Search results for: Finite Temperature Model

Authors: K. J. Sannapapamma, H. Malligawad Lokanath, Sakeena Naikwadi

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Eco-friendly textiles are gaining importance among the consumers and textile manufacturers in the healthcare sector due to increased environmental pollution which leads to several health and environmental hazards. Hence, the research was designed to cultivate and develop the organic cotton knit, to prepare and characterize the Vetiver oil microcapsules for textile finishing and to access the wash durability of finished knits. The cotton SAHANA variety grown under organic production systems was processed and spun into 30 single yarn dyed with four natural colorants (Arecanut slurry, Eucalyptus leaves, Pomegranate rind and Indigo) and eco dyed yarn was further used for development of single jersy knitted fabric. Vetiveria zizanioides is an aromatic grass which is being traditionally used in medicine and perfumery. Vetiver essential oil was used for preparation of microcapsules by interfacial polymerization technique subjected to Gas Chromatography Mass Spectrometry (GCMS), Fourier Transform Infrared Spectroscopy (FTIR), Thermo Gravimetric Analyzer (TGA) and Scanning Electron Microscope (SEM) for characterization of microcapsules. The knitted fabric was finished with vetiver oil microcapsules by exhaust and pad dry cure methods. The finished organic knit was assessed for laundering on antimicrobial efficiency and aroma intensity. GCMS spectral analysis showed that, diethyl phthalate (28%) was the major compound found in vetiver oil followed by isoaromadendrene epoxide (7.72%), beta-vetivenene (6.92%), solavetivone (5.58%), aromadenderene, azulene and khusimol. Bioassay explained that, the vetiver oil and diluted vetiver oil possessed greater zone of inhibition against S. aureus and E. coli than the coconut oil. FTRI spectra of vetiver oil and microcapsules possessed similar peaks viz., C-H, C=C & C꞊O stretching and additionally oil microcapsules possessed the peak of 3331.24 cm^-1 at 91.14 transmittance was attributed to N-H stretches. TGA of oil microcapsules revealed that, there was a minimum weight loss (5.835%) recorded at 467.09°C compared to vetiver oil i.e., -3.026% at the temperature of 396.24°C. The shape of the microcapsules was regular and round, some were spherical in shape and few were rounded by small aggregates. Irrespective of methods of application, organic cotton knits finished with microcapsules by pad dry cure method showed maximum zone of inhibition compared to knits finished by exhaust method against S. aureus and E. coli. The antimicrobial activity of the finished samples was subjected to multiple washing which indicated that knits finished with pad dry cure method showed a zone of inhibition even after 20^th wash and better aroma retention compared to knits finished with the exhaust method of application. Further, the group of respondents rated that the 5^th washed samples had the greater aroma intensity in both the methods than the other samples. Thus, the vetiver microencapsulated organic cotton knits are free from hazardous chemicals and have multi-functional properties that can be suitable for medical and healthcare textiles.

Keywords: Exhaust and pad dry cure finishing, interfacial polymerization, organic cotton knits, vetiver oil microcapsules.

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Authors: S. Z. Sayed Hassen

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The load frequency control problem of power systems has attracted a lot of attention from engineers and researchers over the years. Increasing and quickly changing load demand, coupled with the inclusion of more generators with high variability (solar and wind power generators) on the network are making power systems more difficult to regulate. Frequency changes are unavoidable but regulatory authorities require that these changes remain within a certain bound. Engineers are required to perform the tricky task of adjusting the control system to maintain the frequency within tolerated bounds. It is well known that to minimize frequency variations, a large proportional feedback gain (speed regulation constant) is desirable. However, this improvement in performance using proportional feedback comes about at the expense of a reduced stability margin and also allows some steady-state error. A conventional PI controller is then included as a secondary control loop to drive the steadystate error to zero. In this paper, we propose a robust controller to replace the conventional PI controller which guarantees performance and stability of the power system over the range of variation of the speed regulation constant. Simulation results are shown to validate the superiority of the proposed approach on a simple single-area power system model.

