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).
ردیف | عنوان | نوع |
---|---|---|
1 |
Exploring Potential Applications of Quantum Computing in Transportation Modelling
بررسی کاربردهای بالقوه محاسبات کوانتومی در مدل سازی حمل و نقل-2022 The idea that quantum effects could be harnessed
to allow faster computation was first proposed by Feynman.
As of 2020 we appear to have achieved ‘quantum supremacy’,
that is, a quantum computer that performs a given task faster
than its classical counterpart. This paper examines some possibilities opened up by potential future application of quantum
computing to transportation simulation and planning. To date,
no such research was found to exist, therefore we begin with
an introduction to quantum computing for the programmers
of transport models. We discuss existing quantum computing
research relevant to transportation, finding developments in
network analysis, shortest path computation, multi-objective
routing, optimization and calibration – of which the latter three
appear to offer the greater promise in future research. Two
examples are developed in greater detail, (1) an application of
Grover’s quantum algorithm for extracting the mean, which has
general applicability towards summarizing distributions which
are expensive to compute classically, is applied to an assignment
or betweenness model - quantum speedup is elusive in the
general case but achievable when trading speed for accuracy
for limited outputs; (2) quantum optimization is applied to an
activity-based model, giving a theoretically quadratic speedup.
Recent developments notwithstanding, implementation of quantum transportation algorithms will for the foreseeable future
remain a challenge due to space overheads imposed by the
requirement for reversible computation.
Index Terms: Quantum computing | assignment | betweenness | flows, activity models | tour models. |
مقاله انگلیسی |
2 |
یک اسکریپت Matlab برای آنالیز مورفومتریک رودخانهها، کانالها و درههای روی زمینی، زیرآبی و فرا زمینی
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 29 ویژگی های مورفومتریک نقش مهمی در طبقه بندی و مدل سازی سیستم های رودخانه ای دارند. تمرکز تحقیقات گذشته بر شباهت بین سیستمهای زیرآبی و فرازمینی ناشناخته و سیستمهای رودخانهای رو زمینی است، اما اکنون مطالعات جزئی و دقیق دره و کانال زیرآبی در دریاچهها، مخازن، اقیانوسها و سیستمهای فرازمینی افزایش یافته است. در این مطالعات، اغلب فقط چند ویژگی مورفومتریک (به عنوان مثال، شیب بستر، پهنای کرانه، شعاع خط مرکزی در نوک خم، عمق کرانه) در نظر گرفته می شد، که علت آن فقدان ابزاری کارآمد برای تعیین این ویژگیها بود. در این راستا، یک اسکریپت Matlab ساده برای تعیین مهمترین ویژگیهای مورفومتریک رودخانهها، کانالها و درههای رو زمینی، زیرآبی و فرازمینی ارائه شد. تنها ورودیهای مورد نیاز این اسکریپت ، خاکریز یا تاجهای کناره خاکریز است که تعریف خط مرکزی را بهعنوان مبنای سیستم مرجع خمیده خطی کانال محور امکانپذیر می کند و به محاسبه ویژگیهای پلانفرم (به عنوان مثال، عرض کامل، انحنای تدریجی متغیر، سینوسی) می پردازد. در صورتی که دادههای رقومی ارتفاع بیومتری یا توپوگرافی وجود داشته باشد و قابل تبدیل به سیستم مرجع خمیده خطی کانالمرکز باشند، بنابراین امکان تعیین شیب بستر طولی و ویژگیهای بیشتر مورفومتریک در سطح مقطع های عرضی (به عنوان مثال، عمق کرانه، سطح مقطع، و شیب های کناره ها یا سیلاب ها) فراهم می شود. این اسکریپت به عنوان مثال بر دره زیر آبی در دریاچه کنستانس اجرا شد. این اسکریپت ابزاری کارآمد برای آنالیز مقدار روزافزون مدلهای ارتفاعی دیجیتال (DEMs) در رودخانهها، کانالها و درههای رو زمینی، زیرآبی و فرازمینی است. این اسکریپت به ویژه برای سیستمهای زیر آبی که درک آن ها ضعیف است، مناسب بوده و به درک بزرگترین سیستمهای دره و کانال کمک میکند.
