Search results for: distributed type-2 fuzzy algorithm

Authors: N. Boutaghane, F. Z. Tounsi

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Many physical and technological factors degrade the SPECT images, both qualitatively and quantitatively. For this, it is not always put into leading technological advances to improve the performance of tomographic gamma camera in terms of detection, collimation, reconstruction and correction of tomographic images methods. We have to master firstly the choice of various acquisition and reconstruction parameters, accessible to clinical cases and using the attenuation and scatter correction methods to always optimize quality image and minimized to the maximum dose received by the patient. In this work, an evaluation of qualitative and quantitative tomographic images is performed based on the acquisition parameters (counts per projection) and reconstruction parameters (filter type, associated cutoff frequency). In addition, methods for correcting physical effects such as attenuation and scatter degrading the image quality and preventing precise quantitative of the reconstructed slices are also presented. Two approaches of attenuation and scatter correction are implemented: the attenuation correction by CHANG method with a filtered back projection reconstruction algorithm and scatter correction by the subtraction JASZCZAK method. Our results are considered as such recommandation, which permits to determine the origin of the different artifacts observed both in quality control tests and in clinical images.

Keywords: attenuation, scatter, reconstruction filter, image quality, acquisition and reconstruction parameters, SPECT

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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Authors: Sousan Arafeh

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Educational systems and schools worldwide are increasingly reliant on information and communication technology (ICT). Unfortunately, most educational leadership development programs do not offer formal curricular and/or field experiences that prepare students for managing ICT resources, personnel, and processes. The result is a steep learning curve for the leader and his/her staff and dissipated organizational energy that compromises desired outcomes. To address this gap in education leaders’ development, Arafeh’s Integrated Technology Leadership Model (AITLM) was created. It is a conceptual model and tool that educational leadership students can use to better understand the ICT ecology that exists within their schools. The AITL Model consists of six 'infrastructure types' where ICT activity takes place: technical infrastructure, communications infrastructure, core business infrastructure, context infrastructure, resources infrastructure, and human infrastructure. These six infrastructures are further divided into 16 key areas that need management attention. The AITL Model was created by critically analyzing existing technology/ICT leadership models and working to make something more authentic and comprehensive regarding school leaders’ purview and experience. The AITL Model then served as a tool when it was distributed to over 150 educational leadership students who were asked to review it and qualitatively share their reactions. Students said the model presented crucial areas of consideration that they had not been exposed to before and that the exercise of reviewing and discussing the AITL Model as a group was useful for identifying areas of growth that they could pursue in the leadership development program and in their professional settings. While development in all infrastructures and key areas was important for students’ understanding of ICT, they noted that they were least aware of the importance of the intangible area of the resources infrastructure. The AITL Model will be presented and session participants will have an opportunity to review and reflect on its impact and utility. Ultimately, the AITL Model is one that could have significant policy and practice implications. At the very least, it might help shape ICT content in educational leadership development programs through curricular and pedagogical updates.

Keywords: education leadership, information and communications technology, ICT, leadership capacity building, leadership development

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Majid Afkhami, Maryam Ehsanpour, Rastin Afkhami

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Sea cucumbers are aquatic animals with a wide variety useful for human health. Sea cucumbers are from the aquatic creatures that have many important and useful properties known for human health. Increasing demand for beche-de-mer along with steady price increases have led to worldwide intensification of sea cucumber harvesting. The rearing of sea cucumber with shrimp controls the environmental pollution results from extra enriched nutritious built on the pond bottom. These animals eat detritus and with devouring of organic materials on the surface, not only do they make the environment clean, but also they cause the fast growth of shrimp and themselves. Holothuria scabra is a main species for producing of Beche-de-mer and more exploited in tropical region of the world. The wall of body is used in the process of beche-de-mer production that forms the 56% of the whole body. Holothuria scabra (sandfish) is an aspidochirote holothurian widely distributed in coastal regions throughout the Indo-Pacific region. H. scabra is often found on inner reef flats and near estuaries, half buried in the silt sand during the day and emerging at night to feed. In this study upon to information from local fishermen's in Qeshm island, we Providing some data about fishing methods, processing and distribution in the Qeshm island coastline. Comparative study of fishing status with another part of the world determined that the status of sea cucumber stocks in Qeshm Island is suitable. For preventing of over exploited of sandy sea cucumber capture prohibition should be continue. In this study, 7 explotide sites are recognized, the target size for fishermen's was more than 20 cm and sandy cucumber was the target species in Qeshm Island. In this area the fishing operation was only done by scuba diving and has been done only by men's. Although in another countries women's have an important role in sea cucumber fishing operation. In the coast around Qeshm island it is found in Hmoon, Tolla, kovei, Ramchah, Messen, and Hengam. The maximum length and weight was recorded 35 cm and 1080 gr, respectively.

