Search results for: climate adaptive Building Shells (CABS).

Authors: María L. Jalón, Feargal Brennan

Abstract:

A non-stationary stochastic optimization methodology is applied to an OWC (oscillating water column) to find the design that maximizes the wave energy extraction. Different temporal cycles are considered to represent the long-term variability of the wave climate at the site in the optimization problem. The results of the non-stationary stochastic optimization problem are compared against those obtained by a stationary stochastic optimization problem. The comparative analysis reveals that the proposed non-stationary optimization provides designs with a better fit to reality. However, the stationarity assumption can be adequate when looking at averaged system response.

Keywords: Non-stationary stochastic optimization, oscillating water column, temporal variability, wave energy.

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Authors: Eugene Allevato

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Developing a responsible personal worldview is central to sustainable development, but achieving quality education to promote transformative learning for sustainability is thus far, poorly understood. Most programs involving education for sustainable development rely on changing behavior, rather than attitudes. The emphasis is on the scientific and utilitarian aspect of sustainability with negligible importance on the intrinsic value of nature. Campus sustainability projects include building sustainable gardens and implementing energy-efficient upgrades, instead of focusing on educating for sustainable development through exploration of students’ values and beliefs. Even though green technology adoption maybe the right thing to do, most schools are not targeting the root cause of the environmental crisis; they are just providing palliative measures. This study explores the under-examined factors that lead to pro-environmental behavior by investigating the environmental perceptions of both college business students and personnel of green organizations. A mixed research approach of qualitative, based on structured interviews, and quantitative instruments was developed including 30 college-level students’ interviews and 40 green organization staff members involved in sustainable activities. The interviews were tape-recorded and transcribed for analysis. Categorization of the responses to the open‐ended questions was conducted with the purpose of identifying the main types of factors influencing attitudes and correlating with behaviors. Overall the findings of this study indicated a lack of appreciation for nature, and inability to understand interconnectedness and apply critical thinking. The results of the survey conducted on undergraduate students indicated that the responses of business and liberal arts students by independent t-test were significantly different, with a p‐value of 0.03. While liberal arts students showed an understanding of human interdependence with nature and its delicate balance, business students seemed to believe that humans were meant to rule over the rest of nature. This result was quite intriguing from the perspective that business students will be defining markets, influencing society, controlling and managing businesses that supposedly, in the face of climate change, shall implement sustainable activities. These alarming results led to the focus on green businesses in order to better understand their motivation to engage in sustainable activities. Additionally, a probit model revealed that childhood exposure to nature has a significantly positive impact in pro-environmental attitudes to most of the New Ecological Paradigm scales. Based on these findings, this paper discusses educators including Socrates, John Dewey and Paulo Freire in the implementation of eco-pedagogy and transformative learning following a curriculum with emphasis on critical and systems thinking, which are deemed to be key ingredients in quality education for sustainable development.

Keywords: Eco-pedagogy, environmental behavior, quality education for sustainable development, transformative learning.

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Authors: Hsu-Yung Cheng, Victor Gau, Chih-Wei Huang, Jenq-Neng Hwang, Chih-Chang Yu

Abstract:

In order to achieve better road utilization and traffic efficiency, there is an urgent need for a travel information delivery mechanism to assist the drivers in making better decisions in the emerging intelligent transportation system applications. In this paper, we propose a relayed multicast scheme under heterogeneous networks for this purpose. In the proposed system, travel information consisting of summarized traffic conditions, important events, real-time traffic videos, and local information service contents is formed into layers and multicasted through an integration of WiMAX infrastructure and Vehicular Ad hoc Networks (VANET). By the support of adaptive modulation and coding in WiMAX, the radio resources can be optimally allocated when performing multicast so as to dynamically adjust the number of data layers received by the users. In addition to multicast supported by WiMAX, a knowledge propagation and information relay scheme by VANET is designed. The experimental results validate the feasibility and effectiveness of the proposed scheme.

Keywords: Intelligent Transportation Systems, RelayedMulticast, WiMAX, Vehicular Ad hoc Networks (VANET).

