Search results for: Content- Based Recommendation

Authors: Vipin Pal, Girdhari Singh, R P Yadav

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As wireless sensor networks are energy constraint networks so energy efficiency of sensor nodes is the main design issue. Clustering of nodes is an energy efficient approach. It prolongs the lifetime of wireless sensor networks by avoiding long distance communication. Clustering algorithms operate in rounds. Performance of clustering algorithm depends upon the round time. A large round time consumes more energy of cluster heads while a small round time causes frequent re-clustering. So existing clustering algorithms apply a trade off to round time and calculate it from the initial parameters of networks. But it is not appropriate to use initial parameters based round time value throughout the network lifetime because wireless sensor networks are dynamic in nature (nodes can be added to the network or some nodes go out of energy). In this paper a variable round time approach is proposed that calculates round time depending upon the number of active nodes remaining in the field. The proposed approach makes the clustering algorithm adaptive to network dynamics. For simulation the approach is implemented with LEACH in NS-2 and the results show that there is 6% increase in network lifetime, 7% increase in 50% node death time and 5% improvement over the data units gathered at the base station.

Keywords: Wireless Sensor Network, Clustering, Energy Efficiency, Round Time.

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Authors: N. Mohamad, W. Samiati Andriana Wan Mohd Daud, M. Suhaimi Tohid, M. Fazli Othman, M. Rizal Salleh

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This is a collaborative project of the mural art between The Department of Fine Art from Universiti Teknologi MARA (UiTM) and Petronas Dagangan Berhad (PDB), the most leading retailer and marketer of downstream oil and gas products in Malaysia. Five different states have been identified in showcasing the National Identity of Malaysia at each Petronas gas station; the Air Keroh in Melaka, Pasir Pekan in Kelantan, Pontian in Johor, Simpang Pulai in Perak and also Wakaf Bharu in Terengganu. This project is to analyze the element of national identity that has been demonstrated at the Petronas's Mural. The ultimate aim of the mural is to let the community and local people to be aware about what Malaysians are consists and proud of and how everyone is able to connect with the idea through art. The method that is being explained in this research is by using visual data through research and also self-experience in collecting the visual data in identifying what images are considered as the national identity and idea development and visual analysis is being transferred based upon the visual data collection. In this stage elements and principle of design will be the key in highlighting what is necessary in a work of art. In conclusion, image of the National Identity of Malaysia is able to connect to the audience from local and also to the people from outside the country to learn and understand the beauty and diversity of Malaysia as a unique country with art, through the wall of five Petronas gas stations.

Keywords: Mural art, fine art, national identity, community.

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Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

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Authors: H. López-Moreno, A. Rodríguez-Sánchez, C. Viñas-Arrebola, C. Porras-Amores

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The ventilated façade has great advantages when compared to traditional façades as it reduces the air conditioning thermal loads due to the stack effect induced by solar radiation in the air chamber. Optimizing energy consumption by using a ventilated façade can be used not only in newly built buildings but also it can be implemented in existing buildings, opening the field of implementation to energy building retrofitting works. In this sense, the following three prototypes of façade where designed, built and further analyzed in this research: non-ventilated façade (NVF); slightly ventilated façade (SLVF) and strongly ventilated façade (STVF). The construction characteristics of the three facades are based on the Spanish regulation of building construction “Technical Building Code”. The façades have been monitored by type-k thermocouples in a representative day of the summer season in Madrid (Spain). Moreover, an analysis of variance (ANOVA) with repeated measures, studying the thermal lag in the ventilated and no-ventilated façades has been designed. Results show that STVF façade presents higher levels of thermal inertia as the thermal lag reduces up to 17% (daily mean) compared to the non-ventilated façade. In addition, the statistical analysis proves that an increase of the ventilation holes size in STVF façades can improve the thermal lag significantly (p >0.05) when compared to the SLVF façade.

Keywords: Energy efficiency, experimental study, statistical analysis, thermal behavior, ventilated façade.

