Comparative Analysis of Sound Response from Simple and Fuzzy Algorithm in Saron Virtual Reality

Analisis Komparatif Respon Suara dari Algoritma Sederhana dan Algoritma Fuzzy di Saron Virtual Reality. Game virtual reality dengan konsep alat musik memerlukan respon suara yang dinamis karena musik tidak lepas dari perasaan manusia dalam memainkannya. Suara yang bagus dalam sebuah game tergantung pada kesesuaiannya dengan situasi game. Keterbatasan waktu dan tempat menjadi permasalahan dalam melakukan variasi perekaman sampel suara. Jika sampel suara yang diambil terbatas dan diterapkan dengan algoritma sederhana kemungkinan terdengar repetitif dan kurang sesuai dengan dinamika suara musik sesuai kehidupan nyata manusia. Oleh karena itu, pada penelitian ini dilakukan komparasi implementasi antara algoritma sederhana dengan algoritma fuzzy pada suara game Gamelan Saron. Metode pengolahan data yang digunakan adalah analisis komparatif dan data diperoleh dari hasil eksperimen responden. Pada skala persetujuan satu sampai lima, mayoritas responden setuju adanya perubahan signifikan yang lebih baik setelah diberikan algoritma fuzzy yang digambarkan dengan nilai rata-rata 4,1.Kata Kunci: suara, gamelan, Saron, dinamika, fuzzy Comparative Analysis of Sound Response from Simple and Fuzzy Algorithm in Saron Virtual Reality. Virtual reality games with musical instruments require a dynamic sound response because playing the instrument requires real human feelings. A good sound in a game depends on its suitability for the game situation. Time and place limitations are a problem in recording variations in sound sample recording. If the sound samples taken are limited and a simple algorithm is applied, it may sound repetitive and not match the dynamics of music according to real human life. Therefore, in this study, a comparison of a simple algorithm with the fuzzy algorithm was carried out in the Gamelan Saron game. The data processing method used is a comparative analysis obtained from the experimental results of the respondents. On the agreement scale of one to five, most respondents agree that there is a better significant change after being given a fuzzy algorithm described by a mean value of 4.1. Keywords: sound, gamelan, Saron, dynamics, fuzz

Decision-Making Problems in Sociotechnical Systems

The object of research is a human in complex sociotechnical systems (STS). A particular case of the sociotechnical system is the human-machine system (HMS). The subject of research is the professional activity of a person in the sociotechnical system, the structure of his professionally important qualities, the methods of assessing the professional suitability of a person, and the methods of training and training of operational personnel. The model of vocational aptitude and the process of decision-making in the class of hierarchical systems were developed based on the hierarchy analysis method. Intelligent processing of data was requested to be carried out by the use of decision support systems, which provides support to multicriteria decision in a complex system. The experimental research of vocational aptitude assessment for operators of transport-technological machines was carried out. The outputs of the decision support systems were obtained individual operator’s portraits (IOP) and integrated estimation capabilities. As a result, it became possible to reduce the preparation cost of professionals and to raise the level of the operator’s professional skills. In addition, based on the IOP, we can customize the HMC interface

