Search results for: frequency domain scaling

Authors: Retno A. Vinarti, Lucy M. Hederman

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This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

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Authors: E. Ruíz, W. Aperador

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In this article evaluates the protective effect of the concrete alternative obtained from the fly ash and iron and steel slag mixed in binary form and were placed on structural steel ASTM A 706. The study was conducted comparatively with specimens exposed to natural conditions free of chloride ion. The effect of chloride ion on the specimens was generated of form accelerated under controlled conditions (3.5% NaCl and 25 ° C temperature). The Impedance data were acquired over a range of 1 mHz to 100 kHz. At frequencies high is found the response of the interface means of the exposure-concrete and to frequency low the response of the interface corresponding to concrete-steel.

Keywords: alternative concrete, corrosion, alkaline activation, impedance spectroscopy

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: David Lall, Vikram Vishal, P. G. Ranjith

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Numerical modeling of gas production from hydrate-bearing reservoirs requires the solution of various thermal, hydrological, chemical, and mechanical phenomena in a coupled manner. Among the various reservoir properties that influence gas production estimates, the distribution of permeability across the domain is one of the most crucial parameters since it determines both heat transfer and mass transfer. The aspect of permeability in hydrate-bearing reservoirs is particularly complex compared to conventional reservoirs since it depends on the saturation of gas hydrates and hence, is dynamic during production. The dependence of permeability on hydrate saturation is mathematically represented using permeability-reduction models, which are specific to the expected morphology of hydrate accumulations (such as grain-coating or pore-filling hydrates). In this study, we demonstrate the impact of various permeability-reduction models, and consequently, different morphologies of hydrate deposits on the estimates of gas production using depressurization at the reservoir scale. We observe significant differences in produced water volumes and cumulative mass of produced gas between the models, thereby highlighting the uncertainty in production behavior arising from the ambiguity in the prevalent gas hydrate morphology.

Keywords: gas hydrate morphology, multi-scale modeling, THMC, fluid flow in porous media

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Authors: Pin Yu Chen, Puay Chuan Lee, Yu Jen Loo, Ju Xia Zhang, Deborah Teo, Jack Wei Chieh Tan, Biauw Chi Ong

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Background: Synchronous communication, such as telephone calls, remains the standard communication method between nurses and other healthcare professionals in Singapore public hospitals despite advances in asynchronous technological platforms, such as instant messaging. Although miscommunication is one of the most common causes of lapses in patient care, there is a scarcity of research characterizing baseline inter-professional healthcare communications in a hospital setting due to logistic difficulties. Objective: This study aims to characterize the frequency and patterns of communication behaviours among healthcare professionals. Methods: The one-week observational study was conducted on Monday through Sunday at the nursing station of a cardiovascular medicine and cardiothoracic surgery inpatient ward at the National Heart Centre Singapore. Subjects were shadowed by two physicians for sixteen hours or consecutive morning and afternoon nursing shifts. Communications were logged and characterized by type, duration, caller, and recipient. Results: A total of 1,023 communication events involving the attempted use of the common telephones at the nursing station were logged over a period of one week, corresponding to a frequency of one event every 5.45 minutes (SD 6.98, range 0-56 minutes). Nurses initiated the highest proportion of outbound calls (38.7%) via the nursing station common phone. A total of 179 face-to-face communications (17.5%), 362 inbound calls (35.39%), 481 outbound calls (47.02%), and 1 emergency alert (0.10%) were captured. Average response time for task-oriented communications was 159 minutes (SD 387.6, range 86-231). Approximately 1 in 3 communications captured aimed to clarify patient-related information. The total duration of time spent on synchronous communication events over one week, calculated from total inbound and outbound calls, was estimated to be a total of 7 hours. Conclusion: The results of our study showed that there is a significant amount of time spent on inter-professional healthcare communications via synchronous channels. Integration of patient-related information and use of asynchronous communication channels may help to reduce the redundancy of communications and clarifications. Future studies should explore the use of asynchronous mobile platforms to address the inefficiencies observed in healthcare communications.

Keywords: healthcare communication, healthcare management, nursing, qualitative observational study

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Pitsanu Poonpetpun, Witthaya Mekhum, Warangkana Kongsil

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This research was an attempt to study work motivation of employees in Siam Thai Co., Ltd. The study took place in Rayong with 59 employees as participants. The research tool was questionnaires which consisted of sets of questions about company’s policy, management, executives and good relationship within the firm. The questionnaires style was rating scale with 5 score bands. The questionnaires were analyzed by percentage, frequency, mean and standard deviation. From the study, the result showed that policy and management were in moderate scale, executive and managers were in moderate scale and relationship within the firm were in high scale.

