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Exploring Shifted Domain Problem within MNIST Dataset

Exploring Shifted Domain Problem within MNIST Dataset

引用

2023 International Conference on computer science, Information Technology and engineering, ICCoSITE 2023

作者： Hidayaturrahman Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusatara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Domain data can be shifted in any direction so it will be shared in different distributions to its original domain. This could be a problem since the model was trained with different distributions. It is found that adversarial domain adaptation using domain adversarial neural networks (DANN) can help to solve this problem on some scale. DANN can minimize the discrepancy between source and target data so the model can work well in both domains. The experiment is done by utilizing MNIST dataset that shifted into some conditions. In a condition when the shifting of distribution is too far, DANN is struggling to maintain the knowledge extracted from source data which leads to underperformance in the source and target domain. In contrast, when the shifting is closer, DANN can easily fit the model so it can perform well in both domains. It proves DANN is one of the good approaches to performing domain adaptation in small discrepancies. © 2023 IEEE.

关键词： Adversarial Domain Adaptation Domain Shifting Problem MNIST Transfer Learning

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The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

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2023 International Conference on Networking, electrical engineering, computer science, and Technology, IConNECT 2023

作者： Sirait, Tamsir Hasudungan Lumban Gaol, Ford Supangkat, Suhono Harso Ranti, Benny Bina Nusantara University Binus Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Universitas Indonesia Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350331172

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology. © 2023 IEEE.

关键词： Information management

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Optical-electrical probe for two-phase flow investigation

Optical-electrical probe for two-phase flow investigation

引用

IEEE Sensors

作者： Rosangela Winter Jean Carlos Cardozo da Silva Cicero Martelli Eduardo Nunes dos Santos Marco Jose da Silva Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University of Technology - Parana 3165 Curitiba Parana Brazil 80230-901

ISBN: (纸本)9781509010134

Experimental investigation of two-phase flows is important in many areas of research and industrial application. We introduce a probe based on electrical impedance and Fiber Bragg Grating-based strain measurements, which is able to monitor two-phase flow in pipes. The prototype probe presented consists of an optical fiber with a FBG for sensing encapsulated by a hollow stainless-steel cylinder, which is interrogated for strain and conductance measurements. Raw data is converted to flow parameters such as gas bubble length and velocity. Initial results in a two-phase flow test bench show that the combined optical-electrical technique is feasible and promising to be applied in two-phase flow monitoring.

关键词： flow measurement fiber Bragg grating impedance sensor optical sensor Fiber Bragg gratings TWO PHASE FLOW Flow measurement Probes optical sensors Strain measurement impedance Optical Fibers

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A discretized differential evolution algorithm for the inference of Gene Regulatory Networks

A discretized differential evolution algorithm for the infer...

引用

Latin America Congress on Computational Intelligence (LA-CCI)

作者： Leandro T. Hattori Heitor S. Lopes Fabrício M. Lopes Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University of Technology Curitiba Paraná Brazil Graduate Program in Bioinformatics (PPGBIOINFO) Federal University of Technology Paraná Brazil

Feature selection is a very important procedure in the pattern recognition research field. Feature selection algorithms are particularly important in the inference of Gene Regulatory Networks (GRNs) from its gene expression profiles, which usually involves data with a large number of variables and small number of observations. This work presents the inference of GRNs from two different feature selection approaches: classical (deterministic) SFS and SFFS search algorithms, and (meta-heuristic) Discretized Differential Evolution (DDE) algorithm. Several Artificial Gene Networks (AGNs) were probabilistically generated for testing. They had different sizes and topologies following three models: Erdös-Rényi uniformly-random, Watts-Strogatz small-world, and Barabási-Albert scale-free. Results confirm that, as the number of candidate predicting genes increase, the performance of the compared methods decrease, revealing the exponential characteristic of the problem. Notwithstanding, for all network sizes and topologies studies, the DDE algorithm achieved better results than the other approaches, especially for GRNs with hubs.

关键词： Inference algorithms Network topology Prediction algorithms Topology Bioinformatics Gene expression Entropy

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Boosting the Performance of MOEA/D-DRA with a Multi-Objective Hyper-Heuristic Based on Irace and UCB Method for Heuristic Selection

Boosting the Performance of MOEA/D-DRA with a Multi-Objectiv...

