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Designing Wireless Sensor Network Routing on Agriculture Area Using the LEACH Protocol 3

Designing Wireless Sensor Network Routing on Agriculture Are...

引用

3rd International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2020

作者： Gitakarma, Made Santo Priyambodo, Tri Kuntoro Suyanto, Yohanes Sumiharto, Raden Wijayanto, Danur Universitas Gadjah Mada Post Graduate Program in Computer Science Yogyakarta Indonesia Universitas Gadjah Mada Department of Computer Science and Electronics Yogyakarta Indonesia Universitas Gadjah Mada Master Program of Computer Science Yogyakarta Indonesia

ISBN: (纸本)9781728184067

Microelectronic technology that supports the establishment of wireless sensor networks (WSN) has brought hope to the ease of Internet of Things (IoT) technology that can generate smart environments. A WSN consists of a collection of sensor nodes that are small, intelligent, and inadequate in storage, energy, and processing power. One of the well-known routing techniques in WSN is LEACH. There have been many LEACH studies and their development with random node distribution. Here we designed several scenarios in WSN routing with the position of the sensor nodes specified in the mapping area. MATLAB simulation results show network lifetime can be extended by reducing data packet size. In five experiments, the number of 40 nodes was the optimal number to extend network lifetime. Each scenario has advantages and disadvantages that can be referenced in developing the LEACH protocol. © 2020 IEEE.

关键词： Internet of things

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A Light Weight Multi-Head SSD Model for ADAS Applications 1

A Light Weight Multi-Head SSD Model for ADAS Applications

引用

1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020

作者： Lai, Chun-Yu Wu, Bo-Xun Lee, Tsung-Han Shivanna, Vinay Malligere Guo, Jiun-In National Chiao Tung University Department of Electronics Engineering and Institute of Electronics Hsinchu Taiwan National Chiao Tung University College Doctoral Program of Electrical and Computer Engineering Hsinchu Taiwan

ISBN: (纸本)9781665404839

Moving objects detection is considered as one of the prime safety indicators in the Advanced Driver Assistance System (ADAS). For implementing on resource-limited embedded platforms and still yield sufficient frame rate and quality, the paper proposes a lightweight multi-head single shot detector (SSD) model that strengthens the moving object detection significantly. The paper also introduces focal loss method to deal with imbalance problem of detecting pedestrians and bikes in training datasets (vehicles, bikes, and pedestrians). Lastly, the proposed lightweight network can be deployed on low-power embedded devices to achieve real-time processing performance (512x256) yielding 30fps. © 2020 IEEE.

关键词： Object detection

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The Implementation of Genetic Algorithm in Smote (Synthetic Minority Oversampling Technique) for Handling Imbalanced Dataset Problem 4

The Implementation of Genetic Algorithm in Smote (Synthetic ...

引用

4th International Conference on science and Technology, ICST 2018

作者： Tallo, Tince Etlin Musdholifah, Aina Study Program of Master of Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Department Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9781538658130

An imbalanced dataset is a condition that has a minority class which is a class has far fewer instance distributions than other classes. The imbalanced condition can affect the performance of standard classifier algorithms that lead to the biased of the results classification or tend to become a majority class. The SMOTE method overcomes the imbalanced masses by creating synthetic instances of minority classes. However, the implementation of SMOTE resulted in overgeneralization because generated instances have the same amount regardless of the distribution of instances. As a result, the boundaries between classes are unclear. The SMOTE-Simple Genetic Algorithm (SMOTE-SGA) method is used to determine the sampling rate of each instance in order to obtain unequal amounts of synthetic instances. The tests were performed using some imbalanced datasets by comparing the classification results measured using G-means and F-Measure. The results of the application of genetic algorithm at SMOTE can improve the classification result by obtaining better G-means and F-measure value. © 2018 IEEE.

关键词： Classification (of information)

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Utilization of Linguistic Data for Learner Assessment on e-Learning: Instrument and Processing 7

Utilization of Linguistic Data for Learner Assessment on e-L...

