Search results for: Imperfect channel state information

Authors: Viktória Sugár, Orsolya Frick, Gabriella Horváth, A. Bendegúz Vöröss, Péter Leczovics, Géza Baráth

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Urban greenery has multiple positive effects both on the city and its residents. Apart from the visual advantages, it changes the micro-climate by cooling and shading, also increasing vapor and oxygen, reducing dust and carbon-dioxide content at the same time. The above are all critical factors of livability of an urban fabric. Unfortunately, in a dense, historical district there are restricted possibilities to build green surfaces. The present study collects and systemizes the applicable green solutions in the case of a historical downtown district of Budapest. The study contains a GIS-based measurement of the eligible surfaces for greenery, and also calculates the potential of oxygen production, carbon-dioxide reduction and cooling effect of an increased green surface.  It can be concluded that increasing the green surface has measurable effects on a densely built urban fabric, including air quality, micro-climate and other environmental factors.

Keywords: Urban greenery, green roof, green wall, green surface potential, sustainable city, oxygen production, carbon-dioxide reduction, geographical information system, GIS.

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Authors: A. U. Haque, W. Asrar, A. A. Omar, E. Sulaeman, J. S. Mohamed Ali

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Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angle of attack. As a part of the validation of low fidelity tool, plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficients, the overall trend has under predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: Wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics.

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: Generic knowledge representation, toolkit, toolroom, pervasive computing.

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Authors: R. Varalakshmi

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For the last decade, researchers have started to focus their interest on Multicast Group Key Management Framework. The central research challenge is secure and efficient group key distribution. The present paper is based on the Bit model based Secure Multicast Group key distribution scheme using the most popular absolute encoder output type code named Gray Code. The focus is of two folds. The first fold deals with the reduction of computation complexity which is achieved in our scheme by performing fewer multiplication operations during the key updating process. To optimize the number of multiplication operations, an O(1) time algorithm to multiply two N-bit binary numbers which could be used in an N x N bit-model of reconfigurable mesh is used in this proposed work. The second fold aims at reducing the amount of information stored in the Group Center and group members while performing the update operation in the key content. Comparative analysis to illustrate the performance of various key distribution schemes is shown in this paper and it has been observed that this proposed algorithm reduces the computation and storage complexity significantly. Our proposed algorithm is suitable for high performance computing environment.

Keywords: Multicast Group key distribution, Bit model, Integer Multiplications, reconfigurable mesh, optimal algorithm, Gray Code, Computation Complexity, Storage Complexity.

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Authors: Chang Hsueh-Sheng, Chen Tzu-Ling

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Earthquake is an unpredictable natural disaster and intensive earthquakes have caused serious impacts on social-economic system, environmental and social resilience. Conventional ways to mitigate earthquake disaster are to enhance building codes and advance structural engineering measures. However, earthquake-induced ground damage such as liquefaction, land subsidence, landslide happen on places nearby earthquake prone or poor soil condition areas. Therefore, this study uses spatial statistical analysis to explore the spatial pattern of damaged buildings. Afterwards, principle components analysis (PCA) is applied to categorize the similar features in different kinds of clustered patterns. The results show that serious landslide prone area, close to fault, vegetated ground surface and mudslide prone area are common in those highly damaged buildings. In addition, the oldest building might not be directly referred to the most vulnerable one. In fact, it seems that buildings built between 1974 and 1989 become more fragile during the earthquake. The incorporation of both spatial statistical analyses and PCA can provide more accurate information to subsidize retrofit programs to enhance earthquake resistance in particular areas.

Keywords: Earthquake disaster, spatial statistical analysis, principle components analysis, clustered patterns.

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Authors: Allaeddine Athmani, Abdelhacine Gouasmia, Tiago Ferreira, Romeu Vicente

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The seismic risk mitigation from the perspective of the old buildings stock is truly essential in Algerian urban areas, particularly those located in seismic prone regions, such as Annaba city, and which the old buildings present high levels of degradation associated with no seismic strengthening and/or rehabilitation concerns. In this sense, the present paper approaches the issue of the seismic vulnerability assessment of old masonry building stocks through the adaptation of a simplified methodology developed for a European context area similar to that of Annaba city, Algeria. Therefore, this method is used for the first level of seismic vulnerability assessment of the masonry buildings stock of the old city center of Annaba. This methodology is based on a vulnerability index that is suitable for the evaluation of damage and for the creation of large-scale loss scenarios. Over 380 buildings were evaluated in accordance with the referred methodology and the results obtained were then integrated into a Geographical Information System (GIS) tool. Such results can be used by the Annaba city council for supporting management decisions, based on a global view of the site under analysis, which led to more accurate and faster decisions for the risk mitigation strategies and rehabilitation plans.

