Search results for: fuzzy soft similarity measures

Authors: Giulia Leoni, Cristina Florio

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The paper aims to investigate the factors driving the increasing alignment of Italian earnings management (EM) research to US research on the same field. After characterizing the progressive similarity of Italian EM research with respect to US one by means of an historical comparison, the paper relies on a subsequent secondary source analysis to detect the possible causes of said alignment. Once identified that the alignment increased along three subsequent periods, the paper analyses and discusses this incremental similarity according to new institutional sociology (NIS) and highlights the presence of different combination of isomorphic pressures that help explaining this incremental similarity. The paper contributes to the institutional literature by providing evidence of isomorphism in academic research; it also contributes to accounting research by indicating the forces that are able to drive change and development in accounting research at national and international level. The paper also enlarges the explanatory value of NIS in alternative contexts, like academic accounting research.

Keywords: accounting research, earnings management, international comparison, Italy, new institutional sociology, US

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Authors: Katie Strong, Brian P. O'Connor, Jacqueline M. Kanippayoor

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To date, self-report measures of psychopathy have largely been conceptualized with a male-focused understanding of the disorder, with the presumption that psychopathy expression is uniform across genders. However, generalizing this understanding to the female population may be misleading. The objective of this research was to explore gender differences in the expression of psychopathy and to assess current self-report psychopathy measures for gender bias. It was hypothesized that some items in commonly used measures of psychopathy may show gender bias and that existing measures may not contain enough items that are relevant to the manifestation of psychopathy in women. An exploratory investigation was conducted on statistical bias in common measures of psychopathy, and novel, relevant, but previously neglected items and measures were included in a new data collection. The participant pool included a sample of 403 university students and 354 participants recruited using Amazon Mechanical Turk. Item Response Theory methods - including Differential Item Functioning - were used to assess for the item- and test- level bias across several common self-report measures of psychopathy. Analyses indicated occasional and modest levels of item-level bias, and that some additional female-relevant items merit consideration for inclusion in measures of psychopathy. These findings suggest that current self-report measures of psychopathy may be demonstrating gender-bias and warrant further examination.

Keywords: gender, measurement bias, personality, psychopathy

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

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Authors: Jun Yu, Yat-Hei Lam, Boris Grinberg, Kevin Chai Tshun Chuan

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This paper presents a 5-V to 30-V current-mode boost converter for powering the drive circuit of a micro-electro-mechanical sensor. The design of a transconductance amplifier and an integrated current sensing circuit are presented. In addition, essential building blocks for power-on protection such as a soft-start and clamp block and supply and clock ready block are discussed in details. The chip is fabricated in a 0.18-μm CMOS process. Measurement results show that the soft-start and clamp block can effectively limit the inrush current during startup and protect the boost converter from startup failure.

Keywords: boost converter, current sensing, power-on protection, step-up converter, soft-start

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Authors: Li Chen, Alex Skvortsov, Chris Norwood

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Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.

Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model

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Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

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This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: control, fuzzy logic, sensitive system, technological proves

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

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Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha

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Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.

Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models

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Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins's problem, double-input rule module, fuzzy inference model, obstacle avoidance, single-input rule module

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Authors: N. Chayaopas, W. Assawinchaichote

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In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG.

Keywords: doubly fed induction generator, H-infinity fuzzy integral control, linear matrix inequality, wind energy system

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Authors: Salman Hameed

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In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: Azadeh Rouhandeh, Chris Joslin, Zhen Qu, Yuu Ono

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The centre of rotation of the hip joint is needed for an accurate simulation of the joint performance in many applications such as pre-operative planning simulation, human gait analysis, and hip joint disorders. In human movement analysis, the hip joint center can be estimated using a functional method based on the relative motion of the femur to pelvis measured using reflective markers attached to the skin surface. The principal source of errors in estimation of hip joint centre location using functional methods is soft tissue artefacts due to the relative motion between the markers and bone. One of the main objectives in human movement analysis is the assessment of soft tissue artefact as the accuracy of functional methods depends upon it. Various studies have described the movement of soft tissue artefact invasively, such as intra-cortical pins, external fixators, percutaneous skeletal trackers, and Roentgen photogrammetry. The goal of this study is to present a non-invasive method to assess the displacements of the markers relative to the underlying bone using optical motion capture data and tissue thickness from ultrasound measurements during flexion, extension, and abduction (all with knee extended) of the hip joint. Results show that the artefact skin marker displacements are non-linear and larger in areas closer to the hip joint. Also marker displacements are dependent on the movement type and relatively larger in abduction movement. The quantification of soft tissue artefacts can be used as a basis for a correction procedure for hip joint kinematics.

Keywords: hip joint center, motion capture, soft tissue artefact, ultrasound depth measurement

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

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Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Alireza Gilani

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In this paper, we consider the fuzzification of implicative pseudo-ideal in a pseudo-BCK algebra, and then we investigate some of their properties. We prove that the family of fuzzy implicative pseudo-ideal is completely distributive lattice.