引用

7th International Conference on Informatics and Computing, ICIC 2022

作者： Yuniarti, Wenty Dwi Hartati, Sri Priyanta, Sigit Surjono, Herman Dwi Doctoral Program of Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Universitas Islam Negeri Walisongo Semarang Indonesia Universitas Gadjah Mada Department of Computer Science and Electronics Yogyakarta Indonesia Universitas Negeri Yogyakarta Faculty of Engineering Department of Informatics Engineering Education Yogyakarta Indonesia

ISBN: (纸本)9798350345711

The increasingly massive use of e-Learning illustrates the speed and need for innovation in learning. According to the National Higher Education Standards (SN-Dikti), constructive alignment is required between learning outcomes, processes, and assessments to properly implement learning in e-Learning. Assessment is an essential component of e-Learning. Unfortunately, the problem of assessment in e-Learning is still found. One of them is the limitations of e-Learning in accommodating and processing various assessment data, primarily linguistic. Even though the variety of assessment data, both numerical, linguistic, and a combination of the two, supports a comprehensive assessment. On the other hand, the accommodation of linguistic data raises problems regarding how to process of unifying linguistic data is carried out. Research related to linguistic data using computing with words has been carried out, but it still needs more precise results from the unification of the linguistic data. Therefore, this study proposes providing an assessment instrument to accommodate linguistic data in e-Learning, as well as showing how to process of unifying linguistic data is carried out using 2-Tuple Fuzzy Linguistic. This approach can avoid the loss of assessment information by presenting more informative and precise results in a 2-tuple (s, α) where s indicates the ability level, and α shows a comparison of abilities with other learners and the potential of the learner to achieve higher abilities. This proposal has the potential to be applied in a learner assessment system for higher education e-Learning. © 2022 IEEE.

关键词： Linguistics

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Pattern recognition and knowledge discovery from road traffic accident data in Ethiopia: Implications for improving road safety

Pattern recognition and knowledge discovery from road traffi...

引用

2011 World Congress on Information and Communication Technologies, WICT 2011

作者： Beshah, Tibebe Ejigu, Dejene Abraham, Ajith Snasel, Vaclav Kromer, Pavel IT Doctoral Program Addis Ababa University Addis Ababa Ethiopia Department of Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9781467301251

This research tries to view accident data collection and analysis as a system that requires a special view towards understanding the whole and making sense out of it for improved decision making in the effort of reducing the problem of road safety. Under the umbrella of an information architecture research for road safety in developing countries, the objective of this machine learning experimental research is to explore and predict the role of road users on possible injury risks. The research employed Classification and Adaptive Regression Trees (CART) and RandomForest approaches. To identify relevant patterns and illustrate the performance of the techniques for the road safety domain, road accident data collected from Addis Ababa Traffic Office is exposed to many sided analyses. Empirical results showed that the models could classify accidents with promising accuracy. © 2011 IEEE.

关键词： Developing countries

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Amniotic fluid segmentation based on pixel classification using local window information and distance angle pixel

Amniotic fluid segmentation based on pixel classification us...

引用

作者： Ayu, Putu Desiana Wulaning Hartati, Sri Musdholifah, Aina Nurdiati, Detty S. Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia Department of Obstetrics and Gynecology Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia Department of Information Technology Faculty Computer and Informatics Institut Teknologi dan Bisnis STIKOM Bali Denpasar Indonesia

The amniotic fluid surrounds and protects the fetus from colliding with one another during the uterus development process. It also protects the umbilical cord from the uterine wall pressure, helps fetus movement, and develops muscles and bones. Selection of the most profound areas of improper and withdrawal points are not straight caliper is very likely that affect the outcome screening. Furthermore, there are similarities in texture and gray level between objects, especially in the boundary area between amniotic fluid and other objects, such as the placenta and uterus, which causes the border area to be less clear. Therefore, this research proposes a novel pixel classification model to separate amniotic fluid from other objects with a limit on the specified window size to solve this issue. In contrast to the most existing semantic segmentation methods or pixel-wise classification, we use the sampling window technique to construct train sets of data to produce pixel-level information more specifically in certain areas. Furthermore, each window extracts pixel information on gray level features and local variance (GLLV), using a novel Distance Angle Pixel (DAP). To evaluate the proposed model performance, we perform an extensive comparison with state-of-art methods by testing it on amniotic fluid ultrasound images. The results showed that the proposed model with a 3 × 3 window and random forest classifier could achieve the best value using an average Dice similarity coefficient (DSC) of 0.876, Jaccard/IoU of 0.768, and Pixel accuracy of 85.7%. The proposed model has 0.324 DSC improved from U-Net, 0.046 from gray-level pixel classification, 0.092 from thresholding, 0,252 from active contour, and 0.19 from rectangle window sampling. © 2021

关键词： Pixels

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Modeling a PV panel using the manufacturer data & a hybrid adaptive method 8

Modeling a PV panel using the manufacturer data & a hybrid a...

