研究者詳細 - ケッペン　マリオ

論文 - ケッペン　マリオ

分割表示83 件中 1 - 20 件目／全件表示 >>

A metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms 査読有り国際誌

Pamucar D., Deveci M., Gokasar I., Tavana M., Köppen M.

Technological Forecasting and Social Change 182 2022年09月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Metaverse comes from the meta-universe, and it is the integration of physical and digital space into a virtual universe. Metaverse technologies will change the transportation system as we know it. Preparations for the transition of the transportation systems into the world of metaverse are underway. This study considers four alternative metaverses: auto-driving algorithm testing for training autonomous driving artificial intelligence, public transportation operation and safety, traffic operation, and sharing economy applications to obtain sustainable transportation. These alternatives are evaluated on thirteen sub-criteria, grouped under four main aspects: efficiency, operation, social and health, and legislation and regulation. A novel Rough Aczel–Alsa (RAA) function and the Ordinal Priority Approach (OPA) method are used in the assessment model. We also present a case study to demonstrate the applicability and exhibit the efficacy of the assessment framework in prioritizing the metaverse implementation alternatives.

DOI： 10.1016/j.techfore.2022.121778

Scopus

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Prioritizing transport planning strategies for freight companies towards zero carbon emission using ordinal priority approach 査読有り国際誌

Pamucar D., Deveci M., Gokasar I., Martínez L., Köppen M.

Computers and Industrial Engineering 169 2022年07月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Freight transportation counts for remarkable negative effects like emissions, noise, and congestion. This urges for a modal shift toward structuring a more efficient systematic network, facilitating full use of potentials among the transportation modes. Decision-makers face uncertainty and restricted information processing skills when assessing the alternatives for sustainable freight transportation. In this study, a novel extension of the Ordinal Priority Approach under picture fuzzy sets (OPA-P) is proposed to rank the alternatives. In the OPA-P algorithm, experts’ preferences are used to determine the weighting coefficients of criteria and rank the alternatives. A case study is employed to demonstrate the formulation and solution of the problem. The outcome of this study suggests the top-ranked and most important solution for the sustainable transport planning. In addition, to verify the stability of the proposed model, a validation analysis is carried out.

DOI： 10.1016/j.cie.2022.108259

Scopus

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Implementing a Hand Gesture Recognition System Based on Range-Doppler Map 査読有り国際誌

Jhaung Y.C., Lin Y.M., Zha C., Leu J.S., Köppen M.

Sensors 22 ( 11 ) 2022年06月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

There have been several studies of hand gesture recognition for human–machine interfaces. In the early work, most solutions were vision-based and usually had privacy problems that make them unusable in some scenarios. To address the privacy issues, more and more research on non-vision-based hand gesture recognition techniques has been proposed. This paper proposes a dynamic hand gesture system based on 60 GHz FMCW radar that can be used for contactless device control. In this paper, we receive the radar signals of hand gestures and transform them into human-understandable domains such as range, velocity, and angle. With these signatures, we can customize our system to different scenarios. We proposed an end-to-end training deep learning model (neural network and long short-term memory), that extracts the transformed radar signals into features and classifies the extracted features into hand gesture labels. In our training data collecting effort, a camera is used only to support labeling hand gesture data. The accuracy of our model can reach 98%.

DOI： 10.3390/s22114260

Scopus

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Supporting farming smart documentation system by modular blockchain solutions 査読有り国際誌

Arsyad, A. A., Widayat, I. W., & Köppen, M.

Decision Making: Applications in Management and Engineering 5 ( 1 ) 1 - 26 2022年03月

SUPPORTING FARMING SMART DOCUMENTATION SYSTEM by MODULAR BLOCKCHAIN SOLUTIONS 査読有り国際誌

Arsyad A.A., Widayat I.W., Köppen M.