Keywords: sea cucumber, Holothuria scabra, fishing status, Qeshm Island

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Authors: Shahid Hussain Abro, Siamak Zohari, Lena H. M. Renström, Désirée S. Jansson, Faruk Otman, Karin Ullman, Claudia Baule

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Infectious bronchitis is an acute, highly contagious respiratory, nephropathogenic and reproductive disease of poultry that is caused by infectious bronchitis virus (IBV). The present study used a large data set of structural gene sequences, including newly generated ones and sequences available in the GenBank database to further analyze the diversity and to identify selective pressures and recombination spots. There were some deletions or insertions in the analyzed regions in isolates of the Italy-02 and D274 genotypes. Whereas, there were no insertions or deletions observed in the isolates of the Massachusetts and 4/91 genotype. The hypervariable nucleotide sequence regions spanned positions 152–239, 554–582, 686–737 and 802–912 in the S1 sub-unit of the all analyzed genotypes. The nucleotide sequence data of the E gene showed that this gene was comparatively unstable and subjected to a high frequency of mutations. The M gene showed substitutions consistently distributed except for a region between nucleotide positions 250–680 that remained conserved. The lowest variation in the nucleotide sequences of ORF5a was observed in the isolates of the D274 genotype. While, ORF5b and N gene sequences showed highly conserved regions and were less subjected to variation. Genes ORF3a, ORF3b, M, ORF5a, ORF5b and N presented negative selective pressure among the analyzed isolates. However, some regions of the ORFs showed favorable selective pressure(s). The S1 and E proteins were subjected to a high rate of mutational substitutions and non-synonymous amino acids. Strong signals of recombination breakpoints and ending break point were observed in the S and N genes. Overall, the results of this study revealed that very likely the strong selective pressures in E, M and the high frequency of substitutions in the S gene can probably be considered the main determinants in the evolution of IBV.

Keywords: IBV, avian infectious bronchitis, structural genes, genotypes, genetic diversity

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Authors: M. Maache, R. Bessaih

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In this study, the effect of the magnetic field direction on the free convection heat transfer in a vertical cylinder filled with an Al₂O₃ nanofluid is investigated numerically. The external magnetic field is applied in either direction axial and radial on a cylinder having an aspect ratio H/R0=5, bounded by the top and the bottom disks at temperatures Tc and Th and by an adiabatic side wall. The equations of continuity, Navier Stocks and energy are non-dimensionalized and then discretized by the finite volume method. A computer program based on the SIMPLER algorithm is developed and compared with the numerical results found in the literature. The numerical investigation is carried out for different governing parameters namely: The Hartmann number (Ha=0, 5, 10, …, 40), nanoparticles volume fraction (ϕ=0, 0.025, …,0.1) and Rayleigh number (Ra=103, Ra=104 and Ra=105). The behavior of average Nusselt number, streamlines and temperature contours are illustrated. The results revel that the average Nusselt number increases with an increase of the Rayleigh number but it decreases with an increase in the Hartmann number. Depending on the magnetic field direction and on the values of Hartmann and Rayleigh numbers, an increase of the solid volume fraction may result enhancement or deterioration of the heat transfer performance in the nanofluid.

