Search results for: fuzzy cognitive maps

Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Eric Mensah, Carlos Mensah

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The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

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Authors: Kartik Gupta, Virendra Kumar, Sanjeev Sinha, N. Jagannathan

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Introduction: A significant number of patients having human immunodeficiency virus (HIV) infection show a neurocognitive decline (NCD) ranging from minor cognitive impairment to severe dementia. The possible causes of NCD in HIV-infected patients include brain injury by HIV before cART, neurotoxic viral proteins and metabolic abnormalities. In the present study, we compared the level of NCD in asymptomatic HIV-infected patients with changes in brain metabolites measured by using magnetic resonance spectroscopy (MRS). Methods: 43 HIV-positive patients (30 males and 13 females) coming to ART center of the hospital and HIV-seronegative healthy subjects were recruited for the study. All the participants completed MRI and MRS examination, detailed clinical assessments and a battery of neuropsychological tests. All the MR investigations were carried out at 3.0T MRI scanner (Ingenia/Achieva, Philips, Netherlands). MRI examination protocol included the acquisition of T2-weighted imaging in axial, coronal and sagittal planes, T1-weighted, FLAIR, and DWI images in the axial plane. Patients who showed any apparent lesion on MRI were excluded from the study. T2-weighted images in three orthogonal planes were used to localize the voxel in left frontal lobe white matter (FWM) and left basal ganglia (BG) for single voxel MRS. Single voxel MRS spectra were acquired with a point resolved spectroscopy (PRESS) localization pulse sequence at an echo time (TE) of 35 ms and a repetition time (TR) of 2000 ms with 64 or 128 scans. Automated preprocessing and determination of absolute concentrations of metabolites were estimated using LCModel by water scaling method and the Cramer-Rao lower bounds for all metabolites analyzed in the study were below 15\%. Levels of total N-acetyl aspartate (tNAA), total choline (tCho), glutamate + glutamine (Glx), total creatine (tCr), were measured. Cognition was tested using a battery of tests validated for Indian population. The cognitive domains tested were the memory, attention-information processing, abstraction-executive, simple and complex perceptual motor skills. Z-scores normalized according to age, sex and education standard were used to calculate dysfunction in these individual domains. The NCD was defined as dysfunction with Z-score ≤ 2 in at least two domains. One-way ANOVA was used to compare the difference in brain metabolites between the patients and healthy subjects. Results: NCD was found in 23 (53%) patients. There was no significant difference in age, CD4 count and viral load between the two groups. Maximum impairment was found in the domains of memory and simple motor skills i.e., 19/43 (44%). The prevalence of deficit in attention-information processing, complex perceptual motor skills and abstraction-executive function was 37%, 35%, 33% respectively. Subjects with NCD had a higher level of Glutamate in the Frontal region (8.03 ± 2.30 v/s. 10.26 ± 5.24, p-value 0.001). Conclusion: Among newly diagnosed, ART-naïve retroviral disease patients from India, cognitive decline was found in 53\% patients using tests validated for this population. Those with neurocognitive decline had a significantly higher level of Glutamate in the left frontal region. There was no significant difference in age, CD4 count and viral load at initiation of ART between the two groups.

Keywords: HIV, neurocognitive decline, neurometabolites, magnetic resonance spectroscopy

