Search results for: knowledge required for parsing.

Authors: Igor Astrov, Andrus Pedai

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the neural control of autonomous constant depth flight of an autonomous underwater vehicle (AUV). Autonomous constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller to govern the process. The AUV, named VORAM, is used as a model for the verification of the proposed hybrid control algorithm. Three neural network controllers, named NARMA-L2 controllers, are designed for fast and stable diving maneuvers of chosen AUV model. This hybrid control strategy for chosen AUV model has been verified by simulation of diving maneuvers using software package Simulink and demonstrated good performance for fast SA in real-time searchand- rescue operations.

Keywords: Autonomous underwater vehicles, depth control, neurocontrollers, situational awareness.

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Authors: Simões, Evelyne Rolim Braun, Marques, Lana Grasiela Alves, Soares, Bruno Marques Pinheiro, Daniel Pascoalino, Santos, Maria Rita Morais Chaves, Pessoa, Claudia

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The prospective analysis is presented as an important tool to identify the most relevant opportunities and needs in research and development from planned interventions in innovation systems. This study chose Phyllanthus niruri, known as "stone break" to describe the knowledge about the specie, by using biotechnological forecasting through the software Vantage Point. It can be seen a considerable increase in studies on Phyllanthus niruri in recent years and that there are patents about this plant since twenty-five years ago. India was the country that most carried out research on the specie, showing interest, mainly in studies of hepatoprotection, antioxidant and anti-cancer activities. Brazil is in the second place, with special interest for anti-tumor studies. Given the identification of the Brazilian groups that exploit the species it is possible to mediate partnerships and cooperation aiming to help on the implementing of the Program of Herbal medicines (phytotherapics) in Brazil.

Keywords: Phyllanthus niruri, phytotherapics, technological forecasting.

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Authors: Karima Qayumi, Alex Norta

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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: Agent-oriented modeling, business Intelligence management, distributed data mining, multi-agent system.

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Authors: Md. Shams Razi Shopnil, Tanvir Imtiaz, Sabrina Mahjabin, Md. Sahadat Hossain

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Saturated hydraulic conductivity is one of the most significant attributes of pavement base course. Determination of hydraulic conductivity is a routine procedure for regular aggregate base courses. However, in many cases, a cement-stabilized base course is used with compromised drainage ability. Traditional hydraulic conductivity testing procedure is a readily available option which leads to two consequential drawbacks, i.e., the time required for the specimen to be saturated and extruding the sample after completion of the laboratory test. To overcome these complications, this study aims at formulating an empirical approach to predicting hydraulic conductivity based on Unconfined Compressive Strength test results. To do so, this study comprises two separate experiments (Constant Head Permeability test and Unconfined Compressive Strength test) conducted concurrently on a specimen having the same physical credentials. Data obtained from the two experiments were then used to devise a correlation between hydraulic conductivity and unconfined compressive strength. This correlation in the form of a polynomial equation helps to predict the hydraulic conductivity of cement-treated pavement base course, bypassing the cumbrous process of traditional permeability and less commonly used horizontal permeability tests. The correlation was further corroborated by a different set of data, and it has been found that the derived polynomial equation is deemed to be a viable tool to predict hydraulic conductivity.

Keywords: Hydraulic conductivity, unconfined compressive strength, recycled plastics, recycled concrete aggregates.

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Authors: Robert F. Kenny, Glenda A. Gunter

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Current technological advances pale in comparison to the changes in social behaviors and 'sense of place' that is being empowered since the Internet made it on the scene. Today-s students view the Internet as both a source of entertainment and an educational tool. The development of virtual environments is a conceptual framework that needs to be addressed by educators and it is important that they become familiar with who these virtual learners are and how they are motivated to learn. Massively multiplayer online role playing games (MMORPGs), if well designed, could become the vehicle of choice to deliver learning content. We suggest that these games, in order to accomplish these goals, must begin with well-established instructional design principles that are co-aligned with established principles of video game design. And have the opportunity to provide an instructional model of significant prescriptive power. The authors believe that game designers need to take advantage of the natural motivation player-learners have for playing games by developing them in such a way so as to promote, intrinsic motivation, content learning, transfer of knowledge, and naturalization.