Keywords: natural convection, nanofluid, magnetic field, vertical cylinder

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Authors: Esra Ece Var

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Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

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Authors: Lan Zhang, Cailing Zhang

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In recent years, many face anti-spoofing algorithms have high detection accuracy when detecting 2D face anti-spoofing or 3D mask face anti-spoofing alone in the field of face anti-spoofing, but their detection performance is greatly reduced in multidimensional and cross-datasets tests. The rPPG method used for face anti-spoofing uses the unique vital information of real face to judge real faces and face anti-spoofing, so rPPG method has strong stability compared with other methods, but its detection rate of 2D face anti-spoofing needs to be improved. Therefore, in this paper, we improve an rPPG(Remote Photoplethysmography) method(MrPPG) for face anti-spoofing which through color space fusion, using the correlation of pulse signals between real face regions and background regions, and introducing the cyclic neural network (LSTM) method to improve accuracy in 2D face anti-spoofing. Meanwhile, the MrPPG also has high accuracy and good stability in face anti-spoofing of multi-dimensional and cross-data datasets. The improved method was validated on Replay-Attack, CASIA-FASD, Siw and HKBU_MARs_V2 datasets, the experimental results show that the performance and stability of the improved algorithm proposed in this paper is superior to many advanced algorithms.

Keywords: face anti-spoofing, face presentation attack detection, remote photoplethysmography, MrPPG

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

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Authors: Paul Kipchumba

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Kenya is an East African Country lying at the Equator. It had a population of 46 million in 2015 with an annual growth rate of 2.7%, making a population of at least 65 million in 2030. Kenya’s GDP in 2015 was about 63 billion USD with per capita GDP of about 1400 USD. The rural population is 74%, whereas urban population is 26%. Kenya grapples with not only access to energy but also with energy security. There is direct correlation between economic growth, population growth, and energy consumption. Kenya’s energy composition is at least 74.5% from renewable energy with hydro power and geothermal forming the bulk of it; 68% from wood fuel; 22% from petroleum; 9% from electricity; and 1% from coal and other sources. Wood fuel is used by majority of rural and poor urban population. Electricity is mostly used for lighting. As of March 2015 Kenya had installed electricity capacity of 2295 MW, making a per capital electricity consumption of 0.0499 KW. The overall retail cost of electricity in 2015 was 0.009915 USD/ KWh (KES 19.85/ KWh), for installed capacity over 10MW. The actual demand for electricity in 2015 was 3400 MW and the projected demand in 2030 is 18000 MW. Kenya is working on vision 2030 that aims at making it a prosperous middle income economy and targets 23 GW of generated electricity. However, cost and non-cost factors affect generation and consumption of electricity in Kenya. Kenya does not care more about CO2 emissions than on economic growth. Carbon emissions are most likely to be paid by future costs of carbon emissions and penalties imposed on local generating companies by sheer disregard of international law on C02 emissions and climate change. The study methodology was a simulated application of carbon tax on all carbon emitting sources of electricity generation. It should cost only USD 30/tCO2 tax on all emitting sources of electricity generation to have solar as the only source of electricity generation in Kenya. The country has the best evenly distributed global horizontal irradiation. Solar potential after accounting for technology efficiencies such as 14-16% for solar PV and 15-22% for solar thermal is 143.94 GW. Therefore, the paper recommends adoption of solar power for generating all electricity in Kenya in order to attain zero carbon electricity generation in the country.

