Search results for: k-ary Tree Generation

Authors: S. V. Kogilavani, C. S. Kanimozhiselvi, S. Malliga

Abstract:

Fast changing knowledge systems on the Internet can be accessed more efficiently with the help of automatic document summarization and updating techniques. The aim of multi-document update summary generation is to construct a summary unfolding the mainstream of data from a collection of documents based on the hypothesis that the user has already read a set of previous documents. In order to provide a lot of semantic information from the documents, deeper linguistic or semantic analysis of the source documents were used instead of relying only on document word frequencies to select important concepts. In order to produce a responsive summary, meaning oriented structural analysis is needed. To address this issue, the proposed system presents a document summarization approach based on sentence annotation with aspects, prepositions and named entities. Semantic element extraction strategy is used to select important concepts from documents which are used to generate enhanced semantic summary.

Keywords: Aspects, named entities, prepositions, update summary.

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Authors: Guguloth Ramesh, T. K. Sunil Kumar

Abstract:

This paper presents congestion management in deregulated power systems. In a deregulated environment, every buyer wants to buy power from the cheapest generator available, irrespective of relative geographical location of buyer and seller. As a consequence of this, the transmission corridors evacuating the power of cheaper generators would get overloaded if all such transactions are approved. Congestion management is a mechanism to prioritize the transactions and commit to such a schedule which would not overload the network. The congestions in the transmission lines are determined by Optimal Power Flow (OPF) solution, which is carried by primal liner programming method. Congestion in the transmission lines are alleviated by connected Distributed Generation (DG) of micro grid at load bus. A method to determine the optimal location of DG unit has been suggested based on transmission line relief sensitivity based approach. The effectiveness of proposed method has been demonstrated on modified IEEE-14 and 30 bus test systems.

Keywords: Congestion management, Distribution Generation (DG), Transmission Line Relief (TLR) sensitivity index, OPF.

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Authors: Domenico Pirozzi, Angelo Ausiello, Gaetano Zuccaro, Filomena Sannino, Abu Yousuf

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The oleaginous yeasts Lipomyces starkey were grown in the presence of dairy industry wastewaters (DIW). The yeasts were able to degrade the organic components of DIW and to produce a significant fraction of their biomass as triglycerides. When using DIW from the Ricotta cheese production or residual whey as growth medium, the L. starkey could be cultured without dilution nor external organic supplement. On the contrary, the yeasts could only partially degrade the DIW from the Mozzarella cheese production, due to the accumulation of a metabolic product beyond the threshold of toxicity. In this case, a dilution of the DIW was required to obtain a more efficient degradation of the carbon compounds and an higher yield in oleaginous biomass. The fatty acid distribution of the microbial oils obtained showed a prevalence of oleic acid, and is compatible with the production of a II generation biodiesel offering a good resistance to oxidation as well as an excellent cold-performance.

Keywords: Yeasts, Lipids, Biodiesel, Dairy industry wastewaters.

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Authors: R. N. Patel

Abstract:

This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.

Keywords: Area control error, Artificial intelligence, Automatic generation control, Genetic Algorithms and modeling, ISE, ITAE, Particle swarm optimization.

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Authors: Khalil el Hindi

Abstract:

This paper presents a simple and effective method for approximate indexing of instances for instance based learning. The method uses an interval tree to determine a good starting search point for the nearest neighbor. The search stops when an early stopping criterion is met. The method proved to be very effective especially when only the first nearest neighbor is required.

Keywords: Instance based learning, interval trees, the knn algorithm, machine learning.

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Authors: Gülfem I. Alptekin, S. Emre Alptekin

Abstract:

The next generation wireless systems, especially the cognitive radio networks aim at utilizing network resources more efficiently. They share a wide range of available spectrum in an opportunistic manner. In this paper, we propose a quality management model for short-term sub-lease of unutilized spectrum bands to different service providers. We built our model on competitive secondary market architecture. To establish the necessary conditions for convergent behavior, we utilize techniques from game theory. Our proposed model is based on potential game approach that is suitable for systems with dynamic decision making. The Nash equilibrium point tells the spectrum holders the ideal price values where profit is maximized at the highest level of customer satisfaction. Our numerical results show that the price decisions of the network providers depend on the price and QoS of their own bands as well as the prices and QoS levels of their opponents- bands.