Keywords: motivation, job, performance, employees

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Authors: Claerchille Jhulia Robin

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This paper discusses the perspective of ESL learners towards pronunciation instruction. It sought to determine how these learners view the type of feedback their speech teacher gives and its impact on their own classroom practice of providing feedback. This study utilized a quantitative-qualitative approach to the problem. The respondents were Education students majoring in English. A survey questionnaire and interview guide were used for data gathering. The data from the survey was tabulated using frequency count and the data from the interview were then transcribed and analyzed. Results showed that ESL learners favor immediate corrective feedback and they do not find any issue in being corrected in front of their peers. They also practice the same corrective technique in their own classroom.

Keywords: ESL, feedback, learner perspective, pronunciation instruction

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Authors: M. A. Hafiz, P. T. Matevenga

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Micro-level machining of metals is a developing field which has shown to be a prospective approach to produce features on the parts in the range of a few to a few hundred microns with acceptable machining quality. It is known that the mechanics (i.e. the material removal mechanism) of micro-machining and conventional machining have significant differences due to the scaling effects associated with tool-geometry, tool material and work piece material characteristics. Shape memory alloys (SMAs) are those metal alloys which display two exceptional properties, pseudoelasticity and the shape memory effect (SME). Nickel-titanium (NiTi) alloys are one of those unique metal alloys. NiTi alloys are known to be difficult-to-cut materials specifically by using conventional machining techniques due to their explicit properties. Their high ductility, high amount of strain hardening, and unusual stress–strain behaviour are the main properties accountable for their poor machinability in terms of tool wear and work piece quality. The motivation of this research work was to address the challenges and issues of micro-machining combining with those of machining of NiTi alloy which can affect the desired performance level of machining outputs. To explore the significance of range of cutting conditions on surface roughness and tool wear, machining tests were conducted on NiTi. Influence of different cutting conditions and cutting tools on surface and sub-surface deformation in work piece was investigated. Design of experiments strategy (L9 Array) was applied to determine the key process variables. The dominant cutting parameters were determined by analysis of variance. These findings showed that feed rate was the dominant factor on surface roughness whereas depth of cut found to be dominant factor as far as tool wear was concerned. The lowest surface roughness was achieved at the feed rate of equal to the cutting edge radius where as the lowest flank wear was observed at lowest depth of cut. Repeated machining trials have yet to be carried out in order to observe the tool life, sub-surface deformation and strain induced hardening which are also expecting to be amongst the critical issues in micro machining of NiTi. The machining performance using different cutting fluids and strategies have yet to be studied.

Keywords: nickel titanium, micro-machining, surface roughness, machinability

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Authors: Smita Mathur

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Play is an innate, player-centric, joyful, fundamental activity of early childhood development that significantly contributes to social, emotional, and academic learning. Leveraging the power of play can enhance these domains by creating engaging, interactive, and developmentally appropriate learning experiences for young children. This research aimed to systematically examine young children’s play behaviors with a focus on four primary objectives: (1) the frequency and duration of on-task behaviors, (2) social interactions and emotional expressions during play, (3) the correlation between academic skills and play, and (4) identifying best practices for integrating play-based curricula. To achieve these objectives, a mixed-method study was conducted among young preschool-aged children in low socio-economic populations in the United States. The children were identified using purposive sampling. The children were observed during structured play in classrooms and unstructured play during outdoor playtime and in their home environments. The study sampled 97 preschool-aged children. A total of 3970 minutes of observations were coded to address the research questions. Thirty-seven percent of children lived in linguistically isolated families, and 76% lived in basic budget poverty. Children lived in overcrowded housing situations (67%), and most families had mixed citizenship status (66%). The observational study was conducted using the observation protocol during the Oxford Study Project. On-task behaviors were measured by tracking the frequency and duration of activities where children maintained focus and engagement. In examining social interactions and emotional expressions, the study recorded social interactions, emotional responses, and teacher involvement during play. The study aimed to identify best practices for integrating play-based curricula into early childhood education. By analyzing the effectiveness of different play-based strategies and their impact on on-task behaviors, social-emotional development, and academic skills, the research sought to provide actionable recommendations for educators and caregivers. The findings from study 1. Highlight play behaviors that increase on-task behaviors and academic, & social skills in young children. 2. Offers insights into teacher preparation and designing play-based curriculum 3. Research critiques observation as a data collection technique.

