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

تعداد مقالات یافته شده: 33
ردیف عنوان نوع
1 Linking big data analytical intelligence to customer relationship management performance
پیوند دادن هوش تحلیلی داده های بزرگ با عملکرد مدیریت ارتباط با مشتری-2020
This study investigates the driving forces of a firm’s assimilation of big data analytical intelligence (BDAI) and how the assimilation of BDAI improve customer relationship management (CRM) performance. Drawing on the resource-based view, this study argues that a firm’s data-driven culture and the competitive pressure it faces in the industry motivate a firm’s assimilation of BDAI. As a firm resource, BDAI enables an organization to develop superior mass-customization capability, which in turn positively influences its CRM performance. In addition, this study proposes that a firm’s marketing capability can moderate the impact of BDAI assimilation on its mass- customization capability. Using survey data collected from 147 business-to-business companies, this study find ssupport for most of the hypotheses. The findings of this study uncover compelling insights about the dynamics involved in the process of using BDAI to improve CRM performance.
Keywords: Big data | Data-driven culture | Competitive pressures | Mass customization | Marketing capability | CRM performance
مقاله انگلیسی
2 Managing the “backend” of LIS research projects: A project management perspective
مدیریت "بخش انتهایی" پروژه های تحقیقاتی LIS: چشم انداز مدیریت پروژه-2020
There is very little guidance in library and information science (LIS) literature about how researchers should manage the scope, time, costs, quality, human resources, communications, and risks associated with LIS research projects. To fill this gap, researchers tested the utility of project management principles (PMP) for planning and managing a project designed to enhance the information, digital, and financial literacy of the people earning less than $2 per day in India. The customization of PMP through 29 mechanisms and 60 action items was used to conduct focus groups and in-person surveys with over 150 participants, in their native language, at 10 public libraries. PMP were most helpful for managing risks (13 solutions), communications (11 solutions), and human resources (10 solutions) of the project and treating participants ethically. PMP developed in the West were helpful before, during, and after data collection in the LIS research project in a developing country.
مقاله انگلیسی
3 Shopping intention at AI-powered automated retail stores (AIPARS)
قصد خرید در فروشگاه های خودکار خرده فروشی مجهز به هوش مصنوعی (AIPARS)-2020
Artificial Intelligence (AI) is transforming the way retail stores operate. AI-Powered Automated Retail Stores are the next revolution in physical retail. Consumers are facing fully automated technology in these retail stores. Therefore, it is necessary to scrutinize the antecedents of consumers’ intention to shop at AI-Powered Automated Retail Stores. This study delves into this area to find the predictors of consumers’ intention to shop at AI-Powered Automated Retail Stores. It extends the technology readiness and acceptance model by the addition of AI contextspecific constructs such as Perceived Enjoyment, Customization and Interactivity from the present literature. The proposed model is tested by surveying 1250 consumers & the data is analyzed using the PLS-SEM technique and empirically validated. The outcome of the study reveals that Innovativeness and Optimism of consumers affect the perceived ease and perceived usefulness. Insecurity negatively affects the perceived usefulness of AI-powered automated retail stores. Perceived ease of use, perceived usefulness, perceived enjoyment, customization and interactivity are significant predictors of shopping intention of consumers in AI-powered automated stores. This research presents insightful academic and managerial implications in the domain of retailing and technology in retail.
Keywords: TRAM | PLS-SEM | Perceived enjoyment | Customization | Interactivity | Artificial intelligence-powered automated | retail stores
مقاله انگلیسی
4 به سوی تقسیم بندی شبکه 5G برای شبکه های ادهاک خودرویی: یک رویکرد انتها به انتها
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 16
شبکه های 5G نه تنها از افزایش نرخ داده ها پشتیبانی می کنند، بکه همچنین می بایست زیرساخت مشترکی را فراهم کنند که براساس آن سرویس های جدید همراه با نیازمندی های بسیار متفاوت کیفیت سرویس (QoS) شبکه با تاخیر کمتر ارائه شود. به طور دقیق تر، کاربردهای شبکه های خودرویی چند منظوره (VANET) که اساساً گرایش آن ها به مسائل ایمنی و سرگرمی است (مانند پخش ویدیویی و مرورگر وب) در حال افزایش است. بیشتر این کاربردها دارای محدودیت های جدی از نظر تاخیر در حد چند میلی ثانیه هستند و نیاز به اطمینان پذیری بالایی دارند. پلتفورم نسل پنجم برای بررسی چنین نیازهایی نیازمند ایجاد شبکه های مجازی برنامه پذیر و راهکارهای مختلف ترافیکی همانند تقسیم بندی (برش) شبکه است. به این منظور در این مقاله یک مکانیزم تقسیم بندی پویا و برنامه پذیر انتها به انتها در شبکه LTE مبتنی بر M-CORD پیشنهاد می دهیم. یکی از ویژگی های کلیدی M-CORD که مکانیزم پیشنهاد تقسیم بندی شبکه از آن استفاده می کند، EPC مجازی است که سفارشی سازی و اصلاح را امکان پذیر می سازد. M-CORD کارکرد ضروری را برای برنامه ریزی تعاریف تقسیم بندی فراهم می کند که در آن مکانیزم پیشنهادی به طور کامل از رویکرد تعریف شده نرم افزاری خود پیروی می کند. علاوه بر این، ما نشان می دهیم که چگونه دستگاه ها انتهایی قرار گرفته در بخش های مختلف براساس QoS های متفاوت براساس نوع کاربر انتهایی تخصیص داده می شوند. این نتایج نشان می دهند که مکانیزم پیشنهادی تقسیم بندی شبکه بخش های مناسب را انتخاب می کند و منابع را به کاربران براساس نیازها و نوع سرویس آن ها اختصاص می دهد.