Keywords: BCK-algebra, pseudo-BCK algebra, pseudo-ideal, implicative pseudo-ideal

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Authors: Omid Heydarnia, Akbar Allahverdizadeh, Behnam Dadashzadeh, M. R. Sayyed Noorani

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Underactuated biped robots control is one of the interesting topics in robotics. The main difficulties are its highly nonlinear dynamics, open-loop instability, and discrete event at the end of the gait. One of the methods to control underactuated systems is the partial feedback linearization, but it is not robust against uncertainties and disturbances that restrict its performance to control biped walking and running. In this paper, fuzzy partial feedback linearization is presented to overcome its drawback. Numerical simulations verify the effectiveness of the proposed method to generate stable and robust biped walking and running gaits.

Keywords: underactuated system, biped robot, fuzzy control, partial feedback linearization

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Authors: Majid Rezayi, Sh. Shahaboddin, HNM E. Mahmud, A. Yadollah, A. Saeid, A. Yatimah

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In this study, the adaptive neuro-fuzzy inference system (ANFIS) was applied to obtain the membrane composition model affecting the potential response of our reported polymeric PVC sensor for determining the titanium (III) ions. The performance statistics of the artificial neural network (ANN) and linear regression models for potential slope prediction of membrane composition of titanium (III) ion selective electrode were compared with ANFIS technique. The results show that the ANFIS model can be used as a practical tool for obtaining the Nerntian slope of the proposed sensor in this study.

Keywords: adaptive neuro fuzzy inference, PVC sensor, titanium (III) ions, Nerntian slope

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Authors: Rungrot Trongsakul

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This paper was aimed to study the strategic cooperation development of Thailand in accordance with the door open policy of Myanmar, by use of DIMES Model: Diplomacy, Information, Military and Economics, Socio-Culture. This research employed qualitative method, aiming to study, analyze and synthesize the content of laws, policies, relevant research papers and documents, and relevant theories, and to study external environment and national power based on DIMES Model. The five steps of strategic development utilized in this study included (1) conceptual framework and definition; (2) environmental scanning; (3) assessing; (4) determining; and (5) drafting strategic plan. The suggested strategies were based on the concept of 'Soft Power'. Therefore, the determination of measures, action plans or projects as strategic means of public and private organizations should be based on sincere participation among people and communities living on the borders shared by both countries. Adoption of education, learning and sharing process is a key to building sustainability of the countries’ strategic cooperation, while an application of 'Soft Power' in all dimensions of the cooperation between the two countries was suggested.

Keywords: education, strategic cooperation, Thailand-Myanmar borders, sustainability

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Sukrita Mukherjee, Anindita Chaudhuri

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Soft skills are a crucial aspect for employees, and these skills are not confined to any particular field rather, it guarantees further career growth and job opportunities for employees who are seeking growth. Soft skills are also regarded as personality-specific skills that are observable and are qualitative in nature, which determines an employee’s strengths as a leader. When an employee intends to hold his job, then the person must make effective use of his personal resources, that, in turn, impacts his employability in a positive manner. An employee at his workplace is expected to make effective use of his personal resources. The resources that are to be used by the employee are generally of two types. First type of resources are occupation related, which is related with the educational background of the employee, and the second type of resources are the psychological resources of the employee, such as self-knowledge, career orientation awareness, sense of purpose and emotional literacy, that are considered crucial for an employee in his workplace. The present study is a qualitative study which includes 10 individuals working in IT Sector and Service Industry, respectively. For IT sector, graduate people are considered, and for the Service Industry, individuals who have done a Professional course in order to get into the industry are considered. The emerging themes from the findings after thematic analysis reveal that different aspect of Soft skills such as communication, decision making, constant learning, keeping oneself updated with the latest technological advancement, emotional intelligence are some of the important factors that helps an employee not only to sustain his job, but also grow in his workplace.

