Search results for: Hybrid grid

Authors: S. Shanthi, V. Muralibhaskaran

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Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

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Authors: Dewan Md. Farid, Nguyen Huu Hoa, Jerome Darmont, Nouria Harbi, Mohammad Zahidur Rahman

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In this paper, we present a new learning algorithm for anomaly based network intrusion detection using improved self adaptive naïve Bayesian tree (NBTree), which induces a hybrid of decision tree and naïve Bayesian classifier. The proposed approach scales up the balance detections for different attack types and keeps the false positives at acceptable level in intrusion detection. In complex and dynamic large intrusion detection dataset, the detection accuracy of naïve Bayesian classifier does not scale up as well as decision tree. It has been successfully tested in other problem domains that naïve Bayesian tree improves the classification rates in large dataset. In naïve Bayesian tree nodes contain and split as regular decision-trees, but the leaves contain naïve Bayesian classifiers. The experimental results on KDD99 benchmark network intrusion detection dataset demonstrate that this new approach scales up the detection rates for different attack types and reduces false positives in network intrusion detection.

Keywords: Detection rates, false positives, network intrusiondetection, naïve Bayesian tree.

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Authors: Lady Marianne E. Polinga, Candy C. Mercado, Camilo A. Polinga

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This study was an investigation on the suitability of Lahar/HDPE composite as a primary material for low-cost smallscale biogas digesters. While sources of raw materials for biogas are abundant in the Philippines, cost of the technology has made the widespread utilization of this resource an indefinite proposition. Aside from capital economics, another problem arises with space requirements of current digester designs. These problems may be simultaneously addressed by fabricating digesters on a smaller, household scale to reach a wider market, and to use materials that may accommodate optimization of overall design and fabrication cost without sacrificing operational efficiency. This study involved actual fabrication of the Lahar/HDPE composite at varying composition and geometry, subsequent mechanical and thermal characterization, and implementation of Statistical Analysis to find intrinsic relationships between variables. From the results, Lahar/HDPE composite was found to be feasible for use as digester material from both mechanical and economic standpoints. 

Keywords: Biogas digester, Composite, High density polyethylene, Lahar.

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Authors: Ali Mirmohammadi, Arash Taheri, Meysam Mohammadi-Amin

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One of the major parts of a jet engine is air intake, which provides proper and required amount of air for the engine to operate. There are several aerodynamic parameters which should be considered in design, such as distortion, pressure recovery, etc. In this research, the effects of lip ice accretion on pitot intake performance are investigated. For ice accretion phenomenon, two supervised multilayer neural networks (ANN) are designed, one for ice shape prediction and another one for ice roughness estimation based on experimental data. The Fourier coefficients of transformed ice shape and parameters include velocity, liquid water content (LWC), median volumetric diameter (MVD), spray time and temperature are used in neural network training. Then, the subsonic intake flow field is simulated numerically using 2D Navier-Stokes equations and Finite Volume approach with Hybrid mesh includes structured and unstructured meshes. The results are obtained in different angles of attack and the variations of intake aerodynamic parameters due to icing phenomenon are discussed. The results show noticeable effects of ice accretion phenomenon on intake behavior.

Keywords: Artificial Neural Network, Ice Accretion, IntakeAerodynamics, Design Parameters, Finite Volume Method.

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia, recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines, to upgrade power systems into smart grids, target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, they are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, and therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we present a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: Anomaly detection, SmartGrid, edge, maintainability, reliability, stochastic process.

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Authors: Muhamad Azani Yahya, Umi Nadiah Nor Ali, Mohammed Alias Yusof, Norazman Mohamad Nor, Vikneswaran Munikanan

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In construction, concrete is one of the materials that can commonly be used as for structural elements. Concrete consists of cement, sand, aggregate and water. Concrete can be added with admixture in the wet condition to suit the design purpose such as to prolong the setting time to improve workability. For strength improvement, concrete is being added with other hybrid materials to increase strength; this is because the tensile strength of concrete is very low in comparison to the compressive strength. This paper shows the usage of a waterproofing agent in concrete to enhance the tensile strength. High tensile concrete is expensive because the concrete mix needs fiber and also high cement content to be incorporated in the mix. High tensile concrete being used for structures that are being imposed by high impact dynamic load such as blast loading that hit the structure. High tensile concrete can be defined as a concrete mix design that achieved 30%-40% tensile strength compared to its compression strength. This research evaluates the usage of a waterproofing agent in a concrete mix as an element of reinforcement to enhance the tensile strength. According to the compression and tensile test, it shows that the concrete mix with a waterproofing agent enhanced the mechanical properties of the concrete. It is also show that the composite concrete with waterproofing is a high tensile concrete; this is because of the tensile is between 30% and 40% of the compression strength. This mix is economical because it can produce high tensile concrete with low cost.