Keywords: Robust control, power system, integral action, minimax LQG control.

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Authors: Abdellatif Kasbi, Abderrafii Rahali

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In an electric power grid connected wind generation system, dynamic control strategy is essential to use the wind energy efficiently as well as for an energy optimization. The present study has focused on decoupled power regulation of doubly fed induction generator, operating in wind turbine, in accordance with the vector control approach by applying fractional order proportional integral (FOPI) controller. The FOPI controller is designed based on a simple method; up such that the response of closed loop process is similar to the response of a specified fractional model whose transfer function is Bode’s ideal function. In this tuning operation, the parameters of the proposed fractional controller are established analytically using the impulse closed-loop response of the controlled process. To show the superior action of the developed FOPI controller in comparison with standard PI controller in different function conditions, the study is validated through simulation using the software MATLAB/Simulink.

Keywords: Wind generation system, DFIG, vector control approach, fractional order PI controller, Bode’s ideal transfer function, impulse response.

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Authors: Hekmatpanah, M.

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Since the beginning of human history, human activities have caused many changes in the environment. Today, a particular attention should be paid to gaining knowledge about water quality of wetlands which are pristine natural environments rich in genetic reserves. If qualitative conditions of industrial areas (in terms of both physicochemical and biological conditions) are not addressed properly, they could cause disruption in natural ecosystems, especially in rivers. With regards to the quality of water resources, determination of pollutant sources plays a pivotal role in engineering projects as well as designing water quality control systems. Thus, using different methods such as flow duration curves, dischargepollution load model and frequency analysis by HYFA software package, risk of various industrial pollutants in international and ecologically important Gavkhoni wetland is analyzed. In this study, a station located at Varzaneh City is used as the last station on Zayanderud River, from where the river water is discharged into the wetland. Results showed that elements- concentrations often exceeded the allowed level and river water can endanger regional ecosystem. In addition, if the river discharge is managed on Q25 basis, this basis can lower concentrations of elements, keeping them within the normal level.

Keywords: Pollutants Risk, Industry, Flow Discharge, Management, Gavkhoni Wetland

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Authors: Georgi Yordanov Georgiev, Michael Daly, Erin Gombos, Amrit Vinod, Gajinder Hoonjan

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Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system - the central processing unit (CPU) of computers. The quantity of organization for several generations of CPUs shows a double exponential rate of change of organization with time. The exact functional dependence has a fine, S-shaped structure, revealing some of the mechanisms of self-organization. The principle of least action helps to explain the mechanism of increase of organization through quantity accumulation and constraint and curvature minimization with an attractor, the least average sum of actions of all elements and for all motions. This approach can help describe, quantify, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self organization to improve their quality. It can be applied to other complex systems from Physics, Chemistry, Biology, Ecology, Economics, Cities, network theory and others where complex systems are present.

Keywords: Organization, self-organization, complex system, complexification, quantitative measure, principle of least action, principle of stationary action, attractor, progressive development, acceleration, stochastic.

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Authors: Anshu Manik, William G. Buttlar, Kasthurirangan Gopalakrishnan

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Over the years, there is a growing trend towards quality-based specifications in highway construction. In many Quality Control/Quality Assurance (QC/QA) specifications, the contractor is primarily responsible for quality control of the process, whereas the highway agency is responsible for testing the acceptance of the product. A cooperative investigation was conducted in Illinois over several years to develop a prototype End-Result Specification (ERS) for asphalt pavement construction. The final characteristics of the product are stipulated in the ERS and the contractor is given considerable freedom in achieving those characteristics. The risk for the contractor or agency depends on how the acceptance limits and processes are specified. Stochastic simulation models are very useful in estimating and analyzing payment risk in ERS systems and these form an integral part of the Illinois-s prototype ERS system. This paper describes the development of an innovative methodology to estimate the variability components in in-situ density, air voids and asphalt content data from ERS projects. The information gained from this would be crucial in simulating these ERS projects for estimation and analysis of payment risks associated with asphalt pavement construction. However, these methods require at least two parties to conduct tests on all the split samples obtained according to the sampling scheme prescribed in present ERS implemented in Illinois.