Keywords: co2 emissions, cost factors, electricity generation, non-cost factors

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Authors: Masoud Safarishaal

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Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

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Authors: Kiatkulchai Jitt-Aer, Graham Wall, Dylan Jones

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As a result of the Indian Ocean tsunami in 2004, logistics applied to disaster relief operations has received great attention in the humanitarian sector. As learned from such disaster, preparing and responding to the aspect of delivering essential items from distribution centres to affected locations are of the importance for relief operations as the nature of disasters is uncertain especially in suffering figures, which are normally proportional to quantity of supplies. Thus, this study proposes a spatial decision support system (SDSS) for humanitarian logistics by integrating Geographical Information Systems (GIS) and the capacitated vehicle routing problem (CVRP). The GIS is utilised for acquiring demands simulated from the tsunami flooding model of the affected area in the first stage, and visualising the simulation solutions in the last stage. While CVRP in this study encompasses designing the relief routes of a set of homogeneous vehicles from a relief centre to a set of geographically distributed evacuation points in which their demands are estimated by using both simulation and randomisation techniques. The CVRP is modeled as a multi-objective optimization problem where both total travelling distance and total transport resources used are minimized, while demand-cost efficiency of each route is maximized in order to determine route priority. As the model is a NP-hard combinatorial optimization problem, the Clarke and Wright Saving heuristics is proposed to solve the problem for the near-optimal solutions. The real-case instances in the coastal area of Phuket, Thailand are studied to perform the SDSS that allows a decision maker to visually analyse the simulation scenarios through different decision factors.

Keywords: demand simulation, humanitarian logistics, geographical information systems, relief operations, capacitated vehicle routing problem

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Authors: Moti Zwilling, Srečko Natek

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This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

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Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

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Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

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Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

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Authors: Samuel Abebe Ebebo

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Scale precipitation causes a major issue for geothermal power plants because it reduces the production rate of geothermal energy. Each geothermal power plant's different chemical and physical conditions can cause the scale to precipitate under a particular set of fluid-rock interactions. Depending on the mineral, it is possible to have scale in the production well, steam separators, heat exchangers, reinjection wells, and everywhere in between. The scale consists mainly of smectite and trace amounts of chlorite, magnetite, quartz, hematite, dolomite, aragonite, and amorphous silica. The smectite scale is one of the difficult scales at injection wells in geothermal power plants. X-ray diffraction and chemical composition identify this smectite as Stevensite. The characteristics and the scale of each injection well line are different depending on the fluid chemistry. The smectite scale has been widely distributed in pipelines and surface plants. Mineral water equilibrium showed that the main factors controlling the saturation indices of smectite increased pH and dissolved Mg concentration due to the precipitate on the equipment surface. This study aims to characterize the scales and geothermal fluids collected from the Onuma geothermal power plant in Akita Prefecture, Japan. Field tests were conducted on October 30–November 3, 2021, at Onuma to determine the pH control methods for preventing magnesium silicate scaling, and as exemplified, the formation of magnesium silicate hydrates (M-S-H) with MgO to SiO2 ratios of 1.0 and pH values of 10 for one day has been studied at 25 °C. As a result, M-S-H scale formation could be suppressed, and stevensite formation could also be suppressed when we can decrease the pH of the fluid by less than 8.1, 7.4, and 8 (at 97 °C) in the fluid from O-3Rb and O-6Rb, O-10Rg, and O-12R, respectively. In this context, the scales and fluids collected from injection wells at a geothermal power plant in Japan were analyzed and characterized to understand the formation conditions of Mg-silicate scales with on-site synthesis experiments. From the results of the characterizations and on-site synthesis experiments, the inhibition method of their scale formation is discussed based on geochemical modeling in this study.

Keywords: magnesium silicate, scaling, inhibitor, geothermal power plant

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Authors: Muhammad Abdullah, Asma Rashid Butt, Nauman Raza

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Biomagnetic fluids like blood play key role in different applications of medical science and bioengineering. In this paper, the magnetohydrodynamic flow of a viscous fluid with magnetic particles through a cylindrical tube is investigated. The fluid is electrically charged in the presence of a uniform external magnetic field. The movement in the fluid is produced due to the cylindrical tube. Initially, the fluid and tube are at rest and at time t=0⁺, the tube starts to move along its axis. To obtain the mathematical model of flow with fractional derivatives fractional calculus approach is used. The solution of the flow model is obtained by using Laplace transformation. The Simon's numerical algorithm is employed to obtain inverse Laplace transform. The hybrid technique, we are employing has less computational effort as compared to other methods. The numerical calculations have been performed with Mathcad software. As the special cases of our problem, the solution of flow model with ordinary derivatives and flow without magnetic particles has been procured. Finally, the impact of non-integer fractional parameter alpha, Hartmann number Ha, and Reynolds number Re on flow and magnetic particles velocity is analyzed and depicted by graphs.