Keywords: cognitive radio networks, game theory, nextgeneration wireless networks, spectrum management.

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Authors: Touahria Mohamed, Khababa Abdallah, Frécon Louis

Abstract:

This paper proposes a declarative language for knowledge representation (Ibn Rochd), and its environment of exploitation (DeGSE). This DeGSE system was designed and developed to facilitate Ibn Rochd writing applications. The system was tested on several knowledge bases by ascending complexity, culminating in a system for recognition of a plant or a tree, and advisors to purchase a car, for pedagogical and academic guidance, or for bank savings and credit. Finally, the limits of the language and research perspectives are stated.

Keywords: Knowledge representation, declarative language, IbnRochd, DeGSE, facets, cognitive approach.

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Authors: Hamid Maidat, Khedidja Bouhadef, Djamel Eddine Ameziani, Azzedine Abdedou

Abstract:

This work consists of a numerical simulation of convective heat transfer in a vertical plane channel filled with a heat generating porous medium, in the absence of local thermal equilibrium. The walls are maintained to a constant temperature and the inlet velocity is uniform. The dynamic range is described by the Darcy-Brinkman model and the thermal field by two energy equations model. A dimensionless formulation is developed for performing a parametric study based on certain dimensionless groups such as, the Biot interstitial number, the thermal conductivity ratio and the volumetric heat generation, q '''. The governing equations are solved using the finite volume method, gave rise to a multitude of results concerning in particular the thermal field in the porous channel and the existence or not of the local thermal equilibrium.

Keywords: Mixed convection, porous medium, power generation, local thermal non equilibrium model.

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Authors: Chien-Ju Li, Chun-Hui Yu, Chi-Chuan Hwang, Tsunglin Liu , Darby Tien-Hao Chang

Abstract:

De novo genome assembly is always fragmented. Assembly fragmentation is more serious using the popular next generation sequencing (NGS) data because NGS sequences are shorter than the traditional Sanger sequences. As the data throughput of NGS is high, the fragmentations in assemblies are usually not the result of missing data. On the contrary, the assembled sequences, called contigs, are often connected to more than one other contigs in a complicated manner, leading to the fragmentations. False connections in such complicated connections between contigs, named a contig graph, are inevitable because of repeats and sequencing/assembly errors. Simplifying a contig graph by removing false connections directly improves genome assembly. In this work, we have developed a tool, SIMGraph, to resolve ambiguous connections between contigs using NGS data. Applying SIMGraph to the assembly of a fungus and a fish genome, we resolved 27.6% and 60.3% ambiguous contig connections, respectively. These results can reduce the experimental efforts in resolving contig connections.

Keywords: Contig graph, NGS, de novo assembly, scaffold.

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Authors: S. Meziane, H. I. Faraoun, C. Esling

Abstract:

Transition metal dichalcogenides have potential applications in power generation devices that convert waste heat into electric current by the so-called Seebeck and Hall effects thus providing an alternative energy technology to reduce the dependence on traditional fossil fuels. In this study, the thermoelectric properties of 1T and 2HTaX2 (X= S or Se) dichalcogenide superconductors have been computed using the semi-classical Boltzmann theory. Technologically, the task is to fabricate suitable materials with high efficiency. It is found that 2HTaS2 possesses the largest value of figure of merit ZT= 1.27 at 175 K. From a scientific point of view, we aim to model the underlying materials properties and in particular the transport phenomena as mediated by electrons and lattice vibrations responsible for superconductivity, Charge Density Waves (CDW) and metal/insulator transitions as function of temperature. The goal of the present work is to develop an understanding of the superconductivity of these selected materials using the transport properties at the fundamental level.

Keywords: Ab initio, high efficiency, power generation devices, transition metal dichalcogenides.

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Authors: Gökhan Silahtaroğlu

Abstract:

Clustering large populations is an important problem when the data contain noise and different shapes. A good clustering algorithm or approach should be efficient enough to detect clusters sensitively. Besides space complexity, time complexity also gains importance as the size grows. Using hierarchies we developed a new algorithm to split attributes according to the values they have and choosing the dimension for splitting so as to divide the database roughly into equal parts as much as possible. At each node we calculate some certain descriptive statistical features of the data which reside and by pruning we generate the natural clusters with a complexity of O(n).

Keywords: Clustering, tree, split, pruning, entropy, gini.

