دانلود و نمایش مقالات مرتبط با Similarity::صفحه 1
دانلود بهترین مقالات isi همراه با ترجمه فارسی 2

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). 

نتیجه جستجو - Similarity

تعداد مقالات یافته شده: 245
ردیف عنوان نوع
1 Graph Kernels Encoding Features of All Subgraphs by Quantum Superposition
ویژگی های رمزگزاری هسته های گراف زیرگراف ها با برهم نهی کوانتومی-2022
Graph kernels are often used in bioinformatics and network applications to measure the similarity between graphs; therefore, they may be used to construct efficient graph classifiers. Many graph kernels have been developed thus far, but to the best of our knowledge there is no existing graph kernel that uses some features explicitly extracted from all subgraphs to measure similarity. We propose a novel graph kernel that applies a quantum computer to measure the similarity obtained from all subgraphs by fully exploiting the power of quantum superposition to encode every subgraph into a feature of particular form. For the construction of the quantum kernel, we develop an efficient protocol that clears the index information of the subgraphs encoded in the quantum state. We also prove that the quantum computer requires less query complexity to construct the feature vector than the classical sampler used to approximate the same vector. A detailed numerical simulation of a bioinformatics problem is presented to demonstrate that, in many cases, the proposed quantum kernel achieves better classification accuracy than existing graph kernels.
Index Terms: Quantum computing | machine learning | bioinfomatics.
مقاله انگلیسی
2 Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM
رویکرد دیجیتال دوقلو برای بهبود بهره وری انرژی در روشنایی داخلی بر اساس بینایی کامپیوتر و BIM پویا-2022
Intelligent lighting systems and surveillance systems have become an important part of intelligent buildings. However, the current intelligent lighting system generally adopts independent sensor control and does not perform multi-source heterogeneous data fusion with other digital systems. This paper fully considers the linkage between the lighting system and the surveillance system and proposes a digital twin lighting (DTL) system that mainly consists of three parts. Firstly, a visualized operation and maintenance (VO&M) platform for a DTL system was established based on dynamic BIM. Secondly, the environment perception, key-frame similarity judgment, and multi-channel key-frame cut and merge mechanism were utilized to preprocess the video stream of the surveillance system in real-time. Lastly, pedestrians detected using YOLOv4 and the ambient brightness perceived by the environment perception mechanism were transmitted to the cloud database and were continuously read by the VO&M platform. The intent here was to aid timely adaptive adjustment of the digital twin and realistic lighting through the internet. The effectiveness of the proposed method was verified by experimenting with a surveillance video stream for 14 days. The key results of the experiments are as follows: (1) the accuracy rate of intelligent decision control reached 95.15%; (2) energy consumption and electricity costs were reduced by approximately 79%; and (3) the hardware cost and energy consumption of detection equipment and the time and cost of operation and maintenance (O&M) were greatly reduced.
keywords: Computer vision | Digital Twin | Dynamic BIM | Energy-efficient buildings | Intelligent lighting control
مقاله انگلیسی
3 Quantum Kernels for Real-World Predictions Based on Electronic Health Records
هسته‌های کوانتومی برای پیش‌بینی‌های دنیای واقعی بر اساس پرونده‌های سلامت الکترونیکی-2022
Research on near-term quantum machine learning has explored how classical machine learning algorithms endowed with access to quantum kernels (similarity measures) can outperform their purely classical counterparts. Although theoretical work has shown a provable advantage on synthetic data sets, no work done to date has studied empirically whether the quantum advantage is attainable and with what data. In this article, we report the first systematic investigation of empirical quantum advantage (EQA) in healthcare and life sciences and propose an end-to-end framework to study EQA. We selected electronic health records data subsets and created a configuration space of 5–20 features and 200–300 training samples. For each configuration coordinate, we trained classical support vector machine models based on radial basis function kernels and quantum models with custom kernels using an IBM quantum computer, making this one of the largest quantum machine learning experiments to date. We empirically identified regimes where quantum kernels could provide an advantage and introduced a terrain ruggedness index, a metric to help quantitatively estimate how the accuracy of a given model will perform. The generalizable framework introduced here represents a key step toward a priori identification of data sets where quantum advantage could exist.
