Search results for: modified fuzzy entropy function

Authors: Khandoker Akib Mohammad

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While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

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Authors: Sheng-Fen Fan, Sung-Hui Tseng

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Attention deficit hyperactivity deficit (ADHD) child display diverse sensory processing difficulty behaviors. There is less evidence to figure out how the association between executive function and sensory deficit. To determine whether sensory deficit influence the executive functions, we examined sensory processing by SPM and try to indicate hot/cold executive function (EF) by BRIEF2, respectively. We found that the hot executive function deficit might associate with auditory processing in a variety of settings, and vestibular input to maintain balance and upright posture; the cold EF deficit might opposite to the hot EF deficit, the vestibular sensory modulation difficulty association with emotion shifting and emotional regulation. These results suggest that sensory processing might be another consideration factor to influence the higher cognitive control or emotional regulation of EF. Overall, this study indicates the distinction between hot and cold EF impairments with different sensory modulation problem. Moreover, for clinician, it needs more cautious consideration to conduct intervention with ADHD.

Keywords: hot executive function, cold executive function, sensory processing, ADHD

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

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A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.

Keywords: ANFIS, large-scale, power system, PSS, stability enhancement

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Haibo Zhao, Thomas Andre, Katherine Avery, Alper Kiziltas, Deborah Mielewski

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Silica aerogels were fabricated through a modified rapid supercritical extraction (RSCE) process. The silica aerogels were made using a tetramethyl orthosilicate precursor and then placed in a hot press and brought to the supercritical point of the solvent, ethanol. In order to control the pressure release without a pressure controller, a needle valve was used. The resulting aerogels were then characterized for their physical and chemical properties and compared to silica aerogels created using similar methods. The aerogels fabricated using this modified RSCE method were found to have similar properties to those in other papers using the unmodified RSCE method. Silica aerogel infused glass blanket composite, graphene reinforced silica aerogel composite were also successfully fabricated by this new method. The modified RSCE process and system is a prototype for better gas outflow control with a lower cost of equipment setup. Potentially, this process could be evolved to a continuous low-cost high-volume production process to meet automotive requirements.

Keywords: aerogel, automotive, rapid supercritical extraction process, low cost production

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Authors: O. Poleshchuk, E. Komarov

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In this paper, semantic spaces with the properties of completeness and orthogonality (complete orthogonal semantic spaces) were chosen as models of expert evaluations. As the theoretical and practical studies have shown all the properties of complete orthogonal semantic spaces correspond to the thinking activity of experts that is why these semantic spaces were chosen for modeling. Two methods of construction such spaces were proposed. Models of comparative and fuzzy cluster analysis of expert evaluations were developed. The practical application of the developed methods has demonstrated their viability and validity.

Keywords: expert evaluation, comparative analysis, fuzzy cluster analysis, theoretical and practical studies

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Authors: M. R. Al-Rashidi, K. M. El-Naggar, M. F. Al-Hajri

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The fuel cost function describes the electric power generation-cost relationship in thermal plants, hence, it sheds light on economical aspects of power industry. Different models have been proposed to describe this relationship with the quadratic function model being the most popular one. Parameters of second order fuel cost function are estimated in this paper using cuckoo search algorithm. It is a new population based meta-heuristic optimization technique that has been used in this study primarily as an accurate estimation tool. Its main features are flexibility, simplicity, and effectiveness when compared to other estimation techniques. The parameter estimation problem is formulated as an optimization one with the goal being minimizing the error associated with the estimated parameters. A case study is considered in this paper to illustrate cuckoo search promising potential as a valuable estimation and optimization technique.

Keywords: cuckoo search, parameters estimation, fuel cost function, economic dispatch

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Authors: Arup K. Sarma, Jayshree Hazarika

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The North-eastern part of India, which receives heavier rainfall than other parts of the subcontinent, is of great concern now-a-days with regard to climate change. High intensity rainfall for short duration and longer dry spell, occurring due to impact of climate change, affects river morphology too. In the present study, an attempt is made to delineate the North-Eastern region of India into some homogeneous clusters based on the Fuzzy Clustering concept and to compare the resulting clusters obtained by using conventional methods and non conventional methods of clustering. The concept of clustering is adapted in view of the fact that, impact of climate change can be studied in a homogeneous region without much variation, which can be helpful in studies related to water resources planning and management. 10 IMD (Indian Meteorological Department) stations, situated in various regions of the North-east, have been selected for making the clusters. The results of the Fuzzy C-Means (FCM) analysis show different clustering patterns for different conditions. From the analysis and comparison it can be concluded that non conventional method of using GCM data is somehow giving better results than the others. However, further analysis can be done by taking daily data instead of monthly means to reduce the effect of standardization.