کلمات کلیدی: تقسیم بندی شبکه | نسل پنجم (5G) | M-CORD | LTE | NSSF | VANET
مقاله ترجمه شده
5 Challenges of 3D printing technology for manufacturing biomedical products: A case study of Malaysian manufacturing firms
چالش های فن آوری چاپ سه بعدی برای تولید محصولات زیست پزشکی: یک مطالعه موردی از شرکت های تولید مالزی-2020
Additive manufacturing has attracted increasing attention worldwide, especially in the healthcare, biomedical, aerospace, and construction industries. In Malaysia, insufficient acceptance of this technology by local industries has resulted in a call for government and local practitioners to promulgate the development of this technology for various industries, particularly for biomedical products. The current study intends to frame the challenges endured by biomedical industries who use 3D printing technology for their manufacturing processes. Qualitative methods, particularly in-depth interviews, were used to identify the challenges faced by manufacturing firms when producing 3D printed biomedical products. This work was able to identify twelve key challenges when deploying additive manufacturing in biomedical products and these include issues related to binder selection, poor mechanical properties, low-dimensional accuracy, high levels of powder agglomeration, nozzle size, distribution size, limited choice of materials, texture and colour, lifespan of materials, customization of fit and design, layer height, and, lastly, build-failure. Furthermore, there also are six challenges in the management of manufacturing biomedical products using 3D printing technology, and these include staff re-education, product pricing, limited guidelines, cyber-security issues, marketing, and patents and copyright. This study discusses the reality faced by 3D printing players when producing biomedical products in Malaysia, and presents a primary reference for practitioners in other developing countries.
Keywords: Business | Biomedical products | Additive manufacturing | 3D printing technology
مقاله انگلیسی
6 Utilization of a reinforcement learning algorithm for the accurate alignment of a robotic arm in a complete soft fabric shoe tongues automation process
استفاده از الگوریتم یادگیری تقویت کننده برای ترازبندی دقیق بازوی رباتیک در فرایند خودکار سازی نمایش نرم افزاری کفش هایفابریک-2020
As usher in Industry 4.0, there has been much interest in the development and research that combine artificial intelligence with automation. The control and operation of equipment in a traditional automated shoemaking production line require a preliminary subjective judgment of relevant manufacturing processes, to determine the exact procedure and corresponding control settings. However, with the manual control setting, it is difficult to achieve an accurate quality assessment of an automated process characterized by high uncertainty and intricacy. It is challenging to replace handicrafts and the versatility of manual product customization with automation techniques. Hence, the current study has developed an automatic production line with a cyber-physical system artificial intelligence (CPS-AI) architecture for the complete manufacturing of soft fabric shoe tongues. The Deep-Q reinforcement learning (RL) method is proposed as a means of achieving better control over the manufacturing process, while the convolutional and long short-term memory artificial neural network (CNN + LSTM) is developed to enhance action speed. This technology allows a robotic arm to learn the specific image feature points of a shoe tongue through repeated training to improve its manufacturing accuracy. For validation, different parameters of the network architecture are tested, and the test convergence accuracy was found to be as high as 95.9 %. During its actual implementation, the production line completed 509 finished products, of which 349 products were acceptable due to the anticipated measurement error. This showed that the production line system was capable of achieving optimum product accuracy and quality with respect to the performance of repeated computations, parameter updates, and action evaluations.
