Search results for: type 2 fuzzy control

Authors: Fatemeh Torfi

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Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some municipalities such as Tehran where a sound demand management calls for a realistic analysis of the routing system. The methodology involved critically investigating a fuzzy least-squares linear regression approach (FLLRs) to estimate the stochastic demands in the vehicle routing problem (VRP) bearing in mind the customer's preferences order. A FLLR method is proposed in solving the VRP with stochastic demands. Approximate-distance fuzzy least-squares (ADFL) estimator ADFL estimator is applied to original data taken from a case study. The SSR values of the ADFL estimator and real demand are obtained and then compared to SSR values of the nominal demand and real demand. Empirical results showed that the proposed methods can be viable in solving problems under circumstances of having vague and imprecise performance ratings. The results further proved that application of the ADFL was realistic and efficient estimator to face the stochastic demand challenges in vehicle routing system management and solve relevant problems.

Keywords: fuzzy least-squares, stochastic, location, routing problems

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Authors: Ran Etgar

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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X ̅-chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter (Y ̅) is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.

Keywords: quality control, process control, round-off, measurement, rounding error

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Authors: Donghwan Lee, Gichun Cha, Jooyoung Park, Junkyeong Kim, Seunghee Park

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3D shape models of the existing structure are required for many purposes such as safety and operation management. The traditional 3D modeling methods are based on manual or semi-automatic reconstruction from close-range images. It occasions great expense and time consuming. The Terrestrial Laser Scanner (TLS) is a common survey technique to measure quickly and accurately a 3D shape model. This TLS is used to a construction site and cultural heritage management. However there are many limits to process a TLS point cloud, because the raw point cloud is massive volume data. So the capability of carrying out useful analyses is also limited with unstructured 3-D point. Thus, segmentation becomes an essential step whenever grouping of points with common attributes is required. In this paper, members segmentation algorithm was presented to separate a raw point cloud which includes only 3D coordinates. This paper presents a clustering approach based on a fuzzy method for this objective. The Fuzzy C-Means (FCM) is reviewed and used in combination with a similarity-driven cluster merging method. It is applied to the point cloud acquired with Lecia Scan Station C10/C5 at the test bed. The test-bed was a bridge which connects between 1st and 2nd engineering building in Sungkyunkwan University in Korea. It is about 32m long and 2m wide. This bridge was used as pedestrian between two buildings. The 3D point cloud of the test-bed was constructed by a measurement of the TLS. This data was divided by segmentation algorithm for each member. Experimental analyses of the results from the proposed unsupervised segmentation process are shown to be promising. It can be processed to manage configuration each member, because of the segmentation process of point cloud.

Keywords: fuzzy c-means (FCM), point cloud, segmentation, terrestrial laser scanner (TLS)

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Authors: G. Peker, Tolga N. Aynur, E. Tinar

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In order to determine the energy consumption level and cooling characteristics of a domestic refrigerator controlled with various cooling system algorithms, a side by side type (SBS) refrigerator was tested in temperature and humidity controlled chamber conditions. Two different control algorithms; so-called drop-in and frequency controlled variable capacity compressor algorithms, were tested on the same refrigerator. Refrigerator cooling characteristics were investigated for both cases and results were compared with each other. The most important comparison parameters between the two algorithms were taken as; temperature distribution, energy consumption, evaporation and condensation temperatures, and refrigerator run times. Standard energy consumption tests were carried out on the same appliance and resulted in almost the same energy consumption levels, with a difference of %1,5. By using these two different control algorithms, the power consumptions character/profile of the refrigerator was found to be similar. By following the associated energy measurement standard, the temperature values of the test packages were measured to be slightly higher for the frequency controlled algorithm compared to the drop-in algorithm. This paper contains the details of this experimental study conducted with different cooling control algorithms and compares the findings based on the same standard conditions.