Keywords: viscous fluid, magnetic particles, fractional calculus, laplace transformation

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Authors: Sharun Akter Khushbu

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‘SOS’ addresses text summary such as feasibility study and allows more comprehensive methods on text of language resources. Resources language has been exploited by the importance of text documental procedure. Throughout this key idea will come out a machine interpreter called an SOS that has built an argumentative as an employed model is LSTM-CNN(long short-term memory- recurrent neural network). Summarization of Bengali text formulated by the information of latent structure instead of brief input string counting as text. Text summarization is the proper utilization of optimal solutions being time reduction, and easy interpretation whenever human-generated summary and machine targeted summary remain similar and without degrading the semantic summarization quality. According to the problem affirmation key idea has advanced an algorithm with the method of encoder and decoder describing a sequential structure that is rigorously connected with actual predicted and meaningful output. Regarding the seq2seq approach aimed in the future with high semantic summarization similarity on behalf of the large data samples that are also enlisted by the method. Thus, the SOS method assigns a discriminator over Bengali text documents where encoded input sequences such as summary and decoded the targeted summary of gist will be an error-free machine.

Keywords: LSTM-CNN, NN, SOS, text summarization

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Authors: Herlandson C. Moura, Jorge H. Bidinotto, Eduardo M. Belo

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The present work proposes the development of an adaptive control system which enables the suppression of Pilot Induced Oscillations (PIO) in Digital Fly-By-Wire (DFBW) aircrafts. The proposed system consists of a Modified Model Reference Adaptive Control (M-MRAC) integrated with the Gain Scheduling technique. The PIO oscillations are detected using a Real Time Oscillation Verifier (ROVER) algorithm, which then enables the system to switch between two reference models; one in PIO condition, with low proneness to the phenomenon and another one in normal condition, with high (or medium) proneness. The reference models are defined in a closed loop condition using the Linear Quadratic Regulator (LQR) control methodology for Multiple-Input-Multiple-Output (MIMO) systems. The implemented algorithms are simulated in software implementations with state space models and commercial flight simulators as the controlled elements and with pilot dynamics models. A sequence of pitch angles is considered as the reference signal, named as Synthetic Task (Syntask), which must be tracked by the pilot models. The initial outcomes show that the proposed system can detect and suppress (or mitigate) the PIO oscillations in real time before it reaches high amplitudes.

Keywords: adaptive control, digital Fly-By-Wire, oscillations suppression, PIO

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Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Paolo Ragazzi, Olivier Peillon, Paul Fauris, Mathias Simon, Raul Navarro, Juan Carlos Martin, Oriol Casasayas, Laura Pacheco, Albert Perez-Bellmunt

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Introduction: The use of stretching techniques in the sports world is frequent and widely used for its many effects. One of the main benefits is the gain in flexibility, range of motion and facilitation of the sporting performance. Recently the use of Roller-Foam (RF) has spread in sports practice both at elite and recreational level for its benefits being similar to those observed in stretching. The objective of the following study is to compare the results of the Roller-Foam with the proprioceptive neuromuscular facilitation stretching (PNF) (one of the stretchings with more evidence) on the hamstring muscles. Study design: The design of the study is a single-blind, randomized controlled trial and the participants are 40 healthy volunteers. Intervention: The subjects are distributed randomly in one of the following groups; stretching (PNF) intervention group: 4 repetitions of PNF stretching (5seconds of contraction, 5 second of relaxation, 20 second stretch), Roller-Foam intervention group: 2 minutes of Roller-Foam was realized on the hamstring muscles. Main outcome measures: hamstring muscles flexibility was assessed at the beginning, during (30’’ of intervention) and the end of the session by using the Modified Sit and Reach test (MSR). Results: The baseline results data given in both groups are comparable to each other. The PNF group obtained an increase in flexibility of 3,1 cm at 30 seconds (first series) and of 5,1 cm at 2 minutes (the last of all series). The RF group obtained a 0,6 cm difference at 30 seconds and 2,4 cm after 2 minutes of application of roller foam. The results were statistically significant when comparing intragroups but not intergroups. Conclusions: Despite the fact that the use of roller foam is spreading in the sports and rehabilitation field, the results of the present study suggest that the gain of flexibility on the hamstrings is greater if PNF type stretches are used instead of RF. These results may be due to the fact that the use of roller foam intervened more in the fascial tissue, while the stretches intervene more in the myotendinous unit. Future studies are needed, increasing the sample number and diversifying the types of stretching.

