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8th Workshop on Communication Networks and Power Systems, WCNPS 2023

作者： Santos, Domingos Savio De O. Dantas, Douglas A. P. De Mattos Neto, Paulo S. G. Siqueira, Hugo Valadares Lima, Aranildo R. Madeiro, Francisco De Oliveira, Joao. F. L. Pereira, Alex C. Marinho, Manoel H. N. Universidade de Pernambuco Escola Politécnica de Pernambuco PE Recife Brazil Universidade Federal de Pernambuco Centro de Informática PE Recife Brazil Federal University of Technology-Paraná Graduate Program in Electrical Engineering PR Ponta Grossa Brazil Aquatic Informatics VancouverV6E 4M3 Canada PE Recife50761-901 Brazil

ISBN: (纸本)9798350343571

Multi-step solar irradiance forecast is an important part of a successful power grid management. However that forecast can be difficult due to nonlinear patterns and random fluctuation. This work applies statistical and machine learning methods to forecast solar irradiance time series from three different locations of Brazil. The applied models are: Autoregressive Integrated Moving Average (ARIMA), Deep Belief Network (DBN), Extreme Learning Machine (ELM), Multi Layer Perceptron neural network (MLP), Random Forest (RF), and Support Vector Regression (SVR). Taking into account these methods, an ensemble of them is proposed, which has the objective of reducing: the uncertainty of selecting a single model, overfitting, and underfitting. Compared with single models and based on two performance metrics, the ensemble found good overall results when applied in the time series with horizons of 6, 12 and 24 hours ahead. © 2023 IEEE.

关键词： Time series

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Handling Data Sparseness in Gene Network Reconstruction

Handling Data Sparseness in Gene Network Reconstruction

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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： G.B. Bezerra T.V. Barra F.J. von Zuben L.N. de Castro Laboratory of Bioinformatics and Bio-Inspired Computing (LBiC) Department of Computer Engineering and Industrial Automation State University of Campinas-UNICAMP Sao Paulo Brazil Graduate Program on Informatics Catholic University of Santos Sao Paulo Brazil

One of the main problems related to regulatory network reconstruction from expression data concerns the small size and low quality of the available dataset. When trying to infer a model from little information it is necessary to give much more precedence to generalization, rather than specificity, otherwise, any attempt will be fated to overfitting. In this paper we address this issue by focusing on data sparseness and noisy information, and propose a density estimation technique that achieves regularized curves when data is scarce. We first compare the proposed method with the EM algorithm for mixture models on density estimation problems. Next, we apply the method, together with Bayesian networks, on realistic simulations of static gene networks, and compare the obtained results with the standard discrete Bayesian network model. We intend to demonstrate that adopting a discrete approach is not justifiable when only a small amount of information is available.

关键词： Intelligent networks Bayesian methods Genetics Bioinformatics Computer networks Reverse engineering Cellular networks Noise robustness Laboratories Data engineering

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Feasibility study of Information Technology Investment (a case study of ODOO ERP: Project Management Module Implementation in Indonesia Based Company)

Feasibility study of Information Technology Investment (a ca...

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International Conference on ICT For Smart Society (ICISS)

作者： Fredy Jingga Raymond Kosala Suhono Harso Supangkat Benny Ranti Computer Science Department BINUS Graduate Program - Doctor of Computer Science Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to determine feasibility of implementation open source ERP system Odoo project management module that replaces current system based on operational, economic, and technical aspects. The method used are Fit / Gap Analysis and Cost Benefit model using economic impact worksheet. The analysis is done by comparing the requirement with features owned by current system and Odoo ERP system. This research resulted that Odoo ERP System is feasible in the 3 aspects, the operational feasibility Odoo reaching 72% Fit, the economic feasibility with ROI of 84%, and technical feasibility indicating the technical requirement can be fulfilled by leasing AWS server. The conclusion is the open source ERP system Odoo project management module is feasible to be applied in terms of 3 aspects that have been studied, those are operational, economic, and technical.

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Using equivalence classes for testing programs for safety instrumented systems

Using equivalence classes for testing programs for safety in...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Kézia de Vasconcelos Oliveira Angelo Perkusich Kyller Costa Gorgônio Leandro Dias da Silva Aldenor Falcão Martins Center of Electrical Engineering and Informatics Federal University of Campina Grande Campina Grande Paraiba Brazil Computing Institute Federal University of Alagoas Maceio Alagoas Brazil Graduate Program in Electrical Engineering Federal University of Campina Grande Campina Grande Paraiba Brazil