Keywords: climate change, conventional and nonconventional methods of clustering, FCM analysis, homogeneous regions

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Authors: Andrew Clark

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McCauley, Bassler, and Gunaratne show that integration I(d) processes as used in economics and finance do not necessarily produce stationary increments, which are required to determine causality in both the short term and the long term. This paper follows their lead and shows I(d) aluminum cash and futures log prices at daily and weekly intervals do not have stationary increments, which means prior causality studies using I(d) processes need to be re-examined. Wavelets based on undifferenced cash and futures log prices do have stationary increments and are used along with transfer entropy (versus cointegration) to measure causality. Wavelets exhibit causality at most daily time scales out to 1 year, and weekly time scales out to 1 year and more. To determine stationarity, localized stationary wavelets are used. LSWs have the benefit, versus other means of testing for stationarity, of using multiple hypothesis tests to determine stationarity. As informational flows exist between cash and futures at daily and weekly intervals, the aluminum market is efficient. Therefore, hedges used by producers and consumers of aluminum need not have a big concern in terms of the underestimation of hedge ratios. Questions about arbitrage given efficiency are addressed in the paper.

Keywords: transfer entropy, nonstationary increments, wavelets, localized stationary wavelets, localized stationary wavelets

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Authors: Sule Sahin, Basak Bulut Karageyik

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This paper introduces a hazard rate function for the time of ruin to calculate the conditional probability of ruin for very small intervals. We call this function the force of ruin (FoR). We obtain the expected time of ruin and conditional expected time of ruin from the exact finite time ruin probability with exponential claim amounts. Then we introduce the FoR which gives the conditional probability of ruin and the condition is that ruin has not occurred at time t. We analyse the behavior of the FoR function for different initial surpluses over a specific time interval. We also obtain FoR under the excess of loss reinsurance arrangement and examine the effect of reinsurance on the FoR.

Keywords: conditional time of ruin, finite time ruin probability, force of ruin, reinsurance

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Authors: Jialin Wu, Zhiwei Lian, Jieyu Tang, Jingyun Shen

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Tornado is a serious and unpredictable natural disaster, which has an important impact on people's production and life. The probability of being hit by tornadoes in China was analyzed considering the principles of tornado formation. Then some suggestions on layout and shapes for newly-built buildings were provided combined with the characteristics of tornado wind fields. Fuzzy clustering and inverse closeness methods were used to evaluate the probability levels of tornado risks in various provinces based on classification and ranking. GIS was adopted to display the results. Finally, wind field single-vortex tornado was studied to discuss the optimized design of rural low-rise houses in Yancheng, Jiangsu as an example. This paper may provide enough data to support building and urban design in some specific regions.

Keywords: tornado probability, computational fluid dynamics, fuzzy mathematics, optimal design

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Authors: Mohamad Syahrizal Ahmad, Illyas M. Isa

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In this paper, a multiwall carbon nanotubes (MWCNT) paste electrode modified by a Zn layered hydroxide-ferulate (ZLH-F) was used for detection of hydroquinone (HQ). The morphology and characteristic of the ZLH-F/MWCNT were investigated by scanning electron microscope (SEM), transmission electron microscope (TEM) and square wave voltammetry (SWV). Under optimal conditions, the SWV response showed linear plot for HQ concentration in the range of 1.0×10⁻⁵ M – 1.0×10⁻³ M. The detection limit was found to be 5.7×10⁻⁶ M and correlation coefficient of 0.9957. The glucose, fructose, sucrose, bisphenol A, acetaminophen, lysine, NO₃⁻, Cl⁻ and SO₄²⁻ did not interfere the HQ response. This modified electrode can be used to determine HQ content in wastewater and cosmetic cream with range of recovery 97.8% - 103.0%.

Keywords: 1, 4-dihydroxybenzene, hydroquinone, multiwall carbon nanotubes, square wave voltammetry

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Madina Hamiane

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Modelling and simulation of an analogy function generator is presented based on a polynomial expansion model. The proposed function generator model is based on a 10th order polynomial approximation of any of the required functions. The polynomial approximations of these functions can then be implemented using basic CMOS circuit blocks. In this paper, a circuit model is proposed that can simultaneously generate many different mathematical functions. The circuit model is designed and simulated with HSPICE and its performance is demonstrated through the simulation of a number of non-linear functions.

Keywords: modelling and simulation, analog function generator, polynomial approximation, CMOS transistors

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Authors: Mehtap Dursun, Zeynep Şener

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Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.

