Search results for: fuzzy cognitive maps

Authors: Yuri Kitahara

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Background: Cognitive reappraisal refers to an emotion regulation strategy in which one changes the interpretation of emotion-eliciting events. Numerous studies show that cognitive reappraisal is associated with mental health and better social functioning. However the examination of the predictive factors of adaptive emotion regulation remains as an issue. The present study examined the factors contributing to the habitual use of cognitive reappraisal, with a focus on emotional awareness and working memory. Methods: Data was collected from 30 junior high school students, using a Japanese version of the Emotion Regulation Questionnaire (ERQ), the Levels of Emotional Awareness Scale for Children (LEAS-C), and N-back task. Results: A positive correlation between emotional awareness and cognitive reappraisal was observed in the high-working-memory group (r = .54, p < .05), whereas no significant relationship was found in the low-working-memory group. In addition, the results of the analysis of variance (ANOVA) showed a significant interaction between emotional awareness and working memory capacity (F(1, 26) = 7.74, p < .05). Subsequent analysis of simple main effects confirmed that high working memory capacity significantly increases the use of cognitive reappraisal for high-emotional-awareness subjects, and significantly decreases the use of cognitive reappraisal for low-emotional-awareness subjects. Discussion: These results indicate that under the condition when one has an adequate ability for simultaneous processing of information, explicit understanding of emotion would contribute to adaptive cognitive emotion regulation. The findings are discussed along with neuroscientific claims.

Keywords: cognitive reappraisal, emotional awareness, emotion regulation, working memory

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Authors: Yasemin Ilkay

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Urban spatial pattern interacts with the minds and bodies of citizens and influences their perception and attitudes, which leads to a two-folded map of the same space: physical and Psychogeographic maps. Psychogeography is a field of inquiry (rooted in literature and fiction) investigating how the environment affects the feelings and behaviors of individuals. This term was posed by Situationist International Movement in the 1950s by Guy Debord; in the course of time, the artistic framework evolved into a political issue, especially with the term Dérive, which indicates ‘deviation’ and ‘resistance’ to the existing spatial reality. The term Dérive appeared on the track of Flânéur after one hundred years; and turned out to be a political tool to transform everyday urban life. The three main concepts of psychogeography [walking, dérive, and palimpsest] construct the epistemological framework for a psychogeographic spatial analysis. Mental representations investigating this framework would provide a designer to capture the invisible layers of the gap between ‘how a space is conceived’ and ‘how the same space is perceived and experienced.’ This gap is a neglected but critical issue to discuss in the planning discipline, and psychogeography provides methodological inputs to cover the interrelation among top-down designs of urban patterning and bottom-up reproductions of ‘the soul’ of urban space at the intersection of geography and psychology. City centers and university campuses exemplify opposite poles of spatial organization and walking practice, which may result in differentiated spatial appropriation forms. There is a traditional city center in Van, located at the core of the city with a dense population and several activities, but not connected to Van Lake, which is the largest lake in the country. On the other hand, the university campus is located at the periphery, and although it has a promenade along the lake’s coast and a regional hospital, it presents a limited walking experience with ambiguous forms of spatial appropriation. The city center draws a vivid urban everyday life; however, the campus presents a relatively natural life far away from the center. This paper aims to reveal the differentiated psychogeographic maps of spatial appropriation at the city center vs. the university campus, which is located at the periphery of the city and along the coast of the largest lake in Turkey. The main question of the paper is, “how do the psychogeographic maps of spatial appropriation differentiate at the city center and university campus in Van within the walking experience with reference to the two-folded map assumption.” The experiential maps of a core group of 15 planning students will be created with the techniques of mental mapping, photographing, and narratives through attentive walks conducted together on selected routes; in addition to these attentive walks, 30 more in-depth interviews will be conducted by the core group. The narrative of psychogeographic mapping of spatial appropriation at the two spatial poles would display the conflicting soul of the city with reference to sub-behavioural regions of walking, differentiated forms of derive and layers of palimpsest.