Keywords: control algorithm, cooling, energy consumption, refrigerator

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Authors: Alice W. Theuri, Anselimo O. Makokha, Florence M. Kyallo

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Type 2 diabetes mellitus (T2DM) is a serious metabolic disorder whose prevalence among adults has been increasing in the last decade. It is estimated that by 2030, the number of cases in Africa will almost double. Diet and lifestyle modifications are considered the cornerstone for the treatment and management of T2DM. Despite this, there is minimum literature assessing the dietary practices and glycemic control in a semi arid region context in Kenya. The objective of this study was to determine the dietary practices of adult T2DM patients attending Kitui out patient clinic in Kitui County. This was a cross sectional study design where every consenting second patient attending diabetic clinic was interviewed. A total of 138 T2DM patients were interviewed using a structured interview guide on socio-economic and dietary practices administered. The study was carried out in April and May 2017. There were more female (64%) than male (36%) in this study with majority being unemployed (38.4%). Forty seven percent (47.6%) had elevated HbA1c. Majority took three meals per day while DDS was 4.3 ± 1.09. The mean energy intake for men and women was 2823.8 ± 82.45 and 2766.3.30 ± 76.74 respectively. There was a non significant positive relationship (r= 131; P value = 0.124) between amount energy consumed and glycemic control. There were suboptimal dietary practices leading to poor glycemic control among T2DM patients attending diabetic clinic at Kitui District Hospital.

Keywords: adults, dietary practices, semi arid region, T2DM

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Authors: Alicia C. Sanchez

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This paper investigates the implementation of RAFU functions (radical functions) in robotics and automation. Specifically, the main goal is to show how these functions may be useful in lane-keeping control and the lateral control of autonomous machines, vehicles, robots or the like. From the knowledge of several points of a certain route, the RAFU functions are used to achieve the lateral control purpose and maintain the lane-keeping errors within the fixed limits. The stability that these functions provide, their ease of approaching any continuous trajectory and the control of the possible error made on the approximation may be useful in practice.

Keywords: automatic navigation control, lateral control, lane-keeping control, RAFU approximation

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Authors: U. Yavas, M. Gokasan

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Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.

Keywords: predictive control, engine control, engine modeling, PID control, feedforward compensation

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Authors: Mohammad Hossain Validad, Maryam Nakhaei-Moghadam, Monire Mahjoob

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Introduction: The prevalence of type 1 diabetes is increasing worldwide, and given the role of ethnicity and race in complications of diabetes, this study was designed to evaluate the ocular complications of type 1 diabetes mellitus in Zahedan. Methods: This prospective cross-sectional study was conducted on Type 1 diabetic children that referred to Alzahra Eye Hospital. All patients had a dilated binocular indirect ophthalmoscopy using a +90 D condensing lens and slit-lamp biomicroscopy. Age, gender, onset, duration of diabetes, and HbA1c level were recorded. Results: 76 type 1 diabetes patients with an age of 11.93 ± 3.76 years participated in this study. Out of 76 patients with diabetes, 19 people (25%) had ocular complications. There was a significant difference in age (P=0.01) and disease duration (P=0.07) between the two groups with and without ocular complications. Odd ratios for ocular complications with age and duration of diabetes were 1.32 and 1.32, respectively. Conclusion: Cataract was the most common ocular complication in type 1 diabetes in Zahedan, a tropical region that was significantly related to the duration of the disease and the age of the patients.

Keywords: diabet mellitus type one, cataract, ocular complication, hemoglobin A1C

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Authors: H. Emari, Z. Emari

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The purpose of this paper is to design an applied framework for strategic thinking which can be applied in all managerial levels and all types of organizational environments. No special applied frame has been presented for this thinking. This paper presents a theoretical framework for the thinking type of a manager by making a historical research and studying the scientific documents about thinking of a strategist. In the new theoretical framework it has been tried to suggest the best type of thinking for a strategist after analyzing the environment of his decisions. So, in this framework, the traditional viewpoint about strategic thinking, which has considered it as a special type of right-brain thinking against other types of right-brain thinking and suggested it for a strategist, was put aside and suggests that the strategist should use a suitable type of thinking under different conditions.