Keywords: employabiliy, soft skils, employees, resources, workplace

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Authors: Sharifullah Ahmed

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Shallow foundation on soft soils without ground improvement can represent a high level of settlement. In such a case, an alternative to pile foundations may be shallow strip footings placed on a soil system in which the upper layer is untreated or cement-treated compacted sand to limit the settlement within a permissible level. This research work deals with a rigid plane-strain strip footing of 2.5m width placed on a soil consisting of untreated or cement treated sand layer underlain by homogeneous soft clay. Both the thin and thick compared the footing width was considered. The soft inorganic cohesive NC clay layer is considered undrained for plastic loading stages and drained in consolidation stages, and the sand layer is drained in all loading stages. FEM analysis was done using PLAXIS 2D Version 8.0 with a model consisting of clay deposits of 15m thickness and 18m width. The soft clay layer was modeled using the Hardening Soil Model, Soft Soil Model, Soft Soil Creep model, and the upper improvement layer was modeled using only the Hardening Soil Model. The system is considered fully saturated. The value of natural void ratio 1.2 is used. Total displacement fields of strip footing and subsoil layers in the case of Untreated and Cement treated Sand as Upper layer are presented. For Hi/B =0.6 or above, the distribution of major deformation within an upper layer and the influence zone of footing is limited in an upper layer which indicates the complete effectiveness of the upper layer in bearing the foundation effectively in case of the untreated upper layer. For Hi/B =0.3 or above, the distribution of major deformation occurred within an upper layer, and the function of footing is limited in the upper layer. This indicates the complete effectiveness of the cement-treated upper layer. Brittle behavior of cemented sand and fracture or cracks is not considered in this analysis.

Keywords: displacement, ground improvement, influence depth, PLAXIS 2D, primary and secondary settlement, sand mat, soft clay

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Authors: Bouharati Lokman, Bouharati Imen, Bouharati Khaoula, Bouharati Oussama, Bouharati Saddek

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Ionizing radiation exposure is an established cancer risk factor. Compared to other common environmental carcinogens, it is relatively easy to determine organ-specific radiation dose and, as a result, radiation dose-response relationships tend to be highly quantified. Nevertheless, there can be considerable uncertainty about questions of radiation-related cancer risk as they apply to risk protection and public policy, and the interpretations of interested parties can differ from one person to another. Examples of tools used in the analysis of the risk of developing cancer due to radiation are characterized by uncertainty. These uncertainties are related to the history of exposure and different assumptions involved in the calculation. We believe that the results of statistical calculations are characterized by uncertainty and imprecision. Having regard to the physiological variation from one person to another. In this study, we develop a tool based on fuzzy logic inference. As fuzzy logic deals with imprecise and uncertain, its application in this area is adequate. We propose a fuzzy system with three input variables (age, sex and body attainable cancer). The output variable expresses the risk of infringement rate of each organ. A base rule is established from recorded actual data. After successful simulation, this will instantly predict the risk of infringement rate of each body following chronic exposure to 0.1 Gy.

Keywords: radiation exposure, cancer, modeling, fuzzy logic

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Authors: Xinyi Le

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In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side.

Keywords: 3d printing, perceptual model, fuzzy evaluation, data-driven approach

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Talal H. Alzanki

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This paper presents a hybrid fuzzy logic control strategy for a unicycle trajectory following robot on irregular terrains. In literature, researchers have presented the design of path tracking controllers of mobile robots on non-frictional surface. In this work, the robot is simulated to drive on irregular terrains with contrasting frictional profiles of peat and rough gravel. A hybrid fuzzy logic controller is utilised to stabilise and drive the robot precisely with the predefined trajectory and overcome the frictional impact. The controller gains and scaling factors were optimised using spiral dynamics optimisation algorithm to minimise the mean square error of the linear and angular velocities of the unicycle robot. The robot was simulated on various frictional surfaces and terrains and the controller was able to stabilise the robot with a superior performance that is shown via simulation results.

Keywords: fuzzy logic control, mobile robot, trajectory tracking, spiral dynamic algorithm

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Authors: Caje F. Pinto, Jivan S. Parab, Gourish M. Naik

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This paper is about the development of non-invasive heart rate and oxygen saturation in human blood using Altera NIOS II soft-core processor system. In today's world, monitoring oxygen saturation and heart rate is very important in hospitals to keep track of low oxygen levels in blood. We have designed an Embedded System On Peripheral Chip (SOPC) reconfigurable system by interfacing two LED’s of different wavelengths (660 nm/940 nm) with a single photo-detector to measure the absorptions of hemoglobin species at different wavelengths. The implementation of the interface with Finger Probe and Liquid Crystal Display (LCD) was carried out using NIOS II soft-core system running on Altera NANO DE0 board having target as Cyclone IVE. This designed system is used to monitor oxygen saturation in blood and heart rate for different test subjects. The designed NIOS II processor based non-invasive heart rate and oxygen saturation was verified with another Operon Pulse oximeter for 50 measurements on 10 different subjects. It was found that the readings taken were very close to the Operon Pulse oximeter.