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Authors: Tiffany Hollis

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Childhood trauma is well documented in mental health research, yet has received little attention in urban schools. Child trauma affects brain development and impacts cognitive, emotional, and behavioral functioning. When educators understand that some of the behaviors that appear to be aggressive in nature might be the result of a hidden diagnosis of trauma, learning can take place, and the child can thrive in the classroom setting. Traumatized children, however, do not fit neatly into any single ‘box.’ Although many children enter school each day carrying with them the experience of exposure to violence in the home, the symptoms of their trauma can be multifaceted and complex, requiring individualized therapeutic attention. The purpose of this study was to examine how prepared educators are to address the unique challenges facing children who experience trauma. Given the vast number of traumatized children in our society, it is evident that our education system must investigate ways to create an optimal learning environment that accounts for trauma, addresses its impact on cognitive and behavioral development, and facilitates mental and emotional health and well-being. The researcher describes the knowledge, attitudes, dispositions, and skills relating to trauma-informed knowledge of induction level teachers in a diverse middle school. The data for this study were collected through interviews with teachers, who are in the induction phase (the first three years of their teaching career). The study findings paint a clear picture of how ill-prepared educators are to address the needs of students who have experienced trauma and the implications for the development of a professional development workshop or series of workshops that train teachers how to recognize and address and respond to the needs of students. The study shows how teachers often lack skills to meet the needs of students who have experienced trauma. Traumatized children regularly carry a heavy weight on their shoulders. Children who have experienced trauma may feel that the world is filled with unresponsive, threatening adults, and peers. Despite this, supportive interventions can provide traumatized children with places to go that are safe, stimulating, and even fun. Schools offer an environment that potentially meets these requirements by creating safe spaces where students can feel at ease and have fun while also learning via stimulating educational activities. This study highlights the lack of preparedness of educators to address the academic, behavioral, and cognitive needs of students who have experienced trauma. These findings provide implications for the creation of a professional development workshop that addresses how to recognize and address the needs of students who have experienced some type of trauma. They also provide implications for future research with a focus on specific interventions that enable the creation of optimal learning environments where students who have experienced trauma and all students can succeed, regardless of their life experiences.

Keywords: educator preparation, induction educators, professional development, trauma-informed

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Ying Shen, Weihua Zhu

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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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Authors: Ivana Hrebickova, Maria Sevcikova, Romana Slamberova

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The present study was aimed at evaluation of cognitive changes following scheduled neonatal methamphetamine exposure in combination with long-term exposure in adulthood of female Wistar rats. Pregnant mothers were divided into two groups: group with indirect exposure (methamphetamine in dose 5 mg/ml/kg, saline in dose 1 ml/kg) during early lactation period (postnatal day 1–11) - progeny of these mothers were exposed to the effects of methamphetamine or saline indirectly via the breast milk; and the second group with direct exposure – all mothers were left intact for the entire lactation period, while progeny was treated with methamphetamine (5 mg/ml/kg) by injection or the control group, which was received needle pick (shame, not saline) at the same time each day of period of application (postnatal day 1–11). Learning ability and memory consolidation were tested in the Morris Water Maze, which consisted of three types of tests: ‘Place Navigation Test ‘; ‘Probe Test ‘; and ‘Memory Recall Test ‘. Adult female progeny were injected daily, after completion last trial with saline or methamphetamine (1 mg/ml/kg). We compared the effects of indirect/direct neonatal methamphetamine exposure and adult methamphetamine treatment on cognitive function of female rats. Statistical analyses showed that neonatal methamphetamine exposure worsened spatial learning and ability to remember the position of the platform. The present study demonstrated that direct methamphetamine exposure has more significant impact on process of learning and memory than indirect exposure. Analyses of search strategies (thigmotaxis, scanning) used by females during the Place Navigation Test and Memory Recall Test confirm all these results.

Keywords: methamphetamine, Morris water maze, neonatal exposure, strategies, Wistar rats

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Authors: Shiuh-Jer Huang, Yu-Sheng Hsu

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On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.

Keywords: vehicle auto-parking, parking space detection, parking path tracking control, intelligent fuzzy controller

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Authors: Mohamed Bendahmane, Brahim Elfalaki, Mohammed Benattou

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One of the major sources of learners' professional difficulties is their heterogeneity. Whether on cognitive, social, cultural or emotional level, learners being part of the same group have many differences. These differences do not allow to apply the same learning process at all learners. Thus, an optimal learning path for one, is not necessarily the same for the other. We present in this paper a model-oriented service to offer to each learner a personalized learning path to acquire the targeted skills.

