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نتیجه جستجو - speed

تعداد مقالات یافته شده: 625
ردیف عنوان نوع
1 Human identification driven by deep CNN and transfer learning based on multiview feature representations of ECG
Human identification driven by deep CNN and transfer learning based on multiview feature representations of ECG-2021
Increasingly smart techniques for counterfeiting face and fingerprint traits have increased the potential threats to information security systems, creating a substantial demand for improved security and better privacy and identity protection. The internet of Things (IoT)-driven fingertip electrocardiogram (ECG) acquisition provides broad application prospects for ECG-based identity systems. This study focused on three major impediments to fingertip ECG: the impact of variations in acquisition status, the high computational complexity of traditional convolutional neural network (CNN) models and the feasibility of model migration, and a lack of sufficient fingertip samples. Our main contribution is a novel fingertip ECG identification system that integrates transfer learning and a deep CNN. The proposed system does not require manual feature extraction or suffer from complex model calculations, which improves its speed, and it is effective even when only a small set of training data exists. Using 1200 ECG recordings from 600 individuals, we consider 5 simulated yet potentially practical scenarios. When analyzing the overall training accuracy of the model, its mean accuracy for the 540 chest- collected ECG from PhysioNet exceeded 97.60 %, and for 60 subjects from the CYBHi fingertip-collected ECG, its mean accuracy reached 98.77 %. When simulating a real-world human recognition system on 5 public datasets, the validation accuracy of the proposed model can nearly reach 100 % recognition, outperforming the original GoogLeNet network by a maximum of 3.33 %. To some degree, the developed architecture provides a reference for practical applications of fingertip-collected ECG-based biometric systems and for information network security.
Keywords: Off-the-person | Fingertip ECG biometric | Human identification | Convolutional neural network (CNN) | Transfer learning
مقاله انگلیسی
2 Optimizing the electrical conductivity of polyacrylonitrile/polyaniline with nickel nanoparticles for the enhanced electrostimulation of Schwann cells proliferation
بهینه سازی رسانایی الکتریکی پلی اکریلونیتریل/پلی آنیلین با نانوذرات نیکل برای تحریک الکتریکی افزایش یافته تکثیر سلول های شوان-2021
Tissue engineering scaffolds made of biocompatible polymers are promising alternatives for nerve reparation. For this application, cell proliferation will be speeded up by electrostimulation, which required electrically-conductive materials. Here, a biomimicking scaffold with optimized conductivity was developed from electrospun polyacrylonitrile/electrically-conductive polyaniline (PAN/PANI) nanofibers doped with Ni nanoparticles. PAN/PANI/Ni was biocompatible for Schwann cells and exhibited a suitable tensile strength and wettability for cell proliferation. When compared with unmodified PAN/PANI, the electrical conductivity of PAN/PANI/Ni was 6.4 fold higher. Without electrostimulation, PAN/PANI and PAN/PANI/Ni exhibited similar Schwann cells’ proliferation rates. Upon electrostimulation at 100 mV cm1 for one hour per day over five days, PAN/PANI/Ni accelerated Schwann cells’ proliferation 2.1 times compared to PAN/PANI. These results demonstrate the importance of expanding the electrical conductivity of the tissue engineering scaffold to ensure optimal electrostimulation of nerve cell growth. Additionally, this study describes a straightforward approach to modulate the electrical conductivity of polymeric materials via the addition of Ni nanoparticles that can be applied to different biomimicking scaffolds for nerve healing.
