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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81 |
Gait recognition based on vision systems: A systematic survey
تشخیص راه رفتن بر اساس سیستم های بینایی: یک مرور سیستماتیک-2021 With the growing popularity of biometrics technology in the pattern recognition field, especially identification of human has gained the attention of researchers from both academia and industry. One such type of biometric technique is Gait recognition, which is used to identify a human being based on their walking style. Generally, two types of approaches are adopted by any algorithm designed for gait recognition, namely model based and model free approaches. The key reason behind the popularity of gait recognition is that it can identify a person from a considerable distance while other biometrics has failed to do so. In this paper, the authors have conducted a survey of extant studies on gait recognition in consideration of gait recognition approaches and phases of a gait cycle. Moreover, some aspects like floor sensors, accelerometer based recognition, the influences of environ- mental factors, which are ignored by exiting surveys, are also covered in our survey study. The information of gait is usually obtained from different parts of silhouettes. This paper also describes different benchmark datasets for gait recognition. This study will provide firsthand knowledge to the researchers working on the gait recognition domain in any real-world field. It has been observed that work done on the gait recognition with sufficiently high accuracy is limited in comparison to research on various other biometric recognition systems and has enough potential for future research. Keywords: Gait recognition | Surveillance | Biometric | Person identification |
مقاله انگلیسی |
82 |
Full cost accounting: A missing consideration in global tailings dam management
حسابداری کامل هزینه: بررسی گمشده در مدیریت سد جهانی-2021 This conceptual paper argues that full cost accounting could fill a gap in the new Global Industry Tailings
Management Standard by bringing knowledge of externalities to account. Tailings dam management continues to
fail the industry, environment and society as one catastrophic disaster follows another. Parties involved have
collaborated to produce a Global Industry Tailings Management Standard which is in the process of being rolled
out. The Standard is short on detail as to the accounting information needed to improve decision making. In
particular there is no provision in the Standard for the cost of environmental and social externalities to be
gathered and reported on, internally to newly created Accountable Executives or externally to potentially
affected stakeholders. The paper develops recommendations for the integration of full cost accounting into
tailings management as the industry transitions towards zero future catastrophic tailings dam disasters and
eventual removal of threats from the destructive powers of tailings dam slurry. It concludes by drawing attention
to some key research issues that need addressing if full cost accounting for the potential external costs of tailings
dam failure is to be assessed and integrated in a standard for best practice tailings management. keywords: حسابداری کامل بهای تمام شده | خارجی ها | فاجعه سد باطله | استاندارد جهانی مدیریت باطله صنعت | Full cost accounting | Externalities | Tailings dam disaster | Global industry tailings management standard |
مقاله انگلیسی |
83 |
A Review of Food Fraud and Food Authenticity across the Food Supply Chain, with an Examination of the Impact of the COVID-19 Pandemic and Brexit on Food Industry
مروری بر تقلب غذایی و اصالت مواد غذایی در سراسر زنجیره تأمین مواد غذایی ، با بررسی تأثیر همه گیر COVID-19 و Brexit در صنایع غذایی-2021 Background
Food fraud is the deliberate and intentional act of substituting, altering or misrepresenting foodstuff for financial gain. Economical motivations for food fraud result in criminals focusing on opportunities to commit fraud rather than targeting specific products, thus reducing the probability of food fraud being detected. Although primarily for financial gain, food fraud can impact consumer wellbeing. Therefore, authenticating food is a key stage in protecting consumers and the supply chain. Food manufacturers, processors and retailers are increasingly fighting back as occurrences of food fraud become more prevalent, resulting in a greater focus on detection and prevention.