Keywords: DEMATEL, group decision making, QFD, supplier selection

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Authors: Mohamed Z. M. Duwahir, Shian Gao

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The main objective of this project was to introduce and test a new scheme for parameterization of subsonic aerofoil, using a function called Shape Function. Python programming was used to create a user interactive environment for geometry generation of aerofoil using NACA and Shape Function methodologies. Two aerofoils, NACA 0012 and NACA 1412, were generated using this function. Testing the accuracy of the Shape Function scheme was done by Linear Square Fitting using Python and CFD modelling the aerofoil in Fluent. NACA 0012 (symmetrical aerofoil) was better approximated using Shape Function than NACA 1412 (cambered aerofoil). The second part of the project involved comparing two turbulent models, k-ε and Spalart-Allmaras (SA), in Fluent by modelling the aerofoils NACA 0012 and NACA 1412 in conditions of Reynolds number of 3 × 106. It was shown that SA modelling is better for aerodynamic purpose. The experimental coefficient of lift (Cl) and coefficient of drag (Cd) were compared with empirical wind tunnel data for a range of angle of attack (AOA). As a further step, this project involved drawing and meshing 3D wings in Gambit. The 3D wing flow was solved and compared with 2D aerofoil section experimental results and wind tunnel data.

Keywords: CFD simulation, shape function, turbulent modelling, aerofoil

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Authors: Nigina Toktasynova, Sholpan Sagyndykova, Zhanat Kenzhebayeva, Maksat Kalimoldayev, Mariya Ishimova, Irbulat Utepbergenov

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Any business needs a stable operation and continuous improvement, therefore it is necessary to constantly interact with the environment, to analyze the work of the enterprise in terms of employees, executives and consumers, as well as to correct any inconsistencies of certain types of processes and their aggregate. In the case of heat supply organizations, in addition to suppliers, local legislation must be considered which often is the main regulator of pricing of services. In this case, the process approach used to build a functional organizational structure in these types of businesses in Kazakhstan is a challenge not only in the implementation, but also in ways of analyzing the employee's salary. To solve these problems, we investigated the management system of heating enterprise, including strategic planning based on the balanced scorecard (BSC), quality management in accordance with the standards of the Quality Management System (QMS) ISO 9001 and analysis of the system based on expert judgment using fuzzy inference. To carry out our work we used the theory of fuzzy sets, the QMS in accordance with ISO 9001, BSC according to the method of Kaplan and Norton, method of construction of business processes according to the notation IDEF0, theory of modeling using Matlab software simulation tools and graphical programming LabVIEW. The results of the work are as follows: We determined possibilities of improving the management of heat-supply plant-based on QMS; after the justification and adaptation of software tool it has been used to automate a series of functions for the management and reduction of resources and for the maintenance of the system up to date; an application for the analysis of the QMS based on fuzzy inference has been created with novel organization of communication software with the application enabling the analysis of relevant data of enterprise management system.

Keywords: balanced scorecard, heat supply, quality management system, the theory of fuzzy sets

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Authors: Mohammed Qasim, Kyoung-Dae Kim

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In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: artificial potential function, autonomous collision avoidance, teleoperation, quadrotor

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

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Cubic equations of state like Redlich–Kwong (RK) EOS have been proved to be very reliable tools in the prediction of phase behavior. Despite their good performance in compositional calculations, they usually suffer from weaknesses in the predictions of saturated liquid density. In this research, RK equation was modified. The result of this study shows that modified equation has good agreement with experimental data.

Keywords: equation of state, modification, ammonia, genetic algorithm

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Daniel Rosero, Johan S. Arana, Sebastian Arango, Alejandro Cruz, Isabel Gomez-Gutierrez, Peter Thomson

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Santiago de Cali is located in the southwestern Colombia in a high seismic hazard zone. About 50% of the city is on the banks of the Cauca River, which is the second most important hydric affluent in the country and whose alluvial deposits contain potentially liquefiable sands. Among the methods used to study a site's liquefaction potential is the finite elements method which use constitutive models to simulate the soil response for different load types. Among the different constitutive models, the Modified UBCSand stands out to study the seismic behavior of sands, and especially the liquefaction phenomenon. In this paper, the dynamic behavior of a potentially liquefiable sand of Santiago de Cali is studied by cyclic triaxial and CPTu tests. Subsequently, the behavior of the sand is simulated using the Modified UBCSand constitutive model, whose parameters are calibrated using the results of cyclic triaxial and CPTu tests. The above with the aim of analyze the constitutive model applicability for studying the geotechnical problems associated to liquefaction in the city.

Keywords: constitutive model, cyclic triaxial test, dynamic behavior, liquefiable sand, modified ubcsand

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Authors: Lanja F. Rauf, Salahalddin S. Ali, Nadhir Al-Ansari

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Evolving groundwater vulnerability from DRASTIC to modified DRASTIC methods helps choose the most accurate areas that are most delicate toward pollution. This study aims to modify DRASTIC with land use and water quality index for groundwater vulnerability assessment in the Halabja-Khurmal sub-basin, NE/Iraq. The Halabja- Khurmal sub-basin groundwater vulnerability index is calculated from nine hydrogeological parameters by the overlay weighting method. As a result, 1.3 % of the total area has a very high vulnerability value and 46.1 % with high vulnerability. The regions with high groundwater vulnerability have a high water table and groundwater recharge. Nitrate concentration was used to validate the result, and the Pearson correlation and recession analysis between the modified DRASTIC index and nitrate concentration depicted a strong relation with 0.76 and 0.7, respectively.