The reliability on Safety Instrumented Systems (SIS) is critical for the safe operation of many industrial applications. In particular, SIS play an important role in oil and gas processing plants. SIS are responsible not only for the continuous operation of the plant, it also keeps the plant in a safe state, avoiding damages to the environment and minimizing risks to employees. Therefore, the correct behavior of such systems is an important goal to achieve when building industrial plants. Verification and testing of SIS programs is a very hard task to accomplish. This happens mainly for two reasons. First, testing the real system is very expensive and sometimes it may take a huge amount of time, weeks or even months. Second, those systems deal with a huge number of variables. It is not always possible for a human tester to check if all of them are correct when performing tests. Providing an automatic and formal testing approach for such systems is an important contribution for the development of such systems. In this work we introduce a new method for generating test cases for SIS programs running on programable Logic Controller (PLC). As we did on previous work, ISA 5.2 diagrams are used as specification of the systems, but now we are using a hardware-in-the-loop technique, and the target artifact is a software running on a PLC. To avoid the execution of redundant tests, we introduced a new test case generation algorithm that is based on equivalence classes. Finally, we discussed a study case in which our method is used to detect error, that were introduced on purpose, on a simple system.

关键词： Automata Testing Safety Valves Input variables Computational modeling Instruments

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Enhanced Wireless Sensor Network setup strategy supported by intelligent software agents

Enhanced Wireless Sensor Network setup strategy supported by...

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IEEE SENSORS

作者： Edison Pignaton de Freitas Tales Heimfarth Ivayr Farah Netto Alex Guimarães Cardoso de Sá Carlos Eduardo Pereira Armando Morado Ferreira Flávio Rech Wagner Tony Larsson IDE Halmstad University Halmstad Sweden Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre Brazil Federal University of Lavras Lavras Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

A well know problem in the Wireless Sensor Network (WSN) research area is the usage of appropriate strategies to setup the sensor nodes such that they may accomplish sensing missions. This problem refers to the selection of appropriate nodes to perform the different tasks required to the missions' accomplishment and may be thus characterized as an instance of the task and resource allocation problem. Traditional approaches consider pre-planned strategies, which are not flexible to deal with changes in the network and environment operating conditions. This paper presents an enhanced agent-oriented strategy, which consists of a usage of mobile intelligent agents to disseminate missions and nodes' information over the network, as well as stationary software agents installed in the sensor nodes to provide advanced reasoning apparatus for decision making purposes. The proposed enhancement complements the original agent-based approach with robustness features required to overcome extreme adverse conditions in which an ordinary WSN presents poor results. Results from simulations provide evidences of the efficiency of the complete enhanced approach.

关键词： Wireless sensor networks Software agents Temperature sensors Conferences Atmosphere Accuracy

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An agent framework to support sensor networks' setup and adaptation

An agent framework to support sensor networks' setup and ada...

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International Multiconference on Computer Science and Information Technology, IMCSIT

作者： Edison Pignaton de Freitas Flávio Rech Wagner Tales Heimfarth Carlos Eduardo Pereira Armando Morado Ferreira Tony Larsson IDE - Halmstad University Sweden Computer Science Department UFLA Lavras Brazil Institute of Informatics UFRGS Porto Alegre Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil IDE - Halmstad University Halmstad Sweden

Sensor networks are being used in several emerging applications not even imagined some years ago due to advances in sensing, computing, and communication techniques. However, these advances also pose various challenges that must be faced. One important challenge is related to the autonomous capability needed to setup and adapt the networks, which decentralizes the control of the network, saving communication and energy resources. Middleware technology helps in addressing this kind of problem, but there is still a need for additional solutions, particularly considering dynamic changes in users' requirements and operation conditions. This paper presents an agent-based framework acting as an integral part of a middleware to support autonomous setup and adaptation of sensor networks. It adds interoperability among heterogeneous nodes in the network, by means of autonomous behavior and reasoning. These features also address the needs for system setup and adaptations in the network, reducing the communication overhead and decentralizing the decision making mechanism. Additionally, preliminary results are also presented.

关键词： Middleware Image sensors Computer networks Communication system control Energy resources Decision making

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A Data Management in a Private Cloud Storage Environment Utilizing High Performance Distributed File Systems

A Data Management in a Private Cloud Storage Environment Uti...

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IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises

作者： Tiago S. Soares M. A. R. Dantas Douglas D. J. de Macedo Michael A. Bauer Informatics and Statistic Department (INE) Federal University of Santa Catarina (UFSC) Post-Graduate Program of Knowledge Engineering and Management Federal University of Santa Catarina (UFSC) Computer Science Department (CSD) University of Western Ontario (UWO)

ISBN: (纸本)9781479904051

The new trend in the process of data-intensive management indicates the importance of a distributed file system for both Internet large scale services and cloud computing environments. I/O latency and application buffering sizes are two of a number of issues that are essential to be analysed on different class of distributed file systems. In this paper, it is presented a research work comparing four different high performance distributed file systems. Those systems were employed to support a medical image server application in a private storage environment. Experimental results highlight the importance of an appropriate distributed file system to provide a differential level of performance considering application specific characteristics.