Keywords: High tensile concrete, waterproofing agent, concrete, rheology.

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Authors: V. Sudha, D. Sriram Kumar

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Orthogonal Frequency Division Multiplexing (OFDM) has been used in many advanced wireless communication systems due to its high spectral efficiency and robustness to frequency selective fading channels. However, the major concern with OFDM system is the high peak-to-average power ratio (PAPR) of the transmitted signal. Some of the popular techniques used for PAPR reduction in OFDM system are conventional partial transmit sequences (CPTS) and clipping. In this paper, a parallel combination/hybrid scheme of PAPR reduction using clipping and CPTS algorithms is proposed. The proposed method intelligently applies both the algorithms in order to reduce both PAPR as well as computational complexity. The proposed scheme slightly degrades bit error rate (BER) performance due to clipping operation and it can be reduced by selecting an appropriate value of the clipping ratio (CR). The simulation results show that the proposed algorithm achieves significant PAPR reduction with much reduced computational complexity.

Keywords: CCDF, OFDM, PAPR, PTS.

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Authors: Alpha Bolinao, Francine Rose De Castro, Jessie Kate Lumba, Raztine Mae Paeste, Hannah Grace Tosio

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The present study aimed to know the role of verbal bullying in the lives of obese teenagers exposed to it. The study employed a qualitative design specifically the phenomenological approach that focuses on the obese teenagers’ verbal bullying experiences. The study also used the social constructivism approach wherein it described the obese teenagers’ verbal bullying experiences as they interact with the social world. Through purposive and referral sampling technique, the researchers were able to choose twelve (12) respondents from different schools around the City of Manila, enrolled in the School Year 2015-2016, ages 16-21 years old, has experienced verbal bullying for the last ten (10) years and with the Body Mass Index (BMI) of equal to or greater than 30. Upon the consent of the respondents, ethical considerations were ensured. In-depth one (1) hour interviews were guided by the researchers’ aide memoir. The recorded interviews were transcribed into a field text and the responses were thoroughly analyzed through Thematic Analysis and Kelly’s Repertory Grid. It was found that the role of verbal bullying in the lives of obese teenagers exposed to it is a process and is best described through a syringe, or the 5S Responses of Obese Teenagers in Bullying, with five conceptual themes which also signify the experiences and the process that obese teenagers have gone through after experiencing verbal bullying. The themes conceptualized were: Suffering, self-doubt, suppression, self-acceptance and sanguineness. This paper may serve as a basis for a counseling program to help the obese teenagers cope with their bullying experiences.

Keywords: Obesity, obese teenagers, bullying, experiences.

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Authors: WooYoung Jung, HoYoung Son

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This study presented to reduce earthquake damage and emergency rehabilitation of critical structures such as schools, hightech factories, and hospitals due to strong ground motions associated with climate changes. Regarding recent trend, a strong earthquake causes serious damage to critical structures and then the critical structure might be influenced by sequence aftershocks (or tsunami) due to fault plane adjustments. Therefore, in order to improve seismic performance of critical structures, retrofitted or strengthening study of the structures under aftershocks sequence after emergency rehabilitation of the structures subjected to strong earthquakes is widely carried out. Consequently, this study used composite material for emergency rehabilitation of the structure rather than concrete and steel materials because of high strength and stiffness, lightweight, rapid manufacturing, and dynamic performance. Also, this study was to develop or improve the seismic performance or seismic retrofit of critical structures subjected to strong ground motions and earthquake aftershocks, by utilizing GFRP-Corrugated Infill Panels (GCIP).

Keywords: Composite material, GFRP, Infill Panel, Aftershock, Seismic Retrofitting.

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Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

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Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

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Authors: S. Srinivasa Moorthy, K. Manonmani

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The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L₉ orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.

Keywords: Analysis of variance (ANOVA), Artificial neural network (ANN), Polymer composites, Taguchi’s orthogonal array.