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

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The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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Authors: Salwa Hagag Abdelaziz, Dorria Salem, Hoda Zaki, Suzan Atteya

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Early detection of breast cancer saves many thousands of lives each year via application of mammography and genetic screening and many more lives could be saved if nurses are involved in breast care screening practices. So, the aim of the study was to identify nurse's role in early detection of breast cancer through mammography and genetic screening and its impact on patient's outcome. In order to achieve this aim, 400 women above 40 years, asymptomatic were recruited for mammography and genetic screening. In addition, 50 nurses and 6 technologists were involved in the study. A descriptive analytical design was used. Five tools were utilized: sociodemographic, mammographic examination and risk factors, women's before, during and after mammography, items relaying to technologists, and items related to nurses were also obtained. The study finding revealed that 3% of women detected for malignancy and 7.25% for fibroadenoma. Statistically significant differences were found between mammography results and age, family history, genetic screening, exposure to smoke, and using contraceptive pills. Nurses have insufficient knowledge about screening tests. Based on these findings the present study recommended involvement of nurses in breast care which is very important to in force population about screening practices.

Keywords: Early detection, Genetic Screening, Mammography.

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Authors: T. Y. Liu, C. H Lin., Y. M Ferng

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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyze the flow field and pressure distributions of the wing blades.

Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm.

Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyze the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: Horizontal Axis Wind Turbine, turbulence model, noise.

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Authors: Yuni Suranindyah, Kustantinah, E. R. Ôêàrskov

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The case study was conducted to show the effect of  milking method in goat called half day milking on the milk production and the growth of kids. Data were collected by  interviewing farmers and investigating goat production in the  communal goat housing from June 2008 to May 2009. The interview  was conducted to collect data about goat management. The  observations were conducted on 10 goats, which were selected based  on the uniformity of age, number of kid born/goat and the milking method in practice. The samples were divided into two groups; those  were full 3 months nursing and half day milked goats (in this group the kids were separated from goat during the previous night milking  and then the kids were allowed to suck the goat during the day). The result showed that the communal goat housing had 138 goats and 25% of the farmers milked the goat. The implementation of half day milking increased the milk production significantly (P<0.05) and it did not affect the kids’ growth. It was concluded that half day milking was beneficial to increase milk production. In the communal goat housing was possible to implement the result of this innovation to all members of the farmer group as a method in increasing goat milk production.

Keywords: Communal goat housing, milk production.

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Authors: Iveta Nováková, Martin-Andrè S. Husby, Boy-Arne Buyle

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The building industry has one of the most significant contributions to global warming due to the production of building materials, transportation, building activities, and demolition of structures when they reach the end of their life. Implementation of circular material flow and circular economy can significantly reduce greenhouse gasses and simultaneously reduce the need for natural resources. The use of recycled concrete aggregates (RCA) is one of the possibilities for reducing the depletion of raw materials for concrete production. Concrete is the most used building material worldwide, and aggregates constitute large part of its volume. RCA can replace a certain amount of natural aggregates (NA), and concrete will still perform as required. The aim of this scientific paper is to evaluate RCA properties with and without mechanical treatment. Analysis of RCA itself will be followed by compressive strength of concrete containing various amounts of treated and non-treated RCA. Results showed improvement in compressive strength of the mix with mechanically treated RCA compared to standard RCA, and even the strength of concrete with mechanically treated RCA in dose 50% of coarse aggregates was higher than the reference mix by 4%. Based on obtained results, it can be concluded that integration of RCA in industrial concrete production is feasible, at a replacement ratio of 50% for mechanically treated RCA and 30% if untreated RCA is used, without affecting the compressive strength negatively.

Keywords: Recycled concrete aggregates, RCA, mechanical treatment, aggregate properties, compression strength.

