Search results for: fuzzy performance measurements

Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

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The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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Authors: Indrajit Ghosh, Jaydip Roy

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Literacy rate is an important indicator for measurement of human development. But this is not a good one to capture the qualitative dimension of educational attainment of an individual or a society. The overall educational level of an area is an important issue beyond the literacy rate. The overall educational level can be thought of as an outcome of the educational levels of individuals. But there is no well-defined algorithm and mathematical model available to measure the overall educational level of an area. A heuristic approach based on accumulated experience of experts is effective one. It is evident that fuzzy logic offers a natural and convenient framework in modeling various concepts in social science domain. This work suggests the implementation of fuzzy logic to develop a mathematical model for measurement of educational attainment of an area in terms of Education Index. The contribution of the study is two folds: conceptualization of “Education Profile” and proposing a new mathematical model to measure educational attainment in terms of “Education Index”.

Keywords: education index, education profile, fuzzy logic, literacy

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Authors: S. Bouharati, F. Allag, M. Belmahdi, M. Bounechada

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In terms of ecology forecast effects of desertification, the purpose of this study is to develop a predictive model of growth and adaptation of species in arid environment and bioclimatic conditions. The impact of climate change and the desertification phenomena is the result of combined effects in magnitude and frequency of these phenomena. Like the data involved in the phytopathogenic process and bacteria growth in arid soil occur in an uncertain environment because of their complexity, it becomes necessary to have a suitable methodology for the analysis of these variables. The basic principles of fuzzy logic those are perfectly suited to this process. As input variables, we consider the physical parameters, soil type, bacteria nature, and plant species concerned. The result output variable is the adaptability of the species expressed by the growth rate or extinction. As a conclusion, we prevent the possible strategies for adaptation, with or without shifting areas of plantation and nature adequate vegetation.

Keywords: climate changes, dry soil, phytopathogenicity, predictive model, fuzzy logic

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Choki, Supatchai Boonpratham, Suwannee Luppanapornlarp

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The objective of this study was to find a correlation between cephalometric measurements and visual perception of facial profile in skeletal type II patients. In this study, 250 lateral cephalograms of female patients from age, 20 to 22 years were analyzed. The profile outlines of all the samples were hand traced and transformed into silhouettes by the principal investigator. Profile ratings were done by 9 orthodontists on Visual Analogue Scale from score one to ten (increasing level of convexity). 37 hard issue and soft tissue cephalometric measurements were analyzed by the principal investigator. All the measurements were repeated after 2 weeks interval for error assessment. At last, the rankings of visual perceptions were correlated with cephalometric measurements using Spearman correlation coefficient (P < 0.05). The results show that the increase in facial convexity was correlated with higher values of ANB (A point, nasion and B point), AF-BF (distance from A point to B point in mm), L1-NB (distance from lower incisor to NB line in mm), anterior maxillary alveolar height, posterior maxillary alveolar height, overjet, H angle hard tissue, H angle soft tissue and lower lip to E plane (absolute correlation values from 0.277 to 0.711). In contrast, the increase in facial convexity was correlated with lower values of Pg. to N perpendicular and Pg. to NB (mm) (absolute correlation value -0.302 and -0.294 respectively). From the soft tissue measurements, H angles had a higher correlation with visual perception than facial contour angle, nasolabial angle, and lower lip to E plane. In conclusion, the findings of this study indicated that the correlation of cephalometric measurements with visual perception was less than expected. Only 29% of cephalometric measurements had a significant correlation with visual perception. Therefore, diagnosis based solely on cephalometric analysis can result in failure to meet the patient’s esthetic expectation.

Keywords: cephalometric measurements, facial profile, skeletal type II, visual perception

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Authors: Shagufta Tabassum

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The study of dielectric properties in a binary mixture of liquids is very useful to understand the liquid structure, molecular interaction, dynamics, and kinematics of the mixture. Time-domain reflectometry (TDR) is a powerful tool for studying the cooperation and molecular dynamics of the H-bonded system. In this paper, we discuss the basic calibration and normalization procedure for time-domain reflectometry measurements. Our approach is to explain the different types of error occur during TDR measurements and how these errors can be eliminated or minimized.