Keywords: serious games, endogenous fantasy, intrinsic motivation, online learning.

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Authors: E. N. Sathishkumar, K. Thangavel, T. Chandrasekhar

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Feature selection is a process to select features which are more informative. It is one of the important steps in knowledge discovery. The problem is that all genes are not important in gene expression data. Some of the genes may be redundant, and others may be irrelevant and noisy. Here a novel approach is proposed Hybrid K-Mean-Quick Reduct (KMQR) algorithm for gene selection from gene expression data. In this study, the entire dataset is divided into clusters by applying K-Means algorithm. Each cluster contains similar genes. The high class discriminated genes has been selected based on their degree of dependence by applying Quick Reduct algorithm to all the clusters. Average Correlation Value (ACV) is calculated for the high class discriminated genes. The clusters which have the ACV value as 1 is determined as significant clusters, whose classification accuracy will be equal or high when comparing to the accuracy of the entire dataset. The proposed algorithm is evaluated using WEKA classifiers and compared. The proposed work shows that the high classification accuracy.

Keywords: Clustering, Gene Selection, K-Mean-Quick Reduct, Rough Sets.

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Authors: Rossitza M. Setchi, Qiao Tang

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Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Keywords: Concepts, indexing, machine learning, ontology, tagging.

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Authors: Roberto Iglesias, Theocharis Kyriacou, Ulrich Nehmzow, Steve Billings

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Fundamental sensor-motor couplings form the backbone of most mobile robot control tasks, and often need to be implemented fast, efficiently and nevertheless reliably. Machine learning techniques are therefore often used to obtain the desired sensor-motor competences. In this paper we present an alternative to established machine learning methods such as artificial neural networks, that is very fast, easy to implement, and has the distinct advantage that it generates transparent, analysable sensor-motor couplings: system identification through nonlinear polynomial mapping. This work, which is part of the RobotMODIC project at the universities of Essex and Sheffield, aims to develop a theoretical understanding of the interaction between the robot and its environment. One of the purposes of this research is to enable the principled design of robot control programs. As a first step towards this aim we model the behaviour of the robot, as this emerges from its interaction with the environment, with the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving Average models with eXogenous inputs). This method produces explicit polynomial functions that can be subsequently analysed using established mathematical methods. In this paper we demonstrate the fidelity of the obtained NARMAX models in the challenging task of robot route learning; we present a set of experiments in which a Magellan Pro mobile robot was taught to follow four different routes, always using the same mechanism to obtain the required control law.

Keywords: Mobile robotics, system identification, non-linear modelling, NARMAX.

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Authors: Almudena Konrad, Tomás Galguera

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Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.

Keywords: Computational thinking, computing education, computer programming curriculum, logic, teaching methods.

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Authors: Sultan Daud, John P. Forth, Nikolaos Nikitas

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The current study aims to highlight the loading characteristics impact on the time evolution (focusing particularly on long term effects) of the deformation of realized reinforced concrete beams. Namely the tension stiffening code provisions (i.e. within Eurocode 2) are reviewed with a clear intention to reassess their operational value and predicting capacity. In what follows the experimental programme adopted along with some preliminary findings and numerical modeling attempts are presented. For a range of long slender reinforced concrete simply supported beams (4200 mm) constant static sustained and repeated cyclic loadings were applied mapping the time evolution of deformation. All experiments were carried out at the Heavy Structures Lab of the University of Leeds. During tests the mid-span deflection, creep coefficient and shrinkage strains were monitored for duration of 90 days. The obtained results are set against the values predicted by Eurocode 2 and the tools within an FE commercial package (i.e. Midas FEA) to yield that existing knowledge and practise is at times over-conservative.

Keywords: Eurocode2, midas fea, repeated, sustained loading.

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Authors: Parvinder S. Sandhu, Sandeep Khimta, Kiranpreet Kaur

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The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.

