دانلود و نمایش مقالات مرتبط با Performance::صفحه 1
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نتیجه جستجو - Performance

تعداد مقالات یافته شده: 3434
ردیف عنوان نوع
1 بازاریابی جاذبه ای دیجیتال: اندازه گیری عملکرد اقتصادی تجارت الکترونیکی خواروبار در اروپا و آمریکا
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 30
این تحقیق به بررسی رابطه هزینه-نتیجه اقدامات بازاریابی جاذبه ای مورد استفاده تجارت الکترونیکی خواروبار می پردازد. این تحلیل بر اساس به کارگیری مدل درفمن و استینر (1954) برای بودجه تبلیغات بهینه است که مولفین آن را با بازاریابی دیجیتال تطبیق می دهند و با تحلیل آماری تجاری تایید میکنند. با توجه به 29 شرکت عمده در شش کشور در افق زمانی شش سال، تحلیل ترکیبی تکنیک های بهینه سازی موتور جستجو و بازاریابی موتور جستجو هدف جذب کارکنان به صفحات وب شرکت ها را دنبال می کند. نتایج تایید می کند که تجارت الکترونیکی بازاریابی جاذبه ای دیجیتال را بهینه سازی می کند. تفاوت ها بسته به نوع فرمت و سطح کشور فرق دارند.
واژگان کلیدی: بازاریابی جاذبه ای | بازاریابی دیجیتال | تجارت الکترونیک | خرده فروشی | عملکرد اقتصادی | بهینه سازی سرمایه گذاری بازاریابی.
مقاله ترجمه شده
2 DEGAN : شبکه های مولد متخاصم غیر متمرکز
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 9 - تعداد صفحات فایل doc فارسی: 23
در این مطالعه، یک چارچوب توزیع شده و غیرمتمرکز از شبکه های مولد متخاصم (GAN) بدون تبادل داده های آموزشی پیشنهاد شد. هر گره شامل مجموعه ی از داده محلی ، یک تفکیک کننده کننده و یک مولد است که فقط گرادیان ژنراتور آن با سایر گره ها به اشتراک گذاشته می شوند. در این مقاله ، تکنیک توزیع جدید معرفی می شود که در آن کارکنان مستقیماً با یکدیگر ارتباط برقرار می کنند و هیچ گره مرکزی وجود ندارد. نتایج تجربی ما در مجموعه داده های معیار ، عملکرد و دقت تقریباً یکسانی را در مقایسه با چارچوب های GAN متمرکز موجود نشان می دهد. چارچوب پیشنهادی به عدم یادگیری غیرمتمرکز برای GAN ها می پردازد.
کلمات کلیدی: یادگیری عمیق | شبکه های مولد متخاصم | یادگیری ماشین توزیع شده | معماری غیرمتمرکز
مقاله ترجمه شده
3 Know when to fold ‘em: An empirical description of risk management in public research funding
بدانید چه موقع برابر شوید: شرح تجربی مدیریت ریسک در بودجه تحقیق عمومی-2020
Public research funding programs typically make grants with minimal intervention by program staff, rather than using a hands-on approach to project management, which is more common in the private sector. In contrast, program staff at the US Department of Energys Advanced Research Projects Agency – Energy (ARPA-E) are given a set of real options with which to manage funded projects: abandon, contract or expand project budgets or timelines. Using internal data from ARPA-E, we show that active project management enables risk mitigation across a portfolio of research projects. We find that program staff modify projects frequently, especially project timelines, and these changes are more sensitive to poor performance than to strong performance. We also find that projects with a shortened timeline or reduced budget are less likely to generate short-term research outputs, compared to those of ultimately similar size. This evidence suggests that the practice of active project management, when combined with high upfront risk tolerance, can be used to enhance the productivity of missionoriented public research funding.