Keywords: time domain reflectometry measurement techinque, cable and connector loss, oscilloscope loss, and normalization technique

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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Authors: M. Mourad, K. Abdelgawwad

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This experimental investigation aimed to determine the influence of using different types of alcohol and gasoline blends such as ethanol - butanol - propanol on the performance of spark ignition engine. The experimental work studied the effect of various fuel blends such as ethanol – butanol/gasoline and propanol/gasoline with two rates of 15% and 20%, at different operating conditions (engine speed and loads), on engine performance emission characteristics. Laboratory experiments are carried out on a four-cylinder spark ignition (SI) engine. In this practical study, all considerations and precautions are taken into account to ensure the quality and accuracy of practical experiments and different measurements. The results show that the performance of the engine improved significantly in the case of ethanol/butanol-gasoline blends. The results also indicated that the engine emitted pollutants such as CO, hydrocarbon (HC) for alcohol fuel blends compared to base gasoline NOx emission increased for different fuel blends either ethanol/butanol-gasoline or propanol-gasoline fuel blend.

Keywords: gasoline engine, performance, emission, fuel blends

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Authors: O. Moussous, T. Medjadj

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The suitability of a Fricke dosimeter for the measurement of a relative depth dose profile and the peak scatter factors was studied. The measurements were carried out in the secondary standard dosimetry laboratory at CRNA Algiers using a collimated 60Co gamma source teletherapy machine. The measurements were performed for different field sizes at the phantom front face, at a fixed source-to-phantom distance of 80 cm. The dose measurements were performed by first placing the dosimeters free-in-air at the distance-source-detector (DSD) of 80.5 cm from the source. Additional measurements were made with the phantom in place. The water phantom type Med-Tec 40x40x40 cm for vertical beam was used in this work as scattering martial. The phantom was placed on the irradiation bench of the cobalt unit at the SSD of 80 cm from the beam focus and the centre of the field coincided with the geometric centre of the dosimeters placed at the depth in water of 5 mm Relative depth dose profile and Peak scatter factors measurements were carried out using our Fricke system. This was intercompared with similar measurements by ionization chamber under identical conditions. There is a good agreement between the relative percentage depth–dose profiles and the PSF values measured by both systems using a water phantom.

Keywords: Fricke dosimeter, depth–dose profiles, peak scatter factors, DSD

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Authors: Wannakorn Sangthongngam, Melissa Huerta, Jaewoo Kim, Doyeon Kim

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Continuous glucose monitoring systems are essential for diabetics to avoid health complications but come at a costly price, especially when insurance does not fully cover the diabetic testing kits needed. This paper proposes a noninvasive continuous glucose monitoring system to provide an accessible, low-cost, and painless alternative method of accurate glucose measurements to help improve quality of life. Using a light source with a wavelength of 850nm illuminates the fingertip for the photodetector to detect the transmitted light. Utilizing SeeDevice’s photon-assisted tunneling photodetector (PAT-PD)-based QMOS™ sensor, fluctuations of voltage based on photon absorption in blood cells are comparable to traditional glucose measurements. The performance of the proposed method was validated using 4 test participants’ transmitted voltage readings compared with measurements obtained from the Accu-Chek glucometer. The proposed method was able to successfully measure concentrations from linear regression calculations.

Keywords: continuous glucose monitoring, non-invasive continuous glucose monitoring, NIR, photon-assisted tunneling photodetector, QMOS™, wearable device

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Authors: Vadivel Ayyasamy

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The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation

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Authors: Lina Feng

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The study aimed at establishing quality evaluation indicators of an early education center for 0~3 years old, and defining the weight system of it. Expert questionnaire and Fuzzy Delphi method were applied. Firstly, in order to ensure the indicators in accordance with the practice of early education, 16 experts were invited as respondents to a preliminary Expert Questionnaire about Quality Evaluation Indicators of Early Education Center for 0~3 Years Old. The indicators were based on relevant studies on quality evaluation indicators of early education centers in China and abroad. Secondly, 20 scholars, kindergarten principals, and educational administrators were invited to form a fuzzy Delphi expert team. The experts’ opinions on the importance of indicators were calculated through triangle fuzzy numbers in order to select appropriate indicators and calculate indicator weights. This procedure resulted in the final Quality Evaluation Indicators of Early education Center for 0~3 Years Old. The Indicators contained three major levels, including 6 first-level indicators, 30 second-level indicators, and 147 third-level indicators. The 6 first-level indicators were health and safety; educational and cultivating activities; development of babies; conditions of the center; management of the center; and collaboration between family and the community. The indicators established by this study could provide suggestions for the high-quality environment for promoting the development of early year children.

