检索结果-内蒙古大学图书馆

1st IEEE Mysore Sub Section international conference, MysuruCon 2021

作者： Caffarena, Gabriel Raya, Rafael Urendes, Eloy Otero, Abraham Mennard, Daniel Escuela PolitÃ©cnica Superior University CEU-San Pablo Madrid Spain Insa Rennes Umr Cnrs Ietr Rennes France

ISBN: (纸本)9780738146621

Embedded systems play a major role in the development of future biomedical devices. Teaching embedded systems in degrees that are not completely focused on electronics is a challenge. It is common that the students perceive courses such as Digital Electronics and Embedded Systems as difficult and disconnected with other subjects as programming and Signal Processing. A way to alleviate this situation and to improve the learning process is to see embedded systems as a means to integrate concepts from Signal Processing, Computer programming and Electronics, as well as the practical aspect of the implementation of actual medical devices. In this paper, an example of the design of a course on embedded systems is presented. It allows securing concepts such as sampling theory, digital filtering, concurrency, real-time programming, etc., without sacrificing the technical basis of embedded systems: CPU architecture, low-level programming, interrupts, interaction with peripherals, etc. Also, implementation techniques such as fixed-point design can be covered. A real-time heart beat detection systems is presented as a case study. © 2021 IEEE.

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

MILP-FBGen: LP/MILP instance generation with feasibility/boundedness 24

MILP-FBGen: LP/MILP instance generation with feasibility/bou...

引用

Proceedings of the 41st international conference on Machine Learning

作者： Yahong Zhang Chenchen Fan Donghui Chen Congrui Li Wenli Ouyang Mingda Zhu Junchi Yan AI Lab Lenovo Research Beijing China School of Artificial Intelligence & Department of Computer Science and Engineering & MoE Lab of AI Shanghai Jiao Tong University Shanghai China

Machine learning (ML) has been actively adopted in Linear programming (LP) and Mixed-Integer Linear programming (MILP), whose potential is hindered by instance scarcity. Current synthetic instance generation methods often fall short in closely mirroring the distribution of original datasets or ensuring the feasibility and boundedness of the generated data -- a critical requirement for obtaining reliable supervised labels in model training. In this paper, we present a diffusion-based LP/MILP instance generative framework called MILP-FBGen. It strikes a balance between structural similarity and novelty while maintaining feasibility/boundedness via a meticulously designed structure-preserving generation module and a feasibility/boundedness-constrained sampling module. Our method shows superiority on two fronts: 1) preservation of key properties (hardness, feasibility, and boundedness) of LP/MILP instances, and 2) enhanced performance on downstream tasks. Extensive studies show two-fold superiority that our method ensures higher distributional similarity and 100% feasibility in both easy and hard datasets, surpassing current state-of-the-art techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Human Computer Interaction Using Arduino and Python

Human Computer Interaction Using Arduino and Python

引用

international conference on Computational science and Technology (ICCst)

作者： C Cibi G Vivekanandhan R Abhinav Krishna S Hemavathi CSE Department Sri Sairam Engineering College Chennai India

ISBN: (纸本)9781665476560

Due to the wide range of applications and the effectiveness of human computer recognition, hand gesture recognition systems have drawn a lot of interest in recent years. Computer functions can be controlled by hand motions thanks to hand gesture control. The play, stop, rewind, volume up, and volume down buttons may all be operated using this hand gesture control. Python programming and Arduino can be used to accomplish it. On detect hand movement, we will externally fix two ultrasonic sensors to laptop computers. PyAutoGUI, a built-in Python library, will be used by us. The Arduino board is attached to the ultrasonic sensor's output pin. Based on predefined movements, the Arduino commands the laptop to carry out the necessary multimedia function.

关键词： Human computer interaction Portable computers Scientific computing Gesture recognition programming Acoustics Libraries

来源：评论

学校读者我要写书评

暂无评论

Evaluating Effects of Power Sector Regulation on System stability during Optimal Operation of Nigeria's 330kV Power Grid 1

Evaluating Effects of Power Sector Regulation on System Stab...

引用

1st international conference on Multidisciplinary engineering and Applied science, ICMEAS 2021

作者： Ukiwe, Ezechukwu Kalu Adeshina, steve A. Jacob, Tsado Nile University of Nigeria Electrical-Electronic Engineering Dept Abuja Nigeria Nile University of Nigeria Computer Engineering Dept Abuja Nigeria Federal University of Technology Electrical-Electronic Engineering Dept Minna Nigeria

ISBN: (纸本)9781665434935

After 15 years of power sector regulation in Nigeria, a retrospective look at the impact of regulation to optimal system operation is necessary. This paper evaluates the effects of regulation on system stability. The 330kV 52 bus arrangement of the Nigeria Power system was modeled and simulated using DC Optimal Power Flow (DCOPF) in General Algebraic Modeling System (GAMS). The objective function of the DCOPF model was formulated to minimize the total cost of system operation, as generation limits of the Hydro Electric Plants (HEP)s at Kainji, Jebba and Shiroro were varied and prioritized over other grid connected thermal plants. The base case was simulated without priority dispatch and the test case was examined under priority dispatch of the HEPs with progressive variation of the priority generation level of the Kainji HEP. The results indicate that raising the lower generation limits of the HEPs can improve system stability by 2.7%. The importance of Regulatory Impact Assessment (RIA) was established to avoid policy summersaults. © 2021 IEEE.