Keywords: attentive walk, body, cognitive geography, derive, experiential maps, psychogeography, Van, Turkey

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Authors: Shiuh-Jer Huang, Yun-Han Yeh

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A 40 steps manual adjusting shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system for a four-wheel drive electric vehicle. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. A fuzzy logic controller was designed to derive appropriate damping target based on vehicle running condition for semi-active suspension system to follow. The damping ratio control of each wheel axis suspension system is executed with a robust fuzzy sliding mode controller (FSMC). Different road surface conditions are chosen to evaluate the control performance of this semi-active suspension system based on wheel axis acceleration signal.

Keywords: semi-active suspension, electric vehicle, fuzzy sliding mode control, accelerometer

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Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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Authors: Mary Anne Roa

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Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

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Authors: Hung Manh Nguyen, Duong Dai Nguyen

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Objective: To evaluate the effects of Tai Chi exercise on cognitive performance of community-dwelling elderly in Vinh city, Vietnam. Design: A randomized controlled trial. Participants: One hundred and two subjected were recruited. Intervention: Subjects were divided randomly into two groups. Tai Chi group was assigned 6-months Tai Chi training. Control group was instructed to maintain their routine daily activities. Outcome measures: Trail Making Test (TMT) is primary outcome measure. Results: Participants in Tai Chi group reported significant improvement in TMT (part A) F(1, 71) = 78.37, p < .001, and in TMT (part B) F(1, 71)= 175.00, p < .001 in comparison with Control group. Conclusion: Tai Chi is beneficial to improve cognitive performance of the elderly.

Keywords: cognitive, elderly, Vietnam, Tai Chi

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Authors: Niranjana Devi N.

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Test case selection is to select the subset of only the fit test cases and remove the unfit, ambiguous, redundant, unnecessary test cases which in turn improve the quality and reduce the cost of software testing. Test cases optimization is the problem of finding the best subset of test cases from a pool of the test cases to be audited. It will meet all the objectives of testing concurrently. But most of the research have evaluated the fitness of test cases only on single parameter fault detecting capability and optimize the test cases using a single objective. In the proposed approach, nine parameters are considered for test case selection and the best subset of parameters for test case selection is obtained using Interval Type-2 Fuzzy Rough Set. Test case selection is done in two stages. The first stage is the fuzzy entropy-based filtration technique, used for estimating and reducing the ambiguity in test case fitness evaluation and selection. The second stage is the ant colony optimization-based wrapper technique with a forward search strategy, employed to select test cases from the reduced test suite of the first stage. The results are evaluated using the Coverage parameters, Precision, Recall, F-Measure, APSC, APDC, and SSR. The experimental evaluation demonstrates that by this approach considerable computational effort can be avoided.

Keywords: ant colony optimization, fuzzy entropy, interval type-2 fuzzy rough set, test case selection

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Authors: Yog Raj Sood, Rajnish Shrivastava, Anchal Wadhwa

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Power transformer is one of the electrical equipment that has a central and critical role in the power system. In order to avoid power transformer failure, information system that provides the transformer condition is needed. This paper presents an information system to know the exact situations prevailing within the transformer by declaring its health index. Health index of a transformer is decided by considering several diagnostic tools. The current work deals with UV-Vis, IFT, FP, BDV and Water Content. UV/VIS results have been pre-accessed using separate FL controller for concluding with the Furan contents. It is broadly accepted that the life of a power transformer is the life of the oil/ paper insulating system. The method relies on the use of furan analysis (insulation paper), and other oil analysis results as a means to declare health index. Fuzzy logic system is used to develop the information system. The testing is done on 5 samples of oil of transformers of rating 132/66 KV to obtain the results and results are analyzed using fuzzy logic model.