INDEX TERMS: Artificial intelligence | digital health | electronic health records (EHR) | empirical quantum advantage (EQA) | machine learning | quantum kernels | real-world data | small data sets | support vector machines (SVM).
مقاله انگلیسی
4 Qutrit-Inspired Fully Self-Supervised Shallow Quantum Learning Network for Brain Tumor Segmentation
شبکه یادگیری کوانتومی کم عمق کاملاً خود نظارتی الهام گرفته از Qutrit برای تقسیم بندی تومور مغزی-2022
Classical self-supervised networks suffer from convergence problems and reduced segmentation accuracy due to forceful termination. Qubits or bilevel quantum bits often describe quantum neural network models. In this article, a novel self-supervised shallow learning network model exploiting the sophisticated three-level qutrit-inspired quantum information system, referred to as quantum fully self-supervised neural network (QFS-Net), is presented for automated segmentation of brain magnetic resonance (MR) images. The QFS-Net model comprises a trinity of a layered structure of qutrits interconnected through parametric Hadamard gates using an eight-connected secondorder neighborhood-based topology. The nonlinear transformation of the qutrit states allows the underlying quantum neural network model to encode the quantum states, thereby enabling a faster self-organized counterpropagation of these states between the layers without supervision. The suggested QFS-Net model is tailored and extensively validated on the Cancer Imaging Archive (TCIA) dataset collected from the Nature repository. The experimental results are also compared with state-of-theart supervised (U-Net and URes-Net architectures) and the selfsupervised QIS-Net model and its classical counterpart. Results shed promising segmented outcomes in detecting tumors in terms of dice similarity and accuracy with minimum human intervention and computational resources. The proposed QFS-Net is also investigated on natural gray-scale images from the Berkeley segmentation dataset and yields promising outcomes in segmentation, thereby demonstrating the robustness of the QFS-Net model.
Index Terms: tum computing | qutrit | U-Net and URes-Net.
مقاله انگلیسی
5 An R-Convolution Graph Kernel Based on Fast Discrete-Time Quantum Walk
یک هسته گراف R-Convolution بر اساس راه رفتن کوانتومی سریع زمان گسسته -2022
In this article, a novel R-convolution kernel, named the fast quantum walk kernel (FQWK), is proposed for unattributed graphs. In FQWK, the similarity of the neighborhood-pair substructure between two nodes is measured via the superposition amplitude of quantum walks between those nodes. The quantum interference in this kind of local substructures provides more information on the substructures so that FQWK can capture finer-grained local structural features of graphs. In addition, to efficiently compute the transition amplitudes of multistep discrete-time quantum walks, a fast recursive method is designed. Thus, compared with all the existing kernels based on the quantum walk, FQWK has the highest computation speed. Extensive experiments demonstrate that FQWK outperforms state-of-the-art graph kernels in terms of classification accuracy for unattributed graphs. Meanwhile, it can be applied to distinguish a larger family of graphs, including cospectral graphs, regular graphs, and even strong regular graphs, which are not distinguishable by classical walk-based methods.
Index Terms: Discrete-time quantum walk (DTQW) | graph classification | graph kernel | R-convolution kernel.
