Search results for: algorithms and data structure

Authors: Maciej Szeląg, Stanisław Fic

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The impact of elevated temperatures on the construction materials manifests in change of their physical and mechanical characteristics. Stresses and thermal deformations that occur inside the volume of the material cause its progressive degradation as temperature increase. Finally, the reactions and transformations of multiphase structure of cementitious composite cause its complete destruction. A particularly dangerous phenomenon is the impact of thermal shock – a sudden high temperature load. The thermal shock leads to a high value of the temperature gradient between the outer surface and the interior of the element in a relatively short time. The result of mentioned above process is the formation of the cracks and scratches on the material’s surface and inside the material. The article describes the use of computer image analysis techniques to identify and assess the structure of the cluster cracks on the surfaces of modified cement pastes, caused by thermal shock. Four series of specimens were tested. Two Portland cements were used (CEM I 42.5R and CEM I 52,5R). In addition, two of the series contained metakaolinite as a replacement for 10% of the cement content. Samples in each series were made in combination of three w/b (water/binder) indicators of respectively 0.4; 0.5; 0.6. Surface cracks of the samples were created by a sudden temperature load at 200°C for 4 hours. Images of the cracked surfaces were obtained via scanning at 1200 DPI; digital processing and measurements were performed using ImageJ v. 1.46r software. In order to examine the cracked surface of the cement paste as a system of closed clusters – the dispersal systems theory was used to describe the structure of cement paste. Water is used as the dispersing phase, and the binder is used as the dispersed phase – which is the initial stage of cement paste structure creation. A cluster itself is considered to be the area on the specimen surface that is limited by cracks (created by sudden temperature loading) or by the edge of the sample. To describe the structure of cracks two stereological parameters were proposed: A ̅ – the cluster average area, L ̅ – the cluster average perimeter. The goal of this study was to compare the investigated stereological parameters with the mechanical properties of the tested specimens. Compressive and tensile strength testes were carried out according to EN standards. The method used in the study allowed the quantitative determination of defects occurring in the examined modified cement pastes surfaces. Based on the results, it was found that the nature of the cracks depends mainly on the physical parameters of the cement and the intermolecular interactions on the dispersal environment. Additionally, it was noted that the A ̅/L ̅ relation of created clusters can be described as one function for all tested samples. This fact testifies about the constant geometry of the thermal cracks regardless of the presence of metakaolinite, the type of cement and the w/b ratio.

Keywords: cement paste, cluster cracks, elevated temperature, image analysis, metakaolinite, stereological parameters

Procedia PDF Downloads 393

Authors: Sang Hee Shin

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The technical improving project is for using the domestic construction technology in the weak soil condition. The improved technology is applied directly under local construction site at OOO, OOO. Existing anchor technology was developed for the case of soft ground as N value 10 or less. In case of soft ground and heavy load, the attachment site per one strand is shortened due to the distributed interval so that the installation site is increased relatively and being economically infeasible. In addition, in case of high tensile load, adhesion phenomenon between wedge and block occurs. To solve these problems, it strengthens the function of the attached strands to treat a ‘bulbing’ on the strands. In the solution for minimizing the internal damage and strengthening the removal function, it induces lubricating action using the film and the attached film, and it makes the buffer structure using wedge lubricating structure and the spring. The technology is performed such as in-house testing and the field testing. The project can improve the reliability of the standardized quality technique. As a result, it intended to give the technical competitiveness.

Keywords: anchor, improving technology, removal anchor, soil reinforcement, weak soil

Procedia PDF Downloads 214

Authors: Wanjiku Karanja

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Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 125

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 209

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

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Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 321

Authors: Daihui Zhang, Marie J. Dumont

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A derivative of 5-hydroxymethylfurfural (HMF) was synthesized for the thiol-Michael addition reaction. The efficiency of the catalysts (base and nucleophiles) and side reactions during the thiol-Michael addition were investigated. Dimethylphenylphosphine efficiently initiated the thiol-Michael addition polymerization for synthesizing a series of bio-based furan polymers with different structure and properties. The benzene rings or hydroxyl groups present in the polymer chains increased the glass transition temperature (Tg) of poly (β-thioether ester). Additionally, copolymers with various compositions were obtained via adding different ratio of 1,6-hexanedithiols to 1,4-benzenedithiols. 1H NMR analysis revealed that experimental ratios of two dithiols monomers matched well with theoretical ratios. The occurrence of a reversible Diels-Alder reaction between furan rings and maleimide groups allowed poly (β-thioether ester) to be dynamically crosslinked. These polymers offer the potentials to produce materials from biomass that have both practical mechanical properties and reprocessing ability.