Keywords: Nerve tissue engineering | Electrospinning | PAN/PANI | Ni nanoparticles | Schwann cells
مقاله انگلیسی
3 Secure mobile internet voting system using biometric authentication and wavelet based AES
سیستم رای گیری اینترنتی تلفن همراه با استفاده از احراز هویت بیومتریک و AES مبتنی بر موجک-2021
The number of mobile phone users increases daily, and mobile devices are used for various applications like banking, e-commerce, social media, internet voting, e-mails, etc. This paper presents a secure mobile internet voting system in which a biometric method authenticates the voter. The biometric image can either be encrypted at the mobile device and send to the server or process the biometric image at the mobile device to generate the biometric template and send it to the server. The implementation of biometrics on mobile devices usually requires simplifying the algorithm to adapt to the relatively small CPU processing power and battery charge. This paper proposes a wavelet-based AES algorithm to speed up the encryption process and reduce the mobile device’s CPU utilization. The experimental analysis of three methods(AES encryption, wavelet-based AES encryption, and biometric template generation) exhibits that wavelet-based AES encryption is much better than AES encryption and template generation. The security analysis of three methods shows that AES and wavelet-based AES encryption provides better security than the biometric template’s protection. The study of the proposed internet voting system shows that biometric authentication defeats almost all the mobile-based threats.
Keywords: Internet voting | Fingerprint template | Iris code | AES encryption | Wavelet based AES encryption
مقاله انگلیسی
4 Ann trained and WOA optimized feature-level fusion of iris and fingerprint
بهینه سازی شبکه‌های عصبی مصنوعی و WOA آموزش دیده همجوشی در سطح ویژگی عنبیه و اثر انگشت-2021
‘‘Uni Uni-modal Biometric systems has been widely implemented for maintaining security and privacy in various applications like mobile phones, banking apps, airport access control, laptop login etc. Due to Advancement in technologies, imposters designed various ways to breach the security and most of the designed biometric applications security can be compromised. The quality of input sample also play an important role to attain the best performance in terms of improved accuracy and reduced FAR & FRR. Researchers has combined the various biometrics modalities to overcome the problems of Uni-modal bio- metrics. In this paper, a multi biometric feature level fusion system of Iris, and Fingerprint is presented. Due to consistency feature of fingerprint and stability feature of iris modality taken into consideration for high security applications. At pre-processing level, the atmospheric light adjustment algorithm is applied to improve the quality of input samples (Iris and Fingerprint). For feature extraction, the nearest neighbor algorithm and speedup robust feature (SURF) is applied to fingerprint and Iris data respectively. Further, for selecting the best features, the extracted features are optimized by GA algorithm. To achieve an excellent recognition rate, the iris and fingerprint data is trained by ANN algorithm. The experimental results show that the proposed system exhibits the improved performance and better security. Finally, the template is secured by applying the AES algorithm and results are compared with DES, 3DES, RSA and RC4 algorithm.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 1st International Con- ference on Computations in Materials and Applied Engineering – 2021.
Keywords: Multimodal biometrics fusion | ANN | SURF | GA | RSA
مقاله انگلیسی
5 Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model
مدیریت پایدار زنجیره تأمین برای محصولات فاسدشدنی در بازارهای نوظهور: یک مدل مسیریابی-موجودی-مکانیابی یکپارچه-2021
The demand for perishable products in emerging markets has been increasing. However, the perishability of products brings tremendous challenges for firms to build a sustainable supply chain. In this paper, we propose an integrated model of location-inventory-routing for perishable products, considering the factors of carbon emissions and product freshness. First, the economic cost, carbon emission levels, and freshness of the perishable products are analyzed. Second, with the goals of achieving the lowest economic cost and carbon emissions and the highest product freshness, a multi-objective planning model is developed, and constraints are established based on the actual location-inventory-routing situation. Third, the YALMIP toolbox is used to solve the model, and the optimal solution to this complex multi-objective problem is obtained. Finally, the effectiveness and feasibility of the proposed method are verified by the case study, as well as the sensitivity vehicle speed to the results. It is found that the integrated model proposed in this paper is able to significantly improve the efficiency of perishable goods supply chain management from the perspective of global optimization, and vehicle speed is able to significantly affect economic costs and carbon emissions.