Scope and approach The aim of this review paper is to highlight and assess food fraud and authenticity throughout the food supply chain. Food fraud is a significant issue across the food industry, with many high-profile cases coming to public attention. Hence, this paper shall discuss the impact of food fraud on both consumers and manufacturers, the current and future trends in food fraud and methods of defence that are currently in use. Furthermore, emerging issues, such as the COVID-19 pandemic and Brexit, shall be discussed alongside the challenges they yield in terms of food fraud detection and prevention. Key findings and conclusions The incidence of food fraud is diverse across the sector, rendering it difficult to quantify and detect. As such, there are numerous food safety and traceability systems in use to ensure the safety and authenticity of food. However, as food fraud continues to diversify and evolve, current methods of detection for guaranteeing authenticity will be drastically challenged. Issues, such as the COVID-19 pandemic and Brexit, have instigated increased demand for food. This combined with reduced industry inspections, weakened governance, audits and ever-increasing pressure on the food industry has exposed greater weaknesses within an already complex system. KEYWORDS: Food Fraud | Food Authenticity | Food Supply Chain | COVID-19 Pandemic | Brexit | Traceability Systems |
مقاله انگلیسی |
84 |
Effect of graphite and Mn3O4 on clay-bonded SiC ceramics for the production of electrically conductive heatable filter
اثر گرافیت و Mn3O4 بر سرامیک های SiC پیوند خورده با خاک رس برای تولید فیلتر قابل گرمایش رسانای الکتریکی-2021 Electrically conductive porous SiC ceramics are attracting substantial attention due to their application in
heatable filters, vacuum chuck, and semiconductor processing parts, etc. The main problem is their high processing cost. Ideal candidates from an engineering ceramic perspective will be mechanically durable and have the
required electrical properties with sufficiently low fabrication costs. To decrease the sintering temperature,
kaolin has been added, but it tended to render the material an insulator. Graphite was used to effectively
decrease the electrical resistivity. Additionally, manganese oxide was used to decrease the quantity of kaolin (the
component that leads to an insulator material after sintering) and decrease the electrical resistivity while
maintaining the mechanical properties. In our study, we found that SiC with 35% kaolin, 20% graphite and 10%
manganese oxide can produce samples with 6.5 × 10− 1 Ω cm electrical resistivity and 43.5 MPa flexural strength
at a low sintering temperature of 1200 ◦C.
Keywords: SiC | Mullite | Electrical resistivity | Mechanical properties | Manganese oxide |
مقاله انگلیسی |
85 |
Automatic fetal biometry prediction using a novel deep convolutional network architecture
پیش بینی بیومتری خودکار جنین با استفاده از معماری شبکه ای پیچیده عمیق جدید-2021 Purpose: Fetal biometric measurements face a number of challenges, including the presence of speckle, limited soft-tissue contrast and difficulties in the presence of low amniotic fluid. This work proposes a convolutional neural network for automatic segmentation and measurement of fetal biometric parameters, including biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) from ultra- sound images that relies on the attention gates incorporated into the multi-feature pyramid Unet (MFP-Unet) network.
