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نتیجه جستجو - production

تعداد مقالات یافته شده: 910
ردیف عنوان نوع
1 Barriers to computer vision applications in pig production facilities
موانع برنامه های بینایی کامپیوتری در تاسیسات تولید خوک-2022
Surveillance and analysis of behavior can be used to detect and characterize health disruption and welfare status in animals. The accurate identification of changes in behavior is a time-consuming task for caretakers in large, commercial pig production systems and requires strong observational skills and a working knowledge of animal husbandry and livestock systems operations. In recent years, many studies have explored the use of various technologies and sensors to assist animal caretakers in monitoring animal activity and behavior. Of these technologies, computer vision offers the most consistent promise as an effective aid in animal care, and yet, a systematic review of the state of application of this technology indicates that there are many significant barriers to its widespread adoption and successful utilization in commercial production system settings. One of the most important of these barriers is the recognition of the sources of errors from objective behavior labeling that are not measurable by current algorithm performance evaluations. Additionally, there is a significant disconnect between the remarkable advances in computer vision research interests and the integration of advances and practical needs being instituted by scientific experts working in commercial animal production partnerships. This lack of synergy between experts in the computer vision and animal health and production sectors means that existing and emerging datasets tend to have a very particular focus that cannot be easily pivoted or extended for use in other contexts, resulting in a generality versus particularity conundrum. This goal of this paper is to help catalogue and consider the major obstacles and impediments to the effective use of computer vision associated technologies in the swine industry by offering a systematic analysis of computer vision applications specific to commercial pig management by reviewing and summarizing the following: (i) the purpose and associated challenges of computer vision applications in pig behavior analysis; (ii) the use of computer vision algorithms and datasets for pig husbandry and management tasks; (iii) the process of dataset construction for computer vision algorithm development. In this appraisal, we outline common difficulties and challenges associated with each of these themes and suggest possible solutions. Finally, we highlight the opportunities for future research in computer vision applications that can build upon existing knowledge of pig management by extending our capability to interpret pig behaviors and thereby overcome the current barriers to applying computer vision technologies to pig production systems. In conclusion, we believe productive collaboration between animal-based scientists and computer-based scientists may accelerate animal behavior studies and lead the computer vision technologies to commercial applications in pig production facilities.
keywords: بینایی کامپیوتر | دامپروری دقیق | رفتار - اخلاق | یادگیری عمیق | مجموعه داده | گراز | Computer vision | Precision livestock farming | Behavior | Deep learning | Dataset | Swine
مقاله انگلیسی
2 Disintegration testing augmented by computer Vision technology
آزمایش تجزیه با فناوری Vision کامپیوتری تقویت شده است-2022
Oral solid dosage forms, specifically immediate release tablets, are prevalent in the pharmaceutical industry. Disintegration testing is often the first step of commercialization and large-scale production of these dosage forms. Current disintegration testing in the pharmaceutical industry, according to United States Pharmacopeia (USP) chapter 〈701〉, only gives information about the duration of the tablet disintegration process. This infor- mation is subjective, variable, and prone to human error due to manual or physical data collection methods via the human eye or contact disks. To lessen the data integrity risk associated with this process, efforts have been made to automate the analysis of the disintegration process using digital lens and other imaging technologies. This would provide a non-invasive method to quantitatively determine disintegration time through computer algorithms. The main challenges associated with developing such a system involve visualization of tablet pieces through cloudy and turbid liquid. The Computer Vision for Disintegration (CVD) system has been developed to be used along with traditional pharmaceutical disintegration testing devices to monitor tablet pieces and distinguish them from the surrounding liquid. The software written for CVD utilizes data captured by cameras or other lenses then uses mobile SSD and CNN, with an OpenCV and FRCNN machine learning model, to analyze and interpret the data. This technology is capable of consistently identifying tablets with ≥ 99.6% accuracy. Not only is the data produced by CVD more reliable, but it opens the possibility of a deeper understanding of disintegration rates and mechanisms in addition to duration.