Keywords: Asphalt Pavement, Risk Analysis, StochasticSimulation, QC/QA.

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Authors: Mohammad Hasan Raouf, Ebrahim Rasooli Anarmarzi, Hamid Lesani, Javad Olamaei

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This paper proposes the application of a hierarchical fuzzy system (HFS) based on multi-input power system stabilizer (MPSS) and also Static Var Compensator (SVC) in multi-machine environment.The number of rules grows exponentially with the number of variables in a conventional fuzzy logic system. The proposed HFS method is developed to solve this problem. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. In fact, by using HFS the total number of involved rules increases only linearly with the number of input variables. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type Power system stabilizer (PSS). Phasor model of SVC is described and used in this paper. The performances of MPSS, Conventional power system stabilizer (CPSS), hierarchical Fuzzy Multi-input Power System Stabilizer (HFMPSS) and the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. By using digital simulations the comparative study is illustrated. It can be seen that the proposed PSS is performing satisfactorily within the whole range of disturbances.

Keywords: Power system stabilizer (PSS), hierarchical fuzzysystem (HFS), Static VAR compensator (SVC)

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Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

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The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: Economic Development, Environmental Destruction, Financial Development, Institutional Development, Seemingly Unrelated Regression.

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Authors: Ali Ridho Barakbah, Yasushi Kiyoki

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This paper presents a new approach for image segmentation by applying Pillar-Kmeans algorithm. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after optimized by Pillar Algorithm. The Pillar algorithm considers the pillars- placement which should be located as far as possible from each other to withstand against the pressure distribution of a roof, as identical to the number of centroids amongst the data distribution. This algorithm is able to optimize the K-means clustering for image segmentation in aspects of precision and computation time. It designates the initial centroids- positions by calculating the accumulated distance metric between each data point and all previous centroids, and then selects data points which have the maximum distance as new initial centroids. This algorithm distributes all initial centroids according to the maximum accumulated distance metric. This paper evaluates the proposed approach for image segmentation by comparing with K-means and Gaussian Mixture Model algorithm and involving RGB, HSV, HSL and CIELAB color spaces. The experimental results clarify the effectiveness of our approach to improve the segmentation quality in aspects of precision and computational time.

Keywords: Image segmentation, K-means clustering, Pillaralgorithm, color spaces.

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Authors: S. A. Che Osmi, W. M. F. Wan Ishak, H. Kim, M. A. Azman, M. A. Ramli

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River is one of important water sources for many activities including industrial and domestic usage such as daily usage, transportation, power supply and recreational activities. However, increasing activities in a river has grown the sources of pollutant enters the water bodies, and degraded the water quality of the river. It becomes a challenge to develop an effective river management to ensure the water sources of the river are well managed and regulated. In Malaysia, several approaches for river management have been implemented such as Integrated River Basin Management (IRBM) program for coordinating the management of resources in a natural environment based on river basin to ensure their sustainability lead by Department of Drainage and Irrigation (DID), Malaysia. Nowadays, Total Maximum Daily Load (TMDL) is one of the best approaches for river management in Malaysia. TMDL implementation is regulated and implemented in the United States. A study on the development of TMDL in Malacca River has been carried out by doing water quality monitoring, the development of water quality model by using Environmental Fluid Dynamic Codes (EFDC), and TMDL implementation plan. The implementation of TMDL will help the stakeholders and regulators to control and improve the water quality of the river. It is one of the good approaches for river management in Malaysia.

Keywords: EFDC, river management, TMDL, water quality modelling.