Keywords: Damage scenarios, masonry buildings, old city center, seismic vulnerability, vulnerability index.

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Authors: Ye Wei, Sitalakshmi Venkatraman, Fahri Benli, Fiona Wahr

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The present digital world poses many challenges to various stakeholders in the education sector. In particular, lecturers of higher education (HE) are faced with the problem of ensuring that students are able to achieve the required learning outcomes despite rapid changes taking place worldwide. Different strategies are adopted to retain student engagement and commitment in classrooms to address the differences in learning habits, preferences and styles of the digital generation of students recently. Further, with the onset of coronavirus disease (COVID-19) pandemic, online classroom has become the most suitable alternate mode of teaching environment to cope with lockdown restrictions. These changes have compounded the problems in the learning engagement and short attention span of HE students. New Agile methodologies that have been successfully employed to manage projects in different fields are gaining prominence in the education domain. In this paper, we present the application of Scrum as an agile methodology to enhance student learning and engagement in an online smart classroom environment. We demonstrate the use of our proposed approach using a case study to teach key topics in information technology that require students to gain technical and business-related data analytics skills.

Keywords: Agile methodology, Scrum, online learning, smart classroom environment, student engagement, active learning.

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Authors: Meng-Lung Lin, Chien-Min Chu, Chung-Hung Tsai, Chih-Cheng Chen, Chen-Yuan Chen

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The study of tourist activities and the mapping of their routes in space and time has become an important issue in tourism management. Here we represent space-time paths for the tourism industry by visualizing individual tourist activities and the paths followed using a 3D Geographic Information System (GIS). Considerable attention has been devoted to the measurement of accessibility to shopping, eating, walking and other services at the tourist destination. I turns out that GIS is a useful tool for studying the spatial behaviors of tourists in the area. The value of GIS is especially advantageous for space-time potential path area measures, especially for the accurate visualization of possible paths through existing city road networks. This study seeks to apply space-time concepts with a detailed street network map obtained from Google Maps to measure tourist paths both spatially and temporally. These paths are further determined based on data obtained from map questionnaires regarding the trip activities of 40 individuals. The analysis of the data makes it possible to determining the locations of the more popular paths. The results can be visualized using 3D GIS to show the areas and potential activity opportunities accessible to tourists during their travel time.

Keywords: Tourist activity analysis, space-time path, GIS, geovisualization, activity-travel pattern.

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Authors: Yanwei Pang, Lei Zhang, Zhengkai Liu

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Studies in neuroscience suggest that both global and local feature information are crucial for perception and recognition of faces. It is widely believed that local feature is less sensitive to variations caused by illumination, expression and illumination. In this paper, we target at designing and learning local features for face recognition. We designed three types of local features. They are semi-global feature, local patch feature and tangent shape feature. The designing of semi-global feature aims at taking advantage of global-like feature and meanwhile avoiding suppressing AdaBoost algorithm in boosting weak classifies established from small local patches. The designing of local patch feature targets at automatically selecting discriminative features, and is thus different with traditional ways, in which local patches are usually selected manually to cover the salient facial components. Also, shape feature is considered in this paper for frontal view face recognition. These features are selected and combined under the framework of boosting algorithm and cascade structure. The experimental results demonstrate that the proposed approach outperforms the standard eigenface method and Bayesian method. Moreover, the selected local features and observations in the experiments are enlightening to researches in local feature design in face recognition.

Keywords: Face recognition, local feature, AdaBoost, subspace analysis.

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Authors: D. I. De Souza, G. P. Azevedo, R. Rocha

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In this paper we will develop a sequential life test approach applied to a modified low alloy-high strength steel part used in highway overpasses in Brazil.We will consider two possible underlying sampling distributions: the Normal and theInverse Weibull models. The minimum life will be considered equal to zero. We will use the two underlying models to analyze a fatigue life test situation, comparing the results obtained from both.Since a major chemical component of this low alloy-high strength steel part has been changed, there is little information available about the possible values that the parameters of the corresponding Normal and Inverse Weibull underlying sampling distributions could have. To estimate the shape and the scale parameters of these two sampling models we will use a maximum likelihood approach for censored failure data. We will also develop a truncation mechanism for the Inverse Weibull and Normal models. We will provide rules to truncate a sequential life testing situation making one of the two possible decisions at the moment of truncation; that is, accept or reject the null hypothesis H0. An example will develop the proposed truncated sequential life testing approach for the Inverse Weibull and Normal models.