keywords: از هم پاشیدگی | اشکال خوراکی جامد | تست تجزیه | یادگیری ماشین | شبکه های عصبی | Disintegration | Oral Solid Dosage Forms | Disintegration Test | Machine Learning | Neural Networks
مقاله انگلیسی
3 Hybrid Classical-Quantum Optimization Techniques for Solving Mixed-Integer Programming Problems in Production Scheduling
تکنیک‌های بهینه‌سازی ترکیبی کلاسیک-کوانتومی برای حل مسائل برنامه‌نویسی عدد صحیح مختلط در زمان‌بندی تولید-2022
Quantum computing (QC) holds great promise to open up a new era of computing and has been receiving significant attention recently. To overcome the performance limitations of near-term QC, utilizing the current quantum computers to complement classical techniques for solving real-world problems is of utmost importance. In this article, we develop QC-based solution strategies that exploit quantum annealing and classical optimization techniques for solving large-scale scheduling problems in manufacturing systems. The applications of the proposed algorithms are illustrated through two case studies in production scheduling. First, we present a hybrid QC-based solution approach for the job-shop scheduling problem. Second, we propose a hybrid QC-based parametric method for the multipurpose batch scheduling problem with a fractional objective. The proposed hybrid algorithms can tackle optimization problems formulated as mixed-integer linear and mixed-integer fractional programs, respectively, and provide feasibility guarantees. Performance comparison between state-of-the-art exact and heuristic solvers and the proposed QC-based hybrid solution techniques is presented for both job-shop and batch scheduling problems. Unlike conventional classical solution techniques, the proposed hybrid frameworks harness quantum annealing to supplement established deterministic optimization algorithms and demonstrate performance efficiency over standard off-the-shelf optimization solvers.
INDEX TERMS: Hybrid techniques | optimization | quantum annealing | quantum computing (QC) | scheduling.
مقاله انگلیسی
4 An exploration of local rules to map spawning processes to regular hardware architectures
کاوشی در قوانین محلی برای نگاشت فرآیندهای تخم ریزی به معماری های سخت افزاری معمولی-2022
This thesis presents an exploration of population growth via simulation in software to ascertain if a massively parallel hardware system can manage applications running within. Task execution happens dynamically and is controlled by the growth mechanism implementing efficient mapping in simulation. Algorithms that provide population simulation models are often inspired by those evidenced in biology and in particular those of cellular automata and L-systems. These algorithms are of particular interest due to their complexity and self-replication and recent research has shown that it is the refinement of the biological methodology that has resulted in their complexity. Further to this, adaptation of the design has moved the algorithm on towards being able to organize and build itself from a single cell. A growth model is utilized in software systems to provide production of meaningful data. The development of bio-inspired software is constrained by using contemporary processor architectures.
مقاله انگلیسی
5 تجزیه و تحلیل پوششی داده مبتنی بر نسبت: یک رویکرد تعاملی برای شناسایی معیار
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 14 - تعداد صفحات فایل doc فارسی: 40
در دنیای واقعی ما با موارد زیادی مواجه هستیم که در آن نسبت داده های ورودی/خروجی برای مدیران بسیار مهم است، بنابراین در این رابطه نمی توان از مدل های سنتی تحلیل پوششی داده (DEA) برای ارزیابی کارایی واحدهای تصمیم گیری (DMU) استفاده کرد، و باید از مدل های DEA بر اساس داده های نسبت بهره برد. برای بدست آوردن معیار مربوطه برای هر واحد تصمیم‌گیری ناکارآمد، باید ورودی‌ها و خروجی‌ها را به ترتیب کاهش و افزایش دهیم و به یک پیش‌بینی واحد و منسجم تصمیم‌گیرنده در مرز کارایی برسیم. در این مقاله ما یک مدل برنامه‌ریزی خطی چندهدفه (MOLP) (multi-objective linear programming) را برای ارزیابی کارایی بر اساس تعریف مجموعه امکان تولید در حضور داده‌های نسبت و به دست آوردن معیار مربوطه برای هر واحد تصمیم‌گیری DMU ارائه می‌کنیم. ما از روش تعاملی زایونتس و والنیوس (Z-W) برای حل مدل MOLP ارائه شده استفاده می‌کنیم. با استفاده از تنظیم هدف توسط مدیر از بین راه حل های حاصل از مسئله MOLP، بهترین راه حل را با توجه به ترجیحات مدیران به عنوان معیار انتخاب می کنیم و در پایان نتایج تحقیق را ارائه می کنیم.