Keywords: strategic thinking, systemic thinking, lateral thinking, intuitive thinking, hybrid thinking

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Authors: Tomoya Oshiro, Hiroko Ono

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Japan's aging population is increasing due to the decrease in birthrate. It causes various problems like the decrease in the gross domestic product of the country. The reason is why the local government of Japan has been on the way to a sustainable city recently. Then it is essential to get control of an urban structure to make the compact city successful. There are many kinds of paper about the compact city; however, the paper about a compact city of the island-type city is less. The purpose of this study is to clarify difference of urban structure between an island-type and a general city type. The method which has conducted in this research has two steps. First of all, by using evaluation indexes in the handbook, we evaluated the urban structures among each same -population-class cities from 50,000 to 100,000 people. Next, to clear the difference about the urban structure and feature between island-type and general-type cities compare the radar chart which is composed with each evaluation indexes of urban structure. Moreover, in order to clarify the relationship between evaluation indexes and the place of residence by using GIS software to show up population density on the map. As a result of this research, the management of local government and the local economy in evaluation indexes are indicated to be negative point in comparison of island-type cities with general cities. However, evaluation indexes of safety/security and low-carbon/energy are proved to be positive point. The research to find the difference features of the island-type of urban structure proves that the management of local government or the local economy is negative point in these island-type cities. In addition, the public transportation coverage in Miyako Island, Sado Island, and Amakusa Island show low value compare with other islands and average value. Relationship between evaluation indexes of an urban structure and the place of residence prove that the place of residence is related to public transportation coverage. If the place of residence is spread out, the public transportation coverage will be decreased. The results of this research reveal that the finances in island-type cities are negative point compare to general cities. This problem is caused by declining population. In addition, the place of residence is related to the public transportation coverage. Even though, it needs a much money to increase the public transportation coverage. It is possibly to cause other problems furthermore the aspect of finance is influenced by that as well. The conclusion in this research suggests that it is important for creating the compact city in island-type cities that we first need to address solving the problems about the management of local government and the local economy.

Keywords: sustainable city, comparative analysis, geographic information system, urban structure

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Authors: Jui-Chen Huang, Shou-Hsiung Cheng

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This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.

Keywords: fall, fuzzy neural network, health belief model, telecare, willingness

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Authors: Ramin Javadzadeh

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The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

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Authors: Seyed Reza Alvani, Norzarina Mohd Zaharim

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Diabetes mellitus is one of the chronic, progressive illnesses that has reached a widespread level all over the world and considered an extreme life-threatening condition in South East Asian countries region include Malaysia. Co-morbid psychological factors like diabetes-related distress and low level of psychological well-being are related to high levels of blood sugar and hypo/hyperglycemia complications. As a result, the implementation of any effective psychological interventions among diabetes patients is necessary. One such intervention is cognitive behavioural therapy (CBT) that is approved and suggested by many professionals as an empirically-supported technique of treatment for people how are suffering from diabetes around the world where there is no clear evidence of using this technique in Malaysia. The target of this study was to see whether or not participation in group CBT would end in an improvement of psychological well-being (by decreasing the levels of depression and anxiety) and diabetes-related distress followed by lower level of blood sugar level. The sample of the present study was 60 type 2 diabetes adults (ages 20-65) with HbA1c ≥ 7 from Universiti Sains Malaysia (USM) clinic. All participants were selected by the convenience sampling technique. Participants completed Well-Being Questionaire (W-BQ) and Distress Scale (DDS-17) after signing written consent form. Those participants who were interested to join CBT groups were placed to the experimental groups, and people who were not interested were assigned to the control group. The experimental groups (n = 30) received group CBT, whereas participants in the control group (n = 30) did not receive any kind of psychological intervention. For testing the effect of intervention, mixed between-within ANOVA used. The entire intervention program took three months, and a significant improvement in the level of psychological well-being and decline in the level of diabetes distress observed among participants from experimental group, but not for those in the control group. Additionally, the result of the study suggested that group CBT could help participants in experimental group achieve more acceptable HbA1c levels in comparison with those in the control group. Malaysian Ministry of Health, researcher and governors should give due interest and commitment to psychological care as a pathway to diabetes mitigation among Malaysian adults.