Decision Making: Applications in Management and Engineering 5 ( 1 ) 1 - 26 2022年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

For more than a decade, various farm-specific models have been developed by collaborating and integrating sensing technologies as a step toward successful data-farm documentation and effective decision-making. However, the stored and gathered data continues to rely on cloud infrastructure or centralized platform control, which is particularly vulnerable to threats such as data tampering, data distortion, confidentiality, and manipulation, which caused the farm product data difficult to trace to its provenance. The objective study in this paper proposes a farm transaction model by demonstrating a flow of farm transaction simulation implicated by Modular Block Chain(MBC) sensing instrument with an array of sensors, controllers, networking hardware, computing equipment, and internal memory functions to enhance data integrity and security farm object. Based on the proposed model, a proof-of-concept experimental system called Encapsulating Block Mesh (EBM) integrates blockchain technology with the specific application case of cocoa production has been implemented. Results have shown that farm objects represented by MBC take turn recording information on the process of generating, transacting, and consuming a farm product and encrypting it into a block was validated and linked in the EBM with the hash of transaction data that connected to each cocoa farm object in a simulation environment. The findings from this study are twofold: the approach has been shown to be feasible and effective, but also capable to be expanded to other stages of the food supply chain, such as manufacturing, supermarkets, food consumption (consumers), and recycling in real-world environments.

DOI： 10.31181/dmame0326022022a

Scopus

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Personal Mobility in Metaverse With Autonomous Vehicles Using Q-Rung Orthopair Fuzzy Sets Based OPA-RAFSI Model 査読有り国際誌

Deveci M., Pamucar D., Gokasar I., Koppen M., Gupta B.B.

IEEE Transactions on Intelligent Transportation Systems 2022年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

The term metaverse, which shows a 3D-designed virtual medium where people can connect through their avatars to spend time, telecommute, and socialize, has entered our lives fast. There are limitless implementations that can take place in the metaverse. Integration of another technological innovation, which is autonomous vehicles to the metaverse, is at hand. There are numerous alternative uses of autonomous vehicles in the metaverse. In this study, three alternative implementation options for autonomous vehicles in the metaverse are investigated. These alternatives are evaluated using the proposed multi-criteria decision-making (MCDM) method under twelve different criteria, which are grouped under four main aspects, namely technological, societal, legal and ethical, and transportation. A novel hybrid model based on q-rung orthopair fuzzy sets (q-ROFSs) which consists of three stages is presented to express the framework definition, calculate the weight coefficients of the criteria, and rank various alternatives. In the first stage, the structure of the problem is created. In the second stage, q-ROFSs based OPA algorithm is used to calculate the weights of the criteria. In the last stage, q-ROFSs based RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval) is applied to choose the best alternative among the three alternatives. Finally, we present a case study to verify our proposed method. The results of this study have the potential to be used as a guide by decision-makers of the metaverse while integrating autonomous vehicles into the transportation system.

DOI： 10.1109/TITS.2022.3186294

Scopus

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Calibration Cost Reduction of Indoor Localization Using Bluetooth Low Energy Beacon 査読有り国際誌

As M., Shimizu H., Benaissa B., Yoshida K., Koppen M.

Journal of Advanced Computational Intelligence and Intelligent Informatics 26 ( 1 ) 97 - 106 2022年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Indoor localization based on Bluetooth low energy (BLE) beacons has been rapidly developed, and many approaches have been developed to achieve higher estimation accuracy. In these methods, the received signal strength (RSS) is the input. However, the measurement of indoor environments is affected easily; the signal may be reflected and attenuated by obstacles such as the human body, walls, and furniture, which creates a challenge for methods based on signal mapping. In this study, BLE signal characteristics are investigated in an indoor localization setting. An experiment is performed using one BLE beacon and multiple receivers installed at different wall and ceiling positions. The raw RSS is observed, and the relationship between the BLE beacon signal strength characteristics against the human body effect as well as the receiver's placement in the observation area are discussed. Signal mapping is performed, where the signal strength is measured from all receivers simultaneously. The position estimation accuracy is examined based on different data scenarios. The results show that the estimation position estimated by the BLE beacon based on extensive BLE beacon data does not affect the estimation accuracy.

DOI： 10.20965/jaciii.2022.p0097

Scopus

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Blockchain Simulation Environment on Multi-image Encryption for Smart Farming Application 査読有り国際誌

Widi Widayat I., Köppen M.