Keywords: Growing Neural Gas, data clustering, fault prediction.

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Authors: Hazem M. El-Bakry

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Neural processors have shown good results for detecting a certain character in a given input matrix. In this paper, a new idead to speed up the operation of neural processors for character detection is presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single faster neural processor. Furthermore, faster character detection is obtained by using parallel processing techniques to test the resulting sub-images at the same time using the same number of faster neural networks. In contrast to using only faster neural processors, the speed up ratio is increased with the size of the input image when using faster neural processors and image decomposition. Moreover, the problem of local subimage normalization in the frequency domain is solved. The effect of image normalization on the speed up ratio of character detection is discussed. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.

Keywords: Fast Character Detection, Neural Processors, Cross Correlation, Image Normalization, Parallel Processing.

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Authors: E. Kissi, V. K. Acheamfour, J. J. Gyimah, T. Adjei-Kumi

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Factoring accounts receivable is widely accepted as an alternative financing source and utilized in almost every industry that sells business-to-business or business-to-government. However, its patronage in the construction industry is very limited as some barriers hinder its application in the construction industry. This study aims at assessing the barriers to the use of factoring accounts receivables in the Ghanaian construction industry. The study adopted the sequential exploratory research method where structured and unstructured questionnaires were conveniently distributed to D1K1 and D2K2 construction firms in Ghana. Using the one-sample t-test and Kendall’s Coefficient of concordance data were analyzed. The most severe challenge concluded is the high cost of factoring patronage. Other critical challenges identified were low knowledge on factoring processes, inadequate access to information on factoring, and high risks involved in factoring. Hence, it is recommended that contractors should be made aware of the prospects of factoring of accounts receivables in the construction industry. This study serves as basis for further rigorous research into factoring of accounts receivables in the industry.

Keywords: Barriers, contractors, factoring accounts receivables, Ghanaian, perception.

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Authors: Mohamad Reza. Mohaghegh, Majid. Malek Jafarian

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This research proposes an algorithm for the simulation of time-periodic unsteady problems via the solution unsteady Euler and Navier-Stokes equations. This algorithm which is called Time Spectral method uses a Fourier representation in time and hence solve for the periodic state directly without resolving transients (which consume most of the resources in a time-accurate scheme). Mathematical tools used here are discrete Fourier transformations. It has shown tremendous potential for reducing the computational cost compared to conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy. The accuracy and efficiency of this technique is verified by Euler and Navier-Stokes calculations for pitching airfoils. Because of flow turbulence nature, Baldwin-Lomax turbulence model has been used at viscous flow analysis. The results presented by the Time Spectral method are compared with experimental data. It has shown tremendous potential for reducing the computational cost compared to the conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy, because results verify the small number of time intervals per pitching cycle required to capture the flow physics.

Keywords: Time Spectral Method, Time-periodic unsteadyflow, Discrete Fourier transform, Pitching airfoil, Turbulence flow

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Authors: Goh Yen Nee

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This research aimed to find out the determining factors for ISO 14001 EMS implementation among SMEs in Malaysia from the Resource based view. A cross-sectional approach using survey was conducted. A research model been proposed which comprises of ISO 14001 EMS implementation as the criterion variable while physical capital resources (i.e. environmental performance tracking and organizational infrastructures), human capital resources (i.e. top management commitment and support, training and education, employee empowerment and teamwork) and organizational capital resources (i.e. recognition and reward, organizational culture and organizational communication) as the explanatory variables. The research findings show that only environmental performance tracking, top management commitment and support and organizational culture are found to be positively and significantly associated with ISO 14001 EMS implementation. It is expected that this research will shed new knowledge and provide a base for future studies about the role played by firm-s internal resources.

