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pattern recognition approach to Predict Renewable Energy Consumption

Pattern Recognition approach to Predict Renewable Energy Con...

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international Multi-Topic ICT conference (IMTIC)

作者： Asif Gulraiz Syed Sajjad Haider Zaidi Abdul Samad National University of Science and Technology Islamabad Pakistan Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9781665482950

the microgrid has been presented in recent years to meet energy requirements as a complementary option. the micro grid comprises of renewable generation, energy storage units and demand management via the low-voltage distribution network, which are part of the intelligent grid implementation. Renewable energy resources, including solar and wind energy, are now used worldwide because of the quick technological progress and environmental benefits. However, it is important to integrate renewable production in the micro grid in advance, for this reason, future power generation from renewable sources must now be predicted. Predicting future energy generation will be helpful in finding requirement for grid integration. Forecasting is the ability to determine periods of stable generation from renewable sources. In this paper a renewable energy generation is predicted which is comprised of solar and wind energy to know the requirements for energy in future. With the help of these results Grid will be configured well in advance to fulfill electricity generation requirements from renewable energy resources. ANN (Artificial Neural Network) and ARMA (Auto-Regressive Moving Average) models are used for prediction of different energy resources. Raw data is first processed using feature extraction technique and then it is used in ANN and ARMA modelling.

关键词： Renewable energy sources Wind energy Artificial neural networks Production Microgrids Predictive models Smart grids

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Development of Marker-Based Web Augmented Reality Educational Board Games for Learning Process Support in Computer Science

Development of Marker-Based Web Augmented Reality Educationa...

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Experiment@ international conference (exp.at)

作者： Oleksandr Blazhko Natalia Shtefan Department of Information Systems Odessa Polytechnic National University Odesa Ukraine Department of Information Technology Odessa State Environmental University Odesa Ukraine

ISBN: (数字)9798350314403

ISBN: (纸本)9798350314410

this article demonstrates the results of the implementation of the strategy while students are studying the topics of the discipline “Operating systems” based on the development of educational board games with augmented reality technology. Relationships between the development of education augmented reality board games and soft skills in computer science are shown. Recommendations on the use of play-components of game mechanics (random, select, manage, move, shoot, write) for board game elements (dice, coin, card, token) with paper markers are given.

关键词： Computer science Operating systems Education Games Teamwork pattern recognition Problem-solving

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Systematic Literature Review: Deep Learning and Machine Learning Analysis for Batik Peranakan Tionghoa Datasets

Systematic Literature Review: Deep Learning and Machine Lear...

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international conference on Cybernetics and Intelligent System (ICORIS)

作者： Mochammad Haldi Widianto Mulyani Karmagatri Rachmi Kumala Widyasari Aris Darisman Hazmilah Hasan Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Department RIG SMEEI Bina Nusantara University Jakarta Indonesia Interior Design Department Bina Nusantara University Jakarta Indonesia Communication Design Department Bina Nusantara University Jakarta Indonesia Faculty of Technology Management and Technopreneurship Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

this research focuses on searching for Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Systematic Literature Reviews (SLR). After that, the use of Deep Learning (DL) and Machine Learning (ML) will be analyzed. this study also presents a dataset that makes it possible to utilize ML and DL. SLR results obtained 21 research papers focusing on ML and DL analysis (classification and pattern recognition). However, both algorithms also have their respective advantages and disadvantages. For this reason, this research presents the advantages and disadvantages of both ML and DL analysis for Chinese Peranakan Batik.

关键词： Deep learning Machine learning algorithms Focusing Classification algorithms pattern recognition Intelligent systems Cybernetics Systematic literature review

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Identification and Sorting of Waste using Artificial Intelligence Based on Convolutional Neural Network

Identification and Sorting of Waste using Artificial Intelli...

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international conference on Electrical, Telecommunication and Computer Engineering (ELTICOM)

作者： Fahmi Fahmi Baharsyah Pratama Lubis Department of Electrical Engineering Universitas Sumatera Utara Medan INDONESIA

ISBN: (纸本)9798350320725

Indonesia is one of the biggest producers of waste in the world. Every day there is rubbish that is not thrown in the trash, those that have been thrown in its place but are still wrong in distinguishing the type of garbage. In general, one of the types of waste is based on its nature, some are easy to decompose (organic), and some are difficult to decompose (inorganic). this research introduces five organic and inorganic waste objects by seeing whether the system can read objects at every position in the background and the number of objects in 1 picture frame. this system uses Tensorflow with a sample of 100 images for each object. Each sample object is given an identifier according to the object’s name and type. the sample is given an identifier for the system to learn to recognize the patterns and shapes of objects from the data objects we take. the results showed that the average percentage of system accuracy in detecting objects reached 90%, with the highest data accuracy reaching 99% tested on the banana peel, leaves, grass, cardboard, styrofoam, broken glass, bottles, cans, and nails. Furthermore, the authors try to put two or more different objects in the same frame and produce an average percentage value of 90%, as well as testing two or more similar objects in one frame simultaneously and producing an average value of 90%. From the test results, grass and bottle objects are samples that do not have read errors in the system design. For testing two or more objects in one frame, the author puts two similar objects and objects of different types. the result is that the system can recognize objects in the frame.