Keywords: copolymers, Diels-Alder reaction, hydroxymethylfurfural, Thiol-Michael addition

Procedia PDF Downloads 331

Authors: Iftikhar A. Tayubi, Tabrej Khan, Mansoor M. Alsubei, Fahad A. Alsaferi

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LIZTOXD provides a single source of high-quality information about proteinaceous lizard toxins that will be an invaluable resource for pharmacologists, neuroscientists, toxicologists, medicinal chemists, ion channel scientists, clinicians, and structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to explore the detail information of Lizard and toxin proteins. It includes common name, scientific name, entry id, entry name, protein name and length of the protein sequence. The utility of this database is that it can provide a user-friendly interface for users to retrieve the information about Lizard, toxin and toxin protein of different Lizard species. These interfaces created in this database will satisfy the demands of the scientific community by providing in-depth knowledge about Lizard and its toxin. In the next phase of our project we will adopt methodology and by using A MySQL and Hypertext Preprocessor (PHP) which and for designing Smart Draw. A database is a wonderful piece of equipment for storing large quantities of data efficiently. The users can thus navigate from one section to another, depending on the field of interest of the user. This database contains a wealth of information on species, toxins, toxins, clinical data etc. LIZTOXD resource that provides comprehensive information about protein toxins from lizard toxins. The combination of specific classification schemes and a rich user interface allows researchers to easily locate and view information on the sequence, structure, and biological activity of these toxins. This manually curated database will be a valuable resource for both basic researchers as well as those interested in potential pharmaceutical and agricultural applications of lizard toxins.

Keywords: LIZTOXD, MySQL, PHP, smart draw

Procedia PDF Downloads 167

Authors: V. Naciti, L. Pulejo, F. Cesaroni

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This study empirically analyzes whether the composition of the board of directors (BoD) enhances sustainability performance, in order to understand how the BoD contribute to the integration of Sustainable Development Goals (SDGs) in their businesses. Hypotheses are developed based on the agency theory and stakeholder theory. Using a system generalized method of the moment (SGMM) two-step estimator, with data from Sustainalytics and Compustat databases for 362 firms in six regions, we find that firms with more diversity on the board and a separation of chair and CEO roles have higher sustainability performance. Moreover, our findings provide that a higher number of independent directors is negatively associated with sustainability performance. This study contributes to the literature on corporate governance and the firm’s performance by demonstrating that the composition of the board of directors contributes to a better sustainability performance: by the implementation of a particular corporate governance mechanism, it is possible to integrate SDGs in the corporate strategy.

Keywords: sustainable development goals, corporate governance, board of directors, sustainability performance

Procedia PDF Downloads 185

Authors: Axel Thallemer, Aleksandar Kostadinov, Abel Fam, Alex Teo

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For centuries, the forming processes in nature served as a source of inspiration for both architects and designers. It seems as most human artifacts are based on ideas which stem from the observation of the biological world and its principles of growth. As a fact, in the cultural history of Homo faber, materials have been mostly used in their solid state: From hand axe to computer mouse, the principle of employing matter has not changed ever since the first creation. In the scope of history only recently and by the help of additive-generative fabrication processes through Computer Aided Design (CAD), designers were enabled to deconstruct solid artifacts into an outer skin and an internal lattice structure. The intention behind this approach is to create a new topology which reduces resources and integrates functions into an additively manufactured component. However, looking at the currently employed lattice structures, it is very clear that those lattice structure geometries have not been thoroughly designed, but rather taken out of basic-geometry libraries which are usually provided by the CAD. In the here presented study, a group of 20 industrial design students created new and unique lattice structures using natural paragons as their models. The selected natural models comprise both the animate and inanimate world, with examples ranging from the spiraling of narwhal tusks, off-shooting of mangrove roots, minimal surfaces of soap bubbles, up to the rhythmical arrangement of molecular geometry, like in the case of SiOC (Carbon-Rich Silicon Oxicarbide). This ideation process leads to a design of a geometric cell, which served as a basic module for the lattice structure, whereby the cell was created in visual analogy to its respective natural model. The spatial lattices were fabricated additively in mostly [X]3 by [Y]3 by [Z]3 units’ volumes using selective powder bed melting in polyamide with (z-axis) 50 mm and 100 µm resolution and subdued to mechanical testing of their elastic zone in a biomedical laboratory. The results demonstrate that additively manufactured lattice structures can acquire different properties when they are designed in analogy to natural models. Several of the lattices displayed the ability to store and return kinetic energy, while others revealed a structural failure which can be exploited for purposes where a controlled collapse of a structure is required. This discovery allows for various new applications of functional lattice structures within industrially created objects.

