Soft Computing Systems Research Articles

DISAIN KURIKULUM INTER-DISIPLINER BERBASIS KKNI: PROGRAM STUDI ILMU KOMPUTER DENGAN FOKUS SOFT COMPUTING DAN INTELLIGENT SYSTEM

The development of technology demands Computer Science graduates to have interdisciplinary knowledge and skills. Traditional curricula are less adaptive in addressing the dynamic industry needs and focus on developing soft skills. This article discusses the design of an interdisciplinary curriculum based on KKNI for Computer Science programs with a focus on soft computing and intelligent systems. This curriculum design integrates knowledge and skills from various disciplines, with an emphasis on the development of soft skills. The curriculum structure is divided into two tracks: the Mandatory Track focusing on the fundamental foundations of Computer Science and soft skills, and the Elective Track focusing on deepening interests and talents in the field of soft computing and intelligent systems, such as Artificial Neural Networks, Microcontrollers, Data Mining, Embedded Systems, Fuzzy Logic, and Computer Vision. This research adopts a Research and Development (R&D) approach with the ADDIE model. Data are collected through surveys, interviews, and document analysis. It is expected that this curriculum design will produce Computer Science graduates with comprehensive, adaptive knowledge and skills, ready for the digital era workforce, particularly in the field of soft computing and intelligent systems.

Soft computing and intelligent systems: Techniques and applications

Soft computing and intelligent systems: Techniques and applications

Microfinance, an Alternative for Financing Entrepreneurship: Implications and Trends-Bibliometric Analysis

Microfinance has become one of the most important financing alternatives for business start-ups, especially for vulnerable groups in poor regions. Microfinance provides access to financial products, especially to people who have been excluded from the traditional financial system. However, the mainstream literature on microfinance shows its impact on poverty alleviation, but it is not yet well developed to understand its dynamizing role in the entrepreneurial sector. There is still a large gap in the literature on analyzing microfinance as a financing alternative, so this paper seeks to find this relationship in the literature. A bibliometric analysis is applied, both of the performance of the publications and a word co-occurrence analysis during the period 2017–2022. The articles indexed in the Web of Science have been considered and systematized through the SCIMAT software v1.1.04, developed by the Soft Computing and Intelligent Information Systems Research Group, University of Granada, Granada, Spain. Microfinance institutions, education, entrepreneurship, organizational performance, business microcredits, and women microentrepreneurs have been identified as driving themes to be considered in future analyses. At the end of the document, the proposed future lines of research are presented. In addition, the results show the growing interest of the academic community in the topic, with 2022 being the year with the highest number of articles published on the topic.

Soft computing and intelligent systems: Techniques and applications

Soft computing and intelligent systems: Techniques and applications

Selection of Best Soft Computing Systems for the Analysis of Heavy Metal Concentration in Soils of a Waste Disposal Site in Khulna

Collection of soil samples is labored, time-consuming and the determination of heavy metal concentrations in the laboratory are expensive. The aim of this study was to fix the functions, algorithms as well as optimization of methods for soft computing system such as ANFIS, SVM, and ANN based on their best performance. In this study, soil samples were collected from eighty five distinct locations in and around of a selected open disposal site at old Rajbandh, Khulna, Bangladesh at a depth 0-30 cm from the existing ground surface. In the laboratory, the concentration of heavy metals such as Pb, Cu, Ni, Zn, Co, Cd, As, Sc, Hg, Mn, Cr, Ti, Sb, Sr, V and Ba in soils were measured. The soft computing systems such as ANFIS, SVM, and ANN were implemented for the analysis of heavy metal concentrations in soil. The result reveals model with SCP, gaussmf, linear and hybrid was the best-fitted model of ANFIS. In addition, in SVM analysis, the model SVM-RBF with 15 folds was selected. In ANN, the model LT (Levenberg-Marqardt and Tansig functions) with neuron structure 2-10-1 was selected. The accuracy of the predicted results was checked based on the acceptable limits of prediction parameters such as R value, RMSE, MAPE, GRI and percentage recovery. The result demonstrates that ANFIS model was a reliable technique than that of other counterparts of SVM and ANN with the acceptable degree of robustness and accuracy. Therefore, the performance of soft computing systems may be expressed by the sequence of ANFIS > SVM > ANN. Here it can be noted that one can easily be computed the concentration of a particular heavy metal in soil by inserting GPS values (latitude and longitude) only in the developed rule viewer of ANFIS.

