Search results for: fuzzy aggregation operator

Authors: Agung Budi Muljono, I Made Ginarsa, I Made Ari Nrartha

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A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.

Keywords: ANFIS, large-scale, power system, PSS, stability enhancement

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: O. Poleshchuk, E. Komarov

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In this paper, semantic spaces with the properties of completeness and orthogonality (complete orthogonal semantic spaces) were chosen as models of expert evaluations. As the theoretical and practical studies have shown all the properties of complete orthogonal semantic spaces correspond to the thinking activity of experts that is why these semantic spaces were chosen for modeling. Two methods of construction such spaces were proposed. Models of comparative and fuzzy cluster analysis of expert evaluations were developed. The practical application of the developed methods has demonstrated their viability and validity.

Keywords: expert evaluation, comparative analysis, fuzzy cluster analysis, theoretical and practical studies

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Authors: Arup K. Sarma, Jayshree Hazarika

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The North-eastern part of India, which receives heavier rainfall than other parts of the subcontinent, is of great concern now-a-days with regard to climate change. High intensity rainfall for short duration and longer dry spell, occurring due to impact of climate change, affects river morphology too. In the present study, an attempt is made to delineate the North-Eastern region of India into some homogeneous clusters based on the Fuzzy Clustering concept and to compare the resulting clusters obtained by using conventional methods and non conventional methods of clustering. The concept of clustering is adapted in view of the fact that, impact of climate change can be studied in a homogeneous region without much variation, which can be helpful in studies related to water resources planning and management. 10 IMD (Indian Meteorological Department) stations, situated in various regions of the North-east, have been selected for making the clusters. The results of the Fuzzy C-Means (FCM) analysis show different clustering patterns for different conditions. From the analysis and comparison it can be concluded that non conventional method of using GCM data is somehow giving better results than the others. However, further analysis can be done by taking daily data instead of monthly means to reduce the effect of standardization.

Keywords: climate change, conventional and nonconventional methods of clustering, FCM analysis, homogeneous regions

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Authors: Aamir Shahzad, Hubert Roth

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This paper is presenting the bilateral telecontrol of AutoMerlin Mobile Robot having communication delay. Passivity Observers has been designed to monitor the net energy at both ports of a two port network and if any or both ports become active making net energy negative, then the passivity controllers dissipate the proper energy to make the overall system passive in the presence of time delay. The environment force is modeled and sent back to human operator so that s/he can feel it and has additional information about the environment in the vicinity of mobile robot. The experimental results have been presented to show the performance and stability of bilateral controller. The results show the whenever the passivity observers observe active behavior then the passivity controller come into action to neutralize the active behavior to make overall system passive.

Keywords: bilateral control, human operator, haptic device, communication network, time domain passivity control, passivity observer, passivity controller, time delay, mobile robot, environment force

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Authors: Jialin Wu, Zhiwei Lian, Jieyu Tang, Jingyun Shen

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Tornado is a serious and unpredictable natural disaster, which has an important impact on people's production and life. The probability of being hit by tornadoes in China was analyzed considering the principles of tornado formation. Then some suggestions on layout and shapes for newly-built buildings were provided combined with the characteristics of tornado wind fields. Fuzzy clustering and inverse closeness methods were used to evaluate the probability levels of tornado risks in various provinces based on classification and ranking. GIS was adopted to display the results. Finally, wind field single-vortex tornado was studied to discuss the optimized design of rural low-rise houses in Yancheng, Jiangsu as an example. This paper may provide enough data to support building and urban design in some specific regions.