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Authors: Brennan Lodge

Abstract:

Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLMs is exciting, such models do have their downsides. LLMs cannot easily expand or revise their memory, and they cannot straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: Retrieval Augmented Generation, Governance Risk and Compliance, Cybersecurity, AI-driven Compliance, Risk Management, Generative AI.

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Authors: Vinod Kumar Khera, R. K. Sharma, A. K. Gupta

Abstract:

Power dissipation increases exponentially during test mode as compared to normal operation of the circuit. In extreme cases, test power is more than twice the power consumed during normal operation mode. Test vector generation scheme is key component in deciding the power hungriness of a circuit during testing. Test vector count and consequent leakage current are functions of test vector generation scheme. Fault based test vector count optimization has been presented in this work. It helps in reducing test vector count and the leakage current. In the presented scheme, test vectors have been reduced by extracting essential child vectors. The scheme has been tested experimentally using stuck at fault models and results ensure the reduction in test vector count.

Keywords: Low power VLSI testing, independent fault, essential faults, test vector reduction.

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Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing

Abstract:

Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.

Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.

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Authors: Abdolreza Roozbeh, Reza Sedaghati, Ali Asghar Baziar, Mohammad Reza Tabatabaei

Abstract:

This paper presents dynamic models of distributed generators (DG) and investigates dynamic behavior of the DG units in the micro grid system. The DG units include photovoltaic and fuel cell sources. The voltage source inverter is adopted since the electronic interface which can be equipped with its controller to keep stability of the micro grid during small signal dynamics. This paper also introduces power management strategies and implements the DG load sharing concept to keep the micro grid operation in gridconnected and islanding modes of operation. The results demonstrate the operation and performance of the photovoltaic and fuel cell as distributed generators in a micro grid. The entire control system in the micro grid is developed by combining the benefits of the power control and the voltage control strategies. Simulation results are all reported, confirming the validity of the proposed control technique.

Keywords: Stability, Distributed Generation, Dynamic, Micro Grid.

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Authors: Kolar Jan, Dvorak Vaclav

Abstract:

In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.

Keywords: Grid deformation, Micro-genetic algorithm, shapebased sequence, supersonic ejector.

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Authors: Tomáš Bublík, Miroslav Virius

Abstract:

This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and subgraph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, Scripthon, source code recognition

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Authors: Sharmistha Roy

Abstract:

In Singapore, there are about 1 million baby boomers, defined as those born between 1947 and 1964. They constitute a sizeable proportion (about 30 per cent) of the resident population comprising Singapore citizens and permanent residents. The first batches of these baby boomers have already 65 years old by 2012. Thereafter, baby boomers will swell the ranks of the elderly population in Singapore until 2030. The baby boomers in this study are divided into broad groups, namely, the early baby boomers (born 1947-54) and late baby boomers (1955-64). Continuing decline in fertility and mortality rates in the past three decades as well as improvements in health care facilities and services have changed the demography of Singapore from a “pyramid-shape” young, post war baby boomers population to a rapidly ageing population. With the ageing of the baby boom generation, the population of Singapore is about to grey rapidly over the next three decades. As such, there is a need for Singapore to understand the profile, perceptions and aspirations of this group, and devise strategies to address the needs and concerns as well as opportunities that arise with the ageing of baby boomers are discussed and presented in this work.

Keywords: Ageing index, Baby boomers, Demographic dependency ratio (DDR), Fertility and mortality rate, Life expectancy, Singapore.

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Authors: Rim Bouhaouel, Naoufel Kraïem, Zuhoor Al Khanjari

Abstract:

Unified Modeling Language (UML) is considered as one of the widespread modeling language standardized by the Object Management Group (OMG). Therefore, the model driving engineering (MDE) community attempts to provide reuse of UML diagrams, and do not construct it from scratch. The UML model appears according to a specific software development process. The existing method generation models focused on the different techniques of transformation without considering the development process. Our work aims to construct an UML component from fragments of UML diagram basing on an agile method. We define UML fragment as a portion of a UML diagram, which express a business target. To guide the generation of fragments of UML models using an agile process, we need a flexible approach, which adapts to the agile changes and covers all its activities. We use the software product line (SPL) to derive a fragment of process agile method. This paper explains our approach, named RECUP, to generate UML fragments following an agile process, and overviews the different aspects. In this paper, we present the approach and we define the different phases and artifacts.