Keywords: Sequential life testing, normal and inverse Weibull models, maximum likelihood approach, truncation mechanism.

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Authors: Mustafa Bayram Gücen, Coşkun Yakar

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In this study, we have investigated the strict stability of fuzzy differential systems and we compare the classical notion of strict stability criteria of ordinary differential equations and the notion of strict stability of fuzzy differential systems. In addition that, we present definitions of stability and strict stability of fuzzy differential equations and also we have some theorems and comparison results. Strict Stability is a different stability definition and this stability type can give us an information about the rate of decay of the solutions. Lyapunov’s second method is a standard technique used in the study of the qualitative behavior of fuzzy differential systems along with a comparison result that allows the prediction of behavior of a fuzzy differential system when the behavior of the null solution of a fuzzy comparison system is known. This method is a usefull for investigating strict stability of fuzzy systems. First of all, we present definitions and necessary background material. Secondly, we discuss and compare the differences between the classical notion of stability and the recent notion of strict stability. And then, we have a comparison result in which the stability properties of the null solution of the comparison system imply the corresponding stability properties of the fuzzy differential system. Consequently, we give the strict stability results and a comparison theorem. We have used Lyapunov second method and we have proved a comparison result with scalar differential equations.

Keywords: Fuzzy systems, fuzzy differential equations, fuzzy stability, strict stability.

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Authors: Alireza Osareh, Bita Shadgar

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Segmenting the lungs in medical images is a challenging and important task for many applications. In particular, automatic segmentation of lung cavities from multiple magnetic resonance (MR) images is very useful for oncological applications such as radiotherapy treatment planning. However, distinguishing of the lung areas is not trivial due to largely changing lung shapes, low contrast and poorly defined boundaries. In this paper, we address lung segmentation problem from pulmonary magnetic resonance images and propose an automated method based on a robust regionaided geometric snake with a modified diffused region force into the standard geometric model definition. The extra region force gives the snake a global complementary view of the lung boundary information within the image which along with the local gradient flow, helps detect fuzzy boundaries. The proposed method has been successful in segmenting the lungs in every slice of 30 magnetic resonance images with 80 consecutive slices in each image. We present results by comparing our automatic method to manually segmented lung cavities provided by an expert radiologist and with those of previous works, showing encouraging results and high robustness of our approach.

Keywords: Active contours, breast cancer, fuzzy c-means segmentation, treatment planning.

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Authors: Mokgadi Moletsane-Kekae, Robert Kananga Mukuna

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The study focused on the analysis of the Adjusted Rorschach Comprehensive System’s responses. The objective of this study is to analyse the participants’ response rate of the Adjusted Rorschach Comprehensive System with regards to critical psychology approach. The use of critical psychology theory in this study was crucial because it responds to the current inadequate western theory or practice in the field of psychology. The study adopted a qualitative approach and a case study design. The study was grounded on interpretivist paradigm. The sample size comprised six learners (three boys and three girls, aged of 14 years) from historically disadvantaged school in the Western Cape, South Africa. The Adjusted Rorschach Comprehensive System (ARCS) administration procedure, biographical information, semi-structured interviews, and observation were used to collect data. Data was analysed using thematic framework. The study found out that, factors that increased the response rates during the administration of ARCS were, language, seating arrangement, drawing, viewing, and describing. The study recommended that, psychological test designers take into consideration the philosophy or worldviews of the local people for whom the test is designed to minimize low response rates.

Keywords: Adjusted Rorschach comprehensive system, critical psychology, learners, responses.

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Authors: A. Rattanapittayapron, O. Vanijajiva

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Canna indica is a prominent species complex in tropical and subtropical areas. They become indigenous in Southeast Asia where they have been introduced. At present, C. indica complex comprises over hundred hybrids, are cultivated as commercial horticulture. The species complex contains starchy rhizome having economic value in terms of food and herbal medicine. In addition, bright color of the flowers makes it a valuable ornamental plant and potential source for natural colorant. This study aims to assess genetic diversity of four varieties of C. indica complex based on SRAP (sequence-related amplified polymorphism) and iPBS (inter primer binding site) markers. We also examined phytochemical characteristics and antioxidant properties of the flower extracts from four different color varieties. Results showed that despite of the genetic variation, there were no significant differences in phytochemical characteristics and antioxidant properties of flowers. The SRAP and iPBS results agree with the more primitive traits showed by morphological information and phytochemical and antioxidant characteristics from the flowers. Since Canna flowers has long been used as natural colorants together with the antioxidant activities from the ethanol extracts in this study, there are likely to be good source for cosmetics additives.