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Authors: Subramaniam Chandran

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The significance of psychology in studying politics is embedded in philosophical issues as well as behavioural pursuits. For the former is often associated with Sigmund Freud and his followers. The latter is inspired by the writings of Harold Lasswell. Political psychology or psychopolitics has its own impression on political thought ever since it deciphers the concept of human nature and political propaganda. More importantly, psychoanalysis views political thought as a textual content which needs to explore the latent from the manifest content. In other words, it reads the text symptomatically and interprets the hidden truth. This paper explains the paradigm of dream interpretation applied by Freud. The dream work is a process which has four successive activities: condensation, displacement, representation and secondary revision. The texts dealing with political though can also be interpreted on these principles. Freud's method of dream interpretation draws its source after the hermeneutic model of philological research. It provides theoretical perspective and technical rules for the interpretation of symbolic structures. The task of interpretation remains a discovery of equivalence of symbols and actions through perpetual analogies. Psychoanalysis can help in studying political thought in two ways: to study the text distortion, Freud's dream interpretation is used as a paradigm exploring the latent text from its manifest text; and to apply Freud's psychoanalytic concepts and theories ranging from individual mind to civilization, religion, war and politics.

Keywords: Psychoanalysis, political thought, dreaminterpretation, latent content, manifest content

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Authors: Mi Ok Kang

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This study examined the influences of including LGBTQ-related content in a multicultural teacher education course on the development of prospective teachers’ social justice identities. Appling a content analysis to 53 reflection texts written by participating prospective teachers in response to the relevant course content, this study deduced the stages of social justice identity development (naïve, acceptance, resistance, redefinition, and internalization) that participants reached during the course. The analysis demonstrated that the participants reached various stages in the social identity development model and none of the participants remained at the naïve stage during/after class. The majority (53%) of the participants reached the internalization stage during the coursework and became conscious about the heterosexual privileges they have had and aware of possible impacts of such privilege on their future LGBTQ students. Also the participants had begun to develop pedagogic action plans and devised applicable teaching strategies for their future students based on the new understanding of heteronormativity. We expect this study will benefit teacher educators and educational administrators who want to address LGBTQ-related issues in their multicultural education programs and/or revisit the goals, directions, and implications of their approach.

Keywords: LGBTQ, heteronormativity, social justice identity, teacher education, multicultural education, content analysis.

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Authors: Saeid Rabiei Majd, Motahareh Alvandi, Mehrad Rabiei

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The rapid economic and technological development of any country depends on access to cheap sources of energy. Competition for access to petroleum resources is always accompanied by numerous environmental risks. These factors have caused more attention to environmental issues and sustainable development in petroleum contracts and activities. Nowadays, a sign of developed countries is adhering to the principles and rules of international environmental law and sustainable development of commercial contracts. China has entered into play through the massive project plan, One Belt, One Road. China is becoming a new emerging power in the world. China's bilateral investment treaties have an impact on environmental rights and sustainable development through regional and international foreign direct investment. The aim of this research is to examine China's key position to promote and improve environmental principles and international law and sustainable development in the energy sector in the world through the initiative, One Belt, One Road. Based on this hypothesis, it seems that in the near future, China's investment bilateral investment treaties will become popular investment model used in global trade, especially in the field of energy and sustainable development. They will replace the European and American models. The research method is including literature review, analytical and descriptive methods.

Keywords: Principles of sustainable development, oil and gas law, Chinas BITs, one belt one road, environmental rights.

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Authors: K. N. C. Njoku, Chinwendu Best Eleje, Christian Chukwuemeka Nwandu

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One of the problems facing most insurance companies is how best the burden of paying claims to its policy holders can be managed whenever need arises. Hence there is need for the insurer to buy a reinsurance contract in order to reduce risk which will enable the insurer to share the financial burden with the reinsurer. In this paper, the insurer’s and reinsurer’s strategy is investigated under the modified constant elasticity of variance (M-CEV) process and proportional administrative charges. The insurer considered investment in one risky asset and one risk free asset where the risky asset is modeled based on the M-CEV process which is an extension of constant elasticity of variance (CEV) process. Next, a nonlinear partial differential equation in the form of Hamilton Jacobi Bellman equation is obtained by dynamic programming approach. Using power transformation technique and variable change, the explicit solutions of the optimal investment strategy and optimal reinsurance strategy are obtained. Finally, some numerical simulations of some sensitive parameters were obtained and discussed in details where we observed that the modification factor only affects the optimal investment strategy and not the reinsurance strategy for an insurer with exponential utility function.