Keywords: bio-inspired, biomimetic, lattice structures, additive manufacturing

Procedia PDF Downloads 152

Authors: Salma Akter, Mohammad M. Haque, Lawrence Akwetey

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An empirical research design will analyze different factors/predictors children use to influence their parents in the family buying decision process in the unexplored area of British Bangladeshi children in the United Kingdom. The proposed conceptual model of factors- buying decision making process will be tested by the Structure Equation Model. A structured Questionnaire and secondary sources will employ to collect data and analyse and measure the validity by Statistical tools (SPSS) and Microsoft Excel. The Contemporary research aims to use the deductive approach developing the research questions and testing the hypothesis to identify the impact of different strategies British Bangladeshi children used to influence their parents in the family buying decision which was overlooked in the previous research.

Keywords: British Bangladeshi children, buying decision process, children influence, influential factors

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Authors: Salam Khalifa, Naveed Ahmed

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We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

Procedia PDF Downloads 375

Authors: Neda Sinaei, Davood Zare, Mehrdad Azin

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Polyhydroxyalkanoates (PHAs) are biocompatible and biodegradable polymers produced by a wide range of bacterial strains. These biopolymers are significantly studied for drug delivery and tissue engineering applications because of their fascinating physicochemical properties. Polyhydroxybutyrate (PHB) scaffold that has been extracted from a novel bacteria using oil wastewater was selected to study. Some physical parameters affecting scaffold properties such as PHB concentration, solvent evaporation speed, and ultrasonic time were investigated. Scanning electron microscopy was used to evaluate the porosity. Afterward, the biocompatibility of PHB scaffold was assessed. Initial results showed the highly porous PHB scaffold structure with a variety of pore sizes. Subsequent results indicated that more unique pore sizes can be obtained by optimizing physical factors. It would be noticed that the morphology of the pore structure was accordingly affected by ultrasonic time. Hence, In vitro cell viability tests on the PHB scaffold using human foreskin fibroblasts revealed strong cell attachment and proliferation supports. Therefore, it can be concluded that the cost-effective PHB scaffold has the potential using as a biomaterial cell adhesion substrate in therapeutic applications.

Keywords: Polyhydroxybutyrate, biocompatible, scaffold, porous, tissue engineering

Procedia PDF Downloads 240

Authors: Kiwon Yeom

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Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

Procedia PDF Downloads 170

Authors: Oshma Chakoory, Sophie Comtet-Marre, Pierre Peyret

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Metagenomic classifiers are widely used for the taxonomic profiling of metagenomic data and estimation of taxa relative abundance. Small subunit rRNA genes are nowadays a gold standard for the phylogenetic resolution of complex microbial communities, although the power of this marker comes down to its use as full-length. We benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then built a pipeline called RiboTaxa to generate a highly sensitive and specific metataxonomic approach. Using metagenomics data, RiboTaxa gave the best results compared to other tools (Kraken2, Centrifuge (1), METAXA2 (2), PhyloFlash (3)) with precise taxonomic identification and relative abundance description, giving no false positive detection. Using real datasets from various environments (ocean, soil, human gut) and from different approaches (metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not seen by current bioinformatics analysis opening new biological perspectives in human and environmental health. In a study focused on corals’ health involving 20 metagenomic samples (4), an affiliation of prokaryotes was limited to the family level with Endozoicomonadaceae characterising healthy octocoral tissue. RiboTaxa highlighted 2 species of uncultured Endozoicomonas which were dominant in the healthy tissue. Both species belonged to a genus not yet described, opening new research perspectives on corals’ health. Applied to metagenomics data from a study on human gut and extreme longevity (5), RiboTaxa detected the presence of an uncultured archaeon in semi-supercentenarians (aged 105 to 109 years) highlighting an archaeal genus, not yet described, and 3 uncultured species belonging to the Enorma genus that could be species of interest participating in the longevity process. RiboTaxa is user-friendly, rapid, allowing microbiota structure description from any environment and the results can be easily interpreted. This software is freely available at https://github.com/oschakoory/RiboTaxa under the GNU Affero General Public License 3.0.