关键词： Linear programming

来源：评论

学校读者我要写书评

暂无评论

A Prefatory Analysis of Brain Computer Interfacing Based On EEG 1

A Prefatory Analysis of Brain Computer Interfacing Based On ...

引用

1st international conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Pathre, Ayonija Veenadhari, S. Department of Computer Science and Engineering Rabindranath Tagore University Madhya Pradesh Bhopal India

ISBN: (纸本)9781607685395

An extremely developing area of application systems science is defined by brain programming interface technology. In health fields, its contributions range from treatment to synaptic healing for severe injuries. The special fingerprint of mind reading and remote contact in several areas, such as education, self-regulation, manufacturing, marketing, protection, entertainment & games. It induces shared trust between consumers & systems around them. Deep learning has already received mainstream recognition and has been used in numerous applications like natural language processing (NLP), computer vision & voice. For MI EEG signal classification however, deep learning has seldom been used. This paper highlights the fields of application that could advantage from brain waves in promoting or attaining their objectives. We also answer big usableness & technological problems facing the use of brain signals in different BCI device components. Various solutions aimed at minimizing and reducing their effects have also been studied. The popular spatial pattern (CSP) approach, which is generally utilized is applied to extract variance-based CSP functions, that are then fed for classification to DNN. DNN practice has been thoroughly studied for classification of MI-BCI & best framework found has been explored. © The Electrochemical Society

关键词： BCI Deep Neural Network (DNN) Electroencephalography (EEG) Motor Imagery

来源：评论

学校读者我要写书评

暂无评论

An Investigation into the Practical Use of Internet of Things Technology in Smart City Applications

An Investigation into the Practical Use of Internet of Thing...

引用

Cognitive, Green and Ubiquitous Computing (IC-CGU), international conference on

作者： Rashmi Prava Das Debendra Muduli Ashish Kumar Luhach Computer Science and Engineering Department CV Raman Global University Bhubaneswar India Department of Electrical and Communication Engineering Papua New Guinea University of Technology Lae Morobe Papua New Guinea

ISBN: (数字)9798350361780

ISBN: (纸本)9798350361797

This study presents a comprehensive method of mixing randomly generated simulated datasets to analyze several Internet of Things (IoT) applications in the context of smart cities Using matplotlib and numpy libraries, combined with Python programming language, analysis simulate real-time data on temperature, air quality and energy consumption. The learning methodology includes making pie charts, line plots, bar graphs etc. to present the findings graphically for understanding the application of Internet of Things in smart cities. Devery of smart city experiences, weather water system, traffic reduction, temperature over time, smart homes, smart parking areas. From temperature change to smart home to parking lot and city specific of car reduction experiences, each model provides insight into the dynamic features of a smart city implementation method of learning that combines visual techniques and simulated randomly produced information providing a strong foundation for analyzing potential technological impacts Enhances the discussion on smart and sustainable urban development towards the goal of creating resilient and adaptive smart cities.

关键词： Temperature distribution Visualization Fluctuations Smart cities Smart homes Real-time systems Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Analysis of Skin Cancer Classification using Deep Learning Techniques

Analysis of Skin Cancer Classification using Deep Learning T...

引用

Innovative engineering sciences and Technological Research (ICIEstR), international conference on

作者： S. Muthuselvi R. Sumathi Department of Computer Applications Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India

ISBN: (数字)9798350348637

ISBN: (纸本)9798350348644

Skin cancer is defined as abnormal development and proliferation of skin cells. It is in various steps. Malignant skin cancer is classified into different kinds: carcinoma of the basal cell, carcinoma of the squamous, and melanoma or melanocytic carcinoma. Each of these is called by its name because it occurs in specific cells. Cancer tumors can be observed because skin cancer occurs in the upper layer of the skin, the epidermis. Unlike other cancers, these can be detected and treated at an early stage, which is why the death rate from this type of cancer is relatively low. The primary cause of skin cancer is prolonged exposure to ultraviolet rays emitted by radiation. Melanoma along with additional skin cancers are more prevalent in the general population than lung, colon, breast, and prostate tumors. Melanoma is the deadliest form of malignancy of the skin and has a high death rate compared to other skin cancers, although melanoma is less common in the general population. Among the most common skin cancers are non-melanoma skin cancers. Some people have the possibility of developing melanoma later in life because of a large birthmark (large mole) that appears at birth or later due to melanocytes. Therefore, evidence-based automatic identification of cancer of the skin is useful for improving pathologists' precision and competency in their initial phase. In this work, we suggest a model developed by RCNN deep learning for accurately distinguishing between malignant and benign lesions in the skin. First, we implement a filter or kernel programming to remove noise and artifacts; then, we normalize the source pictures and determine characteristics assisting in precise classification. Furthermore, data enrichment builds up the overall count of images, which gets a better classifying rate its precision. The performance of our proposed RCNN model is comparable to other transfer learning approaches like the algorithm AlexNet, ResNet, The VGG model 16, DenseNet, MobileNet,

关键词： Deep learning Training Transfer learning Noise Mortality Melanoma programming Data models Skin cancer Testing

来源：评论

学校读者我要写书评

暂无评论

Networked Nanoparticle Arrays for Autonomous Computing: (Invited Paper)

Networked Nanoparticle Arrays for Autonomous Computing: (Inv...