Keywords: interfacial tension analyzer (ift), flash point (fp), furfuraldehyde (fal), health index

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Authors: Anusha M., V. Srikanth

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Maximizing spectrum usage and numerous applications of the wireless communication networks have forced to a high interest of available spectrum. Cognitive Radio control its receiver and transmitter features exactly so that they can utilize the vacant approved spectrum without impacting the functionality of the principal licensed users. The Use of various channels assists to address interferences thereby improves the whole network efficiency. The MAC protocol in cognitive radio network explains the spectrum usage by interacting with multiple channels among the users. In this paper we studied about the architecture of cognitive wireless mesh network and traditional TDMA dependent MAC method to allocate channels dynamically. The majority of the MAC protocols suggested in the research are operated on Common-Control-Channel (CCC) to handle the services between Cognitive Radio secondary users. In this paper, an extensive study of Multi-Channel Multi-Radios or frequency range channel allotment and continually synchronized TDMA scheduling are shown in summarized way.

Keywords: TDMA, MAC, multi-channel, multi-radio, WMN’S, cognitive radios

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Mihai Caramihai, Dan Vasilescu

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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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Authors: Priyashri Kamlesh Sridhar, Suranga Nanayakkara

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Current frameworks in assessment follow lesson delivery and rely heavily on test performance or teacher’s observations. This, however, neglects the underlying cognitive load during the learning process. Identifying the pivotal points when the load occurs helps design effective pedagogies and tools that respond to learners’ cognitive state. There has been limited research on quantifying cognitive load in preschoolers, real-time. In this study, we recorded electrodermal activity and heart rate variability (HRV) from 10 kindergarteners performing executive function tasks and Johnson Woodcock test of cognitive abilities. Preliminary findings suggest that there are indeed sensitive task-dependent markers in skin conductance (number of SCRs and average amplitude of SCRs) and HRV (mean heart rate and low frequency component) captured during the learning process.

Keywords: early childhood, learning, methodologies, pedagogies

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Authors: Ekpeti Bukola Grace, Mahmoudi Sabar Esmail, Chaer Issa

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Global energy consumption has been increasing steadily over the last half - century, and this trend is projected to continue. As energy demand rises in many countries throughout the world due to population growth, natural ventilation in buildings has been identified as a viable option for lowering these demands, saving costs, and also lowering CO2 emissions. However, natural ventilation is driven by forces that are generally unpredictable in nature thus, it is important to manage the resulting airflow in order to maintain pleasant indoor conditions, making it a complex system that necessitates specific control approaches. The effective application of fuzzy logic technique amidst other intelligent systems is one of the best ways to bridge this gap, as its control dynamics relates more to human reasoning and linguistic descriptions. This article reviewed existing literature and presented practical solutions by applying fuzzy logic control with optimized techniques, selected input parameters, and expert rules to design a more effective control system. The control monitors used indoor temperature, outdoor temperature, carbon-dioxide levels, wind velocity, and rain as input variables to the system, while the output variable remains the control of window opening. This is achieved through the use of fuzzy logic control tool box in MATLAB and running simulations on SIMULINK to validate the effectiveness of the proposed system. Comparison analysis model via simulation is carried out, and with the data obtained, an improvement in control actions and energy savings was recorded.

Keywords: fuzzy logic, intelligent control systems, natural ventilation, optimization

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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: Jung Hyoung Yoon

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This paper examines ways of building socio-economic sustainability for artists with cognitive disabilities who pursue professional artistic careers in Australia. It investigates two case studies of supported studios in terms of management, inclusivity and accessibility to facilitate professional development and create socio-economic values for artists with cognitive disabilities. This study uses semi-structured interviews with key art directors and staff of supported studios to unfold their experiences on the professional development of artists with cognitive disability at the individual, organizational and societal levels. It also analyses secondary data collection related to management, business strategic plans and marketing. This paper discusses the potentials of socio-economic sustainability for artists with cognitive disabilities through their art practice and careers, as well as the central role of the supported studio in order to achieve such goals for individual artists.