مقاله انگلیسی
6 Significance of variable electrical conductivity on non-Newtonian fluid flow between two vertical plates in the coexistence of Arrhenius energy and exothermic chemical reaction
Noneاهمیت رسانایی الکتریکی متغیر بر جریان سیال غیرنیوتنی بین دو صفحه عمودی در همزیستی انرژی آرنیوس و واکنش شیمیایی گرمازا-2021
The present study is designed to model the combustible materials of two vertical plates with Arrhenius energy and exothermic chemical reaction. The magnetohydrodynamics fluid is considered to experience an exothermic chemical reaction inside the channel. Additional effects incorporated to the novelty of the model are the rheological Casson fluid term and the variable electrical conductivity. The model has transformed appropriately to its dimensionless form using similarity renovation and the Solution is numerically obtained using the Chebyshev collocation scheme. The influences of controlling parameters on the fluid velocity, temperature, concentration, and heat transfer rate are analyzed using graph and quantitatively discussed. Analyses reveal that the activation energy declines the fluid velocity, while the existence of the variable electrical conductivity parameter has the opposite effect. The heat transfer rate is enhanced with higher values of concentration buoyancy (Gc) and variable electrical conductivity parameter. Moreover, the non-Newtonian Casson fluid parameter shows a solid characteristic when yield stress is more than the shear stress. Thermal and chemical engineering, as well as service-worthiness of industrial products, will benefit from the findings of this study.
Keywords: Magnetohydrodynamics fluid | Rheological Casson fluid | Arrhenius energy and exothermic chemical | reaction
مقاله انگلیسی
7 Cultural consensus knowledge of rice farmers for climate risk management in the Philippines
دانش اجماع فرهنگی کشاورزان برنج برای مدیریت ریسک آب و هوایی در فیلیپین-2021
Despite efforts and investments to integrate weather and climate knowledges, often dichotomized into the scientific and the local, a top-down practice of science communication that tends to ignore cultural consensus knowledge still prevails. This paper presents an empirical application of cultural consensus analysis for climate risk management. It uses mixed methods such as focus groups, freelisting, pilesorting, and rapid ethnographic assessment to understand farmers’ knowledge of weather and climate conditions in Barangay Biga, Oriental Mindoro, Philippines. Multi-dimensional scaling and aggregate proximity matrix of items are generated to assess the similarity among the different locally perceived weather and climate conditions. Farmers’ knowledge is then qualitatively compared with the technical classification from the government’s weather bureau. There is cultural agreement among farmers that the weather and climate con- ditions can be generally grouped into wet, dry, and unpredictable weather (Maria Loka). Damaging hazards belong into two subgroups on the opposite ends of the wet and dry scale, that is, tropical cyclone is grouped together with La Ni˜na, rainy season, and flooding season, while farmers perceive no significant difference between El Ni˜no, drought, and dry spells. Ethnographic information reveals that compared to the technocrats’ reductive knowledge, farmers imagine weather and climate conditions (panahon) as an event or a phenomenon they are actively experiencing by observing bioindicators, making sense of the interactions between the sky and the landscape, and the agroecology of pest and diseases, while being subjected to agricultural regulations on irrigation, price volatility, and control of power on subsidies and technologies. This situated local knowledge is also being informed by forecasts and advisories from the weather bureau illustrating a hybrid of technical science, both from the technocrats and the farmers, and personal experiences amidst agricultural precarities. Speaking about the hybridity of knowledge rather than localizing the scientific obliges technocrats and scientists to productively engage with different ways of knowing and the tensions that mediate farmers’ knowledge as a societal experience.
keywords: دانش اجماع | پیش بینی آب و هوا | کشاورزی | خطر ابتلا به آب و هوا | Consensus knowledge | Weather forecasting | Agriculture | Climate risk
مقاله انگلیسی
8 Managing expert knowledge in water network expansion project implementation
مدیریت دانش تخصصی در اجرای پروژه توسعه شبکه آب-2021
The implementation of expansion projects of water networks supplying growing cities is deemed to be a complex decision-making problem involving both technical aspects and expert knowledge. Management and control processes must rely on experts in the field whose knowhow must be coupled with techniques able to deal with the natural subjectivity that affects input evaluations. Given the presence of many decision-making elements, the choice of proper hydraulic technical parameters may be linked to the main aspects of analysis requiring formal expert evaluation. In this contribution, the simulation of hydraulic indicators is integrated with a multi-criteria approach able to eventually determine those areas of a water network through which organising the expansion may be more beneficial. The software EPAnet 2.0 is first used for hydraulic simulations, whereas the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) will eventually rank network’s nodes. A case study is solved to demonstrate the applicability and effectiveness of the proposed approach.
keywords: Complex Systems | Management and Control | Water Distribution Networks | Expansion Project | EPAne | software 2.0 | TOPSIS.