Keywords: Reinsurance strategy, Hamilton Jacobi Bellman equation, power transformation, M-CEV process, exponential utility.

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Authors: Tatsuya Kasuga, Hidehisa Shimada, Kimio Oguchi

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Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.

Keywords: Electric power consumption, LED color, LED lighting, plant factory.

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Authors: B. O. Olawale, C. R. Chatwin, R. C. D. Young, P. M. Birch, F. O. Faithpraise, A. O. Olukiran

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In this paper, we present a four-step ortho-rectification procedure for real-time geo-referencing of video data from a low-cost UAV equipped with a multi-sensor system. The basic procedures for the real-time ortho-rectification are: (1) decompilation of the video stream into individual frames; (2) establishing the interior camera orientation parameters; (3) determining the relative orientation parameters for each video frame with respect to each other; (4) finding the absolute orientation parameters, using a self-calibration bundle and adjustment with the aid of a mathematical model. Each ortho-rectified video frame is then mosaicked together to produce a mosaic image of the test area, which is then merged with a well referenced existing digital map for the purpose of geo-referencing and aerial surveillance. A test field located in Abuja, Nigeria was used to evaluate our method. Video and telemetry data were collected for about fifteen minutes, and they were processed using the four-step ortho-rectification procedure. The results demonstrated that the geometric measurement of the control field from ortho-images is more accurate when compared with those from original perspective images when used to pin point the exact location of targets on the video imagery acquired by the UAV. The 2-D planimetric accuracy when compared with the 6 control points measured by a GPS receiver is between 3 to 5 metres.

Keywords: Geo-referencing, ortho-rectification, video frame, self-calibration, UAV, target tracking.

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Authors: H. B. Mehta, Vipul M. Patel, Jyotirmay Banerjee

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The present paper discusses the prediction of gas-liquid two-phase frictional pressure drop in a 2.12 mm horizontal circular minichannel using Artificial Neural Network (ANN). The experimental results are obtained with air as gas phase and water as liquid phase. The superficial gas velocity is kept in the range of 0.0236 m/s to 0.4722 m/s while the values of 0.0944 m/s, 0.1416 m/s and 0.1889 m/s are considered for superficial liquid velocity. The experimental results are predicted using different Artificial Neural Network (ANN) models. Networks used for prediction are radial basis, generalised regression, linear layer, cascade forward back propagation, feed forward back propagation, feed forward distributed time delay, layer recurrent, and Elman back propagation. Transfer functions used for networks are Linear (PURELIN), Logistic sigmoid (LOGSIG), tangent sigmoid (TANSIG) and Gaussian RBF. Combination of networks and transfer functions give different possible neural network models. These models are compared for Mean Absolute Relative Deviation (MARD) and Mean Relative Deviation (MRD) to identify the best predictive model of ANN.

Keywords: Minichannel, Two-Phase Flow, Frictional Pressure Drop, ANN, MARD, MRD.

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Authors: Abdullah M. Alodhaiani, Yasir A. Alturki, Mohamed A. Elkady

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Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF’s) or power transfer distribution factors (PTDF’s), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF’s), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method.

Keywords: Distribution Factors, Power System, Sensitivity Factors, Electricity Market.

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Authors: Shu-Yin Yu

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With the advancement of artificial intelligence technology, most companies are aware of the profound potential of artificial intelligence in commercial marketing. Man-machine dialogue has become the latest trend in marketing customer service. However, chatbots are often considered to be lack of intelligent or unfriendly conversion, which instead reduces the communication effect of chatbots. To ensure that chatbots represent the brand image and provide a good user experience, companies and users attach great importance. In this study, customer service chatbot was used as the research sample. The research variables are based on the theory of artificial intelligence emotions, integrating the technology acceptance model and innovation diffusion theory, and the three aspects of pleasure, arousal, and dominance of the human-machine PAD (Pleasure, Arousal and Dominance) dimension. The results show that most of the participants have a higher acceptance of innovative technologies and are high pleasure and arousal in the user experience. Participants still have traditional gender (female) service stereotypes about customer service chatbots. Users who have high trust in using chatbots can easily enhance brand acceptance and easily accept brand messages, extend the trust of chatbots to trust in the brand, and develop a positive attitude towards the brand.