引用

IEEE conference on Nanotechnology

作者： Xingfei Wei Ewa Harazinska Yinong Zhao Rigoberto Hernandez Department of Chemistry Johns Hopkins University Baltimore Maryland USA Department of Chemical & Biomolecular Engineering Johns Hopkins University Baltimore Maryland USA Department of Material Science & Engineering Johns Hopkins University Baltimore Maryland USA

ISBN: (数字)9798350386240

ISBN: (纸本)9798350386257

We have pursued the use of polymer-networked engineered nanoparticles as a candidate material capable of retaining information or perhaps even processing information in some prescribed way. Such operations would be of use for the neuromorphic engineering of materials that can compute intrinsically-that is, that they are in no way subject to a von Neumann architecture-and they have been identified as autonomous computing materials. Using trajectories integrated to much longer time steps than previously observed, we can now confirm that the response of the polymer-networked engineered nanoparticle arrays are highly sensitive to external perturbations. That is, the specific internal connections around given nanopar-ticles can be assigned to states useful for information processing, and the variations in their physical properties can result in specific responses allowing the state to be read. Moreover, their resulting equilibrium properties also depend on such external driving, and hence are subject to control which is a minimal requirement for these materials to be candidates for autonomous computing. We also demonstrate that using long polymer chains can help regulate the networks structures by increasing the 1st nearest links and reducing other links.

关键词： Nanoparticles Training Neuromorphic engineering Perturbation methods Time series analysis Anisotropic programming

来源：评论

学校读者我要写书评

暂无评论

A Knowledge Graph-Based Deep Learning Framework for Efficient Content Similarity Search of Sustainable Development Goals Data

引用

Data Intelligence 2023年第3期5卷 663-684页

作者： Irene Kilanioti George A.Papadopoulos School of Electrical and Computer Engineering National Technical University of Athens9 Heroon Polytechneiou St.Zografou Campus Athens15780Greece Department of Computer Science University of Cyprus1 University AvenueAglantziaCY-2109NicosiaCyprus

Sustainable development denotes the enhancement ofliving standards in the present without compromising future generations'*** Development Goals(SDGs)quantify the accomplishment of sustainable development and pave the way for a world worth living in for future *** can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data,as intended by this *** propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves(HSFCs)in order to semantically cluster new uncategorised SDG data and novel indicators,and efficiently place them in the environment of a distributed knowledge graph ***,a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment,for retrieval of indicators and loadbalancing along with an approach for data classification of entrant-indicators is ***,a thorough case study in a distributed knowledge graph environment experimentally evaluates our *** results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data,including intergovernmental organizations,government agencies and social welfare *** approach empowers SDG knowledge graphs for causal analysis,inference,and manifold interpretations of the societal implications of SDG-related actions,as data are accessed in reduced retrieval *** facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching,as semantic cohesion of data is preserved.

来源：评论

学校读者我要写书评

暂无评论

Intelligent Differential Evolution-Dingo Metaheuristic for Efficient structural Optimization of Cantilever Beam Designs

Intelligent Differential Evolution-Dingo Metaheuristic for E...

引用

Computational Intelligence Approaches and Applications (ICCIAA), international conference on

作者： Hussam Fakhouri Mohammed Akhoirshida Data Science and Artificial Intelligence Department University of Petra Amman Jordan Engineering and Computer science San Francisco Bay University California USA

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

This paper introduces a Hybrid Differential Evolution-Dingo Optimization Algorithm (DE-DOA) and applies it to the cantilever beam design problem. Cantilever beams, widely used in structural and mechanical engineering, demand an optimal balance between material usage and performance constraints (e.g., stress and deflection). Traditional optimization methods often face challenges in efficiently exploring the highly nonlinear design space and avoiding local optima. The proposed hybrid approach harnesses the global exploration capability of Differential Evolution (DE) to traverse complex search landscapes, followed by the Dingo Optimization Algorithm (DOA), which refines and exploits the most promising regions. Benchmark evaluations on CEC2017 functions and comparisons with other state-of-the-art algorithms highlight the method's robust performance and improved solution quality. When applied to cantilever beam optimization, Hybrid DE-DOA consistently achieves lower objective values with minimal variance, confirming its reliability and effectiveness. The results demonstrate that combining DE's exploratory power with DOA's cooperative “hunting” strategies offers an efficient and accurate framework for engineering optimization problems, particularly where structural reliability and computational efficiency are paramount.

关键词： Navigation Metaheuristics Benchmark testing Reliability engineering Large-scale systems structural beams Mechanical engineering Optimization stress standards

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：