Keywords: metagenomics profiling, microbial diversity, SSU rRNA genes, full-length phylogenetic marker

Procedia PDF Downloads 126

Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

Procedia PDF Downloads 136

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: M. Tehranizadeh, E. Shoushtari Rezvani

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Seismic performance of steel moment-resisting frame structures is investigated considering nonlinear soil-structure interaction (SSI) effects. 10-, 15-, and 20-story planar building frames with aspect ratio of 3 are designed in accordance with current building codes. Inelastic seismic demands of the superstructure are considered using concentrated plasticity model. The raft foundation system is designed for different soil types. Beam-on-nonlinear Winkler foundation (BNWF) is used to represent dynamic impedance of the underlying soil. Two sets of pulse-like as well as no-pulse near-fault earthquakes are used as input ground motions. The results show that the reduction in drift demands due to nonlinear SSI is characterized by a more uniform distribution pattern along the height when compared to the fixed-base and linear SSI condition. It is also concluded that beneficial effects of nonlinear SSI on displacement demands is more significant in case of pulse-like ground motions and performance level of the steel moment-resisting frames can be enhanced.

Keywords: soil-structure interaction, uplifting, soil plasticity, near-fault earthquake, tall building

Procedia PDF Downloads 552

Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

Procedia PDF Downloads 148

Authors: Raed Alsufyani, Hissam Tawfik, Victor Chang, Muthu Ramachandran

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This study investigates the factors that influence the decision by players in the healthcare sector to embrace Cloud Business Intelligence Technology with a focus on healthcare organizations in Saudi Arabia. To bring this matter into perspective, this study primarily considers the Technology-Organization-Environment (TOE) framework and the Human Organization-Technology (HOT) fit model. A survey was hypothetically designed based on literature review and was carried out online. Quantitative data obtained was processed from descriptive and one-way frequency statistics to inferential and regression analysis. Data were analysed to establish factors that influence the decision to adopt Cloud Business intelligence technology in the healthcare sector. The implication of the identified factors was measured, and all assumptions were tested. 66.70% of participants in healthcare organization backed the intention to adopt cloud business intelligence system. 99.4% of these participants considered security concerns and privacy risk have been the most significant factors in the adoption of cloud Business Intelligence (CBI) system. Through regression analysis hypothesis testing point that usefulness, service quality, relative advantage, IT infrastructure preparedness, organization structure; vendor support, perceived technical competence, government support, and top management support positively and significantly influence the adoption of (CBI) system. The paper presents quantitative phase that is a part of an on-going project. The project will be based on the consequences learned from this study.

Keywords: cloud computing, business intelligence, HOT-fit model, TOE, healthcare and innovation adoption

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Authors: Ju-Hong Lee, Chong-Jia Ciou

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This paper deals with the problem of two-dimensional (2-D) recursive two-channel quincunx quadrature mirror filter (QQMF) banks design. The analysis and synthesis filters of the 2-D recursive QQMF bank are composed of 2-D recursive digital allpass lattice filters (DALFs) with symmetric half-plane (SHP) support regions. Using the 2-D doubly complementary half-band (DC-HB) property possessed by the analysis and synthesis filters, we facilitate the design of the proposed QQMF bank. For finding the coefficients of the 2-D recursive SHP DALFs, we present a structure of 2-D recursive digital allpass filters by using 2-D SHP recursive digital all-pass lattice filters (DALFs). The novelty of using 2-D SHP recursive DALFs to construct a 2-D recursive QQMF bank is that the resulting 2-D recursive QQMF bank provides better performance than the existing 2-D recursive QQMF banks. Simulation results are also presented for illustration and comparison.