INTELIGENTNY SYSTEM DIAGNOSTYKI I STEROWANIA PRZEPŁYWAMI DWUFAZOWYMI NA PODSTAWIE POMIARÓW 3D ECT

In this paper the new intelligent system for two-phase flows diagnosis and control is presented. The authors developed a fuzzy inference system for two phase flows recognition based on the raw 3D ECT data statistical analysis and fuzzy classification which identify the flow structure in real-time mode. The non-invasive three-dimensional monitoring is possible to conduct even in non-transparent and non-accessible parts of the pipeline. Presented system is also equipped with the two phase gas-liquid flows installation control module based on fuzzy inference which includes the feedback information from the recognition module.  The intelligent control module working in a feed-back loop keep the sets of required flow regime. Presented in this paper fuzzy algorithms allow to recognize the two phase processes similar to the human expert and to control the process in the same, very intuitively way. Using of the artificial intelligence in the industrial applications allows to avoid any random errors as well as breakdowns and human mistakes suffer from lack of objectivity. An additional feature of the system is a universal multi-touched monitoring-control panel which is an alternative for commercial solution and gives the opportunity to build user own virtual model of the flow rig to efficiently monitor and control the process.W artykule zaprezentowany został inteligentny system diagnostyki i sterowania przepływami dwufazowymi gaz-ciecz. Autorzy opracowali rozmyty system wnioskowania oparty o statystyczną analizę i klasyfikację rozmytą surowych danych pomiarowych 3D ECT realizujący w czasie rzeczywistym identyfikację struktury przepływu oraz wyznaczanie objętościowego udziału faz. Nieinwazyjny trójwymiarowy monitoring przepływu możliwy jest w nieprzezroczystych i trudno dostępnych fragmentach rurociągów w czasie rzeczywistym. Prezentowany system wyposażony jest również w moduł sterowania instalacją w oparciu o wnioskowanie rozmyte, któremu na wejście podawane są informacje zwrotne od modułu rozpoznawania. Inteligentny regulator rozmyty pracujący w pętli sprzężenia zwrotnego utrzymuje żądane nastawy parametrów przepływu w oparciu o zadany reżim przepływu. Przedstawione w niniejszym opracowaniu algorytmy rozmyte umożliwiają identyfikację procesów dwu-fazowych w sposób analogiczny do tego, jak to robią specjaliści oraz jednocześnie pozwalają kontrolować proces w ten sam bardzo intuicyjny sposób. Zastosowanie sztucznej inteligencji w aplikacjach przemysłowych pozwala uniknąć przypadkowych ludzkich błędów podatnych na brak obiektywizmu, a także zapobiegać awarii. Cechą dodatkową systemu jest uniwersalny dotykowy panel monitorująco-sterujący stanowiący alternatywę dla drogich komercyjnych rozwiązań umożliwiający budowanie wirtualnego modelu instalacji, aby w szybki i skuteczny sposób móc ją monitorować i nią sterować

Application of Neuro-Fuzzy system to solve Traveling Salesman Problem

This paper presents the application of adaptive neuro-fuzzy inference system (ANFIS) in solving the traveling salesman problem. Takagi-Sugeno-Kang neuro-fuzzy architecture model is used for this purpose. TSP, although, simple to describ

An Interval Type-2 Fuzzy Logic Based Map Matching Algorithm for Airport Ground Movements

Airports and their related operations have become the major bottlenecks to the entire air traffic management system, raising predictability, safety and environmental concerns. One of the underpinning techniques for digital and sustainable air transport is airport ground movement optimisation. Currently, real ground movement data is made freely available for the majority of aircraft at many airports. However, the recorded data is not accurate enough due to measurement errors and general uncertainties. In this paper, we aim to develop a new interval type-2 fuzzy logic based map matching algorithm, which can match each raw data point to the correct airport segment. To this aim, we first specifically design a set of interval type-2 Sugeno fuzzy rules and their associated rule weights, as well as the model output, based on preliminary experiments and sensitivity tests. Then, the fuzzy membership functions are fine-tuned by a particle swarm optimisation algorithm. Moreover, an extra checking step using the available data is further integrated to improve map matching accuracy. Using the real-world aircraft movement data at Hong Kong Airport, we compared the developed algorithm with other well-known map matching algorithms. Experimental results show that the designed interval type-2 fuzzy rules have the potential to handle map matching uncertainties, and the extra checking step can effectively improve map matching accuracy. The proposed algorithm is demonstrated to be robust and achieve the best map matching accuracy of over 96% without compromising the run time

Real Time NIR Imaging Image Enhancement by using 2D Frangi Filter via Segmentation

This paper presents the NIR imaging images enhancement by using 2D Frangi Filter segmentation which specifically apply in biomedical NIR vein localization imaging. The unseen subcutaneous vein causing clinical practitioner face the difficulties to perform intravenous catheterization and thus lead to the needles tick injuries. There are few imaging techniques which can be used for bein localization but the most widely used is Near Infrared (NIR) imaging due to its non-invasive and non-ionizing properties. The input images from NIR imaging setup is processed in order to enhance the vein visibility and contrast between vein and skin tissue. It is required to filter noise from the display image using some image processing technique. This work is done by applying image segmentation method to NIR venous image in order to extract veins and eliminate the noise. First, the gray scale image was segmented to 10 pieces of fragment plane with constant step size to produce 3 set of 2D planes. Second, these 3 sets of 2D planes will then apply in Frangi filter in order to obtain the eigenvalue image structure. Lastly, a least noise image is produce by this integrated plane through the 2D Frangi filter