Keywords: tornado probability, computational fluid dynamics, fuzzy mathematics, optimal design

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Authors: Alldila Hendy, Agi Satria

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Background: A colostomy procedure is an important part in the management of surgical procedures in some diseases involving the gastrointestinal tract. So it is necessary to find the factors that influence the occurrence of complications. Methods: This is a retrospective cross-sectional analytic study in Cipto Mangunkusumo Hospital noting medical records of patients after the colostomy from January 2012 to December 2014 at the Division of Digestive Surgery. Results: In 136 cases of post-colostomy, 66 cases have complications, 14 is early-onset, and 52 is late-onset. 70 is without complications. Most complications are dermatitis, which is 31 (22.8%), cases of infection/abscess/fistula and intestinal obstruction are 13 (9.6%) and 5 patients (4.4%). A rare complication is colostomy retraction by 2 patients (1.5%), colostomy prolapse and necrosis/gangrene, which is only 3 patients (2.2%). A colostomy procedure in emergency surgery is riskier than elective surgery for complications after colostomy (p < 0.007, OR 2.85), Based on the operator who performs a colostomy procedure, the consultant had a lower risk of complications than fellow or resident (p < 0.0001). Based on the age factor, where the age of about 50 years has a risk of complications after colostomy (p < 0.018). Conclusion: The timing of operation (emergency or elective), age, and operator who perform a colostomy procedure have a significant relationship with an increased prevalence of complications after colostomy in RSCM.

Keywords: colostomy, complications, factors, procedure

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Sakina Fatima, Joseph-Patrick W. E. Clarke, Patricia A. Thibault, Subha Kalyaanamoorthy, Michael Levin, Aravindhan Ganesan

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Heteronuclear ribonucleoprotein (hnRNPA1 or A1) is associated with the pathology of different diseases, including neurological disorders and cancers. In particular, the aggregation and dysfunction of A1 have been identified as a critical driver for neurodegeneration (NDG) in Multiple Sclerosis (MS). Structurally, A1 includes a low-complexity domain (LCD) and two RNA-recognition motifs (RRMs), and their interdomain coordination may play a crucial role in A1 aggregation. Previous studies propose that RNA-inhibitors or nucleoside analogs that bind to RRMs can potentially prevent A1 self-association. Therefore, molecular-level understanding of the structures, dynamics, and nucleotide interactions with A1 RRMs can be useful for developing therapeutics for NDG in MS. In this work, a combination of computational modelling and biochemical experiments were employed to analyze a set of RNA-A1 RRM complexes. Initially, the atomistic models of RNA-RRM complexes were constructed by modifying known crystal structures (e.g., PDBs: 4YOE and 5MPG), and through molecular docking calculations. The complexes were optimized using molecular dynamics simulations (200-400 ns), and their binding free energies were computed. The binding affinities of the selected complexes were validated using a thermal shift assay. Further, the most important molecular interactions that contributed to the overall stability of the RNA-A1 RRM complexes were deduced. The results highlight that adenine and guanine are the most suitable nucleotides for high-affinity binding with A1. These insights will be useful in the rational design of nucleotide-analogs for targeting A1 RRMs.

Keywords: hnRNPA1, molecular docking, molecular dynamics, RNA-binding proteins

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Authors: Nigina Toktasynova, Sholpan Sagyndykova, Zhanat Kenzhebayeva, Maksat Kalimoldayev, Mariya Ishimova, Irbulat Utepbergenov

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Any business needs a stable operation and continuous improvement, therefore it is necessary to constantly interact with the environment, to analyze the work of the enterprise in terms of employees, executives and consumers, as well as to correct any inconsistencies of certain types of processes and their aggregate. In the case of heat supply organizations, in addition to suppliers, local legislation must be considered which often is the main regulator of pricing of services. In this case, the process approach used to build a functional organizational structure in these types of businesses in Kazakhstan is a challenge not only in the implementation, but also in ways of analyzing the employee's salary. To solve these problems, we investigated the management system of heating enterprise, including strategic planning based on the balanced scorecard (BSC), quality management in accordance with the standards of the Quality Management System (QMS) ISO 9001 and analysis of the system based on expert judgment using fuzzy inference. To carry out our work we used the theory of fuzzy sets, the QMS in accordance with ISO 9001, BSC according to the method of Kaplan and Norton, method of construction of business processes according to the notation IDEF0, theory of modeling using Matlab software simulation tools and graphical programming LabVIEW. The results of the work are as follows: We determined possibilities of improving the management of heat-supply plant-based on QMS; after the justification and adaptation of software tool it has been used to automate a series of functions for the management and reduction of resources and for the maintenance of the system up to date; an application for the analysis of the QMS based on fuzzy inference has been created with novel organization of communication software with the application enabling the analysis of relevant data of enterprise management system.