Keywords: hamstring muscle, stretching, neuromuscular facilitation stretching, roller foam

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Authors: Myoung Ah Kim, Dong Ho Sin, Chul Gyu Song

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Blood oxygen saturation system is a well-established, noninvasive photoplethysmographic method to monitor vital signs. Conventional blood oxygen saturation measurements for the two LED light source is the ambiguity of the oxygen saturation measurement principle and the measurement results greatly influenced and heat and motion artifact. A high accuracy in order to solve these problems blood oxygen saturation measuring method has been proposed using a broadband light source that can be easily understood by the algorithm. The measurement of blood oxygen saturation based on broad-band light source has advantage of simple testing facility and easy understanding. Broadband light source based on blood oxygen saturation measuring program proposed in this paper is a combination of LabVIEW and MATLAB. Using the wavelength range of 450 nm-750 nm using a floating light absorption of oxyhemoglobin and deoxyhemoglobin to measure the blood oxygen saturation. Hand movement is to fix the probe to the motor stage in order to prevent oxygen saturation measurement that affect the sample and probe kept constant interval. Experimental results show that the proposed method noticeably increases the accuracy and saves time compared with the conventional methods.

Keywords: oxygen saturation, broad-band light source, CCD, light reflectance theory

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Authors: Ravi Verma

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Cryosorption pump is the best solution to achieve clean, vibration free ultra-high vacuum. Furthermore, the operation of cryosorption pump is free from the influence of electric and magnetic fields. Due to these attributes, this pump is used in the space simulation chamber to create the ultra-high vacuum. The cryosorption pump comprises of three parts (a) panel which is cooled with the help of cryogen or cryocooler, (b) an adsorbent which is used to adsorb the gas molecules, (c) an epoxy which holds the adsorbent and the panel together thereby aiding in heat transfer from adsorbent to the panel. The performance of cryosorption pump depends on the temperature of the adsorbent and hence, on the thermal conductivity of the epoxy. Therefore we have made an attempt to increase the thermal conductivity of epoxy adhesive by mixing nano-sized graphene filler particles. The thermal conductivity of epoxy-graphene composite adhesive is measured with the help of indigenously developed experimental setup in the temperature range from 4.5 K to 7 K, which is generally the operating temperature range of cryosorption pump for efficiently pumping of hydrogen and helium gas. In this article, we have presented the experimental results of epoxy-graphene composite adhesive in the temperature range from 4.5 K to 7 K. We have also proposed an analytical heat conduction model to find the thermal conductivity of the composite. In this case, the filler particles, such as graphene, are randomly distributed in a base matrix of epoxy. The developed model considers the complete spatial random distribution of filler particles and this distribution is explained by Binomial distribution. The results obtained by the model have been compared with the experimental results as well as with the other established models. The developed model is able to predict the thermal conductivity in both isotropic regions as well as in anisotropic region over the required temperature range from 4.5 K to 7 K. Due to the non-empirical nature of the proposed model, it will be useful for the prediction of other properties of composite materials involving the filler in a base matrix. The present studies will aid in the understanding of low temperature heat transfer which in turn will be useful towards the development of high performance cryosorption pump.