Keywords: Emerging market | Sustainable operations | Perishable product supply chain | Location-inventory-routing integration | Carbon emissions
مقاله انگلیسی
6 Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds
اختلالات مربوط به تأمین و سایبر در شرکت های زنجیره تامین ابر: تعیین بهترین سرعت بازیابی-2021
This study investigated the speeds (i.e., radical, incremental, relaxed benchmarking, rigorous benchmarking, matching, and market-driven) of firms’ recovery from supply- and cyber-related disruptions in cloud supply chains (SCs). Supply-related disruptions downgrade the firm’s operational capabilities (e.g., production capacity and labor supply), and cyber-related disruptions reduce its intangible capabilities (e.g., reputation, brand image, and public trust). This study introduced a cellular automata (CA) simulation model to determine the best recovery speeds following the loss of operational and intangible capabilities. Furthermore, to investigate the impact of cloud adoption on an SC firm’s best speeds of recovery from supply-related disruptions, we compared firms that had adopted the cloud with those using the on-site data centers.
Keywords: Supply chain | Cloud computing | Disruption | Recovery | Cellular automata simulation
مقاله انگلیسی
7 The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach
استراتژی مبتنی بر صندوق بازیابی بهینه برای اختلالات نامشخص زنجیره تأمین: رویکرد برنامه ریزی تصادفی دو مرحله ای ریسک پذیر-2021
For a supply chain subject to uncertain production disruptions, the joint optimization of invest- ment intervention on recovery speed and duration of disrupted production capacity and location and inventory management has not been well studied. In this paper, a novel recovery strategy is introduced and studied, which uses investment to adjust the recovery speed and duration of production capacity, and two recovery behaviors responding to different types of disruptions are modeled. Considering uncertain disruption scenarios and their ripple effects over the supply chain, a risk-averse two-stage stochastic programming model (RTSPM) is established to study the integrated supply chain management of selection of distribution centers, multi-period inventory, transportation flows, and recovery-fund based mitigation policy. The RTSPM incorporates the risk preference of managers in decision making. We propose a trust-region-based decomposition method to solve the RTSPM and demonstrate its efficiency by benchmarking on state-of-the-art commercial solvers. Through numerical examples, we deeply analyze the effectiveness of RTSPM and the relations of optimal recovery investment decisions with the uncertain disruption factors. Finally, we provide implications and suggestions induced from the models and findings to aid the decisions on renting of distribution centers and the emergency investment and operational decisions when suffering the disruptions.
Keywords: Supply chain disruption management | Recovery-fund based mitigation strategy | Location-inventory-transportation model | Risk-averse two-stage stochastic programming | Trust-region-based decomposition method
مقاله انگلیسی
8 Optimization of volleyball motion estimation algorithm based on machine vision and wearable devices
بهینه سازی الگوریتم برآورد حرکت والیبال بر اساس بینایی ماشین و دستگاه های پوشیدنی-2021
Volleyball is a team sport of track video-based analysis essential. However, this is difficult, especially in machine vision and wearable devices. Due to the ball’s small size, its speed of motion blur is generated, generally blocked. Older systems find it difficult to analyze the level of volleyball. When tracking with machine vision and wearable devices, it is recommended that Volleyball Motion Estimation Algorithms improve robustness to player confusion between different particle series. Faster processing speed and less confusing players presented herein as a method superior to the conventional particulate filter. The ball and Volleyball Motion Estimation Algorithm uses ma- chine vision and wearable devices to detect differential picture, and motion machine vision wearable device is optimized. Optimized toss Volleyball is correct by the Volleyball Motion Estimation Algorithm, and the trajectorys almost equal to the false prediction of the ball’s size. Machine vision and wearable devices can provide a new sports attendance watching experience through predictive images superimposed on live broadcasts. This also shows that the method can identify some important parts of the body to help predict thrown. Compared to the previous system, which provides better results.