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Authors: Mohammad Jafarifar

Abstract:

This paper presents a speed estimation scheme based on second-order sliding-mode Super Twisting Algorithm (STA) and Model Reference Adaptive System (MRAS) estimation theory for Sensorless control of multiphase induction machine. A stator current observer is designed based on the STA, which is utilized to take the place of the reference voltage model of the standard MRAS algorithm. The observer is insensitive to the variation of rotor resistance and magnetizing inductance when the states arrive at the sliding mode. Derivatives of rotor flux are obtained and designed as the state of MRAS, thus eliminating the integration. Compared with the first-order sliding-mode speed estimator, the proposed scheme makes full use of the auxiliary sliding-mode surface, thus alleviating the chattering behavior without increasing the complexity. Simulation results show the robustness and effectiveness of the proposed scheme.

Keywords: Multiphase induction machine, field oriented control, sliding mode, super twisting algorithm, MRAS algorithm.

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya

Abstract:

In the present world, predicting rainfall is considered to be an essential and also a challenging task. Normally, the climate and rainfall are presumed to have non-linear as well as intricate phenomena. For predicting accurate rainfall, we necessitate advanced computer modeling and simulation. When there is an enhanced understanding of the spatial and temporal distribution of precipitation then it becomes enrichment to applications such as hydrologic, climatic and ecological. Conversely, there may be some kind of challenges occur in the community due to some application which results in the absence of consistent precipitation observation in remote and also emerging region. This survey paper provides a multifarious collection of methodologies which are epitomized by various researchers for predicting the rainfall. It also gives information about some technique to forecast rainfall, which is appropriate to all methods like numerical, traditional and statistical.

Keywords: Satellite Image, Segmentation, Feature Extraction, Classification, Clustering, Precipitation Estimation.

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Authors: Peerapong Uthansakul, Sakkarin Chaokuntod, Monthippa Uthansakul

Abstract:

In literatures, many researches proposed various methods to reduce PAPR (Peak to Average Power Ratio). Among those, DSI (Dummy Sequence Insertion) is one of the most attractive methods for WiMAX systems because it does not require side information transmitted along with user data. However, the conventional DSI methods find dummy sequence by performing an iterative procedure until achieving PAPR under a desired threshold. This causes a significant delay on finding dummy sequence and also effects to the overall performances in WiMAX systems. In this paper, the new method based on DSI is proposed by finding dummy sequence without the need of iterative procedure. The fast DSI method can reduce PAPR without either delays or required side information. The simulation results confirm that the proposed method is able to carry out PAPR performances as similar to the other methods without any delays. In addition, the simulations of WiMAX system with adaptive modulations are also investigated to realize the use of proposed methods on various fading schemes. The results suggest the WiMAX designers to modify a new Signal to Noise Ratio (SNR) criteria for adaptation.

Keywords: WiMAX, OFDM, PAPR, Dummy SequenceInsertion method.

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Authors: S. Shanthi, V. Muralibhaskaran

Abstract:

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: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

Abstract:

This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

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Authors: Bozena Dohnalkova, Jakub Hodul, Rostislav Drochytka, Jana Kosikova

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This paper deals with a proposal of a new methodology for durability assessment of solidification product for its safe further use. The new methodology is based on a review of the current state of assessment of treated waste in Czech Republic and abroad. The aim of the paper is to propose an optimal evaluation methodology for verifying properties of solidification product to ensure its safe further use in building industry.

Keywords: Solidification/stabilization, durability, waste.

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Authors: Thejaswi H. Raya, Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

For over a decade, the Pulse Coupled Neural Network (PCNN) based algorithms have been successfully used in image interpretation applications including image segmentation. There are several versions of the PCNN based image segmentation methods, and the segmentation accuracy of all of them is very sensitive to the values of the network parameters. Most methods treat PCNN parameters like linking coefficient and primary firing threshold as global parameters, and determine them by trial-and-error. The automatic determination of appropriate values for linking coefficient, and primary firing threshold is a challenging problem and deserves further research. This paper presents a method for obtaining global as well as local values for the linking coefficient and the primary firing threshold for neurons directly from the image statistics. Extensive simulation results show that the proposed approach achieves excellent segmentation accuracy comparable to the best accuracy obtainable by trial-and-error for a variety of images.