Keywords: composite adhesive, computational modelling, cryosorption pump, thermal conductivity

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Authors: Trieu Anh Ngoc, Nguyen Quang Kim

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Located at the downstream of the Mekong Delta, the Vietnamese Mekong Delta is well-known as 'rice bowl' of Vietnam. The Vietnamese Mekong Delta experiences widespread flooding annually where is habitat for about 17 million people. The economy of this region mainly depends on the agricultural productivities. The suspended sediment load in the Mekong River plays an important role in carrying contaminants and nutrients to the delta and changing the geomorphology of the delta river system. In many past decades, flooding and suspended sediment were considered as indispensable factors in agricultural cultivations. Although flooding in the wet season caused serious inundation in paddy field and affected livelihoods, it is an effective facility for flushing acid and saline to this area - alluvial soil heavily contaminated with acid and salt intrusion. In addition, sediment delivery to this delta contained rich-nutrients distributed and deposited on the fields through flooding process. In recent decades, the changing of flow and sediment transport have been strongly and clearly occurring due to upstream dam development and climate change. However, effects of sediment delivery on agricultural cultivations were less attention. This study investigated the impacts of upstream flow on sediment distribution in the Vietnamese Mekong Delta. Flow fluctuation and sediment distribution were simulated by the Mike 11 model, including hydrodynamics model and advection-dispersion model. Various scenarios were simulated based on anticipated upstream discharges. Our findings indicated that sediment delivery into the Vietnamese Mekong Delta come from not only Tien River but also border of Cambodia floodplains. Sediment distribution in the Vietnamese Mekong Delta is dramatically changed by the distance from the main rivers and the secondary channels. The dam development in the upstream is one of the major factors leading a decrease in sediment discharge as well as sediment deposition. Moreover, sea level rise partially contributed to decrease in sediment transport and change of sediment distribution between upstream and downstream of the Vietnamese Mekong Delta.

Keywords: sediment transport, sea level rise, climate change, Mike Model

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Authors: Ziaul Islam, Asad Sultan, Sarzamin Khan

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Organic acids and micro encapsulated phyto essential oils have revealed great potential as an antibiotic replacement and as an additive to work tremendously for the health maintenance of broiler chicken. To explore more about organic acids, a total of 600 day-old broiler chicks (Cobb-500) were procured from a local hatchery and distributed into 5 treatment groups having 6 replicates of 20 birds each; the duration of the biological trial was of 35 days. Group T1 served as a control group that were fed on corn soy-based diet only. T2 were fed with a diet having 6% poultry by-product meal (PBM) diet, T3, T4, and T5 were served as the same diet as T2 but supplemented with an organic acid, phyto essential oils alone, and a combination, respectively. The findings declared significant improvement (p<0.05) in body weight gain and FCR in groups T3, T4, and T5 while feed intake was not affected. European broiler performance indicators like production efficiency factor (EPEF) and broiler index (EBI) were improved significantly (p<0.05) by the treatments T3, T4, and T5 compared with T1 and T2. Carcass evaluation depicted significantly better (p<0.05) dressed and eviscerated weight along with carcass yield (T3, T4, T5). Broilers fed organic acid and phyto essential oils supplemented diet had significantly lower (p<0.05) Clostridium perfringens, Escherichia coliand Salmonella and increased Lactobacillus counts. Likewise, antibody titer against ND, IB, and IBD were also significantly (p<0.05) improved by the treatments T3, T4 and T5compared with the T1and T2. Litter moisture content was significantly (p<0.05) reduced by treatmentsT3, T4, and T5 on day 28 and 35 compared with the T1 and T2. These findings of the present study revealed that supplementation of organic acids blend and phyto-essential oils as an as an substitute to improve the performance of broilers without the use of feed antibiotics in broilers fed with 6% poultry by-product meal based diet.