Keywords: R&D funding | Project management | Real options | Managerial flexibility
مقاله انگلیسی
4 Extending Fitts’ law in three-dimensional virtual environments with current low-cost virtual reality technology
گسترش قانون Fitts در محیط های مجازی سه بعدی با فناوری واقعیت مجازی کم هزینه فعلی-2020
Virtual reality (VR) interfaces require users to perform three-dimensional reaching and pointing movements to interact with objects positioned within the users arms reach. However, there has been limited work that has evaluated the applicability of established models of human motor control to model performance of these tasks in 3D virtual reality environments using current low-cost technologies. In this study, a 3D discrete pointing task using the Oculus Rift system was used to explore potential influences on movement in VR and to account for these influences in a new formulation of Fitts’ law. Target size and distance from the starting point of movement were systematically varied to generate a broad range of index of difficulty (ID) values. Target locations were specified using a spherical coordinate system in which inclination angle corresponded to the pitch of the movement axis with respect to the starting point of movements and azimuth angle corresponded to the roll of the movement axis with respect to the horizontal plane. In line with previous work, we observed that target size, radial distance, and inclination angle had a significant effect on movement time. The effect of inclination angle varied with target size, which suggests that target size affected depth estimation. Significant target characteristics and interaction effects were used to develop an extended Fitts’ law model, which accounted for 64.5% of the variation in movement times. Comparisons to other Fitts’ law models revealed that models accounting for the effects of target depth improved predictive power relative to the traditional Fitts’ law formulation. Together, these findings support the value of extending Fitts’ law models to account for domain-specific constraints in VR environments. We discuss these results in the context of previous work examining HMD display deficiencies and discrete 3D pointing tasks, and suggest several directions for future work.
Keywords: Fitts’ law | Virtual reality | Oculus Rift | Depth perception | Stereoscopic display
مقاله انگلیسی
5 Identification and differentiation of commercial and military explosives via high performance liquid chromatography – high resolution mass spectrometry (HPLC-HRMS), X-ray diffractometry (XRD) and X-ray fluorescence spectroscopy (XRF): Towards a forensic substance database on explosives
شناسایی و تمایز مواد منفجره تجاری و نظامی از طریق کروماتوگرافی مایع با کارایی بالا - طیف سنجی جرمی با وضوح بالا (HPLC-HRMS) ، پراش سنجی اشعه ایکس (XRD) و طیف سنجی فلورسانس اشعه ایکس (XRF): به سمت پایگاه داده مواد پزشکی قانونی در مورد مواد منفجره-2020
The identification of confiscated commercial and military explosives is a crucial step not only in the uncovering of distribution pathways, but it also aids investigating officers in criminal casework. Even though commercial and military explosives mainly rely on a small number of high-energy compounds, a great variety of additives and synthesis by-products can be found that can differ depending on the brand, manufacturer and application. This makes the identification of commercial and military explosives based on their overall composition a promising approach that can be used to establish a pan-European Forensic Substance Database on Explosives. In this work, three analytical techniques were employed to analyze 36 samples of commercial and military explosives from Germany and Switzerland. An HPLC-HRMS method was developed, using 27 analytes of interest that encompass high-energy compounds, synthesis by-products and additives. HPLCHRMS and XRD were used to gather and confirm molecular information on each sample and XRF analyses were carried out to gain insight on the elemental composition. Combining the results from all three techniques, 41 different additives could be identified as being diagnostic analytes and all samples showed a unique analytical fingerprint, which allows for a differentiation of the samples. Therefore, this work presents a set of methods that can be used as a foundation for the creation and population of a database on explosives that enables the assigning of specific formulations to certain brands, manufacturers and countries of origin.
Keywords: HPLC-HRMS | Powder XRD | XRF | Explosives | Commercial explosives | Military explosives
مقاله انگلیسی
6 Industrial smart and micro grid systems e A systematic mapping study
سیستم های هوشمند و ریز شبکه صنعتی و یک مطالعه نقشه برداری منظم-2020
Energy efficiency and management is a fundamental aspect of industrial performance. Current research presents smart and micro grid systems as a next step for industrial facilities to operate and control their energy use. To gain a better understanding of these systems, a systematic mapping study was conducted to assess research trends, knowledge gaps and provide a comprehensive evaluation of the topic. Using carefully formulated research questions the primary advantages and barriers to implementation of these systems, where the majority of research is being conducted with analysis as to why and the relative maturity of this topic are all thoroughly evaluated and discussed. The literature shows that this topic is at an early stage but already the benefits are outweighing the barriers. Further incorporation of renewables and storage, securing a reliable energy supply and financial gains are presented as some of the major factors driving the implementation and success of this topic.