Lecture Notes in Networks and Systems 312 316 - 326 2022年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The certainty of food provenance on the agriculture ecosystem brings one of the most popular research topics to smart farming. The global epidemic enforces consumers to be warned of the originality of food supply. Various technology unification is included to address this problem. Heterogeneous IoT sensors for sensing agricultural or plantation land provide system automation and monitoring for certain commodities. Sensor data and captured images of surveillance cameras are the results of IoT devices sensing capability. However, the originality of the data being stored is questioned; even worse, the data records are deleted. Such as problems occur due to several things: network congestion, device reliability, storage media, and operator. One of the findings proposed in this research is storing sensing results from each sensor and camera surveillance to a global database that is decentralized, immutable, and synchronized, known as the blockchain. All the parties involved in the smart farming system, such as farmers, food suppliers, and customers, are connected to a global blockchain network. Multi-Image Encryption (MIE) yields to secure the authenticity of captured images from multiple cameras. A specific MIE algorithm will compile and randomized the captured image from cameras to produce an encrypted image stored in the blockchain database with a unique identifier. This study provides a simulated model of blockchain technology that can be implemented in a smart farming environment using Ganache as the test net. In the smart contract, every entity connected to the blockchain network appears as a node account that is digitally assigned based on each role. Therefore, the transaction was successfully done from one node to the others. This research is the initial stages of implementing a smart farming system into the unification of various technology in the development of sustainable agriculture.

DOI： 10.1007/978-3-030-84910-8_33

Scopus

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A Genetic Algorithm for Parallel Unmanned Aerial Vehicle Scheduling: A Cost Minimization Approach 査読有り国際誌

Mantau A.J., Widayat I.W., Köppen M.

Lecture Notes in Networks and Systems 312 125 - 135 2022年01月

担当区分：最終著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In recent years, there are many research achievements in the Unmanned Aerial Vehicle (UAV) fields. UAV can be used to deliver the logistics and do surveillance as well. Two main problems in this field are UAV-routing and UAV-scheduling. In this paper, we focus on the UAV scheduling problem, which is the problem to search for the scheduling order of the UAV using a fixed number of UAVs and a fixed number of targets. The objective of this paper is to minimize the total cost for efficient realization. A Genetic Algorithm (GA) method is used to solve the UAV-scheduling problem considering the time-varying cost or Time-of-Use tariff (ToU) constraints. The Job Delay Mechanism is also used to improve cost optimization, as a kind of post-processing for the fitness evaluation of an individual schedule, and show that GA alone can not find it. Finally, a numerical experiment is conducted to implement the idea in this paper. Experiment results showed that the proposed method is quite promising and effective in solving the related problem.

DOI： 10.1007/978-3-030-84910-8_14

Scopus

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Behavior selection metaheuristic search algorithm for the pollination optimization: A simulation case of cocoa flowers 査読有り

Syafruddin W.A., Paweroi R.M., Köppen M.

Algorithms 14 ( 8 ) 2021年08月

記述言語：英語掲載種別：研究論文（学術雑誌）

Since nature is an excellent source of inspiration for optimization methods, many optimization algorithms have been proposed, are inspired by nature, and are modified to solve various optimization problems. This paper uses metaheuristics in a new field inspired by nature; more precisely, we use pollination optimization in cocoa plants. The cocoa plant was chosen as the object since its flower type differs from other kinds of flowers, for example, by using cross-pollination. This complex relationship between plants and pollinators also renders pollination a real-world problem for chocolate production. Therefore, this study first identified the underlying optimization problem as a deferred fitness problem, where the quality of a potential solution cannot be immediately determined. Then, the study investigates how metaheuristic algorithms derived from three well-known techniques perform when applied to the flower pollination problem. The three techniques examined here are Swarm Intelligence Algorithms, Individual Random Search, and Multi-Agent Systems search. We then compare the behavior of these various search methods based on the results of pollination simulations. The criteria are the number of pollinated flowers for the trees and the amount and fairness of nectar pickup for the pollinator. Our results show that Multi-Agent System performs notably better than other methods. The result of this study are insights into the co-evolution of behaviors for the collaborative pollination task. We also foresee that this investigation can also help farmers increase chocolate production by developing methods to attract and promote pollinators.

DOI： 10.3390/a14080230

Scopus

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A Genetic Algorithm for Parallel Unmanned Aerial Vehicle Scheduling: A Cost Minimization Approach 査読有り

Mantau, A.J., Widayat, I.W., Köppen, M.