کلمات کلیدی: رانندگی خودکار | محلی سازی سطح لاین | تشخیص لاین | GNSS | GPS | تطبیق نقشه |
مقاله ترجمه شده |
3 |
Deep unsupervised methods towards behavior analysis in ubiquitous sensor data
روش های عمیق بدون نظارت برای تجزیه و تحلیل رفتار در داده های حسگر همه جا حاضر-2022 Behavioral analysis (BA) on ubiquitous sensor data is the task of finding the latent distribution of
features for modeling user-specific characteristics. These characteristics, in turn, can be used for a
number of tasks including resource management, power efficiency, and smart home applications.
In recent years, the employment of topic models for BA has been found to successfully extract the
dynamics of the sensed data. Topic modeling is popularly performed on text data for mining
inherent topics. The task of finding the latent topics in textual data is done in an unsupervised
manner. In this work we propose a novel clustering technique for BA which can find hidden
routines in ubiquitous data and also captures the pattern in the routines. Our approach efficiently
works on high dimensional data for BA without performing any computationally expensive
reduction operations. We evaluate three different techniques namely Latent Dirichlet Allocation
(LDA), the Non-negative Matrix Factorization (NMF), and the Probabilistic Latent Semantic
Analysis (PLSA) for comparative study. We have analyzed the efficiency of the methods by using
performance indices like perplexity and silhouette on three real-world ubiquitous sensor datasets
namely, the Intel Lab, Kyoto, and MERL. Through rigorous experiments, we achieve silhouette
scores of 0.7049 over the Intel Lab dataset, 0.6547 over the Kyoto dataset, and 0.8312 over the
MERL dataset for clustering. In these cases, however, it is di cult to validate the results obtained as
the datasets do not contain any ground truth information. Towards that, we investigate a self-
supervised method that will be capable of capturing the inherent ground truths that are avail-
able in the dataset. We design a self-supervised technique which we apply on datasets containing
ground truth and also without. We see that our performance on data without ground truth differs
from that with ground truth by approximately 8% (F-score) hence showing the efficacy of self-
supervised techniques towards capturing ground truth information. keywords: تحلیل داده های فراگیر | تحلیل رفتار | یادگیری خود نظارتی | Ubiquitous data analysis | Behavior analysis | Self supervised learning |
مقاله انگلیسی |
4 |
Analysing the inhibitors of complexity for achieving sustainability and improving sustainable performance of petroleum supply chain
تجزیه و تحلیل مهارکننده های پیچیدگی برای دستیابی به پایداری و بهبود عملکرد پایدار زنجیره تأمین نفت-2021 In the era of business sustainability, the modern supply chain is becoming complex due to several inhibitors such as uncertainty in the market, technological innovation, environmental protocols, cross-border trade regulations, and many stakeholders’ involvement. In the existing literature, minimal discussion to study the inhibit supply chain complexity (SCC) inhibitors for achieving sustainability. Therefore, the study analyses the inhibitors to SCC and supply chain sustainability (SCS) jointly. The combined examination of the underlying relationship for improving the Petroleum Supply Chain’s sustainable performance (PSC) is arguably one of the complex sectors with a significant impact on the environment and sustainability. The inhibitors to SCC and SCS are identified through extensive literature review and experts’ opinions. Through a structured questionnaire, data were collected from PSC experts. An integrated approach of analytic hierarchy process (AHP) and interpretive structural modelling (ISM) is proposed to prioritize and examine the underlying relationship between inhibitors. This study explores the driving and dependence power of the inhibitors. The results indicate that most of the SCS inhibitors, such as institutional pressures (laws and regulations), strategic lack of strategic supplier alliance, market threat, act as drivers of SCC inhibitors, such as technological complexity, horizontal complexity, and complexity of customers. The study’s findings would help the supply chain managers and the petroleum sector policymakers to make better decision to overcome the challenges for achieving sustainability in PSC. Keywords: Petroleum supply chain | Environment and sustainability | Complexity | Business strategy | Interpretive structural modelling | Performance |
مقاله انگلیسی |
5 |
A review and perspectives on predicting the performance and durability of electrical contacts in automotive applications
بررسی و دیدگاههایی در مورد پیشبینی عملکرد و دوام کنتاکتهای الکتریکی در کاربردهای خودرو-2021 This review reports the recent progress in predicting the performance and long-term durability of
electrical connectors in the automotive industry. The review features a short introduction to
electrical contacts as well as the validation process before product launch, followed by a study of
fretting wear and the latest mathematical models describing this phenomenon. We discuss approaches to numerical modeling in the micro- and macro-scale, including the identification of the
most promising research approaches to allow durability prediction of an electrical connector.