Keywords: Brand attitude, chatbot, emotional interaction, user experience.

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Authors: W. Du, X. Wang, Jun Cao, H. F. Wang

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Due to the randomness and uncertainty of wind energy, modern power systems integrating large-scale wind generation will be significantly impacted in terms of system performance and technical challenges. System inertia with high wind penetration is decreasing when conventional thermal generators are gradually replaced by wind turbines, which do not naturally contribute to inertia response. The power imbalance caused by wind power or demand fluctuations leads to the instability of system frequency. Accordingly, the need to attach the supplementary virtual inertia control to wind farms (WFs) strongly arises. When multi-wind farms are connected to the grid simultaneously, the selection of which critical WFs to install the virtual inertia control is greatly important to enhance the stability of system frequency. By building the small signal model of wind power systems considering frequency regulation, the installation locations are identified by the geometric measures of the mode observability of WFs. In addition, this paper takes the impacts of grid topology and selection of feedback control signals into consideration. Finally, simulations are conducted on a multi-wind farms power system and the results demonstrate that the designed virtual inertia control method can effectively assist the frequency regulation.

Keywords: Frequency regulation, virtual inertia control, installation locations, observability, wind farms.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Phool Singh, Ashok Jangid, N. S. Tomer, Deepa Sinha

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The aim of this paper is to investigate twodimensional unsteady flow of a viscous incompressible fluid about stagnation point on permeable stretching sheet in presence of time dependent free stream velocity. Fluid is considered in the influence of transverse magnetic field in the presence of radiation effect. Rosseland approximation is use to model the radiative heat transfer. Using time-dependent stream function, partial differential equations corresponding to the momentum and energy equations are converted into non-linear ordinary differential equations. Numerical solutions of these equations are obtained by using Runge-Kutta Fehlberg method with the help of Newton-Raphson shooting technique. In the present work the effect of unsteadiness parameter, magnetic field parameter, radiation parameter, stretching parameter and the Prandtl number on flow and heat transfer characteristics have been discussed. Skin-friction coefficient and Nusselt number at the sheet are computed and discussed. The results reported in the paper are in good agreement with published work in literature by other researchers.

Keywords: Magneto hydrodynamics, stretching sheet, thermal radiation, unsteady flow.

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Authors: Handan Ertaş

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The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process.It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: Konya, Organizational Justice, Organizational.

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Authors: Sunil Patel, Pallab Maji

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To study the effect of adversarial attack environment must be controlled. Autonomous driving includes mainly 5 phases sense, perceive, map, plan, and drive. Autonomous vehicles sense their surrounding with the help of different sensors like cameras, radars, and lidars. Deep learning techniques are considered Blackbox and found to be vulnerable to adversarial attacks. In this research, we study the effect of the various known adversarial attacks with the help of the Unreal Engine-based, high-fidelity, real-time raytraced simulated environment. The goal of this experiment is to find out if adversarial attacks work in moving vehicles and if an unknown network may be targeted. We discovered that the existing Blackbox and Whitebox attacks have varying effects on different traffic signs. We observed that attacks that impair detection in static scenarios do not have the same effect on moving vehicles. It was found that some adversarial attacks with hardly noticeable perturbations entirely blocked the recognition of certain traffic signs. We observed that the daylight condition has a substantial impact on the model's performance by simulating the interplay of light on traffic signs. Our findings have been found to closely resemble outcomes encountered in the real world.

Keywords: Adversarial attack simulation, computer simulation, ray-traced environment, realistic simulation, unreal engine.