Advances in Intelligent Networking and Collaborative Systems. INCoS 2021. Lecture Notes in Networks and Systems 312 2021年08月

Blockchain Simulation Environment on Multi-image Encryption for Smart Farming Application 査読有り国際誌

Widi Widayat, I., Köppen, M.

Advances in Intelligent Networking and Collaborative Systems. INCoS 2021. Lecture Notes in Networks and Systems 312 2021年08月

Behavior Selection Metaheuristic Search Algorithm for the Pollination Optimization: A Simulation Case of Cocoa Flowers 査読有り国際誌

Syafruddin, Willa A., Rio M. Paweroi, and Mario Köppen

Algorithms 14 ( 8 ) 230 2021年07月

Design and implementation of lora based iot scheme for Indonesian rural area 査読有り

Prakosa S.W., Faisal M., Adhitya Y., Leu J.S., Köppen M., Avian C.

Electronics (Switzerland) 10 ( 1 ) 1 - 12 2021年01月

記述言語：英語掲載種別：記事・総説・解説・論説等（その他）

The development of the Internet of Things (IoT) in electronics, computer, robotics, and internet technology is inevitable and has rapidly accelerated more than before as the IoT paradigm is a promising solution in terms of solving real world problems, especially for digitizing and monitoring in real time. Various IoT schemes have successfully been applied to some areas such as smart health and smart agriculture. Since the agriculture areas are getting narrow, the development of IoT in agriculture should be prioritized to enhance crop production. This paper proposes the IoT scheme for long range communication based on Long Range (LoRa) modules applied to smart agriculture. The scheme utilizes the low power modules and long-distance communication for monitoring temperature, humidity, soil moisture, and pH soil. Our IoT design has successfully been applied to agriculture areas which have unstable network connections. The design is analyzed to obtain the maximum coverage using different spreading factors and bandwidths. We show that as the spreading factor increases to 12, the maximum coverage can be transmitted to 1000 m. However, the large coverage also comes with the disadvantages of the increased delays.

DOI： 10.3390/electronics10010077

Scopus

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An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions 査読有り

Saraji M.K., Mardani A., Köppen M., Mishra A.R., Rani P.

Artificial Intelligence Review 2021年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

DOI： 10.1007/s10462-021-10029-9

Scopus

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An Empirical Investigation on Evolutionary Algorithm Evolving Developmental Timings 査読有り

Kei Ohnishi, Kouta Hamano and Mario Köppen

International Journal of Electronics ( MDPI ) 9 ( 11 ) 1 - 27 2020年11月

記述言語：英語掲載種別：研究論文（学術雑誌）

Recently, evolutionary algorithms that can efficiently solve decomposable binary optimization problems have been developed. They are so-called model-based evolutionary algorithms, which build a model for generating solution candidates by applying a machine learning technique to a population. Their central procedure is linkage detection that reveals a problem structure, that is, how the entire problem consists of sub-problems. However, the model-based evolutionary algorithms have been shown to be ineffective for problems that do not have relevant structures or those whose structures are hard to identify. Therefore, evolutionary algorithms that can solve both types of problems quickly, reliably, and accurately are required. The objective of the paper is to investigate whether the evolutionary algorithm evolving developmental timings (EDT) that we previously proposed can be the desired one. The EDT makes some variables values more quickly converge than the remains for any problems, and then, decides values of the remains to obtain a higher fitness value under the fixation of the variables values. In addition, factors to decide which variable values converge more quickly, that is, developmental timings are evolution targets. Simulation results reveal that the EDT has worse performance than the linkage tree genetic algorithm (LTGA), which is one of the state-of-the-art model-based evolutionary algorithms, for decomposable problems and also that the difference in the performance between them becomes smaller for problems with overlaps among linkages and also that the EDT has better performance than the LTGA for problems whose structures are hard to identify. Those results suggest that an appropriate search strategy is different between decomposable problems and those hard to decompose.