Keywords: learning path, web service, trace analysis, personalization

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Authors: Bahadır Erişti

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Values are the behavioral procedures of society based communication and interaction process that includes social and cultural backgrounds. The policy of learning and teaching in higher education is oriented towards constructing knowledge and skills, based on theorist framework of cognitive and psychomotor aspects. This approach makes people not to develop generosity, empathy, affection, solidarity, justice, equality and so on. But the sensorial gains of education system provide the integrity of society interaction. This situation carries out the necessity of values education’s in higher education. The current study aims to consider values education from the viewpoint of students in higher education. Within the framework of the current study, an open ended survey based scenario of higher education students was conducted with the students’ social, cognitive, affective and moral developments. In line with this purpose, the following situations of the higher education system were addressed based on the higher education students’ viewpoint: The views of higher education students’ regarding values that are tried to be gained at the higher education system; The higher education students’ suggestions regarding values education at the higher education system; The views of the higher education students’ regarding values that are imposed at the higher education system. In this study, descriptive qualitative research method was used. The study group of the research is composed of 20 higher education postgraduate students at Curriculum and Instruction Department of Educational Sciences at Anadolu University. An open-ended survey was applied for the purpose of collecting qualitative data. As a result of the study, value preferences, value judgments and value systems of the higher education students were constructed on prioritizes based on social, cultural and economic backgrounds and statues. Multi-dimensional process of value education in higher education need to be constructed on higher education-community-cultural background cooperation. Thus, the act of judgement upon values between higher education students based on the survey seems to be inherent in the system of education itself. The present study highlights the students’ value priorities and importance of values in higher education. If the purpose of the higher education system gains on values, it is possible to enable society to promote humanity.

Keywords: higher education, value, values education, values in higher education

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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Authors: Kyere Vincent Nartey, Klaus Greve, Atiemo Sampson

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E-waste is discarded electrical electronic equipment inclusive of all components, sub-assemblies and consumables which are part of the product at the time of discarding and known to contain both hazardous and valuable fractions. E-waste is recycled within the proposed ecological restoration of the Agbogbloshie enclave using crude and rudimental recycling procedures such as open burning and manual dismantling which result in pollution and contamination of soil, water and air. Using GIS, this study was conducted to examine the spatial distribution and extent of soil contamination by heavy metals from the e-waste recycling site in Agbogbloshie. From the month of August to November 2013, 146 soil samples were collected in addition to their coordinates using GPS. Elemental analysis performed on the collected soil samples using X-Ray fluorescence revealed over 30 elements including, Ni, Cr, Zn, Cu, Pb and Mn. Using geostatistical techniques in ArcGIS 10.1 spatial assessment and distribution maps were generated. Mathematical models or equations were used to estimate the degree of contamination and pollution index. Results from soil analysis from the Agbogbloshie enclave showed that levels of measured or observed elements were significantly higher than the Canadian EPA and Dutch environmental standards.

Keywords: e-waste, geostatistics, soil contamination, spatial distribution

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Authors: Michael Luc Andre, Célia Maintenant

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Theory of mind is a milestone in child development which allows children to understand that others could have different mental states than theirs. Understanding the developmental stages of theory of mind in children leaded researchers on two Connected research problems. In one hand, the link between executive function and theory of mind, and on the other hand, the relationship of theory of mind and syntax processing. These two lines of research involved a great literature, full of important results, despite certain level of disagreement between researchers. For a long time, these two research perspectives continue to grow up separately despite research conclusion suggesting that the three variables should implicate same developmental period. Indeed, our goal was to study the relation between theory of mind, executive function, and language via a unique research question. It supposed that between executive function and language, one of the two variables could play a critical role in the relationship between theory of mind and the other variable. Thus, 112 children aged between three and six years old were recruited for completing a receptive and an expressive vocabulary task, a syntax understanding task, a theory of mind task, and three executive function tasks (inhibition, cognitive flexibility and working memory). The results showed significant correlations between performance on theory of mind task and performance on executive function domain tasks, except for cognitive flexibility task. We also found significant correlations between success on theory of mind task and performance in all language tasks. Multiple regression analysis justified only syntax and general abilities of language as possible predictors of theory of mind performance in our preschool age children sample. The results were discussed in the perspective of a great role of language abilities in theory of mind development. We also discussed possible reasons that could explain the non-significance of executive domains in predicting theory of mind performance, and the meaning of our results for the literature.