Keywords: organic acid, phyto essential oils, growth performance, PBM, gut health, microbiota, immunity

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Authors: Partha Sarathi Majee, S. Bhattacharyya

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Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Keywords: debye length, double layer polarization, electrophoresis, mobility reversal, soft particle

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Authors: Leixuri Aguirre, Iñaki Milton-Laskibar, Elizabeth Hijona, Luis Bujanda, Agnes M. Rimando, Maria P. Portillo

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Introduction: In recent years great attention has been paid by scientific community to phenolic compounds as active biomolecules naturally present in foodstuffs due to their beneficial effects on health. Pterostilbene is a resveratrol dimethylether derivative which shows higher biodisponibility. Objective. To analyze the effects of two doses of pterostilbene on several markers of thermogenic capacity in a model of genetic obesity, which shows reduced thermogenesis. Methods: The experiment was conducted with thirty Zucker (fa/fa) rats that were distributed in 3 experimental groups, the control group and two groups orally administered with pterostilbene at 15 and 30 mg/kg body weight/day for 6 weeks. Gene expression of Ucp1, Pgc-1α, Cpt1b, Pparα, Nfr1, Tfam and Cox-2 were assessed by RT-PCR, protein expression of UCP1 and GLUT4 by western blot and enzyme activity of carnitine palmitoyl transferase 1b and citrate synthase by spectrophotometry in interscapular brown adipose tissue (iBAT). Statistical analysis was performed by using one way ANOVA and Newman-Keuls as post-hoc test. Results: Pterostilbene did not change gene expression of Pgc-1α. However, significant increases were found in the expression of Ucp1, Pparα, Nfr-1 and Cox-2. Protein expression of UCP1 and GLUT4 was increased in animals treated with pterostilbene, as well as the activities of CPT-1b and CS. These effects were observed with both doses of pterostilbene, without differences between them. Conclusions: These results show that pterostilbene increases thermogenic and oxidative capacity of brown adipose tissue in obese rats. Whether these effects effectively contribute to the anti-obesity properties of these compound needs further research. Acknowledgments: MINECO-FEDER (AGL2015-65719-R), Basque Government (IT-572-13), University of the Basque Country (ELDUNANOTEK UFI11/32), Institut of Health Carlos III (CIBERobn). Iñaki Milton is a fellowship from the Basque Government.

Keywords: brown adipose tissue, pterostilbene, thermogenesis, uncoupling protein 1

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

Procedia PDF Downloads 92

Authors: Joanna Peksa, Faith Dillon-Lee

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Current developments in the Western economies have turned some universities into corporate institutions driven by practices of production and commodity. Academia is increasingly becoming integrated into national economies as a result of students paying fees and is consequently using business practices in student retention and engagement. With these changes, pedagogy status as a priority within the institution has been changing in light of these new demands. New strategies have blurred the boundaries that separate a student from a client. This led to a change of the dynamic, disrupting the traditional idea of the knowledge market, and emphasizing the corporate aspect of universities. In some cases, where students are seen primarily as a customer, the purpose of academia is no longer to educate but sell a commodity and retain fee-paying students. This paper considers opposing viewpoints on the commodification of higher education, reflecting on the reality of maintaining a pedagogic grounding in an increasingly commercialized sector. By analysing a case study of the Student Success Festival, an event that involved academic and marketing teams, the differences are considered between the respective visions of the pedagogic arm of the university and the corporate. This study argues that the initial concept of the event, based on the principles of gamification, independent learning, and cognitive criticality, was more clearly linked to a grounded pedagogic approach. However, when liaising with the marketing team in a crucial step in the creative process, it became apparent that these principles were not considered a priority in terms of their remit. While the study acknowledges in the power of pedagogy, the findings show that a pact of concord is necessary between different stakeholders in order for students to benefit fully from their learning experience. Nevertheless, while issues of power prevail and whenever power is unevenly distributed, reaching a consensus becomes increasingly challenging and further research should closely monitor the developments in pedagogy in the UK higher education.

Keywords: economic pressure, commodification, pedagogy, gamification, public service, marketization

Procedia PDF Downloads 107