Methods: The proposed approach, referred to as Attention MFP-Unet, learns to extract/detect salient regions automatically to be treated as the object of interest via the attention gates. After determining the type of anatomical structure in the image using a convolutional neural network, Niblack’s thresholding technique was applied as pre-processing algorithm for head and abdomen identification, whereas a novel algorithm was used for femur extraction. A publicly-available dataset (HC18 grand-challenge) and clinical data of 1334 subjects were utilized for training and evaluation of the Attention MFP-Unet algorithm. Results: Dice similarity coefficient (DSC), hausdorff distance (HD), percentage of good contours, the conformity coefficient, and average perpendicular distance (APD) were employed for quantitative evaluation of fetal anatomy segmentation. In addition, correlation analysis, good contours, and conformity were employed to evaluate the accuracy of the biometry predictions. Attention MFP-Unet achieved 0.98, 1.14 mm, 100%, 0.95, and0.2 mm for DSC, HD, good contours, conformity, and APD, respectively. Conclusions: Quantitative evaluation demonstrated the superior performance of the Attention MFP-Unet compared to state-of-the-art approaches commonly employed for automatic measurement of fetal biometric parameters. Keywords: Fetal biometry | Ultrasound imaging | Deep learning | Convolutional neural network | Image classification |
مقاله انگلیسی |
86 |
Electrical explosion spray of Ag/C composite coating and its deposition behavior
اسپری انفجار الکتریکی پوشش کامپوزیت Ag/C و رفتار رسوبی آن-2021 Ag–C composite coating exhibits excellent electrical and thermal conductivities, good arc mobility, and low
contact resistance, making it has a good prospect in switch contact of high voltage isolators. At present, the
electro-deposition method is mainly used to prepare Ag/C composite coatings. However, the production efficiency of the electro-deposition method is low and the obtained coatings are thin. The electrical explosion
spraying, due to its simplicity and high efficiency, has attracted significant attention in coating preparation. In
this study, a new method that confines Ag and graphite powders in a tube for electrical explosion spraying was
proposed. Powder electrical explosion spraying was used for preparing an Ag/C composite coating by employing
a self-designed device. The heating behavior of the powder during exploding, macroscopic morphology,
micromorphology, deposition efficiency, and thickness of the coatings, as well as the deposition behavior of the
sprayed particles, were investigated. After a single spraying, a dense and uniform Ag/C composite coating was
obtained at the charging voltage of 13 kV and a spray distance of 18 mm. The results show that the coating area is
approximately 39.25 mm2, the coating thickness was 50 μm, and the deposition efficiency was 35%. the coatings
have good adhesion with the substrate. the interface between the coating and the substrate appeared as an interdiffusion of elements, which was typical of a metallurgical bonding interface. Graphite is evenly distributed in
the coating. Furthermore, the underlying deposition behavior of the coating was carefully characterized.
Keywords: Powder electrical explosion spraying | Composite coating | Heating behavior | Deposition behavior |
مقاله انگلیسی |
87 |
Power network robustness analysis based on electrical engineering and complex network theory
تجزیه و تحلیل استحکام شبکه قدرت بر اساس مهندسی برق و نظریه شبکه پیچیده-2021 The growing importance of power systems in the development of modern society
has increasingly focused the attention on the various dangers to which these systems
are exposed. This paper proposes a robust analysis framework based on complex
network theory with the aim of exploring the robustness of the power system from a
methodological perspective. The analysis framework establishes three models: a purely
topological model, an artificial flow model, and a direct current power flow model to
analyze the power system structure and functional robustness. We present different
analysis metrics under different models, simulate three fault scenarios, and conduct
an evaluation and analysis. The validity of the evaluation analysis was further verified
by adopting IEEE300 and two randomly generated 1000-node network models that
meet the characteristics of small world and scale, respectively, for detailed robustness
analysis. The results show that the proposed method can effectively analyze a power
system from the perspectives of pure topology, artificial flow, and direct current power
flow. The case analysis based on the IEEE300 network and systems with different
network characteristics proves that the framework is effective for the evaluation of
power systems with different characteristics.
Keywords: Power network | Robustness | Topological model | Artificial flow | Direct current power flow |
مقاله انگلیسی |
88 |
MISS-D: A fast and scalable framework of medical image storage service based on distributed file system
MISS-D: یک چارچوب سریع و مقیاس پذیر از خدمات ذخیره سازی تصویر پزشکی بر اساس سیستم فایل توزیع شده-2020 Background and Objective Processing of medical imaging big data is deeply challenging due to the size of
data, computational complexity, security storage and inherent privacy issues. Traditional picture archiving
and communication system, which is an imaging technology used in the healthcare industry, generally
uses centralized high performance disk storage arrays in the practical solutions. The existing storage solutions
are not suitable for the diverse range of medical imaging big data that needs to be stored reliably
and accessed in a timely manner. The economical solution is emerging as the cloud computing which
provides scalability, elasticity, performance and better managing cost. Cloud based storage architecture
for medical imaging big data has attracted more and more attention in industry and academia.