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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: Mughal Yar M, Israr Ul Haq, Bushra Noman

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The stem cells have ability to differentiated themselves through mitotic cell division and various range of specialized cell types. Cellular differentiation is a way by which few specialized cell develops into more specialized.This paper studies the fundamental problem of computational schema for an artificial neural network based on chemical, physical and biological variables of state. By doing this type of study system could be model for a viable propagation of various economically important stem cells differentiation. This paper proposes various differentiation outcomes of artificial neural network into variety of potential specialized cells on implementing MATLAB version 2009. A feed-forward back propagation kind of network was created to input vector (five input elements) with single hidden layer and one output unit in output layer. The efficiency of neural network was done by the assessment of results achieved from this study with that of experimental data input and chosen target data. The propose solution for the efficiency of artificial neural network assessed by the comparatative analysis of “Mean Square Error" at zero epochs. There are different variables of data in order to test the targeted results.

Keywords: Computational shcmin, meiosis, mitosis, neuralnetwork, Stem cell SOM;

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Authors: Gul Afreen, Sreedevi Upadhyayula, Mahendra K. Sunkara

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One-dimensional (1D) nanostructures like nanowires, nanotubes, and nanorods find variety of practical application owing to their unique physico-chemical properties. In this work, TiO₂ nanowires were synthesized by direct oxidation of titanium particles in a unique microwave plasma jet reactor. The prepared TiO₂ nanowires manifested the flexible features, and were characterized by using X-ray diffraction, Brunauer-Emmett-Teller (BET) surface area analyzer, UV-Visible and FTIR spectrophotometers, Scanning electron microscope, and Transmission electron microscope. Further, the photodegradation efficiency of these nanowires were tested against toxic organic dye like methylene blue (MB) and the results were compared with the commercial TiO₂. It was found that TiO₂ nanowires exhibited superior photocatalytic performance (89%) as compared to commercial TiO₂ (75%) after 60 min of reaction. This is attributed to the lower recombination rate and increased interfacial charge transfer in TiO₂ nanowire. Pseudo-first order kinetic modelling performed with the experimental results revealed that the rate constant of photodegradation in case of TiO₂ nanowire was 1.3 times higher than that of commercial TiO₂. Superoxide radical (O₂˙⁻) was found to be the major contributor in the photodegradation mechanism. Based on the trapping experiments, a plausible mechanism of the photocatalytic reaction is discussed.

Keywords: Heterogeneous catalysis, photodegradation, reactive oxygen species, TiO2 nanowires.

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

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Cosmic showers, from their places of origin in space, after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of EAS and similar High Energy Particle Showers involve a plethora of experimental setups with certain constraints for which soft-computational tools like Artificial Neural Network (ANN)s can be adopted. The optimality of ANN classifiers can be enhanced further by the use of Multiple Classifier System (MCS) and certain data - dimension reduction techniques. This work describes the performance of certain data dimension reduction techniques like Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Self Organizing Map (SOM) approximators for application with an MCS formed using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN). The data inputs are obtained from an array of detectors placed in a circular arrangement resembling a practical detector grid which have a higher dimension and greater correlation among themselves. The PCA, ICA and SOM blocks reduce the correlation and generate a form suitable for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

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

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Authors: A. Deręgowska, J. Depciuch, R. Wojnarowska, J. Polit, D. Broda, H. Nechai, M. Gonchar, and E. Sheregii

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16-Mercaptohexadecanoic acid (MHDA) and tripeptide glutathione conjugated with gold nanoparticles (Au-NPs) are characterized by Fourier Transform InfaRared (FTIR) spectroscopy combined with Surface-enhanced Raman scattering (SERS) spectroscopy. Surface Plasmon Resonance (SPR) technique based on FTIR spectroscopy has become an important tool in biophysics, which is perspective for the study of organic compounds. FTIR-spectra of MHDA shows the line at 2500 cm-1 attributed to thiol group which is modified by presence of Au-NPs, suggesting the formation of bond between thiol group and gold. We also can observe the peaks originate from characteristic chemical group. A Raman spectrum of the same sample is also promising. Our preliminary experiments confirm that SERS-effect takes place for MHDA connected with Au-NPs and enable us to detected small number (less than 106 cm-2) of MHDA molecules. Combination of spectroscopy methods: FTIR and SERS – enable to study optical properties of Au- NPs and immobilized bio-molecules in context of a bio-nano-sensors.