Finally, we address some gaps in the research which require further investigation. This would
allow further development of numerical models enabling the prediction of automotive connector
durability with regard to its electrical and mechanical performance, and hence, the performance
of the entire wire harness.
Keywords: Fretting | Modeling and simulation | Numerical modeling | Mechanics of materials | Electrical and electronic engineering | Modeling of degradation | LSR aging |
مقاله انگلیسی |
6 |
Effect of CNT additives on the electrical properties of derived nanocomposites (experimentally and numerical investigation)
تأثیر افزودنیهای CNT بر خواص الکتریکی نانوکامپوزیتهای مشتقشده (بررسی تجربی و عددی)-2021 In this work, two simulations models have been developed to study the electrical percolation and the
electrical conductivity of epoxy-based nanocomposite containing Multi-walled Carbon Nanotubes. The
models are based on resistor-model and finite element analysis. The former was evaluated using
MATLAB code and the finite element analysis using DIGIMAT software. The maximum tunneling distance
and its influence on the percolation probability and final electrical conductivity were studied. Electrical
measurements on the samples were conducted for numerical validation. The experimental data showed a
percolation achievement around 2 wt%, which was confirmed in the numerical simulations. This study
provides evidence of the effectiveness of the resistor model and finite element method approach to predict the electrical conductivity of nanocomposites.
Keywords: Polymer-matrix composites (PMCs) | Nanocomposites | Carbon nanotube | Electrical properties | Computational modelling |
مقاله انگلیسی |
7 |
An efficient biometric-based continuous authentication scheme with HMM prehensile movements modeling
یک طرح احراز هویت مداوم مبتنی بر بیومتریک با مدل سازی حرکات پیش ساخته HMM-2021 Biometric is an emerging technique for user authentication thanks to its efficiency compared to the traditional methods, such as passwords and access-cards. However, most existing biometric authentication systems require the cooperation of users and provide only a login time authentication. To address these drawbacks, we propose in this paper a new, efficient continuous authentication scheme based on the newly biometric trait that still under development: prehensile movements. In this work, we model the movements through Hidden Markov Model-Universal Background Model (HMM-UBM) with continuous observations based on Gaussian Mixture Model (GMM). Unlike the literature, the gravity signal is included. The results of the experiments conducted on a public database HMOG and on a proprietary database, collected under uncontrolled conditions, have shown that prehensile movements are very promising. This new biometric feature will allow users to be authenticated continuously, passively and in real time. Keywords: Biometric | Authentication | Prehensile movement | HMM-UBM | GMM |
مقاله انگلیسی |
8 |
Construction of carbonate reservoir knowledge base and its application in fracture-cavity reservoir geological modeling
ساخت پایگاه دانش مخزن کربناته و کاربرد آن در مدلسازی زمین شناسی مخزن شکستگی-حفره ای-2021 To improve the efficiency and accuracy of carbonate reservoir research, a unified reservoir knowledge base linking
geological knowledge management with reservoir research is proposed. The reservoir knowledge base serves high-quality
analysis, evaluation, description and geological modeling of reservoirs. The knowledge framework is divided into three
categories: technical service standard, technical research method and professional knowledge and cases related to geological
objects. In order to build a knowledge base, first of all, it is necessary to form a knowledge classification system and knowledge
description standards; secondly, to sort out theoretical understandings and various technical methods for different geologic
objects and work out a technical service standard package according to the technical standard; thirdly, to collect typical outcrop
and reservoir cases, constantly expand the content of the knowledge base through systematic extraction, sorting and saving,
and construct professional knowledge about geological objects. Through the use of encyclopedia based collaborative editing
architecture, knowledge construction and sharing can be realized. Geological objects and related attribute parameters can be
automatically extracted by using natural language processing (NLP) technology, and outcrop data can be collected by using
modern fine measurement technology, to enhance the efficiency of knowledge acquisition, extraction and sorting. In this paper,
the geological modeling of fracture-cavity reservoir in the Tarim Basin is taken as an example to illustrate the construction of
knowledge base of carbonate reservoir and its application in geological modeling of fracture-cavity carbonate reservoir.