Keywords: early education center for 0~3 years old, educational management, fuzzy delphi method, quality evaluation indicator

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Authors: Aydin M. Torkabadi, Ehsan Pourjavad

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A decade after the introduction of Lean in Saskatchewan’s public healthcare system, its effectiveness remains a controversial subject among health researchers, workers, managers, and politicians. Therefore, developing a framework to quantitatively assess the Lean achievements is significant. This study investigates the success of initiatives across Saskatchewan health regions by recognizing the Lean healthcare criteria, measuring the success levels, comparing the regions, and identifying the areas for improvements. This study proposes an integrated intelligent computing approach by applying Fuzzy Inference System (FIS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FIS is used as an efficient approach to assess the Lean healthcare criteria, and TOPSIS is applied for ranking the values in regards to the level of leanness. Due to the innate uncertainty in decision maker judgments on criteria, principals of the fuzzy theory are applied. Finally, FIS-TOPSIS was established as an efficient technique in determining the lean merit in healthcare systems.

Keywords: lean healthcare, intelligent computing, fuzzy inference system, healthcare evaluation, technique for order of preference by similarity to ideal solution, multi-criteria decision making, MCDM

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Authors: Noor Ul Ain Bhatti, M. Junaid Khan, Javed Ahmad, Murtaza Saleem, Shahid M. Ramay, Saadat A. Siddiqi

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Manganese oxide is being recently used as electrode material for rechargeable batteries. In this study, Al incorporated Mn₂O₃ compositions were synthesized to study the effect of Al doping on electrochemical performance of host material. Structural studies were carried out using X-ray diffraction analysis to confirm the phase stability and explore the lattice parameters, crystallite size, lattice strain, density and cell volume. Morphology and composition were analyzed using field emission scanning electron microscope and energy dispersive X-ray spectroscopy, respectively. Dynamic light scattering analysis was performed to observe the average particle size of the compositions. FTIR measurements exhibit the O-Al-O and O-Mn-O and Al-O bonding and with increasing the concentration of Al, the vibrational peaks of Mn-O become sharper. An enhanced electrochemical performance was observed in compositions with higher Al content.

Keywords: Mn2O3, electrode materials, energy storage and conversion, electrochemical performance

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Authors: Amira Bousselmi

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This article presents a PIFA antenna designed for geolocation applications (GNSS) operating on 1.278 GHz, 2.8 GHz, 5.7 GHz and 10 GHz. To improve the performance of the antenna, an artificial magnetic conductor structure (AMC) was used. Adding the antenna with AMC resulted in a measured gain of 4.78 dBi. The results of simulations and measurements are presented. CST Microwave Studio is used to design and compare antenna performance. An antenna design methodology, design and characterization of the AMC surface are described as well as the simulated and measured performances of the AMC antenna are then discussed. Finally, in Section V, there is a conclusion.

Keywords: antenna multiband, global navigation system, AMC, Galeleo

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Authors: Huilan Yao, Huaixin Zhang

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Simulations of the transition flow of model propellers are important for predicting hydrodynamic performance and studying scale effects. In this paper, the transition flow of a model propeller under different loadings are simulated using a transition model provided by STAR-CCM+, and the influence of turbulence intensity (TI) on the transition, especially friction and pressure components of propeller performance, was studied. Before that, the transition model was applied to simulate the transition flow of a flat plate and an airfoil. Predicted transitions agree well with experimental results. Then, the transition model was applied for propeller simulations in open water, and the influence of TI was studied. Under the heavy and moderate loadings, thrust and torque of the propeller predicted by the transition model (different TI) and two turbulence models are very close and agree well with measurements. However, under the light loading, only the transition model with low TI predicts the most accurate results. Above all, the friction components of propeller performance predicted by the transition model with different TI have obvious difference.