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Congress on Evolutionary Computation

作者： Lucas Prestes Myriam R. Delgado Ricardo Lüders Richard Gonçalves Carolina P. Almeida Graduate Program in Electrical and Computer Engineering UTFPR Computer Science Department UNICENTRO

Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamical Resource Allocation (MOEA/D-DRA) is one of the most successful decomposition based multiobjective algorithm. Its main feature is a mechanism to allocate different computational effort proportional to the difficult of each subproblem. Despite its success, MOEA/D-DRA has a large set of parameters and operators, whose selection could be a difficult task. This paper aims at improving the performance of MOEA/D-DRA by means of a hyper-heuristic using two parameter/operator selection phases: one off-line strongly based on Iterated Race Automatic Algorithm Configuration (Irace) and another one (online) based on the Upper Confidence Bound (UCB) technique. The proposed approach is compared with the original MOEA/D-DRA, NSGAII and IBEA over 51 instances of 7 well known benchmarks (CEC 2009, GLT, LZ09, MOP, DTLZ, ZDT and WFG). Results show that Irace and UCB are interesting methods to support the hyper-heuristic functioning when selecting parameters/operators of MOEA/D-DRA in the addressed problems.

关键词： Optimization Evolutionary computation Resource management Sociology Statistics Tuning Task analysis

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DCMSim: Didactic cache memory simulator 33

DCMSim: Didactic cache memory simulator

引用

33rd Annual Frontiers in Education, FIE 2003

作者： Cordeiro, Eduardo Santos Abdanur Stefani, Italo Giovani Do Amaral Pales Soares, Tays Cristina Da Silva Martins, Carlos Augusto Paiva Pontifical Catholic University of Minas Gerais Graduate Program in Computer Science 500 Av. Dom Cabral Coração Eucaristico Belo HarizonteMinas Gerais Brazil Pontifical Catholic University of Minas Gerais Graduate Program in Computer Science Graduate Program in Electrical Engineering 500 Av. Dom Cabral Coração Eucaristico Belo HarizonteMinas Gerais Brazil

ISBN: (纸本)0780379616

We present a functional and structural didactic simulator of Cache Memory Systems developed at the Pontifical Catholic University of Minas Gerais, Brazil. The development occurred during the undergraduate computer Architecture discipline, in the computer science course. Its implementation is one part of a new didactic method, in which developers (students of the computer Architecture discipline) must learn the concepts and theory of the discipline topics to correctly apply them in the simulator. In our simulator, DCMSim, there are features to allow students to construct and verify knowledge, testing and comparing several different configurations and memory access traces. © 2003 IEEE.

关键词： Cache memory

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Applying genetic algorithms to the information sets search problem

Applying genetic algorithms to the information sets search p...

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IEEE Latin-American Conference on Communications, LATINCOM

作者： José R. Hoffmann Marcos M. Tenório Emilio C. G. Wille Walter Godoy Graduate School of Electrical Engineering and Computer Science (CPGEI) Federal University of Technology of Paraná (UTFPR) Curitiba Parana Brazil

Error-correction coding is essentially a signal processing technique that is used to improve the reliability of digital communication systems. In the Information Set (IS) decoding a collection of information sets are used to generate candidate codewords. The procedure then selects as the decoded codeword the one which is closest to the received sequence. This decoding approach can reduces the complexity and time processing in comparison to maximum-likelihood decoding (MLD), and may presents the same decoding level. The performance of the IS algorithm depends on the number of error patterns that the collection of information sets can cover. There are no known constructive procedures for finding optimum collection of information sets. This paper presents an approach for obtaining optimum collections of information sets using genetic algorithms. Using this approach we found, in short time, collections of information sets with high covering capacity. Results from computer simulation show that the performance of the IS algorithm with optimized collections is nearly identical to the maximum-likelihood decoding.