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Authors: Lei Dou, Mitsuhiro Nakagawa, Fei Yan, Ping Li

Abstract:

Participation in global trade means that Chinas vegetables and fruits industry faces international food safety standards and increased scrutiny worldwide. The objectives of this paper were to investigate how existing food safety standards and regulations in the importing countries impact the export of vegetables and fruits from China. This paper discussed the current and historical situations of Chinas vegetables and fruits export from 1996 to 2010, analyzed the Maximum Residual Limit (MRL) standards of pesticides imposed by importing countries, quantitatively estimated the impacts of food safety standards on Chinas vegetables and fruits export based on a gravity model. The results showed that although transportation distance between trade partners and tariff rates on vegetables and fruits were still the importantly resistant factors for China export, vegetables and fruits export was sensitive to the number of regulated pesticides, the strictness, and the level of food safety standards imposed by importing countries, which showed a significant trade flow effect, stricter food safety standards, increased number of regulated pesticides significantly inhibit China export of vegetables and fruits. Moreover, Chinas food safety standards also showed a significantly effect on vegetables and fruits export, which inhibited export to some extent. KeywordsFood safety standards, MRL, Vegetables, Fruits, Export.

Keywords: Food safety standards, MRL, Vegetables, Fruits, Export.

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Authors: Suby Khanam, Jamshed Siddiqui, Faisal Talib

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Total Quality Management (TQM) is a managerial approach that improves the competitiveness of the industry, meanwhile Information technology (IT) was introduced with TQM for handling the technical issues which is supported by quality experts for fulfilling the customers’ requirement. Present paper aims to utilise AHP (Analytic Hierarchy Process) methodology to priorities and rank the hierarchy levels of TQM enablers and IT resource together for its successful implementation in the Information and Communication Technology (ICT) industry. A total of 17 TQM enablers (nine) and IT resources (eight) were identified and partitioned into 3 categories and were prioritised by AHP approach. The finding indicates that the 17 sub-criteria can be grouped into three main categories namely organizing, tools and techniques, and culture and people. Further, out of 17 sub-criteria, three sub-criteria: top management commitment and support, total employee involvement, and continuous improvement got highest priority whereas three sub-criteria such as structural equation modelling, culture change, and customer satisfaction got lowest priority. The result suggests a hierarchy model for ICT industry to prioritise the enablers and resources as well as to improve the TQM and IT performance in the ICT industry. This paper has some managerial implication which suggests the managers of ICT industry to implement TQM and IT together in their organizations to get maximum benefits and how to utilize available resources. At the end, conclusions, limitation, future scope of the study are presented.

Keywords: Analytic Hierarchy Process, Information Technology, Information and Communication Technology, Prioritization, Total Quality Management.

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: Dana M. Ragab, Jasim A. Ghaeb

Abstract:

The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: Three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality.

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: Intelligent transportation systems, object detection, video processing, road traffic, vehicle counting, vehicle classification.

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Authors: L. Dixon, D. Gavani

Abstract:

Objective: Sharing devastating news with patients is often considered the most difficult task of doctors. This study aimed to explore patients’ perceptions of receiving bad news including which features improve the experience and which areas need refining. Methods: A questionnaire was written based on the steps of the SPIKES model for breaking bad new. 20 patients receiving treatment for a hematological malignancy completed the questionnaire. Results: Overall, the results are promising as most patients praised their consultation. ‘Poor’ was more commonly rated by women and participants aged 45-64. The main differences between the ‘excellent’ and ‘poor’ consultations include the doctor’s sensitivity and checking the patients’ understanding. Only 35% of patients were asked their existing knowledge and 85% of consultations failed to discuss the impact of the diagnosis on daily life. Conclusion: This study agreed with the consensus of existing literature. The commended aspects include consultation set-up and information given. Areas patients felt needed improvement include doctors determining the patient’s existing knowledge and checking new information has been understood. Doctors should also explore how the diagnosis will affect the patient’s life. With a poorer prognosis, doctors should work on conveying appropriate hope. The study was limited by a small sample size and potential recall bias.

Keywords: Communication, diagnosis, hematology, patients.

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