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Authors: Ion Smeureanu, Marian Dardala, Adriana Reveiu

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The new programming technologies allow for the creation of components which can be automatically or manually assembled to reach a new experience in knowledge understanding and mastering or in getting skills for a specific knowledge area. The project proposes an interactive framework that permits the creation, combination and utilization of components that are specific to mathematical training in high schools. The main framework-s objectives are: • authoring lessons by the teacher or the students; all they need are simple operating skills for Equation Editor (or something similar, or Latex); the rest are just drag & drop operations, inserting data into a grid, or navigating through menus • allowing sonorous presentations of mathematical texts and solving hints (easier understood by the students) • offering graphical representations of a mathematical function edited in Equation • storing of learning objects in a database • storing of predefined lessons (efficient for expressions and commands, the rest being calculations; allows a high compression) • viewing and/or modifying predefined lessons, according to the curricula The whole thing is focused on a mathematical expressions minicompiler, storing the code that will be later used for different purposes (tables, graphics, and optimisations). Programming technologies used. A Visual C# .NET implementation is proposed. New and innovative digital learning objects for mathematics will be developed; they are capable to interpret, contextualize and react depending on the architecture where they are assembled.

Keywords: Adaptor, automatic assembly learning component and user control.

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Authors: Atif Elahi, Ijaz Mansoor Qureshi, Mehreen Atif, Noor Gul

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Orthogonal frequency division multiplexing (OFDM) is one of the best candidates for dynamic spectrum access due to its flexibility of spectrum shaping. However, the high sidelobes of the OFDM signal that result in high out-of-band radiation, introduce significant interference to the users operating in its vicinity. This problem becomes more critical in cognitive radio (CR) system that enables the secondary users (SUs) users to access the spectrum holes not used by the primary users (PUs) at that time. In this paper, we present a generalized OFDM framework that has a capability of describing any sidelobe suppression techniques, despite of whether one or a number of techniques are used. Based on that framework, we propose cancellation carrier (CC) technique in conjunction with the generalized sidelobe canceller (GSC) to reduce the out-of-band radiation in the region where the licensed users are operating. Simulation results show that the proposed technique can reduce the out-of-band radiation better when compared with the existing techniques found in the literature.

Keywords: Cognitive radio, cancellation carriers, generalized sidelobe canceller, out-of-band radiation, orthogonal frequency division multiplexing.

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Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: Bistatic radar cross section, passive radar, propagation losses, radar coverage.

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Authors: Marco Raciti Castelli, Alberto Castelli, Ernesto Benini

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The construction of a civil structure inside a urban area inevitably modifies the outdoor microclimate at the building site. Wind speed, wind direction, air pollution, driving rain, radiation and daylight are some of the main physical aspects that are subjected to the major changes. The quantitative amount of these modifications depends on the shape, size and orientation of the building and on its interaction with the surrounding environment.The flow field over a flat roof model building has been numerically investigated in order to determine two-dimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data.Several turbulence models and spatial node distributions have been tested for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions.The proposed calculations have allowed the development of a preliminary procedure to be used as a guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a twodimensional roof architecture dominated by flow separation.

Keywords: CFD, roof, building, wind.

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Authors: R. Kamalakannan, N. Ravi Kumar

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The global energy consumption is increasing persistently and need for distributed power generation through renewable energy is essential. To meet the power requirements for consumers without any voltage fluctuations and losses, modeling and design of multilevel inverter with Flexible AC Transmission System (FACTS) capability is presented. The presented inverter is provided with 13-level cascaded H-bridge topology of Insulated Gate Bipolar Transistor (IGBTs) connected along with inbuilt Distributed Static Synchronous Compensators (DSTATCOM). The DSTATCOM device provides control of power factor stability at local feeder lines and the inverter eliminates Total Harmonic Distortion (THD). The 13-level inverter utilizes 52 switches of each H-bridge is fed with single DC sources separately and the Pulse Width Modulation (PWM) technique is used for switching IGBTs. The control strategy implemented for inverter transmits active power to grid as well as it maintains power factor to be stable with achievement of steady state power transmission. Significant outcome of this project is improvement of output voltage quality with steady state power transmission with low THD. Simulation of inverter with DSTATCOM is performed using MATLAB/Simulink environment. The scaled prototype model of proposed inverter is built and its results were validated with simulated results.

Keywords: FACTS devices, distributed-Static synchronous compensators, DSTATCOM, total harmonics elimination, modular multilevel converter.

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Authors: P.L.D.N.M. de Silva, S.G. Edirisinghe, R. Weerasuriya

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High Peak-to-Average Power Ratio (PAPR) is a concern of Orthogonal Frequency Division Multiplexing (OFDM) based Visible Light Communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. In this study, the improvement which can be harnessed by hybridizing these two techniques for VLC system is being studied. Within the study, efficient techniques such as Hamming coding and Convolutional coding have been studied. Thus, we present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems, using MATLAB simulations.

Keywords: Convolutional Coding, Discrete Fourier Transform spread Orthogonal Frequency Division Multiplexing (DFT-s OFDM), Hamming Coding, Peak-to-Average Power Ratio (PAPR), Visible Light Communications (VLC).