Keywords: child development, executive function, general language, syntax, theory of mind

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Authors: Parinyaporn Thanaboonpuang, Siridej Sujiva, Shotiga Pasiphul

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The higher education reform that integration of nursing programmes into the higher education system. Learning outcomes represent one of the essential building blocks for transparency within higher education systems and qualifications. The purpose of this study is to develop a toolkit of undergraduate nursing student’desirable characteristics assessment on Thai Qualifications Framework for Higher education and to test psychometric property for this instrument. This toolkit seeks to improve on the Computer Multimedia test. There are three skills to be examined: Cognitive skill, Responsibility and Interpersonal Skill, and Information Technology Skill. The study was conduct in 4 phases. In Phase 1. Based on developed a measurement model and Computer Multimedia test. Phase 2 two round focus group were conducted, to determine the content validity of measurement model and the toolkit. In Phase 3, data were collected using a multistage random sampling of 1,156 senior undergraduate nursing student were recruited to test psychometric property. In Phase 4 data analysis was conducted by descriptive statistics, item analysis, inter-rater reliability, exploratory factor analysis and confirmatory factor analysis. The resulting TNDC consists of 74 items across the following four domains: Cognitive skill, Interpersonal Skill, Responsibility and Information Technology Skill. The value of Cronbach’ s alpha for the four domains were .781, 807, .831, and .865, respectively. The final model in confirmatory factor analysis fit quite well with empirical data. The TNDC was found to be appropriate, both theoretically and statistically. Due to these results, it is recommended that the toolkit could be used in future studies for Nursing Program in Thailand.

Keywords: toolkit, nursing student’ desirable characteristics, Thai qualifications framework

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

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Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

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Authors: Indira Makhazhan, Azamat Taigarayev, Perizat Yerlan, Batyrbay Gulbike, Samal Abzhanova

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Aitys is a competitional performance of two or more poets creating instantly the lyrics of music concerning the social issues accompanied with the traditional instrument dombra. It is an unique music genre, because it is not practical to create music and lyrics spontaneous in anywhere else. This research study tends to approach to this particular music genre Aitys and identify its significance not only in the sense of the Kazakh cultural heritage, but also from the perspective of personal development as the improvisational , oratory, public performance skills within the ability to think critically over the social problems and represent them in convenient to public form. Through conducting this research, this paper aims to reveal the importance and beneficence of aitys in terms of both prevalence of cultural heritage and its function in personal development of the singer. In order to answer to the research question, we conducted a survey and an in-depth interview with the students of Nazarbayev University. In the survey it was asked to answer the general questions about aitys and its importance, whereas in the interview part, we asked their opinion on the importance of aitys in improving the personal skills. The results of findings was more surprising than it was expected. They agreed that the aitys lessons, workshops and concerts have high outcomes in terms improvements of improvisational, oratory, and leadership skills. Students of NU as a representors of young generation have shown a great interest in aitys, and even more interested in the topics/social issues, where the poets have to defend their usually controversial position. To conclude, the research study has focused on the importance of the aitys in personal development of different leadership skills. The given research lead us to think about the aitys as a part of cognitive musicology, where within the learning of music it represents the process of cognition as well.