Keywords: UML, component, fragment, agile, SPL.

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Authors: Fayssal Amrane, Azeddine Chaiba

Abstract:

In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.

Keywords: Doubly fed induction generetor, direct power control, space vector modulation, type-2 fuzzy logic control, neuro-fuzzy control, maximum power point tracking.

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Authors: Lorenzo Maiorino, Fabio Fortuna, Giovanni Panebianco, Marco Sanzari, Gabriella Arcese, Valerio Maria Paolozzi

Abstract:

It is well known that sport is a factor of social cohesion and the breaking down of barriers between people. From this point of view, the aim is to demonstrate how, through the (re)generation of sustainable structures, it is possible to give life to a new social, cultural and economic pathway, where possible, in peripheral areas with problems of abandonment and degradation. The aim of this paper is therefore to study realities such as European programs and funds and to highlight the ways in which planning can be used to respond to critical issues such as urban decay, abandonment, and the mitigation of social differences. For this reason, the analysis will be carried out through the Multiannual Financial Framework (MFF) package, the next generation EU, the Recovery and Resilience Facility (RRF), the Cohesion Fund, the European Social Fund, and other managed funds. The procedure will rely on sources and data of unquestionable origin, and the relation to the object of study in question will be highlighted. The project lends itself to be ambitious and explore a further aspect of the sports theme, which as we know, is one of the foundations for a healthy society

.

Keywords: Sport, social inclusion, urban regeneration, sport facilities, European funds.

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Authors: Zia Abbas, Giuseppe Scotti, Mauro Olivieri

Abstract:

Current mode circuits like current conveyors are getting significant attention in current analog ICs design due to their higher band-width, greater linearity, larger dynamic range, simpler circuitry, lower power consumption and less chip area. The second generation current controlled conveyor (CCCII) has the advantage of electronic adjustability over the CCII i.e. in CCCII; adjustment of the X-terminal intrinsic resistance via a bias current is possible. The presented approach is based on the CMOS implementation of second generation positive (CCCII+), negative (CCCII-) and dual Output Current Controlled Conveyor (DOCCCII) and its application as Universal filter. All the circuits have been designed and simulated using 65nm CMOS technology model parameters on Cadence Virtuoso / Spectre using 1V supply voltage. Various simulations have been carried out to verify the linearity between output and input ports, range of operation frequency, etc. The outcomes show good agreement between expected and experimental results.

Keywords: CCCII+, CCCII-, DOCCCII, Electronic tunability, Universal filter

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Authors: Sayani Sil, Sukanta Das

Abstract:

This paper reports a distributed mutual exclusion algorithm for mobile Ad-hoc networks. The network is clustered hierarchically. The proposed algorithm considers the clustered network as a logical tree and develops a token passing scheme to get the mutual exclusion. The performance analysis and simulation results show that its message requirement is optimal, and thus the algorithm is energy efficient.

Keywords: Critical section, Distributed mutual exclusion, MobileAd-hoc network, Token-based algorithms.

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Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya, Vladimir A. Makarov, Yulia G. Sokolovskaya

Abstract:

The laser-ultrasonic method is realized for quantifying the influence of porosity on the local Young’s modulus of isotropic composite materials. The method is based on a laser thermooptical method of ultrasound generation combined with measurement of the phase velocity of longitudinal and shear acoustic waves in samples. The main advantage of this method compared with traditional ultrasonic research methods is the efficient generation of short and powerful probing acoustic pulses required for reliable testing of ultrasound absorbing and scattering heterogeneous materials. Using as an example samples of a metal matrix composite with reinforcing microparticles of silicon carbide in various concentrations, it is shown that to provide an effective increase in Young’s modulus with increasing concentration of microparticles, the porosity of the final sample should not exceed 2%.

Keywords: Laser ultrasonic, longitudinal and shear ultrasonic waves, porosity, composite, local elastic moduli.

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Authors: Mohammed I. Abouheaf, Sofie Haesaert, Wei-Jen Lee, Frank L. Lewis

Abstract:

Economic Dispatch is one of the most important power system management tools. It is used to allocate an amount of power generation to the generating units to meet the load demand. The Economic Dispatch problem is a large scale nonlinear constrained optimization problem. In general, heuristic optimization techniques are used to solve non-convex Economic Dispatch problem. In this paper, ideas from Reinforcement Learning are proposed to solve the non-convex Economic Dispatch problem. Q-Learning is a reinforcement learning techniques where each generating unit learn the optimal schedule of the generated power that minimizes the generation cost function. The eligibility traces are used to speed up the Q-Learning process. Q-Learning with eligibility traces is used to solve Economic Dispatch problems with valve point loading effect, multiple fuel options, and power transmission losses.

