با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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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 |