Keywords: aitys, cultural heritage, Kazakh language, musicology, personal development

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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Authors: Thomas Rockstuhl, Kok Yee Ng, Guido Gianasso, Soon Ang

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Two meta-analyses show that intercultural experience is not related to intercultural adaptation or performance in international assignments. These findings have prompted calls for a deeper grounding of research on international experience in the phenomenon of global work. Two issues, in particular, may limit current understanding of the relationship between international experience and global work performance. First, intercultural experience is too broad a construct that may not sufficiently capture the essence of global work, which to a large part involves sensemaking and managing intercultural conflicts. Second, the psychological mechanisms through which intercultural experience affects performance remains under-explored, resulting in a poor understanding of how experience is translated into learning and performance outcomes. Drawing on recognition primed decision-making (RPD) research, the current study advances a cognitive processing model to highlight the importance of intercultural conflict familiarity. Compared to intercultural experience, intercultural conflict familiarity is a more targeted construct that captures individuals’ previous exposure to dealing with intercultural conflicts. Drawing on RPD theory, we argue that individuals’ intercultural conflict familiarity enhances their ability to make accurate judgments and generate effective responses when intercultural conflicts arise. In turn, the ability to make accurate situation judgements and effective situation responses is an important predictor of global work performance. A relocation program within a multinational enterprise provided the context to test these hypotheses using a time-lagged, multi-source field study. Participants were 165 employees (46% female; with an average of 5 years of global work experience) from 42 countries who relocated from country to regional offices as part a global restructuring program. Within the first two weeks of transfer to the regional office, employees completed measures of their familiarity with intercultural conflicts, cultural intelligence, cognitive ability, and demographic information. They also completed an intercultural situational judgment test (iSJT) to assess their situation judgment and situation response. The iSJT comprised four validated multimedia vignettes of challenging intercultural work conflicts and prompted employees to provide protocols of their situation judgment and situation response. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded the quality of employee’s situation judgment and situation response. Three months later, supervisors rated employees’ global work performance. Results using multilevel modeling (vignettes nested within employees) support the hypotheses that greater familiarity with intercultural conflicts is positively associated with better situation judgment, and that situation judgment mediates the effect of intercultural familiarity on situation response quality. Also, aggregated situation judgment and situation response quality both predicted supervisor-rated global work performance. Theoretically, our findings highlight the important but under-explored role of familiarity with intercultural conflicts; a shift in attention from the general nature of international experience assessed in terms of number and length of overseas assignments. Also, our cognitive approach premised on RPD theory offers a new theoretical lens to understand the psychological mechanisms through which intercultural conflict familiarity affects global work performance. Third, and importantly, our study contributes to the global talent identification literature by demonstrating that the cognitive processes engaged in resolving intercultural conflicts predict actual performance in the global workplace.

Keywords: intercultural conflict familiarity, job performance, judgment and decision making, situational judgment test

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Authors: Hammache Nadir

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The scientific study of human learning and memory is now more than 125 years old. Psychologists have conducted thousands of experiments, correlational analyses, and field studies during this time, in addition to other research conducted by those from neighboring fields. A huge knowledge base has been carefully built up over the decades. Given this backdrop, we may ask ourselves: What great changes in education have resulted from this huge research base? How has the scientific study of learning and memory changed practices in education from those of, say, a century ago? Have we succeeded in building a translational educational science to rival medical science (in which biological knowledge is translated into medical practice) or types of engineering (in which, e.g., basic knowledge in chemistry is translated into products through chemical engineering)? The answer, I am afraid, is rather mixed. Psychologists and psychological research have influenced educational practice, but in fits and starts. After all, some of the great founders of American psychology—William James, Edward L. Thorndike, John Dewey, and others—are also revered as important figures in the history of education. And some psychological research and ideas have made their way into education—for instance, computer-based cognitive tutors for some specific topics have been developed in recent years—and in years past, such practices as teaching machines, programmed learning, and, in higher education, the Keller Plan were all important. These older practices have not been sustained. Was that because they failed or because of a lack of systematic research showing they were effective? At any rate, in 2012, we cannot point to a well-developed translational educational science in which research about learning and memory, thinking and reasoning, and related topics is moved from the lab into controlled field trials (like clinical trials in medicine) and the tested techniques, if they succeed, are introduced into broad educational practice. We are just not there yet, and one question that arises is how we could achieve a translational educational science.