关键词： Shape Neural networks Nails Glass products pattern recognition Object recognition Convolutional neural networks

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Radar Pulse Stream Deinterleaving Based on Interpretable Spiking Neural Network

Radar Pulse Stream Deinterleaving Based on Interpretable Spi...

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international conference on Electronic Engineering and Informatics (EEI)

作者： Zhenghao Luo Zhangmeng Liu CEMEE State Key Laboratory National University of Defense Technology Changsha China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

Radar pulse stream deinterleaving is an important part of electronic support measurement (ESM). However, most of the existing pulse stream deinterleaving methods can only run offline and have poor adaptability to data noise. In this paper, I have developed an interpretable spiking neural network to solve the problem of online deinterleaving of radar pulse streams under severe data noise conditions. Firstly, the PRI pattern information of the target radar is obtained from the database, and then the PRI pattern is loaded into the synaptic connection delay of the interpretable spiking neural network. In the process of continuous input of pulse stream, the pulse substream conforming to the correct pattern makes the voltage of the spiking neuron accumulate continuously. When the voltage of the goal spiking neuron exceeds the threshold, the corresponding radar pulse is successfully deinterleaving. For data noise such as the spurious pulse, the voltage caused by it gradually decays because it does not conform to the delay pattern of the proposed SNN. Simulation results demonstrate the superior performance of the proposed method.

关键词： Radar measurements Pulse measurements Simulation Noise Neurons Radar Spiking neural networks threshold voltage Delays pattern recognition

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A novel method for contrast enhancement of gray scale image based on shadowed sets

A novel method for contrast enhancement of gray scale image ...

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international conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Meysam Alavi Mehrdad Kargari Information Technology Management Tehran Iran

ISBN: (数字)9781728186290

ISBN: (纸本)9781728186306

Image processing is considered to be one of the basic components in intelligent and decision support systems. On the other hand, improving image contrast is one of the most challenging issues in the field of image processing, pattern recognition and machine vision. this process improves understanding the information in the image for the human viewer. this is especially of great importance for medical imaging because low light intensity and high noise levels make it difficult to accurately diagnose specific diseases as well as to document and analyze them. the main motivation in image enhancement is to modify the image properties so that it is suitable for viewing and application, which can be done by removing noise, sharpening the edge and improving contrast enhancement. Due to the importance of the subject, various methods have been proposed by researchers in this field. In this paper, a new method based on shadowed sets is presented to improve image contrast. the results show that this method has acceptable accuracy and efficiency compared to other image enhancement techniques.

关键词： Machine vision Image edge detection Signal processing pattern recognition Intelligent systems Image enhancement Noise level

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Blockchain-Based Multirole Authentication and Authorization in Smart Contracts with a Hierarchical Factory pattern

Blockchain-Based Multirole Authentication and Authorization ...

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Blockchain Computing and Applications (BCCA), international conference on

作者： Muhammad Bin Saif Sara Migliorini Fausto Spoto Department of Computer Science University of Verona Verona Italy

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

the recent spread of smart contracts in several application domains presents challenges in scalability, efficiency, management, and security. In this regard, some design patterns have been proposed to factorize common parts, prevent replicated deployment by promoting reusability, and apply some role-based access control (RBAC) techniques during smart contract execution. In particular, the factory pattern has been widely recognized as a common practice to solve the scalability issue, reducing also the increased gas costs related to both smart contract deployment and its subsequent use. However, in real-world applications, the factory pattern can be considered too limited since it only allows the instantiation of a single type or family of contracts. On the other side, no solutions have been proposed that tightly integrate a factory pattern with RBAC functionalities. In this paper, we propose an extension of the factory pattern, called the hierarchical factory pattern, which integrates a multirole authentication and authorization mechanism tailored explicitly to this pattern since it allows a secure, efficient, and role-specific interaction between the various layers of the hierarchy. the paper ends with some considerations about performance and scalability.