Keywords: artists with cognitive disability, inclusive management, professional development, socio-economic sustainability

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Authors: George Mariano Soriano

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In this study, a Rapid Earthquake Risk Ranking Criteria was formulated by integrating various existing maps and databases by the Department of Public Works and Highways (DPWH) and Philippine Institute of Volcanology and Seismology (PHIVOLCS). Utilizing Geographic Information System (GIS) software, the above-mentioned maps and databases were used in extracting seismic hazard parameters and bridge vulnerability characteristics in order to rank the seismic damage risk rating of bridges in the National Capital Region.

Keywords: bridge, earthquake, GIS, hazard, risk, vulnerability

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Authors: Jiayan Gou, Kexin He, Xin Zhang, Fei Wang, Liuni Zou

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Background: Homocysteine is a high-risk factor for cognitive decline, and folic acid supplementation can lower homocysteine levels. However, current clinical research results are inconsistent, and the effects of folic acid on homocysteine levels and cognitive function in older people are inconsistent. Objective: The objective of this study is to systematically evaluate the effects of folic acid alone or in combination with other nutrients on homocysteine levels and cognitive function in older adults. Methods: Systematic searches were conducted in five databases, including PubMed, Embase, the Cochrane Library, Web of Science, and CINAHL, from inception to June 1, 2023. Randomized controlled trials were included investigating the effects of folic acid alone or in combination with other nutrients on cognitive function in older people. Results: 17 articles were included, with six focusing on the effects of folic acid alone and 11 examining folic acid in combination with other nutrients. The study included 3,100 individuals aged 60 to 83.2 years, with a relatively equal gender distribution (approximately 51.82% male). Conclusion: Folic acid alone or combined with other nutrients can effectively lower homocysteine level and improve cognitive function in patients with mild cognitive impairment. But for patients with Alzheimer's disease and dementia, the intervention only can reduce the homocysteine level, but the improvement in cognitive function is not significant. In healthy older people, high baseline homocysteine levels (>11.3 μmol/L) and good ω-3 fatty acid status (>590 μmol/L) can enhance the improvement effect of folic acid on cognitive function. This trial has been registered on PROSPERO as CRD42023433096.

Keywords: B-complex vitamins, cognitive function, folic acid, homocysteine

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Authors: Haitham Taha

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The cognitive flexibility of 27 asthmatic children with learning difficulties was tested by using the Wisconsin card sorting test (WCST) and compared to the performances of 30 non-asthmatic children who have persistence learning difficulties also. The results revealed that the asthmatic group had poor performance through all the WCST psychometric parameters and especially the preservative errors one. The results were discussed in light of the postulation that poor executive functions and specifically poor cognitive flexibility are in the basis of the learning difficulties of asthmatic children with learning difficulties. Neurophysiologic framework was suggested for explaining the etiology of poor executive functions and cognitive flexibility among children with moderate into severe asthma.

Keywords: asthma, learning disabilities, executive functions, cognitive flexibility, WCST

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Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Muhammad Moaz

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In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.

Keywords: differential drive robot, hybrid fuzzy controller, optimization, path tracking, unicycle robot

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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: Caroline Dupre, David Hupin, Christ Goumou, Francois Belan, Frederic Roche, Thomas Celarier, Bienvenu Bongue

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Background: Previous cohorts have been notably criticized for not studying the different type of physical activity and not investigating household activities. The objective of this work was to analyse the relationship between physical activity and cognitive decline in older people living in the community. Impact of type of physical activity on the results has been realised. Methods: The study used data from the longitudinal and observational study , FrèLE (FRagility: Longitudinal Study of Expressions). The collected data included: socio-demographic variables, lifestyle, and health status (frailty, comorbidities, cognitive status, depression). Cognitive decline was assessed by using: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Physical activity was assessed by the Physical Activity Scale for the Elderly (PASE). This tool is structured in three sections: the leisure activity, domestic activity, and professional activity. Logistic regressions and proportional hazards regression models (Cox) were used to estimate the risk of cognitive disorders. Results: At baseline, the prevalence of cognitive disorders was 6.9% according to MMSE. In total, 1167 participants without cognitive disorders were included in the analysis. The mean age was 77.4 years, and 52.1% of the participants were women. After a 2 years long follow-up, we found cognitive disorders on 53 participants (4.5%). Physical activity at baseline is lower in older adults for whom cognitive decline was observed after two years of follow-up. Subclass analyses showed that leisure and domestic activities were associated with cognitive decline, but not professional activities. Conclusions: Analysis showed a relationship between cognitive disorders and type of physical activity. The current study will be completed by the MoCA for mild cognitive impairment. These findings compared to other ongoing studies, will contribute to the debate on the beneficial effects of physical activity on cognition.

