Party Logistics, a novel supply chain network design problem considering customer psychological behavior is proposed in this paper. First, we calculate the minimum cost of the supply chain network design in Fourth Party Logistics when the demand of customers is fully satisfied. In the shortage of the investment in the process of supply chain network design, the demand of customers can be partially satisfied. Then, customer psychological behavior is considered to maximize the value function of customer satisfaction under cost constraint. After introducing the definitions of the psychological reference point and the service level for customers based on the prospect theory, we formulate a non-linear integer programming model for Fourth Party Logistics network design problem. Since the objective function of the proposed model is non-linear, an approximation linearization method is introduced to adjust the proposed model to be an equivalent linear model. Numerical experiments are designed to justify the effectiveness of the proposed method. Through a thorough analysis on customer psychological behavior, it can be seen that customers tend to be more risk-averse for gains than risk-seeking for losses in Fourth Party Logistics supply chain network design. Moreover, valuable investment insights are recapitulated. This proposed method provides an effective tool for a Fourth Party Logistics provider to give reasonable suggestions to an investor in Fourth Party Logistics supply chain network design. Furthermore, we extended the basic model of 4PL supply chain network design considering customer satisfaction with multiple commodities and provided a solution method based on greedy adding heuristic to further reduce the calculation time for large scale cases.
Key words: Fourth Party Logistics | Supply Chain Network Design | Psychological Behavior | Customer Satisfaction | Approximation Linearization
مقاله انگلیسی
9 Predictors of nurses attitudes and knowledge towards pain management in Italy: A cross-sectional study in the hospital settings
پیش بینی کننده نگرش پرستاران و دانش نسبت به مدیریت درد در ایتالیا:یک مطالعه مقطعی در تنظیمات بیمارستان-2021
Introduction: Pain is multidimensional, and as such it is the chief reason patients require urgent health care services. If inadequately assessed and untreated, pain may negatively impact on the quality of life of the patient. Pain management is an essential part of Nursing. The aim to this study is to examine the level of knowledge and attitudes with regard to pain among Italian nurses who work in clinical settings. Methods: The Ferrell and McCaffery’s Knowledge and Attitudes Survey Regarding Pain was distributed to 266 nurses employed in one specialized hospital in Rome, Italy. The staff in the survey work in three different set- tings: the intensive care unit, the sub-intensive care unit, and an ordinary ward. Descriptive statistics were employed and a logistic regression model was performed to evaluate the factors that may influence the attitude and knowledge of care providers. Results: 49.6% of the sample correctly answered items about attitudes, 47.4% about knowledge, and 36.5% about assessment. The results show that the odds ratio of developing positive attitudes towards pain was 1.76 times higher in nurses employed in the sub-intensive care unit than in other settings. There are no statistically sig- nificant associations of knowledge between setting, sex or education. Conclusions: Our survey revealed a limited overall level of knowledge and attitudes with regards to pain man- agement among nurses. Implementing specific training for health professionals, starting with academic educa- tion, is therefore a priority. Further research is needed on a larger sample of Italian nurses. Key practice points services. What do we already know about this subject? • Pain is universal chief reason patients require urgent health care • Pain management is an essential part of Nursing. What does our study add to the already existing information • Our survey revealed and confirmed a limited overall level of knowledge and attitudes with regards to pain management among Italian nurses. • There are no statistically significant associations of knowledge • It is plausible that occur implementing specific training for nurses, between setting, sex or education. starting with academic education, and master degree.
keywords: نگرش های | دانش | مدیریت درد | پرستاری | Attitudes | Knowledge | Pain management | Nursing | KASRP
مقاله انگلیسی
10 پیش بینی قیمت بیت کوین با استفاده از یادگیری ماشین: یک رویکر برای مهندسی ابعاد نمونه
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 32
پس از فراز و فرودهای قیمت های ارزهای رمزنگاری شده در سال های اخیر، بیت کوین به صورت فزاینده ای به عنوان یک دارایی برای سرمایه گذاری در نظر گرفته شده است. به خاطر ماهیت بسیار بی ثبات قیمت بیت کوین، لازم است تا پیش بینی های مناسبی صورت گیرد تا، بر اساس آن، بتوان در مورد سرمایه گذاری تصمیم گیری نمود. با وجودی که تحقیقات جاری برای پیش بینی دقیق تر قیمت بیت کوین از یادگیری ماشین استفاده کرده اند، تعداد اندکی از آنها به امکان استفاده از تکنیک های مختلف مدل سازی برای نمونه هایی با ساختار داده ای و ویژگی های بعدی مختلف توجه کرده اند. به منظور پیش بینی بهای بیت کوین در فرکانس های مختلف با استفاده از تکنیک های یادگیری ماشین، ابتدا قیمت بیت کوین را بر اساس قیمت روزانه و قیمت فرکانس بالا طبقه بندی می کنیم. مجموعه ای از ویژگی های با ابعاد بالا از جمله دارایی و شبکه، معاملات و بازار، توجه و قیمت لحظه ای طلا برای پیش بینی قیمت روزانه بیت کوین استفاده می شود، در حالی که ویژگی های اصلی تجارت که از تبادل ارز رمزنگاری شده حاصل شده اند، برای پیش بینی قیمت در فواصل 5 دقیقه ای استفاده می شوند. روشهای آماری شامل رگرسیون لجستیک و آنالیز افتراقی خطی برای پیش بینی قیمت روزانه بیت کوین با ویژگی های ابعاد بالا، به دقت 66٪ رسیده و از الگوریتم های یادگیری پیچیده تر ماشین پیشی می گیرند. در مقایسه با نتایج مبنا برای پیش بینی قیمت روزانه، با بالاترین دقت در روش های آماری و الگوریتم های یادگیری ماشینی، به ترتیب 66٪ و 3/65٪، به عملکرد بهتری دست پیدا می کنیم. مدلهای یادگیری ماشینی، شامل جنگل تصادفی ،XGBoost، آنالیز افتراقی درجه دو، ماشین بردار پشتیبان و حافظه کوتاه مدت بلند برای پیش بینی قیمت 5 دقیقه ای بیت کوین که دقت آنها به 67.2% رسیده است، از روشهای آماری بهتر هستند. بررسی ما در مورد پیش بینی قیمت بیت کوین را می توان مطالعه ای مقدماتی در مورد اهمیت ابعاد نمونه در تکنیک های یادگیری ماشین در نظر گرفت.
کلمات کلیدی: مهندسی ابعاد نمونه | اصل Occam’s Razor | پیش بینی قیمت بیت کوین | الگوریتم های یادگیری ماشین
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