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Authors: Meng Wu

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Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: Motion planning, gravity gradient inversion algorithm, ant colony optimization.

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Authors: Angel Daniel Muñoz Guzmán

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E-learning is becoming more and more common every day. For online, hybrid or traditional face-to-face programs, there are some e-teaching platforms like Google classroom, Blackboard, Moodle and Canvas, and there are platforms for full e-learning like Coursera, edX or Udemy. These tools are changing the way students acquire knowledge at schools; however, in today’s changing world that is not enough. As students’ needs and skills change and become more complex, new tools will need to be added to keep them engaged and potentialize their learning. This is especially important in the current global situation that is changing everything: the Covid-19 pandemic. Due to Covid-19, education had to make an unexpected switch from face-to-face courses to digital courses. In this study, the students’ learning experience is analyzed by applying different e-tools and following the Tec21 Model and a flexible and digital model, both developed by the Tecnologico de Monterrey University. The evaluation of the students’ learning experience has been made by the quantitative PrEmo method of emotions. Findings suggest that the quantity of e-tools used during a course does not affect the students’ learning experience as much as how a teacher links every available tool and makes them work as one in order to keep the student engaged and motivated.

Keywords: Student, experience, e-learning, e-teaching, e-tools, technology, education.

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Authors: Fazlollah Moosavinasab, Zhila Motamedi

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An experiment was conducted to study the effects of different types of probiotic on Sucrase enzyme activity of the small intestine mucosa in male broilers. The experimental design was arranged as randomized completely blocks in 4 × 2 factorial arrangement of treatment. 180 male broilers of Ross 308 commercial hybrid were designated into 4 groups. Three replicates of 15 birds were assigned to each treatment. Control treatments (diet contained no probiotic) were fed according to the NRC as base diet and three treatment groups were fed from the same diet plus three different types of probiotics. Birds were slaughtered after 21 and 42 days and different segments of small intestine (at 1,10,30,50,70 and 90% of total length the small intestine) were taken from each replicates (N=2) Sucrase enzyme activities were measured and recorded. Obtained data were analyzed by Spss (P<0.05). In three treatment groups, probiotic had no significant effect on sucrase activity in different ages and segments of small intestine (P<0.05). These data suggested that probiotics administration had no significant effect on treatments comparing to the control group.

Keywords: Broiler, Chicks, Probiotics, Small Intestine, Sucrase

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Authors: Indiramma M., K. R. Anandakumar

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Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Keywords: Collaborative Decision making, Trust, Multi Agent System (MAS), Bayesian Network, Reinforcement Learning.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: Distribution network, machine learning, network topology, phase identification, smart grid.

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Authors: Indrasen Raghupatruni, Michael Glora, Ralf Diekmann, Thomas Demmer

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As the trend in automotive technology is fast moving towards hybridization and electrification to curb emissions as well as to improve the fuel efficiency, air-conditioning systems in passenger cars have not caught up with this trend and still remain as the major energy consumers amongst others. Adsorption based air-conditioning systems, e.g. with silica-gel water pair, which are already in use for residential and commercial applications, are now being considered as a technology leap once proven feasible for the passenger cars. In this paper we discuss a methodology, challenges and feasibility of implementing an adsorption based air-conditioning system in a passenger car utilizing the exhaust waste heat. We also propose an optimized control strategy with interfaces to the engine control unit of the vehicle for operating this system with reasonable efficiency supported by our simulation and validation results in a prototype vehicle, additionally comparing to existing implementations, simulation based as well as experimental. Finally we discuss the influence of start-stop and hybrid systems on the operation strategy of the adsorption air-conditioning system.

Keywords: Adsorption air-conditioning, feasibility study, optimized control strategy, prototype vehicle.

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Authors: F. Boustani

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Energy generated by the force of water in hydropower can provide a more sustainable, non-polluting alternative to fossil fuels, along with other renewable sources of energy, such as wind, solar and tidal power, bio energy and geothermal energy. Small scale hydroelectricity in Iran is well suited for “off-grid" rural electricity applications, while other renewable energy sources, such as wind, solar and biomass, can be beneficially used as fuel for pumping groundwater for drinking and small scale irrigation in remote rural areas or small villages. Small Hydro Power plants in Iran have very low operating and maintenance costs because they consume no fossil or nuclear fuel and do not involve high temperature processes. The equipment is relatively simple to operate and maintain. Hydropower equipment can adjust rapidly to load changes. The extended equipment life provides significant economic advantages. Some hydroelectric plants installed 100 years ago still operate reliably. The Polkolo river is located on Karun basin at southwest of Iran. Situation and conditions of Polkolo river are evaluated for construction of small hydropower in this article. The topographical conditions and the existence of permanent water from springs provide the suitability to install hydroelectric power plants on the river Polkolo. The cascade plant consists of 9 power plants connected with each other and is having the total head as 1100m and discharge about 2.5cubic meter per second. The annual production of energy is 105.5 million kwh.