Keywords: heart rate, NIOS II, oxygen saturation, photoplethysmography, soft-core, SOPC

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Authors: Miriam Filipová, Peter Balco

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At present, in Slovak and Czech Republic, the education within the field of Project Management is carried out either within the higher education or via commercial entities, whilst the most used contents are the commonly used methodologies of project management. Obtaining a diploma after completing a university degree or a training certificate does not automatically mean the success of the project or the success of the project manager. The importance of leadership and soft skills in project management is either not included at all within the training of project managers, or it is only partially reflected. From the methodology perspective, the most important things during the preparation and management of the projects are preparation of the project plan, resource planning, and project realization in accordance with the chosen methodology. However, the key element on which the success of the project depends on are the people – whether they are team members on the supplier's side, the stakeholders, or the end users. This research focuses on the real needs of working project managers, on the development of their strengths, expertise, skills, and knowledge regarding leadership and soft skills. At the same time, it looks into identifying the elements that they consider to be key to the success of the projects they have managed and successfully delivered. The result of this research is the input for creating recommendations for a comprehensive education of project managers in the field of leadership and soft skills.

Keywords: project management, leadership, soft skills, education, academic degree, certificates, skills, talents, knowledge

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Authors: Z. B. Ibrahim, N. Ismail, K. I. Othman

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Fuzzy Differential Equations (FDEs) play an important role in modelling many real life phenomena. The FDEs are used to model the behaviour of the problems that are subjected to uncertainty, vague or imprecise information that constantly arise in mathematical models in various branches of science and engineering. These uncertainties have to be taken into account in order to obtain a more realistic model and many of these models are often difficult and sometimes impossible to obtain the analytic solutions. Thus, many authors have attempted to extend or modified the existing numerical methods developed for solving Ordinary Differential Equations (ODEs) into fuzzy version in order to suit for solving the FDEs. Therefore, in this paper, we proposed the development of a fuzzy version of three-point block method based on Block Backward Differentiation Formulas (FBBDF) for the numerical solution of first order FDEs. The three-point block FBBDF method are implemented in uniform step size produces three new approximations simultaneously at each integration step using the same back values. Newton iteration of the FBBDF is formulated and the implementation is based on the predictor and corrector formulas in the PECE mode. For greater efficiency of the block method, the coefficients of the FBBDF are stored at the start of the program. The proposed FBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing fuzzy version of the Modified Simpson and Euler methods in terms of the accuracy of the approximated solutions. The numerical results show that the FBBDF method performs better in terms of accuracy when compared to the Euler method when solving the FDEs.

Keywords: block, backward differentiation formulas, first order, fuzzy differential equations

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Authors: Jinsiang Shaw, Shih-Chieh Tseng

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Active vibration control is good for low frequency excitation, with advantages of light weight and adaptability. This paper use a macro-fiber composite (MFC) actuator for vibration suppression in a cantilevered beam due to its higher output force to suppress the disturbance. A fuzzy sliding mode controller is developed and applied to this system. Experimental results illustrate that the controller and MFC actuator are very effective in attenuating the structural vibration near the first resonant freuqency. Furthermore, this controller is shown to outperform the traditional skyhook controller, with nearly 90% of the vibration suppressed at the first resonant frequency of the structure.

Keywords: Fuzzy sliding mode controller, macro-fiber-composite actuator, skyhook controller, vibration suppression

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Authors: Johanna Perdomo, Riki Lamont, Edmund Pickering, Naomi C. Paxton, Maria A. Woodruff

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Background: Tissue Engineering (TE) has combined advanced materials, such as biomaterials, to create affordable scaffolds and dynamic systems to generate stimulation of seeded cells on these scaffolds, improving and maintaining the cellular growth process in a cell culture. However, Few TE skin products have been clinically translated, and more research is required to produce highly biomimetic skin substitutes that mimic the native elasticity of skin in a controlled manner. Therefore, this work will be focused on the fabrication of a novel mechanical system to enhance the TE treatment approaches for the reparation of damaged tissue skin. Aims: To archive this, a soft robotic device will be created to emulate different deformation of skin stress. The design of this soft robot will allow the attachment of scaffolds, which will then be mechanically actuated. This will provide a novel and highly adaptable platform for dynamic cell culture. Methods: Novel, low-cost soft robot is fabricated via 3D printed moulds and silicone. A low cost, electro-mechanical device was constructed to actuate the soft robot through the controlled combination of positive and negative air pressure to control the different state of movements. Mechanical tests were conducted to assess the performance and calibration of each electronic component. Similarly, pressure-displacement test was performed on scaffolds, which were attached to the soft robot, applying various mechanical loading regimes. Lastly, digital image correlation test was performed to obtain strain distributions over the soft robot’s surface. Results: The control system can control and stabilise positive pressure changes for long hours. Similarly, pressure-displacement test demonstrated that scaffolds with 5µm of diameter and wavy geometry can displace at 100%, applying a maximum pressure of 1.5 PSI. Lastly, during the inflation state, the displacement of silicone was measured using DIC method, and this showed a parameter of 4.78 mm and strain of 0.0652. Discussion And Conclusion: The developed soft robot system provides a novel and low-cost platform for the dynamic actuation of tissue scaffolds with a target towards dynamic cell culture.

Keywords: soft robot, tissue engineering, mechanical stimulation, dynamic cell culture, bioreactor

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Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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