关键词： Authorization Costs Scalability Smart contracts Authentication Production facilities pattern recognition Blockchains Optimization

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Training of Sigmoidal FFANN using Zero Weight Initialization and Gaussian Learning Rates

Training of Sigmoidal FFANN using Zero Weight Initialization...

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2012 international conference on Computer Technology and Science(ICCTS 2012)

作者： Veenu Pravin Chandra .( Pursuing MTech(IT) 6th sem from USICT GGSIPUNew Delhi )

Neural networks has varying applications in the field of control problems to pattern recognition *** have been used to solve non linear transformation *** common paradigm is for randomizing the various parameters like random initialization of weights to *** first order or second order derivatives are used to minimize the *** this paper the neural network parameter weights are initialized to *** is a bias able method for randomization of the problem by initialization of weights to zero.

关键词： ANN–Artificial Neural Network,FFANN–Feed Forward Artificial Neural Network,Eta–Learning Rate parameter,BP–Back Propagation algorithm

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Brain Computer Interface by use of Electro-encephalograms from Right Frontal Area

Brain Computer Interface by use of Electro-encephalograms fr...

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international conference on Soft Computing and Intelligent Systems

作者： Takahiro Yamanoi Toshimasa Yamazaki Michio Sugeno Hisashi Toyoshima Shin-ichi Ohnishi Elie Sanchez Division of Life Science and Technology Hokkai-Gakuen University Department of Bioscience and Bioinformatics Kyushu Institute of Technology European Center for Soft Computing Edificio Cientifico Tecnologico Japan Technical Software Division of Electronics and Information Engineering Hokkai-Gakuen University MIF Faculty of Medicine The University of Mediterranean

ISBN: (纸本)9781467327428

In order to develop a brain computer interface (BCI), some of the present authors have investigated the brain activity during human recognition of characters and symbols representing directional meaning. they have recorded electroencephalograms (EEGs) from subjects viewing four types of arrows: "↑", "↓", "←" and "→" that were presented on a CRT. the arrows denote direction for upward, downward, leftward and rightward, respectively. Subjects were asked to read them silently. EEGs were averaged for each stimulus type and direction, and event related potentials (ERPs) were obtained. the equivalent current dipole source localization (ECDL) method has been applied to these ERPs. In both cases, ECDs were localized to areas related to the working memory for spatial perception, i. e. the right upper or the right middle frontal areas. And the opposite directional arrows had opposite dipoles in these areas. Taking into account these facts, the authors investigated a single trial EEGs of the subject precisely after the latency at 400ms, and determined effective sampling latencies for the discriminant analysis to four types of arrows. We sampled EEG data at latencies from 400ms to 900ms at 25ms intervals by the four channels such as Fp2, F4, C4 and F8. Data were resampled -1ms and -2ms backward. Results of the discriminant analysis with jack knife method for four types objective variates, the mean discriminant rate for seven sample subjects was almost 85%.

关键词： Component Electroencephalogram Directional symbol Silent reading Discriminant analysis Brain computer interface

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Effectiveness of marker-based augmented reality game on computational thinking skills and cognitive load for middle school students

Effectiveness of marker-based augmented reality game on comp...

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international conference on Advanced Learning Technologies (ICALT)

作者： Toluchuri Shalini Shankar Rao Ajay Shankar Tiwari Utanko Mitra Kaushal Kumar Bhagat Advanced Technology Development Centre Indian Institute of Technology Kharagpur West Bengal India

ISBN: (数字)9798350362053

ISBN: (纸本)9798350362060

Computational thinking (CT) gained significant importance in education, leading to a surge in the development of dedicated instructional platforms. the cultivation of students’ CT skills posed a challenge, often involving the introduction of abstract and challenging-to-visualize programming concepts. this study aimed to bridge this gap by introducing an augmented reality-based coding game—an interactive learning platform designed to facilitate students in acquiring programming skills and enhancing their grasp of computational thinking concepts. the augmented reality (AR) digital game is specifically directed towards fundamental CT skills, such as pattern recognition, decomposition, abstraction, and developing algorithms. To evaluate the effectiveness of the AR game in enhancing CT skills, a study was conducted with 124 middle school students, entailing in grades 6th and 8th. the experimental group (N = 63) utilized the AR game, while the control group (N = 61) relied on conventional text materials. the findings of the experiment strongly supported the integration of AR technology along with game-based learning as a means to enhance CT knowledge and skills while simultaneously reducing cognitive load.

关键词： Codes Education Games Writing Cognitive load Encoding pattern recognition

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