Keywords: cognitive behavioral therapy, diabetes related distress, diabetes type 2, Malaysia, well-being

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Authors: L. Musak, J. Valachova, T. Vasicko, O. Osina

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Introduction: Stainless steel is resistant to electrochemical corrosion by passivation. Welders are greatly exposed to welding fumes of toxic metals, which added to this steel. The content of chromium (Cr) in steel was above 11.5%, Ni and Mo from 2 to 6.5%. The aim of the study was the evaluation of occupational exposure to Cr, chromosome analysis and valuation of individual susceptibility polymorphism of gene CCND1 c.870 G>A. Materials and Methods: The exposed group was consisted from 117 welders of stainless steels. The average age was 38.43 years and average exposure time 7.14 years. Smokers represented 40.17%. The control group consisted of 123 non-exposed workers with an average age of 39.74 years and time employment 16.67 years. Smokers accounted for 22.76%. Analysis of Cr in blood and urine was performed by atomic absorption spectrophotometry (AAS Varian SpectraAA 30P) with electrothermal decomposition of the sample in the graphite furnace. For the evaluation of chromosomal aberrations (CA) was used cytogenetic analysis of peripheral blood lymphocytes, gene polymorphism was determined by PCR-RFLP reaction using appropriate primers and restriction enzymes. For statistical analysis was used the Mann-Whitney U-test. Results: The mean Cr level in exposed group was 0.095 mmol/l (0.019 min-max 0.504). No value does exceed the average normal value. The average value Cr in urine was 7.9 mmol/mol creatinine (min 0.026 to max 19.26). The total number of CA was 1.86% in compared to 1.70% controls. (CTA-type 0.90% vs 0.80% and CSA-type 0.96% vs 0.90%). In the number of total CA was observed statistical difference between smokers and non-smokers of exposed group (S-1.57% vs. NS-2.04%, P<0.05). In CCND1 gene polymorphisms was observed the increasing of the total CA with wild-type allele (WT) via heterozygous to the VAR genotype (1.44%<1.82%<2.13%). There was observed a statistically higher incidence of CTA-type aberrations in variant genotypes between exposed and control groups (1.22% vs. 0.59%, P<0.05). Discussion and conclusions: The work place is usually higher source of exposure to harmful factors. Workers need consistently and checked frequently health control. In assessing the risk of adverse effects of metals is important to consider their persistence, behavior and bioavailability. Prolonged exposure to carcinogens may not manifest symptoms of poisoning, but delayed effects may occur, which resulted in a higher incidence of malignant tumors.

Keywords: genotoxicity, chromium, stainless steels, welders

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Authors: A. Yanik, U. Aldemir

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This study investigates the benefits of implementing the semi-active devices in relation to passive viscous damping in the context of seismically isolated bridge structures. Since the intrinsically nonlinear nature of semi-active devices prevents the direct evaluation of Laplace transforms, frequency response functions are compiled from the computed time history response to sinusoidal and pulse-like seismic excitation. A simple semi-active control policy is used in regard to passive linear viscous damping and an optimal non-causal semi-active control strategy. The control strategy requires optimization. Euler-Lagrange equations are solved numerically during this procedure. The optimal closed-loop performance is evaluated for an idealized controllable dash-pot. A simplified single-degree-of-freedom model of an isolated bridge is used as numerical example. Two bridge cases are investigated. These cases are; bridge deck without the isolation bearing and bridge deck with the isolation bearing. To compare the performances of the passive and semi-active control cases, frequency dependent acceleration, velocity and displacement response transmissibility ratios T_a(w), T_v(w), and T_d(w) are defined. To fully investigate the behavior of the structure subjected to the sinusoidal and pulse type excitations, different damping levels are considered. Numerical results showed that, under the effect of external excitation, bridge deck with semi-active control showed better structural performance than the passive bridge deck case.