Keywords: Canna indica, antioxidant activity, genetic diversity, SRAP, iPBS.

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Authors: Jing Yu Pan, Dahai Liu

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Airlines in the US have taken protective measures to battle the COVID-19 pandemic, with a mask mandate being the most important one, especially in the aircraft cabin. As the airline industry is recovering from the pandemic, mask-wearing will eventually become a personal choice during a flight. Nevertheless, COVID-19 will continue to create uncertainty for a long time into the future, making it necessary to understand the attitude and voluntary use of masks by air travelers on airplanes even after masks are no longer mandatory. This study aimed to understand the relationship between demographic characteristics and mask-wearing intention in the US. For age, gender, income, educational, and ethnicity groups, this study examined three factors – subjective norms, risk avoidance, and information seeking and their influence on the mask-wearing intention onboard airplanes during COVID-19, and whether or not attitude toward masks was an important mediator. The results show that all demographic factors except gender could help to explain the group variations in factor impact and the mediating effect in mask-wearing intentions. In particular, Asian travelers had mask-wearing intentions that were not affected by attitude either directly or indirectly. These findings provide useful implications to enhance the health safety of air travelers, especially in the US where opposing views toward mask-wearing still widely exist.

Keywords: COVID-19, passenger demographics, aircraft cabin, mask-wearing intention, attitude as mediator.

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Authors: Luís Antonio de Almeida Rodriguez, José Maria Parente de Oliveira, Ednelson Oliveira

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In the last two decades, the world’s aviation authorities have made several attempts to create consensus about a global and accepted approach for applying semantics to web services registry descriptions. This problem has led communities to face a fat and disorganized infrastructure to describe aeronautical web services. It is usual for developers to implement ad-hoc connections among consumers and providers and manually create non-standardized service compositions, which need some particular approach to compose and semantically discover a desired web service. Current practices are not precise and tend to focus on lightweight specifications of some parts of the OWL-S and embed them into syntactic descriptions (SOAP artifacts and OWL language). It is necessary to have the ability to manage the use of both technologies. This paper presents an implementation of the ontology OWL-S that describes a Brazilian Aeronautical Web Service Registry, which makes it able to publish, advertise, make multi-criteria semantic discovery aligned with the ideas of the System Wide Information Management (SWIM) Program, and invoke web services within the Air Traffic Management context. The proposal’s best finding is a generic approach to describe semantic web services. The paper also presents a set of functional requirements to guide the ontology development and to compare them to the results to validate the implementation of the OWL-S Ontology.

Keywords: Aeronautical Web Services, OWL-S, Semantic Web Services Discovery, Ontologies.

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Authors: J. R. Wang, H. T. Lin, H. C. Chang, W. K. Lin, W. Y. Li, C. Shih

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This analysis of Kuosheng nuclear power plant (NPP) was performed mainly by TRACE, assisted with FRAPTRAN and FRAPCON. SNAP v2.2.1 and TRACE v5.0p3 are used to develop the Kuosheng NPP SPU TRACE model which can simulate the turbine trip without bypass transient. From the analysis of TRACE, the important parameters such as dome pressure, coolant temperature and pressure can be determined. Through these parameters, comparing with the criteria which were formulated by United States Nuclear Regulatory Commission (U.S. NRC), we can determine whether the Kuoshengnuclear power plant failed or not in the accident analysis. However, from the data of TRACE, the fuel rods status cannot be determined. With the information from TRACE and burn-up analysis obtained from FRAPCON, FRAPTRAN analyzes more details about the fuel rods in this transient. Besides, through the SNAP interface, the data results can be presented as an animation. From the animation, the TRACE and FRAPTRAN data can be merged together that may be realized by the readers more easily. In this research, TRACE showed that the maximum dome pressure of the reactor reaches to 8.32 MPa, which is lower than the acceptance limit 9.58 MPa. Furthermore, FRAPTRAN revels that the maximum strain is about 0.00165, which is below the criteria 0.01. In addition, cladding enthalpy is 52.44 cal/g which is lower than 170 cal/g specified by the USNRC NUREG-0800 Standard Review Plan.