Keywords: Automatic Selection of PCNN Parameters, Image Segmentation, Neural Networks, Pulse Coupled Neural Network

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Authors: Laura Álvarez Antón, Joaquín Díaz

Abstract:

The construction industry is turning towards sustainability. It is a well-known fact that sustainability is based on a balance between environmental, social and economic aspects. In order to achieve sustainability efficiently, these three criteria should be taken into account in the initial project phases, since that is when a project can be influenced most effectively. Thus the aim must be to integrate important tools like BIM and LCA at an early stage in order to make full use of their potential. With the synergies resulting from the integration of BIM and LCA, a wider approach to sustainability becomes possible, covering the three pillars of sustainability.

Keywords: Building Information Modeling (BIM), Construction Industry, Design Phase, Life Cycle Assessment (LCA), Sustainability.

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Authors: Pham Thanh Trung, Huynh Quyet Thang

Abstract:

Reliability is one of the most important quality attributes of software. Based on the approach of Reussner and the approach of Cheung, we proposed the reliability prediction model of component-based software architectures. Also, the value of the model is shown through the experimental evaluation on a web server system.

Keywords: component-based architecture, reliability prediction model, software reliability engineering.

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Authors: J. P. Dubois, P. G. Jreije

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In this paper, a framework is presented trying to make the most secure web system out of the available generic and web security technology which can be used as a guideline for organizations building their web sites. The framework is designed to provide necessary security services, to address the known security threats, and to provide some cover to other security problems especially unknown threats. The requirements for the design are discussed which guided us to the design of secure web system. The designed security framework is then simulated and various quality of service (QoS) metrics are calculated to measure the performance of this system.

Keywords: Web Security, Internet Voting, Firewall, QoS, Latency, Utilization, Throughput.

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Authors: K. Krizova, R. Hela

Abstract:

The paper is focused on monitoring of dependencies of different composition concretes on elastic modulus values. To obtain a summary of elastic modulus development in dependence of concrete composition design variability was the objective of the experiment. Essential part of this work was initiated as a reaction to building practice when questions of elastic moduli arose at the same time and which mostly did not obtain the required and expected values from concrete constructions.

Keywords: Concrete, Compressive strength, Modulus of elasticity, EuroCode 2.

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Authors: Timothee G. Leleu

Abstract:

A new technique of topological multi-scale analysis is introduced. By performing a clustering recursively to build a hierarchy, and analyzing the co-scale and intra-scale similarities, an Iterated Function System can be extracted from any data set. The study of fractals shows that this method is efficient to extract self-similarities, and can find elegant solutions the inverse problem of building fractals. The theoretical aspects and practical implementations are discussed, together with examples of analyses of simple fractals.

Keywords: hierarchical clustering, multi-scale analysis, Similarity hashing.

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Authors: A.Venkadesan, S.Himavathi, A.Muthuramalingam

Abstract:

Rotor Flux based Model Reference Adaptive System (RF-MRAS) is the most popularly used conventional speed estimation scheme for sensor-less IM drives. In this scheme, the voltage model equations are used for the reference model. This encounters major drawbacks at low frequencies/speed which leads to the poor performance of RF-MRAS. Replacing the reference model using Neural Network (NN) based flux estimator provides an alternate solution and addresses such drawbacks. This paper identifies an NN based flux estimator using Single Neuron Cascaded (SNC) Architecture. The proposed SNC-NN model replaces the conventional voltage model in RF-MRAS to form a novel MRAS scheme named as SNC-NN-MRAS. Through simulation the proposed SNC-NN-MRAS is shown to be promising in terms of all major issues and robustness to parameter variation. The suitability of the proposed SNC-NN-MRAS based speed estimator and its advantages over RF-MRAS for sensor-less induction motor drives is comprehensively presented through extensive simulations.