Keywords: affective, education, cognition, pshychology

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Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Gagandeep Singh, Navdeep Singh

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Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

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Authors: Matthew McArthur, Margaret Friend

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The COVID-19 pandemic disrupted the stability of the home environment for families across the world. Potential disruptions include parent work modality (in-person vs. remote), levels of health anxiety, family routines, and caregiving. These disruptions may have interfered with the processes of early vocabulary acquisition, carrying lasting effects over the life course. Our justification for this research is as follows: First, early, stable, caregiver-child reciprocal interactions, which may have been disrupted during the pandemic, contribute to the development of the brain architecture that supports language, cognitive, and social-emotional development. Second, early vocabulary predicts several cognitive outcomes, such as numeracy, literacy, and executive function. Further, disruption in the home is associated with adverse cognitive, academic, socio-emotional, behavioral, and communication outcomes in young children. We are interested in how disruptions related to the COVID-19 pandemic are associated with vocabulary acquisition in children born during the first two waves of the pandemic. We are conducting a moderated online experiment to assess this question. Participants are 16 children (10F) ranging in age from 19 to 39 months (M=25.27) and their caregivers. All child participants were screened for language background, health history, and history of language disorders, and were typically developing. Parents completed a modified version of the COVID-19 Family Stressor Scale (CoFaSS), a published measure of COVID-19-related family stressors. Thirteen items from the original scale were replaced to better capture change in family organization and stability specifically related to disruptions in income, anxiety, family relations, and childcare. Following completion of the modified CoFaSS, children completed a Web-Based version of the Computerized Comprehension Task and the Receptive One Word Picture Vocabulary if 24 months or older or the MacArthur-Bates Communicative Development Inventory if younger than 24 months. We report our preliminary data as a partial correlation analysis controlling for age. Raw vocabulary scores on the CCT, ROWPVT-4, and MCDI were all negatively associated with pandemic-related disruptions related to anxiety (r12=-.321; r1=-.332; r9=-.509), family relations (r12=-.590*; r1=-.155; r9=-.468), and childcare (r12=-.294; r1=-.468; r9=-.177). Although the small sample size for these preliminary data limits our power to detect significance, this trend is in the predicted direction, suggesting that increased pandemic-related disruption across multiple domains is associated with lower vocabulary scores. We anticipate presenting data on a full sample of 50 monolingual English participants. A sample of 50 participants would provide sufficient statistical power to detect a moderate effect size, adhering to a nominal alpha of 0.05 and ensuring a power level of 0.80.

Keywords: COVID-19, early vocabulary, home environment, language acquisition, multiple measures

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Authors: Vahid Anari, Leila Shahmohammadi

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Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction

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Authors: Maryam Safrai, Tewfik Mahdi

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This article presents the stochastic modeling of the Richelieu River flood in Quebec, Canada, occurred in the spring of 2011. With the aid of the one-dimensional Watershed Modeling System (WMS (v.10.1) and HEC-RAS (v.4.1) as a flood simulator, the delineation of the probabilistic flooded areas was considered. Based on the Monte Carlo method, WMS (v.10.1) delineated the probabilistic flooded areas with corresponding occurrence percentages. Furthermore, results of this one-dimensional model were compared with the results of two-dimensional model (SRH-2D) for the evaluation of efficiency and precision of each applied model. Based on this comparison, computational process in two-dimensional model is longer and more complicated versus brief one-dimensional one. Although, two-dimensional models are more accurate than one-dimensional method, but according to existing modellers, delineation of probabilistic flooded areas based on Monte Carlo method is achievable via one-dimensional modeler. The applied software in this case study greatly responded to verify the research objectives. As a result, flood risk maps of the Richelieu River with the two applied models (1d, 2d) could elucidate the flood risk factors in hydrological, hydraulic, and managerial terms.