Keywords: Turbine trip without bypass, Kuosheng NPP, TRACE, FRAPTRAN, SNAP animation.

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Authors: G. Settanni, A. Panarese, R. Vaira, A. Galiano

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Nowadays, artificial intelligence is used successfully in the field of e-commerce for its ability to learn from a large amount of data. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them the most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Also, Long Short-Term Memory algorithms have been implemented and trained on historical data in order to predict customer scores of the different items. Items with the highest scores are recommended to customers.

Keywords: Deep Learning, Long Short-Term Memory, Machine Learning, Recommender Systems, Support Vector Machine.

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Authors: L. P. K. Liyanage, N. R. P. Withana, A. L. Sandika

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The purpose of this study was to determine tourist and community perception-based sustainable tourism indicators as well as Human Pressure Index (HPI) and Tourist Activity Index (TAI). Study was carried out in Sinharaja forest which is considered as one of the major eco-tourism destination in Sri Lanka. Data were gathered using a pre-tested semi-structured questionnaire as well as records from Forest department. Convenient sampling technique was applied. For the majority of issues, the responses were obtained on multi-point Likert-type scales. Visual portrayal was used for display analyzed data. The study revealed that the host community of the Kudawa gets many benefits from tourism. Also, tourism has caused negative impacts upon the environment and community. The study further revealed the need of proper waste management and involvement of local cultural events for the tourism business in the Kudawa conservation center. The TAI, which accounted to be 1.27 and monthly evolution of HPI revealed that congestion can be occurred in the Sinharaja rainforest during peak season. The results provide useful information to any party involved with tourism planning anywhere, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: Kudawa conservation center, Sinharaja world heritage rainforest, sustainability indicators.

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Authors: Amanda M. Tadini, Houssam Hajjoul, Gustavo Nicolodelli, Stéphane Mounier, Célia R. Montes, Débora M. B. P. Milori

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Soil organic matter (SOM) plays an important role in maintaining soil productivity and accounting for the promotion of biological diversity. The main components of the SOM are the humic substances which can be fractionated according to its solubility in humic acid (HA), fulvic acids (FA) and humin (HU). The determination of the chemical properties of organic matter as well as its interaction with metallic species is an important tool for understanding the structure of the humic fractions. Fluorescence spectroscopy has been studied as a source of information about what is happening at the molecular level in these compounds. Specially, soils of Amazon region are an important ecosystem of the planet. The aim of this study is to understand the molecular and structural composition of HA samples from Spodosol of Amazonia using the fluorescence Emission-Excitation Matrix (EEM) and Time Resolved Fluorescence Spectroscopy (TRFS). The results showed that the samples of HA showed two fluorescent components; one has a more complex structure and the other one has a simpler structure, which was also seen in TRFS through the evaluation of each sample lifetime. Thus, studies of this nature become important because it aims to evaluate the molecular and structural characteristics of the humic fractions in the region that is considered as one of the most important regions in the world, the Amazon.

Keywords: Amazonian soil, characterization, fluorescence, humic acid, lifetime.

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Authors: Abass Braimah, Maha Hussein Abdallah

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The global ascendancy of terrorist attacks on building infrastructure with economic and heritage significance has increased awareness of the possibility of terrorism in Canada. Many structures in Canada that are at risk of terrorist attacks include government buildings, built many years ago of historic stone masonry construction. Although many researchers are investigating ways to retrofit masonry stone buildings to mitigate the effect of blast loadings, lack of knowledge on the dynamic behavior of historic stone masonry structures under blast loads makes it difficult to ascertain the effectiveness of the retrofitting techniques. This paper presents a review of open-source literature for the experimental and numerical stone masonry structures under blast loads. This review yielded very little information of the response of the historic stone masonry structures under blast loads. Thus, a comprehensive study is needed to understand the blast load effects on historic stone masonry buildings. The out-of-plane response of historic masonry structures to blast loads is investigated by using single-degree-of-freedom analysis. This approach presents equations that can be used effectively in the analysis of historic masonry walls to out-of-plane blast loading.

Keywords: Blast loads, historical buildings, masonry structure, single-degree-of-freedom analysis.

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Authors: Gupta Amit, Kumar Ramesh, Tewari P. C.

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Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies economic order quantity (EOQ), just in time (JIT), vendor managed inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.