Keywords: aging, cognitive function, physical activity, mixed models

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Authors: Yu Hung Chiang, Hei Chia Wang

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In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

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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: Hudson Akewe

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In this study, we introduce a modified Jungck (Dual Jungck) iterative scheme and use the scheme to approximate the unique common fixed point of a pair of generalized contractive-like operators in a Banach space. The iterative scheme is also shown to be stable with respect to the maps (S,T). An example is taken to justify the convergence of the scheme. Our result is a generalization and improvement of several results in the literature on single map T.

Keywords: generalized contractive-like operators, modified Jungck iterative scheme, stability results, weakly compatible maps, unique common fixed point

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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: R. Rama Kishore, Sunesh

Abstract:

Recent development in the usage of internet for different purposes creates a great threat for the copyright protection of the digital images. Digital watermarking can be used to address the problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field of secured, robust and imperceptible watermarking. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (2, 2) share visual cryptography and Bezier curve based algorithm to improve the security of the watermark. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method. The algorithm is optimized using fuzzy entropy for better results.

Keywords: digital watermarking, fractional transform, visual cryptography, Bezier curve, fuzzy entropy

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

Abstract:

The Wairau Plains are located in the north-east of the South Island of New Zealand in the region of Marlborough. The region is cut by many active crustal faults such as the Wairau, Awatere, and Clarence faults, which give rise to frequent seismic events. This paper presents the preliminary results of the overall project in which liquefaction-induced ground damage maps are developed in the Wairau Plains based on the Ministry of Business, Innovation and Employment NZ guidance. A suite of maps has been developed in relation to the level of details that was available to inform the liquefaction hazard mapping. Maps at the coarsest level of detail make use of regional geologic information, applying semi-quantitative criteria based on geological age, design peak ground accelerations and depth to the water table. The next level of detail incorporates higher resolution surface geomorphologic characteristics to better delineate potentially liquefiable and non-liquefiable deposits across the region. The most detailed assessment utilised CPT sounding data to develop ground damage response curves for areas across the region and provide a finer level of categorisation of liquefaction vulnerability. Linking these with design level earthquakes defined through NZGS guidelines will enable detailed classification to be carried out at CPT investigation locations, from very low through to high liquefaction vulnerability. To update classifications to these detailed levels, CPT investigations in geomorphic regions are grouped together to provide an indication of the representative performance of the soils in these areas making use of the geomorphic mapping outlined above.

Keywords: hazard, liquefaction, mapping, seismicity

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Authors: Bok Check Meng, Goh Ying Soon

Abstract:

Giving additional learning materials such as Chinese fantasy novel to non-native learners can be strenuous. Instructors have to understand the underpinning theories about cognitive theory for new word instruction. This paper discusses the underpinning theories. Relevant literature reviews are given. There are basically five major areas of cognitive related theories mentioned in this article. These include motivational learning theory, Affective theory of learning, Cognitive psychology theory, Vocabulary acquisition theory and Bloom’s cognitive levels theory. A theoretical framework has been constructed. Thus, this will give a hand in ensuring non-native learners might gain positive outcomes in the instruction process. Instructors who are interested in teaching new word from Chinese fantasy novel in specific to support additional learning might be able to get insights from this article.

Keywords: Chinese fantasy novel, new word teaching, non-native learners, cognitive theory, bloom

Procedia PDF Downloads 713