Keywords: Hydropower potential, Iran, SHP, Yasuj.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop, Pairote Sattayatham

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Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte Carlo method in the approximation step. The data reduction has been performed horizontally and vertically through our EMR sampling method. The proposed method is analyzed by a series of experiments. We apply our algorithm on clustering and classification tasks to evaluate the utility of our approach.

Keywords: Data Stream, Monte Carlo, Sampling, DensityEstimation.

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Authors: Vahid Aryanpur , Ehsan Shafiei

Abstract:

This paper presents an environmental and technoeconomic evaluation of light duty vehicles in Iran. A comprehensive well-to-wheel (WTW) analysis is applied to compare different automotive fuel chains, conventional internal combustion engines and innovative vehicle powertrains. The study examines the competitiveness of 15 various pathways in terms of energy efficiencies, GHG emissions, and levelized cost of different energy carriers. The results indicate that electric vehicles including battery electric vehicles (BEV), fuel cell vehicles (FCV) and plug-in hybrid electric vehicles (PHEV) increase the WTW energy efficiency by 54%, 51% and 46%, respectively, compared to common internal combustion engines powered by gasoline. On the other hand, greenhouse gas (GHG) emissions per kilometer of FCV and BEV would be 48% lower than that of gasoline engines. It is concluded that BEV has the lowest total cost of energy consumption and external cost of emission, followed by internal combustion engines (ICE) fueled by CNG. Conventional internal combustion engines fueled by gasoline, on the other hand, would have the highest costs.

Keywords: Well-to-Wheel analysis, Energy Efficiency, GHG emissions, Levelized cost of energy, Alternative fuel vehicles.

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Authors: Mei Shan Ngan, Chee Wei Tan

Abstract:

Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.

Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)

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Authors: Ebtehal Alawi Alsaggaf, Shehab A. Gamalel-Din

Abstract:

Exploring an autistic child in Elementary school is a difficult task that must be fully thought out and the teachers should be aware of the many challenges they face raising their child especially the behavioral problems of autistic children. Hence there arises a need for developing Artificial intelligence (AI) Contemporary Techniques to help diagnosis to discover autistic people. In this research, we suggest designing architecture of expert system that combine Cognitive Maps (CM) with Case Based Reasoning technique (CBR) in order to reduce time and costs of traditional diagnosis process for the early detection to discover autistic children. The teacher is supposed to enter child's information for analyzing by CM module. Then, the reasoning processor would translate the output into a case to be solved a current problem by CBR module. We will implement a prototype for the model as a proof of concept using java and MYSQL. This will be provided a new hybrid approach that will achieve new synergies and improve problem solving capabilities in AI. And we will predict that will reduce time, costs, the number of human errors and make expertise available to more people who want who want to serve autistic children and their families.

Keywords: Autism, Cognitive Maps (CM), Case Based Reasoning technique (CBR).

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Authors: Hendriëtte van der Walt, Lesley Chown, Richard Harris, Ndabenhle Sosibo, Robert Tshikhudo

Abstract:

The use of magnetic and magnetic/gold core/shell nanoparticles in biotechnology or medicine has shown good promise due to their hybrid nature which possesses superior magnetic and optical properties. Some of these potential applications include hyperthermia treatment, bio-separations, diagnostics, drug delivery and toxin removal. Synthesis refinement to control geometric and magnetic/optical properties, and finding functional surfactants for biomolecular attachment, are requirements to meet application specifics. Various high-temperature preparative methods were used for the synthesis of iron oxide and gold-coated iron oxide nanoparticles. Different surface functionalities, such as 11-aminoundecanoic and 11-mercaptoundecanoic acid, were introduced on the surface of the particles to facilitate further attachment of biomolecular functionality and drug-like molecules. Nanoparticle thermal stability, composition, state of aggregation, size and morphology were investigated and the results from techniques such as Fourier Transform-Infra Red spectroscopy (FT-IR), Ultraviolet visible spectroscopy (UV-vis), Transmission Electron Microscopy (TEM) and thermal analysis are discussed.

Keywords: Core/shell, Iron oxide, Gold coating, Nanoparticles.

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