مقاله انگلیسی
9 A relational account of visual short-term memory (VSTM)
یک گزارش ارتباطی از حافظه کوتاه مدت بصری (VSTM)-2021
Visual short-term memory (VSTM) is an important resource that allows temporarily storing visual information. Current theories posit that elementary features (e.g., red, green) are encoded and stored independently of each other in VSTM. However, they have difficulty explaining the similarity effect, that similar items can be remembered better than dissimilar items. In Experiment 1, we tested (N ¼ 20) whether the similarity effect may be due to storing items in a context-dependent manner in VSTM (e.g., as the reddest/yellowest item). In line with a relational account of VSTM, we found that the similarity effect is not due to feature similarity, but to an enhanced sensitivity for detecting changes when the relative colour of a to-be-memorised item changes (e.g., from reddest to not-reddest item; than when an item underwent the same change but retained its relative colour; e.g., still reddest). Experiment 2 (N ¼ 20) showed that VSTM load, as indexed by the CDA amplitude in the EEG, was smaller when the colours were ordered so that they all had the same relationship than when the same colours were out-of-order, requiring encoding different relative colours. With this, we report two new effects in VSTM e a relational detection advantage that describes an enhanced sensitivity to relative changes in change detection, and a relational CDA effect, which reflects that VSTM load, as indexed by the CDA, scales with the number of (different) relative features between the memory items. These findings support a relational account of VSTM and question the view that VSTM stores features such as colours independently of each other.
keywords: حافظه کوتاه مدت بصری (VSTM) | حافظه کاری ویژوال (VWM) | حساب ارتباطی | اثر شباهت | CDA برای دیدن | Visual short-term memory (VSTM) | Visual working memory (VWM) | Relational account | Similarity effect | CDA in EEG
مقاله انگلیسی
10 Matching user accounts with spatio-temporal awareness across social networks
تطبیق حساب های کاربری با آگاهی مکانی-زمانی در سراسر شبکه های اجتماعی-2021
User identification aims at matching user accounts across social sites, which benefits many real-world applications. Existing works based on user trajectories usually address spatial and temporal data separately while not fully utilizing the coupling relation between them. Differently, in this work, we jointly consider spatialtemporal information in users’ acitvities to improve the user identification method. In particular, we observe that check-in records of different users tend to create inconsistent spatialtemporal information. These inconsistencies are useful for eliminating false user matching. Inspired by this observation, we propose a novel user identification method that captures the correlation of spatial and temporal information and the inconsistency in check-in records. It contains three main steps. 1) We measure the similarity of users’ trajectories based on a kernel density estimation, which considers spatial and temporal information simultaneously. 2) We assign a weight to each check-in record to favor discriminative ones. 3) We utilize the inconsistency among check-in records to compute penalties for trajectory similarity. The pair of accounts with higher similarity (than a predefined threshold) is then considered to be from the same user. We evaluate our approach on three ground-truth datasets. The results show that the proposed method offers competitive performance, with F1 values reaching 86.12%, 85.08% and 78.34%, which demonstrates the superiority of the proposed method over state-of-theart methods.
keywords: شناسه کاربر | آگاهی مکانی-زمانی | مطابقت با حساب های کاربری | داده های ورود | مسیر کاربر | User identification | Spatio-temporal awareness | Match user accounts | Check-in data | User trajectory
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 6016 :::::::: بازدید دیروز: 3097 :::::::: بازدید کل: 40283 :::::::: افراد آنلاین: 52