Keywords: ISO 14001 Environmental Management System, Malaysia, Resource based view, SMEs

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Authors: James Moir

Abstract:

The emergence of person-centred discourse based around notions of 'personal development planning- and 'work'life balance' has taken hold in education and the workplace in recent years. This paper examines this discourse with regard to recent developments in higher education as well as the inter-related issue of work-life balance in occupational careers. In both cases there have been national and trans-national policy initiatives directed towards improving both personal opportunities and competitive advantage in a global knowledge-based economy. However, despite an increasing concern with looking outward at this globalised educational and employment marketplace, there is something of a paradox in encouraging people to look inward at themselves in order to become more self-determined. This apparent paradox is considered from a discourse analytic perspective in terms of the ideological effects of an increasing concern with the personal world. Specifically, it is argued that there are tensions that emerge from a concern with an innerdirected process of self-reflection that dissolve any engagement with wider political issues that impact upon educational and career development.

Keywords: Personal development planning, higher education, work-life balance, career.

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Authors: Fumito Yoshikawa, Takumi Kobayashi, Kenji Watanabe, Nobuyuki Otsu

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Extracting in-play scenes in sport videos is essential for quantitative analysis and effective video browsing of the sport activities. Game analysis of badminton as of the other racket sports requires detecting the start and end of each rally period in an automated manner. This paper describes an automatic serve scene detection method employing cubic higher-order local auto-correlation (CHLAC) and multiple regression analysis (MRA). CHLAC can extract features of postures and motions of multiple persons without segmenting and tracking each person by virtue of shift-invariance and additivity, and necessitate no prior knowledge. Then, the specific scenes, such as serve, are detected by linear regression (MRA) from the CHLAC features. To demonstrate the effectiveness of our method, the experiment was conducted on video sequences of five badminton matches captured by a single ceiling camera. The averaged precision and recall rates for the serve scene detection were 95.1% and 96.3%, respectively.

Keywords: Badminton, CHLAC, MRA, Video-based motiondetection

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Authors: M.G.A. Nassef, Linghan Li, C. Schenck, B. Kuhfuss

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Design and modeling of nonlinear systems require the knowledge of all inside acting parameters and effects. An empirical alternative is to identify the system-s transfer function from input and output data as a black box model. This paper presents a procedure using least squares algorithm for the identification of a feed drive system coefficients in time domain using a reduced model based on windowed input and output data. The command and response of the axis are first measured in the first 4 ms, and then least squares are applied to predict the transfer function coefficients for this displacement segment. From the identified coefficients, the next command response segments are estimated. The obtained results reveal a considerable potential of least squares method to identify the system-s time-based coefficients and predict accurately the command response as compared to measurements.

Keywords: feed drive systems, least squares algorithm, onlineparameter identification, short time window

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Authors: Veruska C. Dutra, Mary L. G. S. Senna, Felipe S. Spindler

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The State Park Jalapão - PEJ proved to be one of the protected areas that has attracted tourists from all over the world with its unique scenic landscapes. Although the region already has a considerable tourist flow, to our knowledge there is a lack of continuity of studies in the region capable of drawing a plan of activities, such as the profile of the tourist and analysis of their experiences in the region, carried out from 2006-2007. Therefore, this study was proposed to know the profile and experiences of tourists visiting the park today, making a connection with the earlier study, in order to generate subsidies to trace improvement actions. We conducted interviews with tourists in the main tourism season 2015. The results show that after eight years of carrying out the first study, there were no changes, highlighting the lack of a tourism plan for the park.

Keywords: Jalapão, profile tourist, level of satisfaction.

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Authors: Hamza A. Ali, Waleed A. J. Rasheed

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The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

Keywords: Classification, Recognition, Neural Networks, Pattern Recognition, Generalization.

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Authors: Sunil Gupta, Harsh Kumar Verma, AL Sangal