Keywords: transition flow, model propellers, hydrodynamic performance, numerical simulation

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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Authors: Salisu Umar

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Fruits are a seasonal crop and get spoiled quickly. They are dried to be preserved for a long period. The natural drying process requires more time. The investment on space requirement and infrastructure is large, and cannot be afforded by a middle class farmer. Therefore there is a need for a comparatively small unit with reduced drying times, which can be afforded by a middle class farmer. A controlled environment suitable for fruit drying is developed within a closed chamber and is a three step process. Firstly, the infrared light is used internally to preheated the fruit to speedily remove the water content inside the fruit for fast drying. Secondly, hot air of a specified temperature is blown inside the chamber to maintain the humidity below a specified level and exhaust the humid air of the chamber. Thirdly the microcontroller idles disconnecting the power to the chamber after the weight of the fruits is reduced to a known value of its original weight. This activates a buzzer for duration of ten seconds to indicate the end of the drying process. The results obtained indicate that the system is significantly reducing the drying time without affecting the quality of the fruits compared with the existing dryers.

Keywords: fruit, fuzzy controller, microcontroller, temperature, weight and humidity

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Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

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Authors: F. Sahnoune, M. Belhamel, M. Zelmat

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Solar thermal systems available today provide reliability, efficiency and significant environmental benefits. In housing, they can satisfy the hot water demand and reduce energy bills by 60 % or more. Additionally, collective systems or large scale solar thermal systems are increasingly used in different conditions for hot water applications and space heating in hotels and multi-family homes, hospitals, nursing homes and sport halls as well as in commercial and industrial building. However, in situ real performance data for collective solar water heating systems has not been extensively outlined. This paper focuses on the study of real energy performances of a collective solar water heating system using the remote monitoring technique in Algerian climatic conditions. This is to ensure proper operation of the system at any time, determine the system performance and to check to what extent solar performance guarantee can be achieved. The measurements are performed on an active indirect heating system of 12 m2 flat plate collector’s surface installed in Algiers and equipped with a various sensors. The sensors transmit measurements to a local station which controls the pumps, valves, electrical auxiliaries, etc. The simulation of the installation was developed using the software SOLO 2000. The system provides a yearly solar yield of 6277.5 KWh for an estimated annual need of 7896 kWh; the yearly average solar cover rate amounted to 79.5%. The productivity is in the order of 523.13 kWh / m²/year. Simulation results are compared to measured results and to guaranteed solar performances. The remote monitoring shows that 90% of the expected solar results can be easy guaranteed on a long period. Furthermore, the installed remote monitoring unit was able to detect some dysfunctions. It follows that remote monitoring is an important tool in energy management of some building equipment.

Keywords: large-scale solar water heater, real energy performance, remote monitoring, solar performance guarantee, tool to promote solar water heater

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Authors: DoHyeung Kim, DaeHee Seo, ByungDoo Kim, ByungGil Lee

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As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.

Keywords: collision risk, pose, shape, fuzzy logic

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Authors: Vahid Anari, Mina Bakhshi

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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

Abstract:

The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

Abstract:

The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: J. Al-Dmour, A. Sagahyroon, A. Al-Ali, S. Abusnana

Abstract:

Radio Frequency Based Identification Systems have emerged as one of the possible valuable solutions that can be utilized in healthcare systems. Nowadays, RFID tags are available with built-in human vital signs sensors such as Body Temperature, Blood Pressure, Heart Rate, Blood Sugar level and Oxygen Saturation in Blood. This work proposes the design, implementation, and testing of an integrated mobile RFID-based health care system. The system consists of a wireless mobile vital signs data acquisition unit (RFID-DAQ) integrated with a fuzzy-logic–based software algorithm to monitor and assess patients conditions. The system is implemented and tested in ‘Rashid Center for Diabetes and Research’, Ajman, UAE. System testing results are compared with the Modified Early Warning System (MEWS) that is currently used in practice. We demonstrate that the proposed and implemented system exhibits an accuracy level that is comparable and sometimes better than the widely adopted MEWS system.

Keywords: healthcare, fuzzy logic, MEWS, RFID

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Authors: Abderrahim Siam, Ramdane Maamri, Zaidi Sahnoun

Abstract:

The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines. The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques, and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets

Procedia PDF Downloads 468