Keywords: groundwater vulnerability, modified DRASTIC, land-use, nitrate pollution, water quality index

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Authors: Lucia Rozumová, Ivo Šafařík, Jana Seidlerová, Pavel Kůs

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Biosorption by biological waste materials from agriculture industry could be a cost-effective technique for removing metal ions from wastewater. The performance of new biosorbent systems, consisting of the waste matrixes which were magnetically modified by iron oxide nanoparticles, for the removal of lead ions from an aqueous solution was tested. The use of low-cost and eco-friendly adsorbents has been investigated as an ideal alternative to the current expensive methods. This article deals with the removal of metal ions from aqueous solutions by modified waste products - orange peels, sawdust, peanuts husks, used tea leaves and ground coffee sediment. Magnetically modified waste materials were suspended in methanol and then was added ferrofluid (magnetic iron oxide nanoparticles). This modification process gives the predictions for the formation of the smart materials with new properties. Prepared material was characterized by using scanning electron microscopy, specific surface area and pore size analyzer. Studies were focused on the sorption and desorption properties. The changes of iron content in magnetically modified materials after treatment were observed as well. Adsorption process has been modelled by adsorption isotherms. The results show that magnetically modified materials during the dynamic sorption and desorption are stable at the high adsorbed amount of lead ions. The results of this study indicate that the biological waste materials as sorbent with new properties are highly effective for the treatment of wastewater.

Keywords: biological waste, sorption, metal ions, ferrofluid

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Authors: Dalal N. Hammod, Ekhlas K. Gbashi

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Today, cryptography is used in many applications to achieve high security in data transmission and in real-time communications. AES has long gained global acceptance and is used for securing sensitive data in various industries but has suffered from slow processing and take a large time to transfer data. This paper suggests a method to enhance Advance Encryption Standard (AES) Algorithm based on time and permutation. The suggested method (MAES) is based on modifying the SubByte and ShiftRrows in the encryption part and modification the InvSubByte and InvShiftRows in the decryption part. After the implementation of the proposal and testing the results, the Modified AES achieved good results in accomplishing the communication with high performance criteria in terms of randomness, encryption time, storage space, and avalanche effects. The proposed method has good randomness to ciphertext because this method passed NIST statistical tests against attacks; also, (MAES) reduced the encryption time by (10 %) than the time of the original AES; therefore, the modified AES is faster than the original AES. Also, the proposed method showed good results in memory utilization where the value is (54.36) for the MAES, but the value for the original AES is (66.23). Also, the avalanche effects used for calculating diffusion property are (52.08%) for the modified AES and (51.82%) percentage for the original AES.

Keywords: modified AES, randomness test, encryption time, avalanche effects

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Authors: Negar Miri-Lavasani

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Background: Children with Attention-deficit/hyperactivity disorder (ADHD) show fine motor skills difficulties, and it is controversial whether this difficulty is based on problems in their fine motor skills or their executive function impairments. Objectives of Study: The Fine Motor and Executive Function assessment tool (FiM&EF) was developed to answer the question, ‘Do the fine motor skill deficits in children with ADHD come from their fine motor problems or is it caused by their executive function problems?’. This paper describes the development of a new assessment of Fine Motor and Executive Function (FiM &EF) needed by primary school students with ADHD aged 6-12 years with ADHD. Methods: A study on the content validity established through a survey of a panel of nine experts is explained in detail. Findings: Most the experts agreed such an assessment was needed and two items were deleted as a result of experts’ feedback. Relevance to Clinical Practice: Distinguishing the main reason of fine motor problem in these children could help the clinician for their therapy plans. Knowledge on the influence of executive functioning on fine motor ability in selected age children with ADHD would provide a clearer clinical picture of the fine motor capabilities and executive function for these children.

Keywords: children with ADHD, executive function, fine motor, test

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Authors: Kang-Mo Jung

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The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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Authors: John Knight, Fuchun Li, Yan Xu

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Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: S. Korkut, M. S. Kilic, E. Erhan

Abstract:

In order to detect and quantify the phenolic contents of a wastewater with biosensors, two working electrodes based on modified Poly (Pyrrole) films were fabricated. Enzyme horseradish peroxidase was used as biomolecule of the prepared electrodes. Various phenolics were tested at the biosensor. Phenol detection was realized by electrochemical reduction of quinones produced by enzymatic activity. Analytical parameters were calculated and the results were compared with each other.

Keywords: carbon nanotube, phenol biosensor, polypyrrole, poly (glutaraldehyde)

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