Keywords: flood modeling, HEC-RAS, model comparison, Monte Carlo simulation, probabilistic flooded area, SRH-2D, WMS

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Authors: Nasim Babazadeh

Abstract:

Growing demand for a quieter dwelling environment has turned the attention of construction companies to reducing the propagated noise of their project. In inner-city constructions, close distance between the construction site and surrounding buildings lessens the efficiency of passive noise control methods. Dwellers of the nearby areas may file complaints and lawsuits against the construction companies due to the emitted construction noise, thereby leading to the interruption of processes, compensation costs, or even suspension of the project. Therefore, construction noise should be predicted along with the project schedule. The advantage of managing the noise in the pre-construction phase is two-fold. Firstly, changes in the time plan and construction methods can be applied more flexibly. Thus, the costs related to rescheduling can be avoided. Secondly, noise-related legal problems are expected to be reduced. To implement noise mapping methods for the mentioned prediction, the required detailed information (such as the location of the noisy process, duration of the noisy work) can be exported from the 4D BIM model. The results obtained from the noise maps would be used to help the planners to define different work scenarios. The proposed approach has been applied for the foundation and earthwork of a site located in a residential area, and the obtained results are discussed.

Keywords: building information modeling, construction noise management, noise mapping, 4D BIM

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Authors: Djebbar Atmani, Dina Kilani, Tristan Richard

Abstract:

Medicinal plants are an important source for the discovery of potential new substances for use in medicine and food. Pistacia lentiscus, Fraxinus angustifolia and Clematis flammula, plants growing in the Mediterranean basin, are widely used in traditional medicine. Therefore, the present study was designed to investigate their antioxidant, anti-inflammatory, antidiabetic, anti-mutagenic/genotoxic and neuroprotective potential and identification of active compounds using appropriate methodology. Plant extracts and fractions exhibited high scavenging capacity against known radicals, enhanced superoxide dismutase and catalase activitiesand restored blood glucose levels, in vivo, to normal values, in agreement with the in vitro enzymatic inhibition data, through inhibition of amylase and glucosidase activities. Administration of Pistacia lentiscus extracts significantly decreased carrageenan-induced mice paw oedema and reduced effectively IL-1β levels in cell culture, whereas Fraxinus angustifolia extracts showed good healing capacity against wounds when applied topically on rabbits. Pistacia lentiscus and Fraxinus angustifolia extracts showed good neuro-protection and restored cognitive functions in mice, while Clematis flammula extracts showed potent anti-ulcerogenic activity associated to a promising anti-mutagenic/genotoxic activity. HPLC-MS and NMR analyses allowed the identification and structural elucidation of several known and new anthocyanins, flavonols and flavanols. Therefore, Pistacia lentiscus, Fraxinus angustifolia and Clematis flammulacould be used in palliative treatments against inflammatory conditions and diabetes complications, as well as against deterioration of cognitive functions.

Keywords: pistacia lentiscus, clematis flammula, fraxinus angustifolia, phenolic compounds, biological activity

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Norita Ahmad, Reza Barkhi, Xiaobo Xu

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We design an experimental study to learn about the cognitive implications of the use of avatars in a Virtual World (VW) (i.e., Second Life). The results support our proposed model, where a positive flow experience with VW influences the attitude towards VW, in turn influencing intention to use VW. Furthermore, VW flow experience can itself be impacted by perceived peer influence, familiarity with VW, and personality of the individuals behind the avatars in VW.

Keywords: avatar, flow experience, personality type, second life, virtual world

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Authors: A. A. Behroozpoor, M. M. Mazarei

Abstract:

In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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