Keywords: Inventory Policy, Ranking, DBA, Selection criteria.

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Authors: K. E. Oyetade, S. D. Eyono Obono

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Age ratings are very helpful in providing parents with relevant information for the purchase and use of digital technologies by the children; this is why the non-definition of age ratings for the use of ICTs by children in schools is a major concern; and this problem serves as a motivation for this study whose aim is to examine the factors affecting the perceptions of educators on the learners’ youngest age for the introduction of ICTs in schools. This aim is achieved through two types of research objectives: the identification and design of theories and models on age ratings, and the empirical testing of such theories and models in a survey of educators from the Camperdown district of the South African KwaZulu-Natal province. A questionnaire is used for the collection of the data of this survey whose validity and reliability is checked in SPSS prior to its descriptive and correlative quantitative analysis. The main hypothesis supporting this research is the association between the demographics of educators, their personality, and their perceptions on the learners’ youngest age for the introduction of ICTs in schools; as claimed by existing research; except that the present study looks at personality from three dimensions: self-actualized personalities, fully functioning personalities, and healthy personalities. This hypothesis was fully confirmed by the empirical study conducted by this research except for the demographic factor where only the educators’ grade or class was found to be associated with the personality of educators.

Keywords: Age ratings, Educators, E-learning, Personality Theories.

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: Anammox, filter media, kinetics, nitrogen removal.

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Authors: M. Eisakhani, A. Pauzi, O. Karim, A. Malakahmad, S.R. Mohamed Kutty, M. H. Isa

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Cameron Highlands is a mountainous area subjected to torrential tropical showers. It extracts 5.8 million liters of water per day for drinking supply from its rivers at several intake points. The water quality of rivers in Cameron Highlands, however, has deteriorated significantly due to land clearing for agriculture, excessive usage of pesticides and fertilizers as well as construction activities in rapidly developing urban areas. On the other hand, these pollution sources known as non-point pollution sources are diverse and hard to identify and therefore they are difficult to estimate. Hence, Geographical Information Systems (GIS) was used to provide an extensive approach to evaluate landuse and other mapping characteristics to explain the spatial distribution of non-point sources of contamination in Cameron Highlands. The method to assess pollution sources has been developed by using Cameron Highlands Master Plan (2006-2010) for integrating GIS, databases, as well as pollution loads in the area of study. The results show highest annual runoff is created by forest, 3.56 × 108 m3/yr followed by urban development, 1.46 × 108 m3/yr. Furthermore, urban development causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural activities and forest contribute the highest annual loads for phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr), respectively. Therefore, best management practices (BMPs) are suggested to be applied to reduce pollution level in the area.

Keywords: Cameron Highlands, Land use, Non-point Sources of Pollution

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

Abstract:

Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: Diesel engine, machine learning, NOx emission, semi-empirical.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: A. K. Al-Othman, K. M. EL-Nagger

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Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: Security Constrained Economic Dispatch, Direct Search method, optimization.

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: Band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation.

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Authors: S. Chiali, Z.Eberrichi, M.Malki

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The number of framework conceived for e-learning constantly increase, unfortunately the creators of learning materials and educational institutions engaged in e-formation adopt a “proprietor" approach, where the developed products (courses, activities, exercises, etc.) can be exploited only in the framework where they were conceived, their uses in the other learning environments requires a greedy adaptation in terms of time and effort. Each one proposes courses whose organization, contents, modes of interaction and presentations are unique for all learners, unfortunately the latter are heterogeneous and are not interested by the same information, but only by services or documents adapted to their needs. Currently the new tendency for the framework conceived for e-learning, is the interoperability of learning materials, several standards exist (DCMI (Dublin Core Metadata Initiative)[2], LOM (Learning Objects Meta data)[1], SCORM (Shareable Content Object Reference Model)[6][7][8], ARIADNE (Alliance of Remote Instructional Authoring and Distribution Networks for Europe)[9], CANCORE (Canadian Core Learning Resource Metadata Application Profiles)[3]), they converge all to the idea of learning objects. They are also interested in the adaptation of the learning materials according to the learners- profile. This article proposes an approach for the composition of courses adapted to the various profiles (knowledge, preferences, objectives) of learners, based on two ontologies (domain to teach and educational) and the learning objects.

Keywords: Adaptive educational hypermedia systems (AEHS), E-learning, Learner's model, Learning objects, Metadata, Ontology.

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