Keywords: bridge structures, passive control, seismic, semi-active control, viscous damping

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Authors: Barenten Suciu

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In this paper, a theoretical study on the forced vibration of one degree of freedom system equipped with inerter, working under load-type or displacement-type excitation, is presented. Differential equations of movement are solved under cosinusoidal excitation, and explicit relations for the magnitude, resonant magnitude, phase angle, resonant frequency, and critical frequency are obtained. Influence of the inertance and damping on these dynamic characteristics is clarified. From the obtained results, one concludes that the inerter increases the magnitude of vibration and the phase angle of the damped mechanical system. Moreover, the magnitude ratio and difference of phase angles are not depending on the actual type of excitation. Consequently, such kind of similitude allows for the comparison of various theoretical and experimental results, which can be broadly found in the literature.

Keywords: displacement-type excitation, inerter, load-type excitation, one degree of freedom vibration, parallel connection

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Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

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Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: dissolved gas-in-oil analysis, fuzzy logic, power transformer, prediction

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Authors: Orhun Aydin, Mark V. Janikas, Rodrigo Alves, Renato Assuncao

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In this paper, a tree-based perturbation methodology for regionalization inference is presented. Regionalization is a constrained optimization problem that aims to create groups with similar attributes while satisfying spatial contiguity constraints. Similar to any constrained optimization problem, the spatial constraint may hinder convergence to some global minima, resulting in spatially contiguous members of a group with dissimilar attributes. This paper presents a general methodology for rigorously perturbing spatial constraints through the use of random spanning trees. The general framework presented can be used to quantify the effect of the spatial constraints in the overall regionalization result. We compare several types of stochastic spanning trees used in inference problems such as fuzzy regionalization and determining the number of regions. Performance of stochastic spanning trees is juxtaposed against the traditional permutation-based hypothesis testing frequently used in spatial statistics. Inference results for fuzzy regionalization and determining the number of regions is presented on the Local Area Personal Incomes for Texas Counties provided by the Bureau of Economic Analysis.

Keywords: regionalization, constrained clustering, probabilistic inference, fuzzy clustering

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Authors: Sheren H. Salah, Ahmed Y. Ben Sasi

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The inverted pendulum system is a classic control problem that is used in universities around the world. It is a suitable process to test prototype controllers due to its high non-linearities and lack of stability. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. This paper presents the possibility of balancing an inverted pendulum system using sliding mode control (SMC). The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle and cart's position. Therefore, proportional-integral-derivative (PID) is used for comparison. Results have proven SMC control produced better response compared to PID control in both normal and noisy systems.

Keywords: inverted pendulum (IP), proportional-integral derivative (PID), sliding mode control (SMC), systems and control engineering

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Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Junaid Mahmood Alam, Howarh Humaira Ali, Ishrat Sultana

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Long term irregularity in the glycemic state, especially in Type 2 diabetes mellitus (T2DM) patients, depicted by higher levels of HbA1c, is noted to be correlated with the development of microalbuminuria. The aim of the current study is to investigate the association of urinary microalbumin with HbA1c and with duration of diabetes mellitus in selected male and female T2DM patients. This cross-sectional study was carried out in a total of 70 patients, thirty-five each male and females with diagnosed T2DM, within the age group of 35-60 years. Biochemical parameters of urea, creatinine, urinary microalbumin, HbA1c, fasting blood glucose and post- parendial blood glucose were determined by standard methods. Data was statistically examined by student’s t-test and Pearson’s correlation. Results showed that comparison of healthy control subjects with both male and female T2DM patients depicted significantly elevated levels of all parameters in (P < 0.05 to P < 0.001). Comparison of duration of T2DM with the existence of urinary microalbumin was moderately significant (P < 0.05) when duration was less than 4 years, significant (P < 0.01) with duration of 4-6 years and markedly significant (P < 0.001) with duration of more than 6 years. It is concluded that in male and female T2DM patients, duration of DM as well as poor glycemic control, depicted by higher levels of HbA1c is significantly correlated with elevated levels of urinary microalbumin.