Keywords: Sensor-less operation, vector-controlled IM drives, SNC-NN-MRAS, single neuron cascaded architecture, RF-MRAS, artificial neural network

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Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

Abstract:

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

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Authors: Ángel de J. López-Pérez, Sonia E. Ruiz, Vanessa A. Segovia

Abstract:

Buildings vulnerability due to seismic activity has been highly studied since the middle of last century. As a solution to the structural and non-structural damage caused by intense ground motions, several seismic energy dissipating devices, such as buckling-restrained braces (BRB), have been proposed. BRB have shown to be effective in concentrating a large portion of the energy transmitted to the structure by the seismic ground motion. A design approach for buildings with BRB elements, which is based on a seismic Displacement-Based formulation, has recently been proposed by the coauthors in this paper. It is a practical and easy design method which simplifies the work of structural engineers. The method is used here for the design of the structure-BRB damper system. The objective of the present study is to extend and apply a methodology to find the best combination of design parameters on multiple-degree-of-freedom (MDOF) structural frame – BRB systems, taking into account simultaneously: 1) initial costs and 2) an adequate engineering demand parameter. The design parameters considered here are: the stiffness ratio (α = K_frame/K_total), and the strength ratio (γ = V_damper/V_total); where K represents structural stiffness and V structural strength; and the subscripts "frame", "damper" and "total" represent: the structure without dampers, the BRB dampers and the total frame-damper system, respectively. The selection of the best combination of design parameters α and γ is based on an initial costs analysis and on the structural dynamic response of the structural frame-damper system. The methodology is applied to a 12-story 5-bay steel building with BRB, which is located on the intermediate soil of Mexico City. It is found the best combination of design parameters α and γ for the building with BRB under study.

Keywords: Best combination of design parameters, BRB, buildings with energy dissipating devices, buckling-restrained braces, initial costs.

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Authors: S. K. Satpathy, S. Panda, K. K. Nagwanshi, S. K. Nayak, C. Ardil

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Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.

Keywords: Filtering, Decision Based Algorithm, noise, imagerestoration.

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Authors: Z. Pavlík, J. Kočí, M. Pavlíková, R. Černý

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Combined experimental and computational analysis of hygrothermal performance of an interior thermal insulation system applied on a brick wall is presented in the paper. In the experimental part, the functionality of the insulation system is tested at simulated difference climate conditions using a semi-scale device. The measured temperature and relative humidity profiles are used for the calibration of computer code HEMOT that is finally applied for a long-term hygrothermal analysis of the investigated structure.

Keywords: Additional thermal insulation, hygrothermal analysis, semi-scale testing, long-term computational analysis

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Authors: Erica Cochran Hameen, Bobuchi Ken-Opurum, Shalini Priyadarshini, Berangere Lartigue, Sadhana Anath-Pisipati

Abstract:

School districts throughout the United States are constantly seeking measures to improve test scores, reduce school absenteeism and improve indoor environmental quality. It is imperative to identify key building investments which will provide the largest benefits to schools in terms of improving the aforementioned factors. This study uses Analysis of Variance (ANOVA) tests to statistically evaluate the impact of a school building’s mechanical and plumbing characteristics on a child’s educational performance. The educational performance is measured via three indicators, i.e. test scores, suspensions, and absenteeism. The study investigated 125 New York City school facilities to determine the potential correlations between 50 mechanical and plumbing variables and the performance indicators. Key findings from the tests revealed that elementary schools with pneumatic systems in “good” condition have 48.8% lower percentages of students scoring at the minimum English Language Arts (ELA) competency level compared with those with no pneumatic system. Additionally, elementary schools with “unit heaters/cabinet heaters” in “good to fair” conditions have 1.1% higher attendance rates compared to schools with no “unit heaters/cabinet heaters” or those in inferior condition. Furthermore, elementary schools with air conditioning have 0.6% higher attendance rates compared to schools with no air conditioning, and those with interior floor drains in “good” condition have 1.8% higher attendance rates compared to schools with interior drains in inferior condition.

Keywords: Academic attendance and performance, mechanical and plumbing systems, schools, student health.

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Authors: Jong Han Joo, Jeong Hun Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. However, the effects of echo path changes should be considered for eliminating the undesired echoes. We describe a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: Acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector.