Keywords: Glutathione; gold nanoparticles, Fourier transform infrared spectroscopy, MHDA, surface-enhanced Raman scattering.

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Authors: M. Abdelhamid, I. Beshara, M. Ghoneim

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In Egypt, the concept of Asset Management (AM) is new; however, the need for applying it has become crucial because deteriorating or losing an asset is unaffordable in a developing country like Egypt. Therefore the current study focuses on educational buildings as one of the most important assets regarding planning, building, operating and maintenance expenditures. The main objective of this study is to develop a SAMF for educational buildings in Egypt. The General Authority for Educational Buildings (GAEB) was chosen as a case study of the current research as it represents the biggest governmental organization responsible for planning, operating and maintaining schools in Egypt. To achieve the research objective, structured interviews were conducted with senior managers of GAEB using a pre designed questionnaire to explore the current practice of AM. Gab analysis technique was applied against best practices compounded from a vast literature review to identify gaps between current practices and the desired one. The previous steps mainly revealed; limited knowledge about strategic asset management, no clear goals, no training, no real risk plan and lack of data, technical and financial resources. Based on the findings, a SAMF for GAEB was introduced and Framework implementation steps and assessment techniques were explained in detail.

Keywords: Strategic Asset Management, Educational Building, Framework, Gab Analysis, Developing Country.

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Authors: Y. H. Mugahed Amran, Raizal S. M. Rashid, Farzad Hejazi, Nor Azizi Safiee, A. A. Abang Ali

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Experimental and analytical studies were carried out to investigate the structural behavior of precast foamed concrete sandwich panels (PFCSP) of total number (6) as one-way action slab tested under lateral load. The details of the test setup and procedures were illustrated. The results obtained from the experimental tests were discussed which include the observation of cracking patterns and influence of aspect ratio (L/b). Analytical study of finite element analysis was implemented and degree of composite action of the test panels was also examined in both experimental and analytical studies. Result shows that crack patterns appeared in only one-direction, similar to reports on solid slabs, particularly when both concrete wythes act in a composite manner. Foamed concrete was briefly reviewed and experimental results were compared with the finite element analyses data which gives a reasonable degree of accuracy. Therefore, based on the results obtained, PFCSP slab can be used as an alternative to conventional flooring system.

Keywords: Aspect ratio (L/b), finite element analyses (FEA), foamed concrete (FC), precast foamed concrete sandwich panel (PFCSP), ultimate flexural strength capacity.

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Authors: Minsoo Lee, Yun-mi Kim, Yearn Jeong Kim, Yoon-kyung Lee, Hyejung Yoon

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Biological data has several characteristics that strongly differentiate it from typical business data. It is much more complex, usually large in size, and continuously changes. Until recently business data has been the main target for discovering trends, patterns or future expectations. However, with the recent rise in biotechnology, the powerful technology that was used for analyzing business data is now being applied to biological data. With the advanced technology at hand, the main trend in biological research is rapidly changing from structural DNA analysis to understanding cellular functions of the DNA sequences. DNA chips are now being used to perform experiments and DNA analysis processes are being used by researchers. Clustering is one of the important processes used for grouping together similar entities. There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a clustering algorithm that imitates the ecosystem taking into account the features of biological data. We implemented the system using an Ant-Colony clustering algorithm. The system decides the number of clusters automatically. The system processes the input biological data, runs the Ant-Colony algorithm, draws the Topic Map, assigns clusters to the genes and displays the output. We tested the algorithm with a test data of 100 to1000 genes and 24 samples and show promising results for applying this algorithm to clustering DNA chip data.