Keywords: Economic Dispatch, Non-Convex Cost Functions, Valve Point Loading Effect, Q-Learning, Eligibility Traces.

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Authors: R. Anitha, R. S. Lekshmi

Abstract:

Graph decompositions are vital in the study of combinatorial design theory. A decomposition of a graph G is a partition of its edge set. An n-sun graph is a cycle Cn with an edge terminating in a vertex of degree one attached to each vertex. In this paper, we define n-sun decomposition of some even order graphs with a perfect matching. We have proved that the complete graph K2n, complete bipartite graph K2n, 2n and the Harary graph H4, 2n have n-sun decompositions. A labeling scheme is used to construct the n-suns.

Keywords: Decomposition, Hamilton cycle, n-sun graph, perfect matching, spanning tree.

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Authors: Zhoucheng Bao, Haiyan Zhu, Tingting Pang, Zuling Wang

Abstract:

This paper presents a multi population Differential Evolution (DE) with adaptive mutation and local search for global optimization, named AMMADE in order to better coordinate the cooperation between the populations and the rational use of resources. In AMMADE, the population is divided based on the Euclidean distance sorting method at each generation to appropriately coordinate the cooperation between subpopulations and the usage of resources, such that the best-performed subpopulation will get more computing resources in the next generation. Further, an adaptive local search strategy is employed on the best-performed subpopulation to achieve a balanced search. The proposed algorithm has been tested by solving optimization problems taken from CEC2014 benchmark problems. Experimental results show that our algorithm can achieve a competitive or better result than related methods. The results also confirm the significance of devised strategies in the proposed algorithm.

Keywords: Differential evolution, multi-mutation strategies, memetic algorithm, adaptive local search.

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Authors: Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim

Abstract:

The installation of photovoltaic based distributed generation (PVDG) in active distribution system can lead to voltage fluctuation due to the intermittent and unpredictable PVDG output power. This paper presented a method in mitigating the voltage rise by optimally locating and sizing the battery energy storage system (BESS) in PVDG integrated distribution network. The improved firefly algorithm is used to perform optimal placement and sizing. Three objective functions are presented considering the voltage deviation and BESS off-time with state of charge as the constraint. The performance of the proposed method is compared with another optimization method such as the original firefly algorithm and gravitational search algorithm. Simulation results show that the proposed optimum BESS location and size improve the voltage stability.

Keywords: BESS, PVDG, firefly algorithm, voltage fluctuation.

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Authors: Paula Ferreira, Filipa Vieira

Abstract:

The use of wind energy for electricity generation is growing rapidly across the world and in Portugal. However, the geographical characteristics of the country along with the average wind regime and with the environmental restrictions imposed to these projects create limitations to the exploit of the onshore wind resource. The best onshore wind spots are already committed and the possibility of offshore wind farms in the Portuguese cost is now being considered. This paper aims to make a contribution to the evaluation of offshore wind power projects in Portugal. The technical restrictions are addressed and the strategic, environmental and financial interest of the project is analysed from the private company and public points of view. The results suggest that additional support schemes are required to ensure private investors interest for these projects. Assuming an approach of direct substitution of energy sources for electricity generation, the avoided CO2 equivalent emissions for an offshore wind power project were quantified. Based on the conclusions, future research is proposed to address the environmental and social impacts of these projects.

Keywords: Feed-in tariff, offshore wind power, project evaluation.

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Authors: Doru Anastasiu Popescu, Dan Rădulescu

Abstract:

In this paper, we determine the similarity of two HTML web applications. We are going to use a genetic algorithm in order to determine the most significant web pages of each application (we are not going to use every web page of a site). Using these significant web pages, we will find the similarity value between the two applications. The algorithm is going to be efficient because we are going to use a reduced number of web pages for comparisons but it will return an approximate value of the similarity. The binary trees are used to keep the tags from the significant pages. The algorithm was implemented in Java language.

Keywords: Tag, HTML, web page, genetic algorithm, similarity value, binary tree.

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