واژگان کلیدی: کارایی | DEA-R | معیار | برنامه ریزی چند هدفه | روش تعاملی
مقاله ترجمه شده
6 یک مدل ریاضی چند منظوره برای زنجیره تامین داروسازی با توجه به تراکم دارو در کارخانه‌ها
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 15 - تعداد صفحات فایل doc فارسی: 47
مدیریت زنجیره تامین ( SCM ) , به روش یکی از مسائل مهم در جنبه مدیریتی , نقش مهمی در مقابله با مسایل انسانی و مشکلات ایفا می‌کند . به دلیل برخی محدودیت‌ها ( به عنوان مثال , ظرفیت تولید و ظرفیت ذخیره‌سازی ) و خواسته ها( به عنوان مثال , کاهش هزینه و افزایش درآمد ) , مدیران زنجیره تامین همیشه به دنبال بهترین پاسخ به مقدار و نوع ارتباط بین سطوح مختلف SCM هستند . در تحقیقات آتی , یک زنجیره تامین دارو ( PSC ) با سه تابع هدف توسعه‌یافته , با هدف به حداقل رساندن هزینه‌های کلی , خواسته‌های برآورده نشده , و کاهش زمان انتظار در ورودی کارخانه . در تحقیقات آتی , موضوع کلی و تحقیقات در مدل‌سازی PSC و حل مساله مورد بحث قرار گرفته‌اند . سپس یک مدل برنامه‌ریزی غیرخطی با تحقیقات قبلی برای حل کاستی‌های موجود پیشنهاد شده‌است.
همچنین روش‌های تصمیم‌گیری چند هدفه برای انطباق با اهداف متناقض مدل به طور همزمان استفاده می‌شوند . سپس نرم‌افزار تجاری GAMS برای حل مشکل اندازه‌های مختلف به کار می‌رود . در نهایت ، تحلیل حساسیت گسترده و ارزیابی نتایج مورد بحث قرار می‌گیرد و پیشنهادهای توسعه آتی ارایه می‌شوند.
واژه های کاربردی : زنجیره تامین دارو | فسادپذیری | زمان‌بندی | فهرست | نظریه کیوینگ
مقاله ترجمه شده
7 Proposal of anonymization dictionary using disclosed statements by business operators
پیشنهاد فرهنگ لغت ناشناس با استفاده از اظهارات افشا شده توسط اپراتورهای تجاری-2022
Increasing the number of business operators using anonymously processed information is a critical privacy topic in Japan. To promote the use of the information, an ‘‘anonymization dictionary’’ is proposed and implemented. The dictionary is the system that shares usecases regarding the manner by which business operators produce and provide anonymously processed information. To develop this system, two technical difficulties are resolved: the lack of (i) a method to acquire the use-cases and (ii) a data structure to store the use-cases. In terms of (i), disclosed statements that specify the production and provisioning processes for anonymously processed information is focused. To recognize the statements described in the business operators’ webpages as the use-cases, a web crawler that acquires the statements is developed. The crawler acquires 331 use-cases (statements) in a short duration. In terms of (ii), to define a concrete data structure to store anonymously processed information use-cases, the structure of the use-cases acquired is analyzed. The use-cases are stored into the structure and then in the DB of the dictionary application. This enables a search function to be provided for identifying the necessary use-cases and organizing use-cases in a readable form to the business operators.
keywords: اطلاعات پردازش شده به صورت ناشناس | ناشناس سازی | اظهارات افشا شده | خزنده | حفظ حریم خصوصی | Anonymously processed information | Anonymization | Disclosed statements | Crawler | Privacy preservation
مقاله انگلیسی
8 A framework for intelligent IoT firmware compliance testing
چارچوبی برای تست سازگاری سیستم عامل اینترنت اشیاء هوشمند-2022
The recent mass production and usage of the Internet of Things (IoT) have posed serious concerns due to the unavoidable security complications. The firmware of IoT systems is a critical component of IoT security. Although multiple organizations have released security guidelines, few IoT vendors are following these guidelines properly, either due to a lack of accountability or the availability of appropriate resources. Some tools for this purpose can use static, dynamic, or fuzzing techniques to test the security of IoT firmware, which may result in false positives or failure to discover vulnerabilities. Furthermore, the vast majority of resources are devoted to a single subject, such as networking protocols, web interfaces, or Internet of Things computer applications. This paper aims to present a novel method for conducting compliance testing and vulnerability evaluation on IoT system firmware, communication interfaces, and networking services using static and dynamic analysis. The proposed system detects a broad range of security bugs across a wide range of platforms and hardware architectures. To test and validate our prototype, we ran tests on 4300 firmware images and discovered 13,000þ compliance issues. This work, we believe, will be the first step toward developing a reliable automated compliance testing framework for the IoT manufacturing industry and other stakeholders.