Keywords: type 2 diabetes mellitus, glycosylated hemoglobin, urinary microalbumin, T2DM, HbA1c

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Authors: Elly Usman, S. Dante, Diah Purnamasari

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Type 2 diabetes mellitus ( T2DM ) is a syndrome characterized by a state of increased blood sugar levels due to chronic disorders of insulin secretion by pancreatic beta cells and insulin action or a combination of both. The organic cation transporter 1, encoded by the SLC22A1 gene, responsible for the uptake of the antihyperglycemic drug, metformin, in the hepatocyte. We assessed whether a genetic variation in the SLC22A1 gene was associated with the glucose - lowering effect of metformin. Method case study research design. Samples are children with type 2 diabetes mellitus who meet the inclusion criteria. The results proportions SLC22A1 gene polymorphisms in children with diabetes mellitus type 2 amounted to 52.04 % at position 400T/C, there is one heterozygous and one at position 595T/C Conclusion The presence of SLC22A1 gene polymorphisms in children with diabetes mellitus type 2.

Keywords: diabetes Mellitus type 2, metformin, organic cation transporter 1, pharmacogenomics

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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: Evija Silina, Maris Taube, Maksims Zolovs

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Background: Type 1 diabetes mellitus (T1D) is the most common chronic endocrine pathology in children. The management of type 1 diabetes requires a strong diet, physical activity, lifelong insulin therapy, and proper self-monitoring of blood glucose and is usually complicated and, therefore, may result in a variety of psychosocial problems for children, adolescents, and their families. Metabolic control of the disease is determined by glycated haemoglobin (HbA1c), the main criterion for diabetes compensation. A correlation was observed between anxiety and depression levels and glycaemic control in many previous studies. It is assumed that anxiety and depression symptoms negatively affect glycaemic control. Parental psychological distress was associated with higher child self-report of stress and depressive symptoms, and it had negative effects on diabetes management. Objective: The main objective of this paper is to evaluate the relationship between parental mental health conditions (depression and anxiety) and metabolic control of their adolescents with T1DM. Methods: This cross-sectional study recruited adolescents with T1D (N=251) and their parents (N=251). The respondents completed questionnaires. The 7-item Generalized Anxiety Disorder (GAD-7) scale measured anxiety level; The Patient Health Questionnaire – 9 (PHQ-9) measured depressive symptoms. Glycaemic control of patients was assessed using the last glycated haemoglobin (HbA1c) values. GLM mediation analysis was performed to determine the potential mediating effect of the parent’s mental health conditions (depression and anxiety) on the relationship between the mental health conditions (depression and anxiety) of a child on the level of glycated hemoglobin (HbA1c). To test the significance of the mediated effect (ME) for non-normally distributed data, bootstrapping procedures (10,000 bootstrapped samples) were used. Results: 502 respondents were eligible for screening to detect anxiety and depression symptoms. Mediation analysis was performed to assess the mediating role of parent GAD-7 on the linkage between a dependent variable (HbA1c) and independent variables (child GAD-7 un child PHQ-9). The results revealed that the total effect of child GAD-7 (B = 0.479, z = 4.30, p < 0.001) on HbA1c was significant but the total effect of child PHQ-9 (B = 0.166, z = 1.49, p = 0.135) was not significant. With the inclusion of the mediating variable (parent GAD-7), the impact of child GAD-7 on HbA1c was found insignificant (B = 0.113, z=0.98, p = 0.326), the impact of child PHQ-9 on HbA1c was found also insignificant (B = 0.068, z=0.74, p = 0.458). The indirect effect of child GAD-7 on HbA1c through parent GAD-7 was found significant (B = 0.366, z = 4.31, p < 0.001) and the indirect effect of child PHQ-9 on HbA1c through parent GAD-7 was found also significant (B = 0.098, z = 2.56, p = 0.010). This indicates that the relationship between a dependent variable (HbA1c) and independent variables (child GAD-7 un child PHQ-9) is fully mediated by parent GAD-7. Conclusion: The main result suggests that glycated haemoglobin in adolescents with Type 1 diabetes is related to adolescents’ mental health via parents’ anxiety. It means that parents’ anxiety plays a more significant role in the level of glycated haemoglobin in adolescents than depression and anxiety in the adolescent.