Keywords: balanced scorecard, heat supply, quality management system, the theory of fuzzy sets

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: Trapti Pathak

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Fishes can change their body colour according to their surroundings by. They do so by either aggregation or dispersion of melanosomes within the skin. These movements can regulate by means of sympathetic nerves with the help of cytoskeleton. Employing the melanophores on isolated scales of the fingerling of teleost fish, it is attempted to characterise the concerned nerves and the receptors located on melenocytes along with implication of microtubules a part of cytoskeleton in the pigmentary translocation in the fish. The scales from dorso-lateral trunk of the fish represented the sympathetic– neuromelanophore preparations which were stimulated by chemical means, such as adrenergic agonist, antagonist and the microtubule-disrupting drugs such as yuhombine, dopamine, colchicine etc. Adrenaline is an adrenergic agonist which is strongly induced the dorse-dependent concentration of pigment in innervated melanophores while Yohimbine is an adrenergic antagonist which is known to block effectively the α2-adrenoceptors inhibited the action of adrenaline. Colchicine effectively interferes with melanosome aggregating action of adrenaline. From these results it is concluded that the chromatic fibres of adrenergic nature innervate the melanophores and these cells do possess α2-adrenoceptors which mediate the melanosome aggregation and the movements of pigment granules through microtubules means of transport within the cell. These movements of pigment are linked to paling or darkening achieved of teleost fish respectively when they approach to their background.

Keywords: melenophores, agonists, antagonist, colour change

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Authors: Chul H. Jo, Do Y. Kim, Bong K. Cho, Myeong J. Kim

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The exhaustion of oil and the environmental pollution from the use of fossil fuel are increasing. Tidal current power (TCP) has been proposed as an alternative energy source because of its predictability and reliability. By applying a duct and single point mooring (SPM) system, a TCP device can amplify the generating power and keep its position properly. Because the generating power is proportional to cube of the current stream velocity, amplifying the current speed by applying a duct to a TCP system is an effective way to improve the efficiency of the power device. An SPM system can be applied at any water depth and is highly cost effective. Simple installation and maintenance procedures are also merits of an SPM system. In this study, we designed an SPM system for a duct-type TCP device for use in shallow water. Motions of the duct are investigated to obtain the response amplitude operator (RAO) as the magnitude of the transfer function. Parameters affecting the stability of the SPM system such as the fairlead departure angle, current velocity, and the number of clamp weights are analyzed and/or optimized. Wadam and OrcaFlex commercial software is used to design the mooring line.

Keywords: mooring design, parametric analysis, RAO (Response Amplitude Operator), SPM (Single Point Mooring)

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: N. Lakshmipathy, Ch. S. N. Murthy, M. Aruna

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The design of lighting systems for surface mines is not an easy task because of the unique environment and work procedures encountered in the mines. The primary objective of this paper is to identify the major problems encountered in mine lighting application and to provide guidance in the solution of these problems. In the surface mining reflectance of surrounding surfaces is one of the important factors, which improve the vision, in the night hours. But due to typical working nature in the mines it is very difficult to fulfill these requirements, and also the orientation of the light at work site is a challenging task. Due to this reason machine operator and other workers in a mine need to be able to orient themselves in a difficult visual environment. The haul roads always keep on changing to tune with the mining activity. Other critical area such as dumpyards, stackyards etc. also change their phase with time, and it is difficult to illuminate such areas. Mining is a hazardous occupation, with workers exposed to adverse conditions; apart from the need for hard physical labor, there is exposure to stress and environmental pollutants like dust, noise, heat, vibration, poor illumination, radiation, etc. Visibility is restricted when operating load haul dumper and Heavy Earth Moving Machinery (HEMM) vehicles resulting in a number of serious accidents. one of the leading causes of these accidents is the inability of the equipment operator to see clearly people, objects or hazards around the machine. Results indicate blind spots are caused primarily by posts, the back of the operator's cab, and by lights and light brackets. The careful designed and implemented, lighting systems provide mine workers improved visibility and contribute to improved safety, productivity and morale. Properly designed lighting systems can improve visibility and safety during working in the opencast mines.