keywords: knowledge management | reservoir knowledge base | fracture-cavity reservoir | geological modeling | carbonates | paleo-underground river system | Tahe oilfield | Tarim Basin |
مقاله انگلیسی |
9 |
Malaysia scenario of biomass supply chain-cogeneration system and optimization modeling development: A review
سناریوی مالزی سیستم تولید همزمان زنجیره تأمین زیست توده و توسعه مدل سازی بهینه سازی: یک مرور-2021 The development of biomass-based cogeneration energy systems in Malaysia is progressing to meet the circular economy concept and sustainability goal. This comprehensive review aims to report recent advancements in biomass-based cogeneration/biomass co-firing technology in Malaysia correlated with the optimization modeling role. First, this work presents the outlook and current scenario of cogeneration systems in Malaysia by observing performance and the challenges confronted by the technologies. Next, investigation of technical issues concerning the key players of the technologies and the biomass supply chain. This work had prepared using quantitative content-based analysis-meta-analysis. The practical implication of this review enables a complex optimization model that integrates biomass-based cogeneration and biomass supply chain considering economic and environmental viability. It will further enhance progress toward the Malaysian “Industry 4.0-driven” energy initiative. A novel optimization model grounded on Industry 4.0 parameters will foster new opportunities for researchers. Keywords: Biomass-based cogeneration system | Biomass co-firing | Optimization modeling | Renewable energy | Economic and operational viability |
مقاله انگلیسی |
10 |
Utilizing LiDAR data to map tree canopy for urban ecosystem extent and condition accounts in Oslo
با استفاده از داده های LIDAR به نقشه سایبان درخت برای اکوسیستم های شهری و حساب های وضعیت در اسلو-2021 LiDAR-based segmentation of urban tree canopies and their physical properties (canopy height, canopy diameter,
3D surface and volume) is a replicable, complementary and useful information source for urban ecosystem
condition accounts, and an important basis for ecosystem service modeling and valuation. However, using
available LiDAR data collected for municipal purposes other than vegetation mapping (such as for example
engineering) entails a level of accuracy which may limit the usefulness of the data for change detection in
ecosystem accounts. To account for changes in the urban tree canopy of Oslo (capital city of Norway) between
2011 and 2017, a segmentation model was developed based on available airborne LiDAR data scanned for
general purposes. The results from the entire built-up area of Oslo indicate a general increase in the number of
tall trees (>15 m) and a moderate increase in the number of small trees (<15 m), with the exception of trees
between 6 and 10 m which seem to have a relatively constant development over the given period. The total tree
canopy area within the built-up area increased by 17.15%, with a corresponding 21.35% increase in the tree
canopy volume. The results for the Small House plan area, a policy focus area subject to urban densification and
special regulations for felling of large trees, indicate a large increase in small trees (<10 m) and a moderate
decrease in tall trees (>10 m). The total tree canopy area within the Small House plan area decreased by 1.04%,
with a corresponding 2.13% decrease in the tree canopy volume. With respect to the segmentation accuracy, the
changes in aggregate tree canopy cover are too small to determine canopy change with confidence. This study
demonstrates the potential for identifying ecosystem condition indicators as well as the limitations of using
general purpose LiDAR data to improve the precision of urban ecosystem accounting. For future ecosystem
service accounting in urban environments, we recommend that municipalities implement data acquisition programs that combine concurrent field data sampling and LiDAR campaigns designed for urban tree canopy
detection, as part of general urban structural inventorying. We recommend using LiDAR and satellite remote
sensing data depending on canopy densities. We also recommend that future tree canopy segmentation is done
within a cloud-computing environment to ensure sufficient geoprocessing capacity.
keywords: تشخیص نور و محدوده (LIDAR) | سیستم های اطلاعات جغرافیایی (GIS) | سنجش از راه دور | حسابداری اکوسیستم | خدمات محیط زیستی | تقسیم بندی سایبان درخت | Light Detection And Ranging (LiDAR) | Geographical Information Systems (GIS) | Remote sensing | Ecosystem accounting | Ecosystem services | Tree canopy segmentation |
مقاله انگلیسی |