DOI： 10.3390/electronics9111866

Feature Extraction for Cocoa Bean Digital Image Classification Prediction for Smart Farming Application 査読有り国際誌

Yudhi Adhitya, Setya Widyawan Prakosa, Mario Köppen and Jenq-Shiou Leu

International Journal of Agronomy, ( MDPI ) 10(11) ( 1642 ) 1 - 16 2020年10月

記述言語：英語掲載種別：研究論文（学術雑誌）

The implementation of Industry 4.0 emphasizes the capability and competitiveness in agriculture application, which is the essential framework of a country’s economy that procures raw materials and resources. Human workers currently employ the traditional assessment method and classification of cocoa beans, which requires a significant amount of time. Advanced agricultural development and procedural operations differ significantly from those of several decades earlier, principally because of technological developments, including sensors, devices, appliances, and information technology. Artificial intelligence, as one of the foremost techniques that revitalized the implementation of Industry 4.0, has extraordinary potential and prospective applications. This study demonstrated a methodology for textural feature analysis on digital images of cocoa beans. The co-occurrence matrix features of the gray level co-occurrence matrix (GLCM) were compared with the convolutional neural network (CNN) method for the feature extraction method. In addition, we applied several classifiers for conclusive assessment and classification to obtain an accuracy performance analysis. Our results showed that using the GLCM texture feature extraction can contribute more reliable results than using CNN feature extraction from the final classification. Our method was implemented through on-site preprocessing within a low-performance computational device. It also helped to foster the use of modern Internet of Things (IoT) technologies among farmers and to increase the security of the food supply chain as a whole.

DOI： 10.3390/agronomy10111642

Smart Watering System Based on Framework of Low-Bandwidth Distributed Applications (LBDA) in Cloud Computing 査読有り国際誌

Nurdiansyah Sirimorok, Mansur As, Kaori Yoshida and Mario Köppen

In Proceedings of the 12th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2020). ( Springer, Cham ) 1263 447 - 459 2020年08月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Victoria, Canada 2020年08月31日 - 2020年09月02日

The estimation of soil moisture content is required for agriculture, mainly to build the irrigation scheduling model. In this study, we present a smart watering system to deal with various factors derived from the stochastic information in the agricultural operational, i.e., air temperature, air humidity, soil moisture, soil temperature, and light intensity. The methodology consists of exploiting the Internet of Things (IoT) using Low-Bandwidth Distributed Applications (LBDA) in cloud computing to integrate the real data sets collected by the several sensor technologies. We conducted experiments for the watering system used two types of soil and different plant. Here, the Long Short Term Memory Networks (LSTMs) approach in deep learning techniques used to build smart decisions concerning watering requirements and deal with heterogeneous information coming from agricultural environments. Results show that our models can effectively improve the prediction accuracy for the watering system over various soil and plants.

DOI： 10.1007/978-3-030-57796-4_43

その他リンク： https://link.springer.com/chapter/10.1007%2F978-3-030-57796-4_43

Identification and Classification of Sashimi Food Using Multispectral Technology 査読有り国際誌

Ismail Parewai, Mansur As, Tsunenori Mine and Mario Köppen

Proceedings of the 2020 2nd Asia Pacific Information Technology Conference ( Association for Computing Machinery (ACM) New York, USA ) 73 - 77 2020年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Indonesia 2020年01月17日 - 2020年01月19日

Food quality inspection is an essential factor in our daily lives. Food inspection is analyzing heterogeneous food data from different sources for perception, recognition, judgment, and monitoring. This study aims to provide an accurate system in image processing techniques for the inspection and classification of sashimi food damage based on detecting external data. The external texture was identified based on the visible and invisible system that was acquired using multispectral technology. We proposed the Grey Level Co-occurrence Matrix (GLCM) model for analysis of the texture features of images and the classification process was performed using Artificial Neural Network (ANN) method. This study showed that multispectral technology is a useful system for the assessment of sashimi food and the experimental also indicates that the invisible channels have the potential in the classification model, since the hidden texture features that are not clearly visible to the human eye

DOI： 10.1145/3379310.3379317

Identification and Classification of Sashimi Food Using Multispectral Technology 査読有り国際誌

Ismail Parewai, Mansur As, Tsunenori Mine, and Mario Koeppen

Proceedings of the 2020 2nd Asia Pacific Information Technology Conference (APIT 2020) ( Association for Computing Machinery ) 66 - 72 2020年01月

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