Keywords: contrast, efficacy, illuminance, illumination, light, luminaire, luminance, reflectance, visibility

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Authors: Imoh Philip

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Basà language is classified as belonging to Kainji family, under the sub-phylum Western-Kainji known as Rubasa (Basa Benue) (Croizier & Blench, 1992:32). Basà is an under-described language spoken in the North-Central Nigeria. The language is characterized by subject-verb-object (henceforth SVO) as its canonical word order. Data for this work is sourced from the researcher’s native intuition of the language corroborated with a careful observation of native speakers. This paper investigates the syntactic derivational strategy of information-structure encoding in Basà language. It emphasizes on a negative operator, as a strategy for focusing a constituent or clause that follows it and negativizes a whole proposition. For items that are not nouns, they have to undergo an obligatory nominalization process, either by affixation, modification or conversion before they are moved to the pre verbal position for these operations. The study discovers and provides evidence of the fact showing that deferent constituents in the sentence such as the subject, direct, indirect object, genitive, verb phrase, prepositional phrase, clause and idiophone, etc. can be focused with the same negativizing operator. The process is characterized by focusing the pre verbal NP constituent alone, whereas the whole proposition is negated. The study can stimulate similar study or be replicated in other languages.

Keywords: negation, focus, Basà, nominalization

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Authors: Antoaneta Stefanova, Rositsa Gencheva, Pavlin Groudev

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This paper presents the modeling approach in SBO sequence for VVER 1000 reactors and describes the reactor core behavior at late in-vessel phase in case of late reflooding by HPIS and gives preliminary results for the ASTECv2 validation. The work is focused on investigation of plant behavior during total loss of power and the operator actions. The main goal of these analyses is to assess the phenomena arising during the Station blackout (SBO) followed by primary side high pressure injection system (HPIS) reflooding of already damaged reactor core at very late ‘in-vessel’ phase. The purpose of the analysis is to define how the later HPIS switching on can delay the time of vessel failure or possibly avoid vessel failure. For this purpose has been simulated an SBO scenario with injection of cold water by a high pressure pump (HPP) in cold leg at different stages of core degradation. The times for HPP injection were chosen based on previously performed investigations.

Keywords: VVER, operator action validation, reflooding of overheated reactor core, ASTEC computer code

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: Panyawutthi Rimdusit, Krittapas Charoensuk, Sarawut Rimdusit

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A biobased toughening filler for polylactic acid (PLA) based on natural rubber is developed in this work. Deproteinized natural rubber (DPNR) was modified by grafting polymerization with methyl methacrylate monomer (MMA) and further crosslinked by e-beam irradiation and spray drying process to achieve ultrafine full vulcanized powdered natural rubber grafted with polymethylmethacrylate (UFPNRg-PMMA) to solves in the challenges of incompatibility between natural rubber and PLA. Intriguingly, UFPNR-g-PMMA revealed outstanding and unique properties with minimal particle aggregation. The average particle size of rubber powder obtained from UFPNR-g-PMMA at PMMA grafting content of 20 phr reduced to 3.3±1.2 µm, compared to that of neat UFPNR of 5.3±2.3 µm which also showed partial particle aggregation. It is also found that the impact strength of the filled PLA was enhanced to 33.4±5.6 kJ/m2 at PLA/UFPNR-gPMMA 20 wt% compared to neat PLA of 9.6±3 kJ/m2. The thermal degradation temperature of the PLA composites was enhanced with increasing UFPNR-g-PMMA content without affecting the glass transition temperature of the composites. The fracture surface of PLA/ UFPNR-g-PMMA suggested internal cavitation and crazes are the main effects of rubber toughening PLA with substantial interfacial interaction between the filler and the matrix.