keywords: اینترنت اشیا | امنیت اینترنت اشیا | تست انطباق | آسیب پذیری های میان افزار | IoT | IoT security | Compliance testing | Firmware vulnerabilities
مقاله انگلیسی
9 AgroLens: A low-cost and green-friendly Smart Farm Architecture to support real-time leaf disease diagnostics
AgroLens: یک معماری مزرعه هوشمند کم‌هزینه و سبز پسند برای پشتیبانی از تشخیص بیماری‌های برگ در زمان واقعی-2022
Agriculture is one of the most significant global economic activities responsible for feeding the world population of 7.75 billion. However, weather conditions and diseases impact production efficiency, reducing economic activity and the food sovereignty of economies worldwide. Thus, computational methods can support disease classification based on an image. This classification requires training Artificial Intelligence (AI) models on high-performance computing resources, usually far from the user domain. State of the art has proposed the concept of Edge Computing (EC), which aims to bring computational resources closer to the domain problem to decrease application latency and improve computational power closer to the client. In addition, EC has become an enabling technology for Smart Farms, and the literature has appropriated EC to support these applications. However, predominantly state-of-the-art architectures are dependent on Internet connectivity and do not allow diverse real-time classification of diseases based on crop leaf on mobile devices. This paper sheds light on a new architecture, AgroLens, built with low-cost and green-friendly devices to support a mobile Smart Farm application, operational even in areas lacking Internet connectivity. Among our main contributions, we highlight the functional evaluation of AgroLens for AI-based real-time classification of diseases based on leaf images, achieving high classification performance using a smartphone. Our results indicate that AgroLens supports the connectivity of thousands of sensors from a smart farm without imposing computational overhead on edge-compute. The AgroLens architecture opens up opportunities and research avenues for deployment and evaluation for large-scale Smart Farm applications with low-cost devices.
keywords: بیماری گیاهی | مزرعه هوشمند | اینترنت اشیا | یادگیری عمیق | سبز پسند| Plant disease | Smart Farm | Internet of Things | Deep learning | Green-friendly
مقاله انگلیسی
10 Evaluation of corporate requirements for smart manufacturing systems using predictive analytics
ارزیابی الزامات شرکت برای سیستم‌های تولید هوشمند با استفاده از تجزیه و تحلیل پیش‌بینی‌کننده-2022
Smart manufacturing systems (SMS) are one of the most important applications in the Industry 4.0 era, offering numerous advantages over traditional production systems and rapidly being used as a performance-enhancing strategy of manufacturing enterprises. A few of the technologies that must be connected to construct an SMS are the Industrial Internet of Things (IIoT), Big Data, Robotics, Blockchain, 5G Communication, Artificial Intelligence (AI), and many more. SMS is an innovative and popular manufacturing setup that produces increasingly intelligent production systems; yet, designers must adapt to business tastes and requirements. This study employs an analytical and descriptive research technique to identify and assess functional and non-functional, technological, economic, social, and performance evaluation components that are essential to SMS evaluation. A predictive analytics framework, which is a key component of many decision support systems, is used to assess corporate needs as well as proposed and prioritize SMS services.
keywords: صنعت 4.0 | تجزیه و تحلیل پیش بینی کننده | سیستم های تولید هوشمند | اینترنت اشیاء صنعتی | سیستم پشتیبانی تصمیم | Industry4.0 | Predictive analytics | Smart manufacturing systems | Industrial Internet of Things | Decision support system
مقاله انگلیسی
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