Keywords: Artificial intelligence | Shoemaking automation | Reinforcement learning | Cyber-physical system
مقاله انگلیسی
7 A clustering algorithm for scintillator signals applied to neutron and gamma patterns identification
یک الگوریتم خوشه بندی برای کاربرد سیگنال های دستگاه سینتسلیاتور بمنظور شناسایی الگوهای نوترونی و گاما-2019
In several nuclear applications, scintillators, coupled with a photomultiplier and pulse amplifier, are used in order to detect high energy particles, i.e. neutrons and gamma rays. The different particles incident on the scintillator produce electrical pulses having different shape; moreover, the amplitude of these signals is related to the particles energy. The electrical pulses of the scintillator chain are acquired by digital systems that, generally, perform a triggered acquisition consisting of a stream of pulse windows. The aim of this study is the development of a simplified clustering algorithm able to produce reference patterns in compliance with the pattern recognition algorithm based on the matched filter technique, starting from a stream of pulses generated by particles having different energy and type. This paper contains a general description of the clustering algorithm and of the main customizations performed for the scintillator signals. In order to test in real case the efficiency, the algorithm has been applied on the data acquired during a radiation test performed at Frascati Neutron Generator for Stilbene scintillator. The results show that this algorithm works properly, deriving the centroids of the clusters representing the neutron and gamma shapes, together with their occurrences in the analysed data stream.
Keywords: Clustering algorithm | Digital signal processing | Stilbene scintillator | Neutron and gamma discrimination | Pattern recognition
مقاله انگلیسی
8 راه‌حل‌های هوش مصنوعی برای بازاریابی دیجیتال
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 12
چکیده تکامل تدریجی تکنولوژی در سال‌های اخیر باعث حرکت رو به جلوی صنایع شده است. بازاریابی در سیر تکاملی خود به مرحله‌ای رسیده است که سازگاری با روندهای دیجیتالی ناگزیر است. اگرچه این به صورت فرآیندی تحمیلی بر بازاریاب‌ها به نظر می‌رسد اما در واقع، تمام برنامه‌ها و سیستم‌های خودکار که مبتنی بر هوش مصنوعی هستند تنها از پیچیدگی‌های متداول هدف‌ گذاری و فرآیندهای بومی‌سازی می‌کاهند. در بسیاری از موقعیت‌ها بسترهای مورد استفاده برای تبلیغات آنلاین حاوی الگوریتم‌هایی برای شناسایی بهترین برهمکنش‌ها هستند، در سایر موقعیت‌ها شرکت‌ها ابتکار عمل را برای توسعه و پیاده سازی ساختار‌های ویژه درونی بر عهده می‌گیرد. هدف محققان، توصیف وضعیت فعلی هوش مصنوعی در فرآیندهای بازاریابی و ارائه‌ی یک مدل متوالی چهار مرحله‌ای است که از راه‌حل هوشمند بازاریابی استفاده می‌کند که می‌تواند شفافیت وب سایت را از طریق کلمات کلیدی بهبود بخشد. کلمات کلیدی: هوش مصنوعی | بازاریابی هوشمند | شخصی‌سازی بازاریابی | ماشینی‌سازی فرآیند | یادگیری عمیق.
مقاله ترجمه شده
9 The influence of goal attainment and switching costs on customers’ staying intentions
تاثیر حصول به هدف و سوئیچینگ هزینه بر قصد ماندن مشتریان-2019
It examines the effectiveness of goal attainment (i.e. a value enhancement strategy) and switching costs (i.e. a defensive retention strategy) in enhancing customers’ staying intentions, where the service type is a key boundary condition. The data was collected using a survey design and analyzed using a multi-group SEM approach. Goal attainment played a stronger role in influencing staying intentions in services with passive customer participation and a low degree of customization (i.e. retail banking) than in services with active customer participation and a high degree of customization (i.e. stock brokerage). Different switching costs varied in importance across the two service industries
Keywords: Switching costs | Goal attainment | Customers’ staying intentions | Retail banking | Stockbrokerage services
مقاله انگلیسی
10 Proactive vs: reactive personalization: Can customization of privacy enhance user experience?
شخصی سازی فعالانه در مقابل واکنشی: آیا شخصی سازی حریم شخصی می تواند تجربه کاربر را افزایش دهد؟-2019
Online recommender systems have triggered widespread privacy concerns due to their reliance on personal user data for providing personalized services. To address these concerns, some systems have started allowing users to express their preferences before receiving personalized content (i.e., reactive personalization) rather than automatically pushing it to them (i.e., proactive personalization). However, this would mean constant calls for user action, which can adversely affect user experience. One potential solution is to offer users the ability to customize their privacy settings at the outset, thus obviating the need for constant consultation. We conducted a 2 (Personalization: Reactive vs. Proactive) X 3 (Customization of Settings: Absence vs. Action vs. Cue) factorial experiment (N=299) with a movie recommendation system. Findings show that interface cues suggesting customization enhance user experience, even in the presence of proactive personalization. They also highlight the important role played by negative privacy experiences in the past..
Keywords: Customization | Personalization | Recommender systems | Privacy | User experience | Experiment
مقاله انگلیسی
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