关键词： Distributed File System DICOM HDF5 Telemedicine

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D-SRGAN: DEM Super-Resolution with Generative Adversarial Networks

arXiv

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arXiv 2020年

作者： Demiray, Bekir Z. Sit, Muhammed Demir, Ibrahim Department of Computer Science University of Iowa Iowa City United States Graduate Program in Informatics University of Iowa Iowa City United States Department of Civil & Environmental Engineering University of Iowa Iowa City United States

—LIDAR (light detection and ranging) is an optical remote-sensing technique that measures the distance between sensor and object, and the reflected energy from the object. Over the years, LIDAR data has been used as the primary source of Digital Elevation Models (DEMs). DEMs have been used in a variety of applications like road extraction, hydrological modeling, flood mapping, and surface analysis. A number of studies in flooding suggest the usage of high- resolution DEMs as inputs in the applications improve the overall reliability and accuracy. Despite the importance of high-resolution DEM, many areas in the United States and the world do not have access to high-resolution DEM due to technological limitations or the cost of the data collection. With recent development in Graphical Processing Units (GPU) and novel algorithms, deep learning techniques have become attractive to researchers for their performance in learning features from high-resolution datasets. Numerous new methods have been proposed such as Generative Adversarial Networks (GANs) to create intelligent models that correct and augment large-scale datasets. In this paper, a GAN based model is developed and evaluated, inspired by single image super-resolution methods, to increase the spatial resolution of a given DEM dataset up to 4 times without additional information related to data. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Fine Tuning Swin Transformer Based Pretrained Model for Microscopic Fungi Images Classification

Fine Tuning Swin Transformer Based Pretrained Model for Micr...

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International Conference on Computer, Control, informatics and Its Applications (IC3INA)

作者： Muchamad Galih Anggara Ahmad Hindasyah Julfa Muhammad Amda A. A. Waskita Graduate Program of Informatics Engineering Universitas Pamulang Pamulang Indonesia Research Center for Computing National Research and Innovation Agency Cibinong Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency Bandung Indonesia

ISBN: (数字)9798331542313

ISBN: (纸本)9798331542320

Accurate image classification of microscopic pathogenic fungi is a challenge in the field of mycology. This study proposes a Swin Transformer-based approach to automate the identification process. The Swin Transformer model, known for its ability to capture complex spatial interactions, is adapted from ImageNet’s pre-trained model. The adaptation process is focused on fine-tuning the final classification layer to match the 5 classes of fungi present in the dataset. This classification layer is replaced by a new fully-connected layer that has the number of output according to the number of fungal classes. The weights on these layers are randomly initialized and trained in conjunction with several final convolutional layers. In addition, regularization techniques such as dropouts are applied to prevent overfitting. Adaptation using 5-fold cross-validation was carried out to find the best fold with hyperparameters including AdamW optimizer with a learning rate of 10 −3 , StepLR scheduler, batch size of 128 images, and a total of 9 epochs / iterations. After that, fine-tuning is carried out on the best fold with hyperparameters including AdamW optimizer with a learning rate of 10 −5 , StepLR scheduler, batch size of 32 images, and a total of 100 epochs / iterations. The final result showed excellent performance, with accuracy, precision, recall and an average F1-score of 95%. These results show the potential of the Swin Transformer in becoming an effective tool for mycologists.

关键词： Fungi Training Digital control Adaptation models Accuracy Microscopy Transformers informatics Tuning Image classification

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An effective algorithm for computing all-terminal reliability bounds

An effective algorithm for computing all-terminal reliabilit...

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作者： Silva, Jaime Gomes, Teresa Tipper, David Martins, Lúcia Kounev, Velin Department of Informatics Engineering CISUC University of Coimbra Põlo 2 Pinhal de Marrocos Coimbra3030-290 Portugal Department of Physics CFC University of Coimbra Coimbra3004-516 Portugal Department of Electrical and Computer Engineering University of Coimbra Põlo 2 Pinhal de Marrocos Coimbra3030-290 Portugal INESC Coimbra Rua Antero de Quental 199 Coimbra3000-033 Portugal Graduate Telecommunications and Networking Program University of Pittsburgh PittsburghPA15260 United States

The exact calculation of all-terminal reliability is not feasible in large networks. Hence estimation techniques and lower and upper bounds for all-terminal reliability have been utilized. Here, we propose using an ordered subset of the mincuts and an ordered subset of the minpaths to calculate an all-terminal reliability upper and lower bound, respectively. The advantage of the proposed new approach results from the fact that it does not require the enumeration of all mincuts or all minpaths as required by other bounds. The proposed algorithm uses maximally disjoint minpaths, prior to their sequential generation, and also uses a binary decision diagram for the calculation of their union probability. The numerical results show that the proposed approach is computationally feasible, reasonably accurate and much faster than the previous version of the algorithm. This allows one to obtain tight bounds when it not possible to enumerate all mincuts or all minpaths as revealed by extensive tests on real-world networks. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 282-295 2015.

关键词： Binary decision diagrams

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