Keywords: all-pass digital filter, lattice structure, quincunx QMF bank, symmetric half-plane digital filter

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Authors: Mamoona Rasheed, Salman Iqbal, Muhammad Abdullah

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Organizational capability, in terms of employees’ knowledge is valuable, and difficult to reproduce; and help to build sustainable competitive advantages. Knowledge capability is linked with human resource (HR) practices of an organization. This paper investigates the relationship between HR practices, knowledge management and organization capability. In an organization, employees play key role for the effective organizational performance by sharing their knowledge with management and co-workers that contributes towards organization capability. Pakistan being a developing country has different HR practices and culture. The business opportunities give rise to the discussion about the effect of HR practices on knowledge management and organization capability as innovation performance. An empirical study is conducted through questionnaires form the employees in private banks of Lahore, Pakistan. The data is collected via structured questionnaire with a sample of 120 cases. Data is analyzed using Structure Equation Modeling (SEM), and results are depicted using AMOS software. Results of this study are tabulated, interpreted and crosschecked with other studies. Findings suggest that there is a positive relationship of training & development along with incentives on knowledge management. On the other hand, employee’s participation has insignificant association with knowledge management. In addition, knowledge management has also positive association with organization capability. In line with the previous research, it is suggested that knowledge management is important for improving the organizational capability such as innovation performance and knowledge capacity of firm. Organization capability may improve significantly once specific HR practices are properly established and implemented by HR managers. This Study has key implications for knowledge management and innovation fields theoretically and practically.

Keywords: employee participation, incentives, knowledge management, organization capability, training and development

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

Procedia PDF Downloads 439

Authors: Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Madjid Soltani

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The computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, and drug extravasation from microvascular. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to show how capillary network structure induced by tumor affects drug delivery. The effect of heterogeneous capillary network induced by tumor on interstitial fluid flow and drug delivery is investigated by this multi scale method. The sprouting angiogenesis model is used for generating capillary network induced by tumor. Fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. The Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. Finally, convection-diffusion-reaction equation is used to simulate drug delivery. The dynamic approach which changes the capillary network structure based on signals sent by hemodynamic and metabolic stimuli is used in this study for more realistic assumption. The study indicates that drug delivery to solid tumors depends on the tumor induced capillary network structure. The dynamic approach generates the irregular capillary network around the tumor and predicts a higher interstitial pressure in the tumor region. This elevated interstitial pressure with irregular capillary network leads to a heterogeneous distribution of drug in the tumor region similar to in vivo observations. The investigation indicates that the drug transport properties have a significant role against the physiological barrier of drug delivery to a solid tumor.

Keywords: solid tumor, physiological barriers to drug delivery, angiogenesis, microvascular network, solute transport

Procedia PDF Downloads 317

Authors: Zhiwei Zhong, Xiaofei Li, Deli Wang

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Ecosystem engineering is a powerful force shaping community structure and ecosystem function. Yet, very little is known about the mechanisms by which engineers affect vital ecosystem processes like trophic interactions. Here, we examine the potential for a herbivore ecosystem engineer, domestic sheep, to affect trophic interactions between the web-building spider Argiope bruennichi, its grasshopper prey Euchorthippus spp., and the grasshoppers’ host plant Leymus chinensis. By integrating small- and large-scale field experiments, we demonstrate that: 1) moderate sheep grazing changed the structure of plant communities by suppressing strongly interacting forbs within a grassland matrix; 2) this change in plant community structure drove interaction modifications between the grasshoppers and their grass host plants and between grasshoppers and their spider predators, and 3) these interaction modifications were entirely mediated by plasticity in grasshopper behavior. Overall, ecosystem engineering by sheep grazing strengthened bottom-up effects and weakened top-down effects via trait-mediated interactions, resulting in a nearly two-fold increase in grasshopper densities. Interestingly, the grasshopper behavioral shifts which reduced spider per capita predation rates in the microcosms did not translate to reduced spider predation rates at the larger system scale because increased grasshopper densities offset behavioral effects at larger scales. Our findings demonstrate that 1) ecosystem engineering can strongly alter trophic interactions, 2) such effects can be driven by cryptic trait-mediated interactions, and 3) the relative importance of trait- versus density effects as measured by microcosm experiments may not reflect the importance of these processes at realistic ecological scales due to scale-dependent interactions.