POMEGRANATE FRUIT DISEASES DETECTION USING IMAGE PROCESSING TECHNIQUES: A REVIEW

The Agriculture plant diseases are responsible for farmer economic losses. These diseases affect on plant root, fruit, leaf, and stem. Detection of disease at early stages helps the farmer to improve productivity. In the traditional system agriculture experts and experienced farmer can recognize the plant diseases at the lower accuracy which causes losses to farmers. Currently several researchers are proposing soft computing and expert systems to recognize plant diseases. Plant disease identification by visual way is less accurate because some diseases do not have any visible symptoms or some of the diseases appear too late at the time of harvesting. The modern technology in agriculture sector can substantially improve the agriculture production & sustainability. This paper provides a review for fruit disease detection techniques for pomegranate plants. This study includes preprocessing, segmentation, feature extraction and classification techniques for pomegranate fruit diseases detection systems. This paper also states the comparison and limitations of existing fruit disease detection techniques.

Soft computing and intelligent systems: techniques and applications

Soft computing and intelligent systems: techniques and applications

Soft computing and intelligent systems: techniques and applications

Soft computing and intelligent systems: techniques and applications

Soft computing and intelligent systems: Techniques and applications

Soft computing and intelligent systems: Techniques and applications

Special issue on soft computing and intelligent systems: Tools, techniques and applications

Special issue on soft computing and intelligent systems: Tools, techniques and applications

Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems 開催報告

Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems 開催報告

Hybrid soft computing systems for electromyographic signals analysis: a review

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

A Granular Computing approach to the design of optimized graph classification systems

Research on Graph-based pattern recognition and Soft Computing systems has attracted many scientists and engineers in several different contexts. This fact is motivated by the reason that graphs are general structures able to encode both topological and semantic information in data. While the data modeling properties of graphs are of indisputable power, there are still different concerns about the best way to compute similarity functions in an effective and efficient manner. To this end, suited transformation procedures are usually conceived to address the well-known Inexact Graph Matching problem in an explicit embedding space. In this paper, we propose two graph embedding algorithms based on the Granular Computing paradigm, which are engineered as key procedures of a general-purpose graph classification system. Tests have been conducted on benchmarking datasets relying on both synthetic and real-world data, achieving competitive results in terms of test set classification accuracy.

A Study on Extraction of Pairs of Questions with Opposite Meanings Based on Distance Between Questions

SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan

Combination of Reliability-based Automatic Repeat reQuest with Error Potential-based Error Correction for Improving P300 Speller Performance

SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan

Selected Papers from SCIS & ISIS 2010 – No.2

This second special issue from the Joint 5th International Conference on Soft Computing and Intelligent Systems and the 11th International Symposium on Advanced Intelligent Systems (SCIS & ISIS) 2010 presents 11 progressive papers covering topics from Fuzzy c-Means, clustering, evolutionary algorithms, and self-organizing maps to optimization, spiral phenomena, matroids, multirobot systems, and reinforcement learning. This wide range of research interests reflects current trends in the SCIS & ISIS conference series. As such, they demonstrate how near-future research interests are gradually moving toward exciting new directions. We thank the authors and reviewers for taking time out from their busy schedules to make this publication possible. We are especially grateful to Prof. Toshio Fukuda of Nagoya University and to Prof. Kaoru Hirota of the Tokyo Institute of Technology for giving us the opportunity to guest-edit JACIII. Our special thanks go to Ms. Reiko Ohta of Fuji Technology Press Ltd. for her ongoing support in publication.

Selected Papers from SCIS & ISIS 2010 – No.1

SCIS & ISIS is a biennial international joint conference on soft computing and intelligent systems, with research ranging from fuzzy systems, neural networks, and evolutionary computation to multi-agent systems, artificial intelligence, and robotics. SCIS & ISIS 2010 consisted of the 5th International Conference on Soft Computing and Intelligent Systems (SCIS) and the 11th International Symposium on Advanced Intelligent Systems (ISIS), held at Okayama Convention Center on December 8-12, 2010. Original presentations numbered 302 and participants 322. After preliminary selection by SCIS & ISIS 2010 session chairs, we listed over 70 papers to be published in extended form in the Special Issue of the Journal of Advanced Computational Intelligence and Intelligent Informatics. After inviting these authors to submit papers for this special issue, we had two referees to review them and accepted 27 for publication in Vol.15, Nos.7 and 8 in 2011. This special issue presents 15 of these papers covering most conference topics, including fuzzy theory, learning methods, neural networks, and evolutionary computation, with a focus on reinforcement learning, multi-agent system, nonlinear estimation, and real-world applications to visual system, robotics and energy. We thank the authors and reviewers for their invaluable contributions toward making this special issue possible. We are also grateful to Editors-in-chief Prof. Toshio Fukuda of Nagoya University and Prof. Kaoru Hirota of the Tokyo Institute of Technology for inviting us to serve as Guest Editors.

A Study of Visualization Method with HK Graph Using Concept Words

SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan

A Study on Aggregation of Objective Functions in MaOPs Based on Evaluation Criteria

SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan

A Study on Effects of Migration in MOGA with Island Model by Visualization

Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems, September 17-21, 2008, Nagoya University, Nagoya, Japan