Keywords: natural rubber, ultrafine fully vulcanized powder rubber, polylactic acid, polymer composites

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Ingrid Argote, John Archila, Marcelo Becker

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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: Murat Oral, Seda Bostancı, Sadık Ata, Kevser Dincer

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When evaluating the aesthetics of cities, an analysis of the urban form development depending on design properties with a variety of factors is performed together with a study of the effects of this appearance on human beings. Different methods are used while making an aesthetical evaluation related to a city. Entropy, in its preliminary meaning, is the mathematical representation of thermodynamic results. Measuring the entropy is related to the distribution of positional figures of a message or information from the probabilities standpoint. In this study, analysis of evaluation the urban skylines by the entropy approach was modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between application data and RBMTF is done by using absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of evaluation the urban skylines by the entropy approach. As a result, RBMTF model has shown satisfying relation with experimental results, which suggests an alternative method to evaluation of the urban skylines by the entropy approach.

Keywords: urban skylines, entropy, rule-based Mamdani type, fuzzy logic

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Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

Abstract:

Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

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Authors: G. S. Thyagaraju, U. P. Kulkarni

Abstract:

Context-aware computing refers to a general class of computing systems that can sense their physical environment, and adapt their behaviour accordingly. Context aware computing makes systems aware of situations of interest, enhances services to users, automates systems and personalizes applications. Context-aware services have been introduced into mobile devices, such as PDA and mobile phones. In this paper we are presenting a novel approaches used to realize the context aware mobile. The context aware mobile phone (CAMP) proposed in this paper senses the users situation automatically and provides user context required services. The proposed system is developed by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets theory based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision table based rules for service recommendation. To exemplify and demonstrate the effectiveness of the proposed methods, the context aware mobile phone is tested for college campus scenario including different locations like library, class room, meeting room, administrative building and college canteen.

Keywords: context aware mobile, fuzzy logic, decision table, Bayesian probability

Procedia PDF Downloads 365

Authors: M. Habab, C. Benachaiba, B. Mazari, H. Madi, C. Benoudjafer

Abstract:

The use of Distributed Generation (DG) has been increasing in recent years to fill the gap between energy supply and demand. This paper presents the grid connected wind energy system with UPQC based on fuzzy controller to compensate for voltage and current disturbances. The proposed system can improve power quality at the point of installation on power distribution systems. Simulation results show the capability of the DG-UPQC intelligent system to compensate sags voltage and current harmonics at the Point of Common Coupling (PCC).

Keywords: shunt active filter, series active filter, UPQC, power quality, sags voltage, distributed generation, wind turbine

Procedia PDF Downloads 407

Authors: Priyesh Kumar Pandey, Zakir Husain, R. K. Jarial

Abstract:

Condition monitoring and diagnostic is important for testing of power transformer in order to estimate the remnant life. Concentration of furan content in transformer oil can be a promising indirect measurement of the aging of transformer insulation. The oil gets contaminated mainly due to ageing. The present paper introduces adaptive neuro fuzzy technique to correlate furanic compounds obtained by high performance liquid chromatography (HPLC) test and remnant life of the power transformer. The results are obtained by conducting HPLC test at TIFAC-CORE lab, NIT Hamirpur on thirteen power transformer oil samples taken from Himachal State Electricity Board, India.

Keywords: adaptive neuro fuzzy technique, furan compounds, remnant life, transformer oil

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Authors: Mehdi Ameur, Ahmed Essadki, Tamou Nasser

Abstract:

The purpose of this paper is the evaluation of photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturbing and observing (P&O), incremental conductance (INC) and fuzzy logic controller (FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: fuzzy logic controller, FLC, hill climbing, HC, incremental conductance (INC), perturb and observe (P&O), maximum power point, MPP, maximum power point tracking, MPPT

Procedia PDF Downloads 511

Authors: Gurmail Singh

Abstract:

Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

Abstract:

Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.

Keywords: intuitionistic fuzzy set, rough set, relational database, IF rough relational database

Procedia PDF Downloads 444