Keywords: bottom-up effects, ecosystem engineering, trait-mediated indirect effects, top-down effects

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Authors: Hina Kausher, Sangita Srivastava

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In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Hanane Belayachi, Sarra Bourahla, Amel Belayachi, Fadela Nemchi, Mostefa Belhakem

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The most used techniques to remove pollutants from wastewater are adsorption onto activated carbon (AC) and oxidation using a photocatalyst slurry. The aim of this work is to eliminate such drawbacks by combining AC and titanium dioxide (TiO₂) in a photocatalytically Regenerative Activated Carbon. Anatase titania was deposited on powder-activated carbon made from grape seeds by the impregnation method, and then the composite photocatalyst was employed for the removal of reactive black 5, which is an anionic azo dye, from water. The AGS/TiO₂ was characterized by BET, MEB, RDX and optical absorption spectroscopy. The BET surface area and the pore structure of composite photocatalysts (AGS/TiO₂) and activated grape seeds (AGS) were evaluated from nitrogen adsorption data at 77 K in relation to process conditions. Our results indicate that the photocatalytic activity of AGS/TiO₂ was much higher than single-phase titania. The adsorption equilibrium of reactive black 5 from aqueous solutions on the examined materials was investigated. Langmuir, Freundlich, and Redlich–Petersen models were fitted to experimental equilibrium data, and their goodness of fit is compared. The degradation kinetics fitted well to the Langmuir-Hinselwood pseudo first order rate low. The photocatalytic activity of AGS/TiO₂ was much higher than virgin TiO₂. Chemical oxygen demand (COD) removal was measured at regular intervals to quantify the mineralization of the dye. Above 96% mineralization was observed. These results suggest that UV-irradiated TiO₂ immobilized on activated carbon may be considered an adequate process for the treatment of diluted colored textile wastewater.

Keywords: activated carbon, pollutant, catalysis, TiO₂

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Authors: S. Kaymakçı, D. Gündoğdu, H. Özçelik

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The truck park of a warehouse for a chain of supermarket was going to be constructed on a poor ground. Rather than using a piled foundation, the client was convinced that a ground improvement using a reinforced foundation raft also known as “basal reinforcement” shall work. The retaining structures supporting the truck park area were designed using a hybrid structure made up of the Terramesh® Wall System and MacGrid™ high strength geogrids. The total wall surface area is nearly 2740 sq.m , reaching a maximum height of 13.00 meters. The area is located in the first degree seismic zone of Turkey and the design seismic acceleration is high. The design of walls has been carried out using pseudo-static method (limit equilibrium) taking into consideration different loading conditions using Eurocode 7. For each standard approach stability analysis in seismic condition were performed. The paper presents the detailed design of the reinforced soil structure, basal reinforcement and the construction methods; advantages of using such system for the project are discussed.

Keywords: basal reinforcement, geogrid, reinforced soil raft, reinforced soil wall, soil reinforcement

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Authors: Sunil Kumar

Abstract:

For many years, small organic molecules derived naturally from microbes and plants have delivered a number of expedient therapeutic drug agents. The search for naturally occurring lead compounds has continued in recent years as well, with the constituents of marine flora and fauna along with those of telluric microorganisms and plants being investigated for their anti-bacterial and anti-cancer activities. It has been observed that such promising lead molecules incline to promptly generate substantial attention among scientists like synthetic organic chemists and biologists. Subsequently, the availability of a given precious natural product sample may be enriched, and it may be possible to determine a preliminary idea of structure-activity relationships to develop synthetic analogues. For instance, anti-tumor drug topotecan is a synthetic chemical compound similar in chemical structure to camptothecin which is found in extracts of Camptotheca acuminate. Similarly, researchers at AstraZeneca discovered anti-biotic pyrrolamide through a fragment-based lead generation approach from kibdelomycin, which is isolated from Staphylococcus aureuss.

Keywords: anticancer, antibiotic, lead molecule, natural product, synthetic analogues

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Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes

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Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.

Keywords: airport ontology, energy management, facility data model, ontology modeling

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