Methods This study presents a novel, fast and scalable framework of medical image storage service based
on distributed file system. Two innovations of the framework are introduced in this paper. An integrated
medical imaging content indexing file model for large-scale image sequence is designed to adapt to the
high performance storage efficiency on distributed file system. A virtual file pooling technology is proposed,
which uses the memory-mapped file method to achieve an efficient data reading process and
provides the data swapping strategy in the pool.
Result The experiments show that the framework not only has comparable performance of reading and
writing files which meets requirements in real-time application domain, but also bings greater convenience
for clinical system developers by multiple client accessing types. The framework supports different
user client types through the unified micro-service interfaces which basically meet the needs of
clinical system development especially for online applications. The experimental results demonstrate the
framework can meet the needs of real-time data access as well as traditional picture archiving and communication
system.
Conclusions This framework aims to allow rapid data accessing for massive medical images, which can be
demonstrated by the online web client for MISS-D framework implemented in this paper for real-time
data interaction. The framework also provides a substantial subset of features to existing open-source and
commercial alternatives, which has a wide range of potential applications. Keywords: Hadoop distributed file system | Data packing | Memory mapping file | Message queue | Micro-service | Medical imaging |
مقاله انگلیسی |
89 |
Cooperative control strategy for plug-in hybrid electric vehicles based on a hierarchical framework with fast calculation
استراتژی کنترل تعاونی برای وسایل نقلیه برقی هیبریدی پلاگین بر اساس یک چارچوب سلسله مراتبی با محاسبه سریع-2020 Developing optimal control strategies with capability of real-time implementation for plug-in hybrid
electric vehicles (PHEVs) has drawn explosive attention. In this study, a novel hierarchical control
framework is proposed for PHEVs to achieve the instantaneous vehicle-environment cooperative control.
The mobile edge computation units (MECUs) and the on-board vehicle control units (VCUs) are included
as the distributed controllers, which enable vehicle-environment cooperative control and reduce the
computation intensity on the vehicle by transferring partial work from VCUs to MECUs. On this basis, a
novel cooperative control strategy is designed to successively achieve the energy management planned
by the iterative dynamic programming (IDP) in MECUs and the energy utilization management achieved
by the model predictive control (MPC) algorithm in the VCU. The performance of raised control strategy
is validated by simulation analysis, highlighting that the cooperative control strategy can achieve superior
performance in real-time application that is close to the global optimization results solved offline. Keywords: Cooperative control strategy | Hierarchical framework | Iterative dynamic programming (IDP) | Model predictive control (MPC) | Plug-in hybrid electric vehicles (PHEVs) |
مقاله انگلیسی |
90 |
Establishment and application of intelligent city building information model based on BP neural network model
ایجاد و کاربرد مدل اطلاعات هوشمند شهرسازی براساس مدل شبکه عصبی BP-2020 The construction of smart cities in our country has received extensive attention. Under the situation that
smart cities are vigorously promoted nowadays, compared with traditional construction and operation and
maintenance methods, building information model (BIM) technology is more suitable to serve as an important
foundation for intelligent management in the whole process of construction projects. BIM is an abbreviation
for building information model. BIM relies on a variety of digital technologies, which can be used to realize
information modeling of urban buildings and infrastructure. The efficiency of information exchange in the
process of intelligence construction ensures the integrity and accuracy of information data exchange and
maintains the consistency of information data exchange. Data and information have objectivity, applicability,
transferability, and sharing. Geographic data is a digital representation of various geographical features and
phenomena and their relationships. BIM is a digital representation of physical and functional characteristics
of a facility. It can It is used as a shared knowledge resource for facility information. It becomes a reliable
basis for facility life-cycle decision-making. Input BP neural network, and then learn and train by BP neural
network. Keywords: BP neural network | Smart city | Building information model |
مقاله انگلیسی |