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Authors: M. Elkhoury

Abstract:

A recently developed one-equation turbulence model has been successfully applied to simulate turbulent flows with various complexities. The model, which is based on the transformation of the k-ε closure, is wall-distance free and equipped with lagging destruction/dissipation terms. Test cases included shockboundary- layer interaction flows over the NACA 0012 airfoil, an axisymmetric bump, and the ONERA M6 wing. The capability of the model to operate in a Scale Resolved Simulation (SRS) mode is demonstrated through the simulation of a massive flow separation over a circular cylinder at Re= 1.2 x106. An assessment of the results against available experiments Menter (k-ε)1Eq and the Spalart- Allmaras model that belongs to the single equation closure family is made.

Keywords: Turbulence modeling, complex flow simulation, scale adaptive simulation, one-equation turbulence model.

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

Abstract:

Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: Computing methodologies, interest point, salient region detections, image segmentation.

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Authors: Usman Ghani

Abstract:

Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: Simulation, feedback, training, hands-on, labs.

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Authors: Peter Podbreznik, Božidar Potocnik

Abstract:

A camera in the building site is exposed to different weather conditions. Differences between images of the same scene captured with the same camera arise also due to temperature variations. The influence of temperature changes on camera parameters were modelled and integrated into existing analytical camera model. Modified camera model enables quantitatively assessing the influence of temperature variations.

Keywords: camera calibration, analytical model, intrinsic parameters, extrinsic parameters, temperature variations.

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Authors: S. H. R. Sadeghi, A. Sadoddin, A. Najafinejad

Abstract:

Expansionism and ever-increasing population menace all different resources worldwide. The issue, hence, is critical in developing countries like Iran where new technologies are rapidly luxuriated and unguardedly applied, resulting in unexpected outcomes. However, uncommon and comprehensive approaches are introduced to take all the different aspects involved into consideration. In the last decade, few approaches such as community-based, stakeholders-oriented, adaptive and ultimately integrated management, have emerged and are developing for efficient, Co-management or best management, economic and sustainable development and management of watershed resources in Iran. In the present paper, an attempt has been made to focus on state-of-the-art approaches for the management of watershed resources applied in Iran. The study has been then supported by reports of some case studies conducted throughout the country involving previously mentioned approaches. Scrutinizing results of the researches verified a progressive tendency of the managerial approaches in watershed management strategies leading to a general approaching balance situation. The approaches are firmly rooted in educational, research, executive, legal and policy-making sectors leading to some recuperation at different levels. However, there is a long way ahead to naturalize detrimental effects of unscientific, illegal and over exploitation of the watershed resources in Iran.

Keywords: Comprehensive management, ecosystem balance, integrated watershed management, land resources optimization.

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Authors: Hermenegilde Nkurunziza, Albrecht Gebhardt, Juergen Pilz

Abstract:

The focus in this work is to assess which method allows a better forecasting of malaria cases in Bujumbura ( Burundi) when taking into account association between climatic factors and the disease. For the period 1996-2007, real monthly data on both malaria epidemiology and climate in Bujumbura are described and analyzed. We propose a hierarchical approach to achieve our objective. We first fit a Generalized Additive Model to malaria cases to obtain an accurate predictor, which is then used to predict future observations. Various well-known forecasting methods are compared leading to different results. Based on in-sample mean average percentage error (MAPE), the multiplicative exponential smoothing state space model with multiplicative error and seasonality performed better.

Keywords: Burundi, Forecasting, Malaria, Regressionmodel, State space model.

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Authors: Y. J. Huang, J. D. Yu, B. W. Hong, C. H. Tai, T. C. Kuo

Abstract:

In this paper, a multi-agent robot system is presented. The system consists of four robots. The developed robots are able to automatically enter and patrol a harmful environment, such as the building infected with virus or the factory with leaking hazardous gas. Further, every robot is able to perform obstacle avoidance and search for the victims. Several operation modes are designed: remote control, obstacle avoidance, automatic searching, and so on.

Keywords: autonomous robot, field programmable gate array, obstacle avoidance, ultrasonic sensor, wireless communication.

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