Keywords: Volleyball motion estimation algorithm | Machine vision and wearable devices | Optimization of ball tracking | Classical particle filter | Predicted images
مقاله انگلیسی
9 A big data based architecture for collaborative networks: Supply chains mixed-network
یک معماری مبتنی بر داده های بزرگ برای شبکه های مشارکتی: شبکه های مخلوط شبکه های تأمین-2021
Nowadays, the world knows a high-speed development and evolution of technologies, vulnerable economic environments, market changes, and personalised consumer trends. The issue and challenge related to enterprises networks design are more and more critical. These networks are often designed for short terms since their strategies must be competitive and better adapted to the environment, social and economical changes. As a solution, to design a flexible and robust network, it is necessary to deal with the trade-off between conflicting qualitative and quantitative criteria such as cost, quality, delivery time, and competition, etc. To this end, using Big Data (BD) as emerging technology will enhance the real performances of these kinds of networks. Moreover, even if the literature is rich with BD models and frameworks developed for a single supply chain network (SCN), there is a real need to scale and extend these BD models to networked supply chains (NSCs). To do so, this paper proposes a BD architecture to drive a mixed-network of SCs that collaborate in serial and parallel fashions. The collaboration is set up by sharing their resources, capabilities, competencies, and information to imitate a unique organisation. The objective is to increase internal value to their shareholders (where value is seen as wealth) and deliver better external value to the end-customer (where value represents customer satisfaction). Within a mixed-network of SCs, both values are formally calculated considering both serial and parallel networks configurations. Besides, some performance factors of the proposed BD architecture such as security, flexibility, robustness and resilience are discussed.
Keywords: Big data architecture | Collaborative networks | Enterprises network | Supply chain network | Flexibility | Robustness
مقاله انگلیسی
10 یک مدل برای شبیه‌سازی و طرح‌ریزی پویای مسیر تعویض باند مبتنی بر تابع پارامتری جدید
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 16 - تعداد صفحات فایل doc فارسی: 22
مسأله‌ی تعویض باند (LC) می‌تواند موجب تصادفات شدید شده و ترافیک آزاردهنده‌ای را در جاده‌های چندبانده ایجاد نماید. مدل موجود برای شبیه‌سازی LC با یک سری محدودیت‌ها (انطباق کم، فقدان مشخصه‌های سرعت و شتاب، انحنای زیاد) با استفاده از منحنی مسیرهای شناخته‌شده‌ای همچون منحنی مماس هایپربولیک (HTC)، منحنی مبتنی بر سینوس (SC)، و منحنی چندجمله‌ای (PC) ایجاد شد. در این مقاله، یک منحنی پارامتری جدید با استفاده از دستگاه مختصات خمیده‌خطی ارائه و با پایگاه داده‌ی واقعی شبیه‌سازی نسل آتی (NGSIM) انطباق داده شد. سپس مشخصه‌های جدید سرعت و شتاب با استفاده از منحنی مسیر LC پیشنهاد شدند. انحنای مدل پیشنهادی در هر دو نقطه‌ی آغاز و پایان LC، انحنای مبتنی بر صفر بود. این انحنای پیشنهادی با دو مدل همانند HTC و SC مقایسه شد. خطای متوسط جذر میانگین مربعات مدل پیشنهادی در مقایسه با مدل HTC، برای LC چپ به میزان 1.84% و برای LC راست به میزان 15.48% و در مقایسه با مدل SC به میزان 1.74% برای LC چپ و به میزان 15.60% برای LC راست کاهش می‌یابد. بطور مشابه، مدل پیشنهادی برای مشخصه‌های سرعت و شتاب نسبت به مدل PC تا حد زیادی بهبود می‌یابد. منحنی پارامتری پیشنهادی، نقاط فاصله و برخورد خودروی LC با یک خودروی جلویی و خودروی پشتی در باند هدف را حل می‌کند و می‌توان از آن در برنامه‌ریزی مسیر LC واقعی استفاده کرد.
کلیدواژه ها: مشخصه‌های شتاب | منحنی پارامتری | سرعت | برنامه‌ریزی مسیر
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