引用

8th International Conference on electronics, computers and Artificial Intelligence, ECAI 2016

作者： Enache, Bogdan-Adrian Bîrleanu, Florin-Marian Rǎduţ, Marin Department of Electronics Computer Science and Electrical Engineering University of Pitesti Pitesti Arges Romania Faculty of Electronics Communications and Information Technology Doctoral School of Applied Electronics and Information Technology Bucharest Romania

ISBN: (纸本)9781509020461

This paper presents a new method for establishing the series and parallel resistors for the one-diode model of a PV panel. The proposed method uses only the PV panel data that are provided by the manufacturer to train a feed-forward neural network that computes the values of the two resistors. The developed model is validated by comparing it to a classic one diode model whose resistors are determined through Newton-Raphson method. © 2016 IEEE.

关键词： Newton-Raphson method

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Optimation Cavacity Vehicle Routing Problem with K-Nearest Neighbor in Classification of Goods Ditribution Route 7

Optimation Cavacity Vehicle Routing Problem with K-Nearest N...

引用

7th IEEE International Conference of computer science and Information Technology, ICOSNIKOM 2023

作者： Novelan, Muhammad Syahputra Efendi, Syahril Sihombing, Poltak Mawengkang, Herman Universitas Sumatera Utara Doctoral Program of Computer Science Faculty of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Department of Computer Science Medan Indonesia Universitas Sumatera Utara Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia

ISBN: (纸本)9798350360752

Industrial and distribution service problems that belong to combinatorial optimization include vehicle routing with Vehicle Routing Problem. This research builds a framework and implements it in a multi-class optimization model to reduce overfitting and misclassification results caused by unbalanced multiclassification in the influence of the number of 'nodes' on vehicle routes with machine learning. The problem of imbalance in vehicle route classification has been a challenge in the classification process and attracted the attention of a number of researchers. The purpose of the model in general is to gain an understanding of the mechanism in the problem so as to classify the imbalanced vehicle route data based on JNE delivery routes. The solution method that will be used by applying k-nearest neighbor to determine the amount of carrying capacity of the goods will then determine the delivery location point with the vehicle routing problem. So that this model can be a model in determining vehicle routes based on the capacity limit of the number of shipments of goods. © 2023 IEEE.

关键词： Machine learning

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A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization 7

A Study on Text Feature Selection Using Ant Colony and Grey ...

引用

7th International Conference on Informatics and Computing, ICIC 2022

作者： Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri Universitas Gadjah Mada Doctoral Program Dept. of Computer Science and Electronics Indonesia Universitas Mulawarman Faculty of Engineering Dept. of Informatics Samarinda Indonesia Universitas Gadjah Mada Faculty of Mathematics and Natural Sciences Dept. of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Text classification (TC) is widely used for organizing digital documents. The issues in TC are numerous characteristics and high-element dimensions. Many pattern classification issues require feature selection (FS), which is pertinent. FS removes unneeded and redundant data from the dataset. The Ant Colony Optimization (ACO) and Grey Wolf Optimizer (GWO) for FS are the main topics of our thorough assessment of the literature on the Swarm Intelligence (SI) algorithm. Furthermore, it illustrates how the hybrid SI technique is used in FS across various sectors. The hybrid SI technique uses applicable data from various FS methods to find feature subsets with smaller sizes and better classification performance than those found by regular FS algorithms. © 2022 IEEE.

关键词： Ant colony optimization

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A Systematic Integrated Literature Review of Clinical Data Management Platforms of HL7 FHIR 24

A Systematic Integrated Literature Review of Clinical Data M...

引用

24th IEEE International Conference on High Performance Computing and Communications, 8th IEEE International Conference on Data science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Walter Viktor Walter-Tscharf, Franz Frederik Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology Doctoral Program Industrial Innovation Department of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350319934

This study is dedicated to a critical investigation of the existing approaches toward a data visualization management platform based on Fast Health Interoperability Resources (FHIR). Despite the growing popularity of FHIR, the available evidence provides a compelling reason to believe that its use is still accompanied by a significant number of technical challenges. Therefore, the development of tools to ensure its convenient visualization remains a pressing need for a variety of stakeholders operating in the healthcare industry. Results of the systematic literature review that included 26 studies provide valuable information about the most popular instruments in this area, such as the OpenEHR CKM approach. The review offers a critical discussion of the most important advantages and disadvantages of different approaches. It provides valuable recommendations for further research as well as practical recommendations concerning the best ways to utilize data visualization platforms based on FHIR. It defines the tradeoff of functionality versus the ease of dissemination as one of the most important problems facing most platforms and suggests avenues for developing additional tooling support for visualizing FHIR. The results of the research could be useful both for scientists and practitioners. © 2022 IEEE.

关键词： Data visualization

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