Keywords: Ant colony system, biological data, clustering, DNA chip.

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Authors: Nwakaego C. Onyenokporo

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Cement is the most extensively used construction material due to its strength and versatility of use. However, the production of Portland cement has become unsustainable because of high energy usage, reduction of natural non-renewable resources and emissions of greenhouse gases. Production of cement contributes to anthropogenic greenhouse gases emissions annually. The growing concerns for the environment resulting from this constant and excessive use of cement has therefore raised the need for more green materials and technology. The use of supplementary cementitious materials (SCMs) is considered as one of the many alternatives suited to address this issue and serve as a sustainable partial replacement for cement in construction. This paper will examine the reuse of these waste materials to partially replace Portland cement. It provides a critical review of literature analysing various supplementary cementitious materials which are applicable in the building industry as either partial replacement for cement or aggregates. These materials have been grouped based on source into industrial wastes, domestic/general wastes, and agricultural wastes. The reuse of these waste materials could potentially reduce the negative effects of cement production and reduce landfills which constitute an environmental nuisance. This paper seeks to inform building industry professionals and researchers in the field on the applicability of these waste materials in construction.

Keywords: cement, greenhouse gases, landfills, sustainable, waste materials

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Authors: Nwakaego C. Onyenokporo

Abstract:

Cement is the most extensively used construction material due to its strength and versatility of use. However, the production of Portland cement has become unsustainable because of high energy usage, reduction of natural non-renewable resources and emissions of greenhouse gases. Production of cement contributes to anthropogenic greenhouse gases emissions annually. The growing concerns for the environment resulting from this constant and excessive use of cement has therefore raised the need for more green materials and technology. The use of supplementary cementitious materials (SCMs) is considered as one of the many alternatives suited to address this issue and serve as a sustainable partial replacement for cement in construction. This paper will examine the reuse of these waste materials to partially replace Portland cement. It provides a critical review of literature analysing various supplementary cementitious materials which are applicable in the building industry as either partial replacement for cement or aggregates. These materials have been grouped based on source into industrial wastes, domestic/general wastes, and agricultural wastes. The reuse of these waste materials could potentially reduce the negative effects of cement production and reduce landfills which constitute an environmental nuisance. This paper seeks to inform building industry professionals and researchers in the field on the applicability of these waste materials in construction.

Keywords: Cement, greenhouse gases, landfills, sustainable, waste materials.

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Authors: Chih-Hao Chen, Hsing-Chung Lee, Qingdong Ling, Hsiao-Jung Chen, Sun-Chong Wang, Li-Ching Wu, H.C. Lee

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Segmentation, filtering out of measurement errors and identification of breakpoints are integral parts of any analysis of microarray data for the detection of copy number variation (CNV). Existing algorithms designed for these tasks have had some successes in the past, but they tend to be O(N2) in either computation time or memory requirement, or both, and the rapid advance of microarray resolution has practically rendered such algorithms useless. Here we propose an algorithm, SAD, that is much faster and much less thirsty for memory – O(N) in both computation time and memory requirement -- and offers higher accuracy. The two key ingredients of SAD are the fundamental assumption in statistics that measurement errors are normally distributed and the mathematical relation that the product of two Gaussians is another Gaussian (function). We have produced a computer program for analyzing CNV based on SAD. In addition to being fast and small it offers two important features: quantitative statistics for predictions and, with only two user-decided parameters, ease of use. Its speed shows little dependence on genomic profile. Running on an average modern computer, it completes CNV analyses for a 262 thousand-probe array in ~1 second and a 1.8 million-probe array in 9 seconds

Keywords: Cancer, pathogenesis, chromosomal aberration, copy number variation, segmentation analysis.