关键词： Maximum likelihood decoding Genetic algorithms Biological cells Block codes Search problems Genetics

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Notification-Oriented and Rete Network Inference: A Comparative Study

Notification-Oriented and Rete Network Inference: A Comparat...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Adriano F. Ronszcka Roni F. Banaszewski Robson R. Linhares Cesar A. Tacla Paulo C. Stadzisz Jean M. Simão Graduate School in Electrical Engineering and Industrial Computer Science (CPGEI) Federal University of Technology - Parana (UTFPR) Curitiba PR Brazil

This paper presents a practical and a theoretical comparative study between the so-called Notification-Oriented Inference (NOI) and Rete Network inference. NOI is composed of a network of small computational entities, which communicate only when necessary, avoiding both temporal and structural redundancies in a program inference. The innovative aspect of the considered approach would be that computational entities carry out the inference by means of collaborations based upon direct notifications (reactive inference). This approach differs from usual inference mechanisms of rule-based systems, which are based on checks/searches over passive data. This search based execution is present even on advanced mechanisms such as Rete. In this sense, the focus of this paper is to analyze performance measurements over an experimental application implemented in both mechanisms. Coupling and redundancy problems are also considered in a theoretical analysis. The results show that NOI can perform around 6 times faster than the compiled Rete mechanism and around 20 times faster than the interpreted Rete mechanism in the cases proposed in this paper. Moreover, NOI presents better asymptotic complexity time and decoupling degree, presenting itself as a promising alternative to compose complex, distributed and scalable applications.

关键词： Redundancy Couplings Collaboration programming Correlation Engines Data structures

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Instant Messaging as Information Goldmines to Digital Forensic: A Systematic Review 3

Instant Messaging as Information Goldmines to Digital Forens...

引用

3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Sihombing, Harry Chandra Fajar, Ahmad Nurul Utama, Ditdit Nugeraha Mercu Buana University Master of Electrical Engineering Jakarta Indonesia Information Systems Management Department Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The use of instant messaging (IM) application is very communal among smartphone users, as it delivers ease in interaction and communication. The speed at which technologies, growth, and expansion of networks infrastructure for high-speed data networks (e.g. wifi, 4G, etc.) are changing and the high number of IM applications are available. IM application usage is significantly escalating, also for doing illegitimate purposes, particularly to organize and coordinate criminal acts. They are practically exploited by the criminality groups involved when they target and interact with the victims, or try to run away from criminal occurrences. By systematically conducting a review to understand and to investigate IM applications topic coming from a number of scientific sources (e.g. manuscripts, metadata, files, etc.), a broader picture and opportunity to regain the valuable evidence in the investigation is academically provided. © 2018 IEEE.

关键词： Smartphones

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction 3

Interpretable Machine Learning for Multi-Class Crop Yield Pr...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Nurcahyo, Aldian Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Compuer Science Binus Graduate Program Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia Doctor of Computer Science Bina Nusantara University Binus Graduate Program Compuer Science Departement Jakarta Indonesia

ISBN: (纸本)9798350394559

Crop Yield Analysis and Prediction is a fast-expanding discipline that is critical for optimizing agricultural methods. A lack of trustworthy data is one of the challenges in estimating crop yields. We develop predictive models for 22 different fruits and vegetables data. The goals of this study are to create accurate and interpretable crop recommendation models. We used multiple machine learning (ML) models for multi-class crop production prediction to fulfill our research goal. We thoroughly examined the influence of climate and nutrient factors on crop yield, considering their complex interactions. To improve the dataset, augmented data techniques were applied. Configuring the parameters and fine-tuning the hyperparameters is our technique to increase the model performance. Furthermore, we employ explainable artificial intelligence (XAI) techniques and interpretability tools like Shapley Additive exPlanations (SHAP) to improve the interpretability of our prediction model. Our findings reveal that the XGBoost model has the best performance model with 99.86% accuracy, followed by SVM Poly Kernel with 99.32% and Random Forest with 98.82%. Feature selection and analysis are emphasized, particularly in regional agricultural contexts. This study contributes to the creation of accurate and interpretable crop recommendation models while also addressing the issue of untrustworthy data, providing useful insights for optimizing agricultural practices. © 2023 IEEE.

关键词： Forecasting

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