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Wireless sensor networks can be used to measure and monitor many challenging problems and typically involve in monitoring, tracking and controlling areas such as battlefield monitoring, object tracking, habitat monitoring and home sentry systems. However, wireless sensor networks pose unique security challenges including forgery of sensor data, eavesdropping, denial of service attacks, and the physical compromise of sensor nodes. Node in a sensor networks may be vanished due to power exhaustion or malicious attacks. To expand the life span of the sensor network, a new node deployment is needed. In military scenarios, intruder may directly organize malicious nodes or manipulate existing nodes to set up malicious new nodes through many kinds of attacks. To avoid malicious nodes from joining the sensor network, a security is required in the design of sensor network protocols. In this paper, we proposed a security framework to provide a complete security solution against the known attacks in wireless sensor networks. Our framework accomplishes node authentication for new nodes with recognition of a malicious node. When deployed as a framework, a high degree of security is reachable compared with the conventional sensor network security solutions. A proposed framework can protect against most of the notorious attacks in sensor networks, and attain better computation and communication performance. This is different from conventional authentication methods based on the node identity. It includes identity of nodes and the node security time stamp into the authentication procedure. Hence security protocols not only see the identity of each node but also distinguish between new nodes and old nodes.

Keywords: Authentication, Key management, Wireless Sensornetwork, Elliptic curve cryptography (ECC).

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Authors: Jana Doležalová, Josef Holík, Zdeněk Wimmer, Sándor T. Forczek

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Chlorine is one of the most abundant elements in nature, which undergoes a complex biogeochemical cycle. Chlorine bound in some substances is partly responsible for atmospheric ozone depletion and contamination of some ecosystems. As due to international regulations anthropogenic burden of volatile organochlorines (VOCls) in atmosphere decreases, natural sources (plants, soil, abiotic formation) are expected to dominate VOCl production in the near future. Examples of plant VOCl production are methyl chloride, and bromide emission from (sub)tropical ferns, chloroform, 1,1,1-trichloroethane and tetrachloromethane emission from temperate forest fern and moss. Temperate forests are found to emit in addition to the previous compounds tetrachloroethene, and brominated volatile compounds. VOCls can be taken up and further metabolized in plants. The aim of this work is to identify and quantitatively analyze the formed VOCls in temperate forest ecosystems by a cryofocusing/GC-ECD detection method, hence filling a gap of knowledge in the biogeochemical cycle of chlorine.

Keywords: chloroform, cryofocusing-GC-ECD, ozonedepletion, volatile organochlorines

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Authors: Chinmay Soman, Hrishikesh Pathak, Vishal Shah, Aniket Padhye, Amey Inamdar

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Phishing, or stealing of sensitive information on the web, has dealt a major blow to Internet Security in recent times. Most of the existing anti-phishing solutions fail to handle the fuzziness involved in phish detection, thus leading to a large number of false positives. This fuzziness is attributed to the use of highly flexible and at the same time, highly ambiguous HTML language. We introduce a new perspective against phishing, that tries to systematically prove, whether a given page is phished or not, using the corresponding original page as the basis of the comparison. It analyzes the layout of the pages under consideration to determine the percentage distortion between them, indicative of any form of malicious alteration. The system design represents an intelligent system, employing dynamic assessment which accurately identifies brand new phishing attacks and will prove effective in reducing the number of false positives. This framework could potentially be used as a knowledge base, in educating the internet users against phishing.

Keywords: World Wide Web, Phishing, Internet security, data mining.

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Authors: S. Grouni, R. Ibtiouen, M. Kidouche, O. Touhami

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Induction machine models used for steady-state and transient analysis require machine parameters that are usually considered design parameters or data. The knowledge of induction machine parameters is very important for Indirect Field Oriented Control (IFOC). A mismatched set of parameters will degrade the response of speed and torque control. This paper presents an improvement approach on rotor time constant adaptation in IFOC for Induction Machines (IM). Our approach tends to improve the estimation accuracy of the fundamental model for flux estimation. Based on the reduced order of the IM model, the rotor fluxes and rotor time constant are estimated using only the stator currents and voltages. This reduced order model offers many advantages for real time identification parameters of the IM.

Keywords: Indirect Field Oriented Control (IFOC), InductionMachine (IM), Rotor Time Constant, Parameters ApproachAdaptation. Optimum rotor flux.