Learning and tuning fuzzy logic controllers through reinforcements

A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing

Methoden und Beschreibungssprachen zur Modellierung und Verifikation vonSchaltungen und Systemen: MBMV 2015 - Tagungsband, Chemnitz, 03. - 04. März 2015

Der Workshop Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV 2015) findet nun schon zum 18. mal statt. Ausrichter sind in diesem Jahr die Professur Schaltkreis- und Systementwurf der Technischen Universität Chemnitz und das Steinbeis-Forschungszentrum Systementwurf und Test. Der Workshop hat es sich zum Ziel gesetzt, neueste Trends, Ergebnisse und aktuelle Probleme auf dem Gebiet der Methoden zur Modellierung und Verifikation sowie der Beschreibungssprachen digitaler, analoger und Mixed-Signal-Schaltungen zu diskutieren. Er soll somit ein Forum zum Ideenaustausch sein. Weiterhin bietet der Workshop eine Plattform für den Austausch zwischen Forschung und Industrie sowie zur Pflege bestehender und zur Knüpfung neuer Kontakte. Jungen Wissenschaftlern erlaubt er, ihre Ideen und Ansätze einem breiten Publikum aus Wissenschaft und Wirtschaft zu präsentieren und im Rahmen der Veranstaltung auch fundiert zu diskutieren. Sein langjähriges Bestehen hat ihn zu einer festen Größe in vielen Veranstaltungskalendern gemacht. Traditionell sind auch die Treffen der ITGFachgruppen an den Workshop angegliedert. In diesem Jahr nutzen zwei im Rahmen der InnoProfile-Transfer-Initiative durch das Bundesministerium für Bildung und Forschung geförderte Projekte den Workshop, um in zwei eigenen Tracks ihre Forschungsergebnisse einem breiten Publikum zu präsentieren. Vertreter der Projekte Generische Plattform für Systemzuverlässigkeit und Verifikation (GPZV) und GINKO - Generische Infrastruktur zur nahtlosen energetischen Kopplung von Elektrofahrzeugen stellen Teile ihrer gegenwärtigen Arbeiten vor. Dies bereichert denWorkshop durch zusätzliche Themenschwerpunkte und bietet eine wertvolle Ergänzung zu den Beiträgen der Autoren. [... aus dem Vorwort

Evaluation of a fuzzy-expert system for fault diagnosis in power systems

A major problem with alarm processing and fault diagnosis in power systems is the reliance on the circuit alarm status. If there is too much information available and the time of arrival of the information is random due to weather conditions etc., the alarm activity is not easily interpreted by system operators. In respect of these problems, this thesis sets out the work that has been carried out to design and evaluate a diagnostic tool which assists power system operators during a heavy period of alarm activity in condition monitoring. The aim of employing this diagnostic tool is to monitor and raise uncertain alarm information for the system operators, which serves a proposed solution for restoring such faults. The diagnostic system uses elements of AI namely expert systems, and fuzzy logic that incorporate abductive reasoning. The objective of employing abductive reasoning is to optimise an interpretation of Supervisory Control and Data Acquisition (SCADA) based uncertain messages when the SCADA based messages are not satisfied with simple logic alone. The method consists of object-oriented programming, which demonstrates reusability, polymorphism, and readability. The principle behind employing objectoriented techniques is to provide better insights and solutions compared to conventional artificial intelligence (Al) programming languages. The characteristics of this work involve the development and evaluation of a fuzzy-expert system which tries to optimise the uncertainty in the 16-lines 12-bus sample power system. The performance of employing this diagnostic tool is assessed based on consistent data acquisition, readability, adaptability, and maintainability on a PC. This diagnostic tool enables operators to control and present more appropriate interpretations effectively rather than a mathematical based precise fault identification when the mathematical modelling fails and the period of alarm activity is high. This research contributes to the field of power system control, in particular Scottish Hydro-Electric PLC has shown interest and supplied all the necessary information and data. The AI based power system is presented as a sample application of Scottish Hydro-Electric and KEPCO (Korea Electric Power Corporation)