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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: Hossein Heidari Tabrizi, Azizeh Chalak, Hossein Enayat

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The present study seeks to investigate the application of expansion strategy in Persian subtitles of English crime movies. More precisely, this study aims at classifying the different types of expansion used in subtitles as well as investigating the appropriateness or inappropriateness of the application of each type. To achieve this end, three movies; namely, The Net (1995), Contact (1997) and Mission Impossible 2 (2000), available with Persian subtitles, were selected for the study. To collect the data, the above mentioned movies were watched and those parts of the Persian subtitles in which expansion had been used were identified and extracted along with their English dialogs. Then, the extracted Persian subtitles were classified based on the reason that led to expansion in each case. Next, the appropriateness or inappropriateness of using expansion in the extracted Persian subtitles was descriptively investigated. Finally, an equivalent not containing any expansion was proposed for those cases in which the meaning could be fully transferred without this strategy. The findings of the study indicated that the reasons range from explicitation (explicitation of visual, co-textual and contextual information), mistranslation and paraphrasing to the preferences of subtitlers. Furthermore, it was found that the employment of expansion strategy was inappropriate in all cases except for those caused by explicitation of contextual information since correct and shorter equivalents which were equally capable of conveying the intended meaning could be posited for the original dialogs.

Keywords: Audiovisual translation, English crime movies, expansion strategies, Persian subtitles.

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Authors: Zohreh Soltani, Seyedmohammadhossein Hosseinian

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Reduction of energy consumption in built infrastructure, through the installation of energy-efficient technologies, is a major approach to achieving sustainability. In practice, the viability of energy efficiency projects strongly depends on the cost reimbursement and profitability. These projects are subject to failure if the actual cost savings do not reimburse the project cost promptly. In such cases, refinancing could be a solution to benefit from the long-term returns of the project, if implemented wisely. However, very little is still known about the effect of refinancing options on financial performance of energy efficiency projects. In order to fill this gap, the present study investigates the financial behavior of energy efficiency projects with focus on refinancing options, such as Leveraged Loans. A System Dynamics (SD) model is introduced, and the model application is presented using an actual case-study data. The case study results indicate that while high-interest start-ups make using Leveraged Loan inevitable, refinancing can rescue the project and bring about profitability. This paper also presents some managerial implications of refinancing energy efficiency projects based on the case-study analysis. Results of this study help to implement financially viable energy efficiency projects so that the community could benefit from their environmental advantages widely.

Keywords: Energy efficiency projects, leveraged loan, refinancing, sustainability.

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Authors: M. Govindarajan, R. M. Chandrasekaran

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Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

Keywords: Back propagation, classification accuracy, textmining, time complexity.

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

Abstract:

With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: Cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple-output systems, MIMO, orthogonal frequency division multiplexing, OFDM.

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Authors: Eda Gök

Abstract:

Peridynamics is a new modeling concept of non-local interactions for solid structures. The formulations of Peridynamic (PD) theory are based on integral equations rather than differential equations. Through, undefined equations of associated problems are avoided. PD theory might be defined as continuum version of molecular dynamics. The medium is usually modeled with mass particles bonded together. Particles interact with each other directly across finite distances through central forces named as bonds. The main assumption of this theory is that the body is composed of material points which interact with other material points within a finite distance. Although, PD theory developed for discontinuities, it gives good results for structures which have no discontinuities. In this paper, displacement control of the isotropic plate under the effect of tensile and bending loading has been investigated by means of PD theory. A MATLAB code is generated to create PD bonds and corresponding surface correction factors. Using generated MATLAB code the geometry of the specimen is generated, and the code is implemented in Finite Element Software. The results obtained from non-local continuum theory are compared with the Finite Element Analysis results and analytical solution. The results show good agreement.

Keywords: Flexural loading, non-local continuum mechanics, Peridynamic theory, solid structures, tensile loading.

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Authors: R. Tlili Yaakoubi, H. Nakouri, O. Blanpain, S. Lallahem

Abstract:

The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: Automation, optimization, paradigm, RTC.

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Authors: Alireza Osareh, Bita Shadgar

Abstract:

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: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Atilla Bayram

Abstract:

This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: Computed force control method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss.

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