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Authors: Aline Alves Bandeira, Luís Pedro Lima, Maria Cecília de Paula Silva, Paulo Henrique de Viveiros Tavares

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Nowadays, the study of public policies regarding management efficiency is essential. Public policies are about what governments do or do not do, being an area that has grown worldwide, contributing through the knowledge of technologies and methodologies that monitor and evaluate the performance of public administrators. The information published on official government websites needs to provide for transparency and responsiveness of managers. Thus, transparency is a primordial factor for the execution of accountability, providing, in this way, services to the citizen with the expansion of transparent, efficient, democratic information and that value administrative eco-efficiency. The ecologically balanced management of a Smart City must optimize environmental education, building a fairer society, which brings about equality in the use of quality environmental resources. Smart Cities add value in the construction of public management, enabling interaction between people, enhancing environmental education and the practical applicability of administrative eco-efficiency, fostering economic development and improving the quality of life.

Keywords: Accountability, environmental education, new public administration, smart cities.

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Authors: D.Venkatesan, K.Kannan, S. Raja Balachandar

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In this paper a new Genetic Algorithm based on a heuristic operator and Centre of Mass selection operator (CMGA) is designed for the unbounded knapsack problem(UKP), which is NP-Hard combinatorial optimization problem. The proposed genetic algorithm is based on a heuristic operator, which utilizes problem specific knowledge. This center of mass operator when combined with other Genetic Operators forms a competitive algorithm to the existing ones. Computational results show that the proposed algorithm is capable of obtaining high quality solutions for problems of standard randomly generated knapsack instances. Comparative study of CMGA with simple GA in terms of results for unbounded knapsack instances of size up to 200 show the superiority of CMGA. Thus CMGA is an efficient tool of solving UKP and this algorithm is competitive with other Genetic Algorithms also.

Keywords: Genetic Algorithm, Unbounded Knapsack Problem, Combinatorial Optimization, Meta-Heuristic, Center of Mass

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Authors: M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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The use of anatomical landmarks as a basis for image to patient registration is appealing because the registration may be performed retrospectively. We have previously proposed the use of two anatomical soft tissue landmarks of the head, the canthus (corner of the eye) and the tragus (a small, pointed, cartilaginous flap of the ear), as a registration basis for an automated CT image to patient registration system, and described their localization in patient space using close range photogrammetry. In this paper, the automatic localization of these landmarks in CT images, based on their curvature saliency and using a rule based system that incorporates prior knowledge of their characteristics, is described. Existing approaches to landmark localization in CT images are predominantly semi-automatic and primarily for localizing internal landmarks. To validate our approach, the positions of the landmarks localized automatically and manually in near isotropic CT images of 102 patients were compared. The average difference was 1.2mm (std = 0.9mm, max = 4.5mm) for the medial canthus and 0.8mm (std = 0.6mm, max = 2.6mm) for the tragus. The medial canthus and tragus can be automatically localized in CT images, with performance comparable to manual localization, based on the approach presented.

Keywords: Anatomical Landmarks, CT, Localization.

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Authors: W. A. D. P. Wanigasundera, P. C. B. Alahakoon

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Kandy district in Sri Lanka, has small scale and rain-fed paddy farming, and highly vulnerable to climate change. In this study, the status of climate change was assessed using meteorological data and compared with the perceptions of paddy farming community. Factors affecting the adaptation to the climate smart farming were also assessed.

 Meteorological data for 33 years were collected and the changes over time compared with the perceptions of farmers. The temperature, rainfall and number of rainy days have increased in both locations. The onset of rains also has shifted. The perceptions of the majority of the farmers were in line with the actual changes. The knowledge and attitudes about the causes of climate change and adaptation were medium and related to level of adoption. Formulating effective communication strategies, and a collaborative approach involving state, private sector, civil society to make Sri Lankan agriculture ‘climate-smart’ is urgently needed.

Keywords: Adaptation of climate-smart technology, climate change, perception, rain-fed paddy.

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Authors: Mahmoud Saeidi, Khadijeh Saeidi, Mahmoud Khaleghi

Abstract:

In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership functions. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.

Keywords: Image Sequences, Noise Reduction, fuzzy algorithm, triangular membership function

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Authors: Miroslav Popelka, Jakub Nožička

Abstract:

The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, Real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software.

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