Keywords: Industrial smart grid | Industrial micro grid | Systematic mapping study | Strategic energy management | Industrial facility optimization | Renewable energy resources
مقاله انگلیسی
7 Towards optimal control of air handling units using deep reinforcement learning and recurrent neural network
به سمت کنترل بهینه واحدهای مدیریت هوا با استفاده از یادگیری تقویتی عمیق و شبکه عصبی بازگشتی -2020
A new generation of smart stormwater systems promises to reduce the need for new construction by enhancing the performance of the existing infrastructure through real-time control. Smart stormwater systems dynamically adapt their response to individual storms by controlling distributed assets, such as valves, gates, and pumps. This paper introduces a real-time control approach based on Reinforcement Learning (RL), which has emerged as a state-of-the-art methodology for autonomous control in the artificial intelligence community. Using a Deep Neu- ral Network, a RL-based controller learns a control strategy by interacting with the system it controls - effectively trying various control strategies until converging on those that achieve a desired objective. This paper formulates and implements a RL algorithm for the real-time control of urban stormwater systems. This algorithm trains a RL agent to control valves in a distributed stormwater system across thousands of simulated storm scenarios, seeking to achieve water level and flow set-points in the system. The algorithm is first evaluated for the control of an individual stormwater basin, after which it is adapted to the control of multiple basins in a larger watershed (4 km 2 ). The results indicate that RL can very effectively control individual sites. Performance is highly sensitive to the reward formulation of the RL agent. Generally, more explicit guidance led to better control performance, and more rapid and stable convergence of the learning process. While the control of multiple distributed sites also shows promise in reducing flooding and peak flows, the complexity of controlling larger systems comes with a number of caveats. The RL controller’s performance is very sensitive to the formulation of the Deep Neural Network and requires a significant amount of computational resource to achieve a reasonable performance en- hancement. Overall, the controlled system significantly outperforms the uncontrolled system, especially across storms of high intensity and duration. A frank discussion is provided, which should allow the benefits and draw- backs of RL to be considered when implementing it for the real-time control of stormwater systems. An open source implementation of the full simulation environment and control algorithms is also provided.
Keywords: Real-time control | Reinforcement learning | Smart stormwater systems
مقاله انگلیسی
8 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
مقاله انگلیسی
9 Performance assessment of coupled green-grey-blue systems for Sponge City construction
ارزیابی عملکرد سیستم های سبز و خاکستری-آبی همراه برای ساخت و ساز شهر اسفنجی-2020
In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source, grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal. However, the current approaches for assessing the performance of Sponge City construction are confined to green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river system models are coupled to provide quantitative simulation evaluations of a number of indicators of landbased and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement. This framework can be applied to Sponge City projects to achieve the enhancement of urban water management.
Keywords: Low impact development | Sponge City | Green-grey-blue system | Performance assessment | TOPSIS
مقاله انگلیسی
10 توسعه معیاری برای بازاریابی کارآفرینانه: آشکارسازی چارچوب درونی آن و پیش بینی عملکرد
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 34
بازاریابی کارآفرینانه (EM) یک مفهوم بازاریابی برای شرکت هایی در نظر گرفته می شود که تلاش می کنند برنامه های بازاریابی کارآفرینانه، بازار محور و همچنین مشتری مدار را ایجاد کنند، که این برنامه ها در شرایط محدودیت های منابع بخوبی عمل کنند. با این وجود، حتی پس از گذشت سه دهه از پیدایش آن، محققان همچنان بر اعتبارسنجی ابعاد منحصربفرد مفهوم EM (چارچوب خارجی آن) تمرکز می کنند، اما نمی پرسند که نقطه مشترک این ابعاد چیست(چارچوب داخلی آن). این مقاله با استفاده از 1156 شرکت نمونه، یک معیار معتبر ایجاد می کند و تاثیر آن بر عملکرد شرکت را تحلیل می کند. نتایج نشان می دهند که EM شامل سه بعد بهم پیوسته می باشد: 1) تغییر محور، 2) خود گردان سازی، و 3) ریسک پذیر است که تاثیر مثبتی بر عملکرد شرکت دارند واژگان کلیدی: بازاریابی کارآفرینانه | ایجاد معیار | جهت گیری کارآفرینانه | جهت گیری مشتری | بهره برداری از منابع | بازار محور
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