Keywords: type 1 diabetes, adolescents, parental diabetes-specific mental health conditions, glycated haemoglobin, anxiety, depression

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Authors: Wael M. Elawady, Mohamed F. Asar, Amany M. Sarhan

Abstract:

This paper adopts a continuous sliding mode control scheme for trajectory tracking control of robot manipulators with structured and unstructured uncertain dynamics and external disturbances. In this algorithm, the equivalent control in the conventional sliding mode control is replaced by a PID control action. Moreover, the discontinuous switching control signal is replaced by a continuous proportional-integral (PI) control term such that the implementation of the proposed control algorithm does not require the prior knowledge of the bounds of unknown uncertainties and external disturbances and completely eliminates the chattering phenomenon of the conventional sliding mode control approach. The closed-loop system with the adopted control algorithm has been proved to be globally stable by using Lyapunov stability theory. Numerical simulations using the dynamical model of robot manipulators with modeling uncertainties demonstrate the superiority and effectiveness of the proposed approach in high speed trajectory tracking problems.

Keywords: PID, robot, sliding mode control, uncertainties

Procedia PDF Downloads 481

Authors: A. Zare Javid, H. Babaee, E. Ashrafzadeh, H. Yousefimanesh, M. Zakerkish, K. Ahmadi Angali, M. Ravanbakhsh

Abstract:

Introduction: Type 2 diabetes mellitus and periodontal disease hold a physiologically relationship. Periodontal disease, a common widespread chronic disease, is considered as an important complication in diabetes mellitus. The prevalence and severity of periodontal disease are increased among diabetic patients. A balanced nutrition may improve either diabetes or periodontal disease by controlling one of them. The aim of this study was to evaluate the effects of cranberry juice enriched with n-3 PUFA and their individual consumption on glycemic control and antioxidant status in diabetic patients with periodontal disease. Methods: In this randomized clinical trial 41 diabetic patients (35 – 65 y) with chronic adult periodontal disease were recruited from Endocrinology Clinic of Golestan Hospital in Ahvaz city, Iran. Subjects were randomly assigned to four groups as follow: one control group (n=12) and three intervention groups as receiving 1 g n-3 PUFA capsule (n=10), 400 ml cranberry juice (n=9), 400 ml cranberry juice enriched with 1g n-3 PUFA (n=10) for 8 weeks. Non-surgical periodontal therapy was provided for all patients during study. Fasting blood glucose, glycated hemoglobin, plasma and saliva TAOC and MDA, pocket depth and bleeding on probing were measured at baseline and post intervention. Results: There was a significant reduction in glycated hemoglobin observed in intervention groups of receiving n-3 PUFA and cranberry enriched with n-3 PUFA (11 %, P = 0.01 and 7 %, P = 0.01, respectively). The intervention group receiving n-3 PUFA had significantly lower glycated hemoglobin compared with control group. There was no significant difference found in FBS between and within groups. Furthermore, there was a significant increase in plasma TAOC only in cranberry enriched with n-3 PUFA group. Moreover, plasma MDA significantly decreased in intervention groups of receiving cranberry and cranberry enriched with n-3 PUFA. A significant increase was observed in TAOC of salvia in cranberry enriched with n-3 PUFA group compared to control group .The intervention group receiving cranberry enriched with n-3 PUFA had significantly lower MDA of salvia compared with control group. Pocket depth were significantly decreased in all groups, however, bleeding on probing didn’t significantly changed in patients post intervention. Conclusion: It is suggested that consumption of cranberry juice enriched with n-3 PUFA as a nutritional approach in adjunct with non-surgical periodontal therapy may help to improve glycosylated hemogolobin and TAOC in salvia and plasma in diabetic patients with periodontal disease.

Keywords: antioxidant, cranberry, oxidant status, periodontal disease, type 2 diabetes mellitus

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Authors: O. Poleshchuk, E. Komarov

Abstract:

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

Procedia PDF Downloads 513

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 164