Keywords: play, early childhood education, social-emotional development, academic development

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Authors: Melanie Ostermann, Eivind Birkeland, Ying Xue, Alexander Sauter, Mihaela R. Cimpan

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Background: New reliable and robust techniques to assess biological effects of nanomaterials (NMs) in vitro are needed to speed up safety analysis and to identify key physicochemical parameters of NMs, which are responsible for their acute cytotoxicity. The central aim of this study was to validate and evaluate the applicability and reliability of an impedance-based flow cytometry (IFC) technique for the high-throughput screening of NMs. Methods: Eight inorganic NMs from the European Commission Joint Research Centre Repository were used: NM-302 and NM-300k (Ag: 200 nm rods and 16.7 nm spheres, respectively), NM-200 and NM- 203 (SiO₂: 18.3 nm and 24.7 nm amorphous, respectively), NM-100 and NM-101 (TiO₂: 100 nm and 6 nm anatase, respectively), and NM-110 and NM-111 (ZnO: 147 nm and 141 nm, respectively). The aim was to assess the biological effects of these materials on human monoblastoid (U937) cells. Dispersions of NMs were prepared as described in the NANOGENOTOX dispersion protocol and cells were exposed to NMs at relevant concentrations (2, 10, 20, 50, and 100 µg/mL) for 24 hrs. The change in electrical impedance was measured at 0.5, 2, 6, and 12 MHz using the IFC AmphaZ30 (Amphasys AG, Switzerland). A traditional toxicity assay, Trypan Blue Dye Exclusion assay, and dark-field microscopy were used to validate the IFC method. Results: Spherical Ag particles (NM-300K) showed the highest toxic effect on U937 cells followed by ZnO (NM-111 ≥ NM-110) particles. Silica particles were moderate to non-toxic at all used concentrations under these conditions. A higher toxic effect was seen with smaller sized TiO2 particles (NM-101) compared to their larger analogues (NM-100). No interferences between the IFC and the used NMs were seen. Uptake and internalization of NMs were observed after 24 hours exposure, confirming actual NM-cell interactions. Conclusion: Results collected with the IFC demonstrate the applicability of this method for rapid nanotoxicity assessment, which proved to be less prone to nano-related interference issues compared to some traditional toxicity assays. Furthermore, this label-free and novel technique shows good potential for up-scaling in directions of an automated high-throughput screening and for future NM toxicity assessment. This work was supported by the EC FP7 NANoREG (Grant Agreement NMP4-LA-2013-310584), the Research Council of Norway, project NorNANoREG (239199/O70), the EuroNanoMed II 'GEMN' project (246672), and the UH-Nett Vest project.

Keywords: cytotoxicity, high-throughput, impedance, nanomaterials

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Authors: Raeda F. Abualrub, Amani Abdulnabi

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Aim: The aims of this study were to (a) examine the levels of nurses' political efficacy and involvement in health policy; and (b) explore the relationships between political efficacy, involvement in health policy, and participants’ background variables. Background: Nurses as citizens and health care providers have the right to express their opinions and beliefs in regard to issues that are concerned with the health care system or the public health domain. Methods: A descriptive, cross-sectional design using was utilized. A self-administered questionnaire (Political Efficacy Scale & Involvement in Health Policy Scale) was completed by a convenience sample of 302 nurses. Results: The results of this study showed low levels of involvement in health policy and political efficacy and a positive weak correlation between political efficacy and involvement in health policy. The perceived level of political efficacy was associated positively with nurses’ age and experience. Conclusions: Nurse administrators and managers may empower, support, and encourage nurses to enhance their involvement in health policy. Implications for Nursing Management: The findings have implications for nursing leaders and administrators to design appropriate strategies to enhance nurses’ involvement in health policy development.

Keywords: health policy, Jordan, nurses, political efficacy

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Authors: Song Ni, Junxiang Xu

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This paper concerns quasi-periodic perturbations with parameters of 2-dimensional degenerate systems. If the equilibrium point of the unperturbed system is elliptic-type degenerate. Assume that the perturbation is real analytic quasi-periodic with diophantine frequency. Without imposing any assumption on the perturbation, we can use a path of equilibrium points to tackle with the Melnikov non-resonance condition, then by the Leray-Schauder Continuation Theorem and the Kolmogorov-Arnold-Moser technique, it is proved that the equation has a small response solution for many sufficiently small parameters.

Keywords: quasi-periodic systems, KAM-iteration, degenerate equilibrium point, response solution

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Authors: Yong-Taeg Lee, Jun-Ho Na, Seung-Hun Kim, Seong-Uk Hong

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Damages from noise and vibration are increasing every year, most of which are noises between floors in deteriorated building caused by floor impact sound. In this study, the concrete slab measured vibration impact sound for evaluation floor vibration of deteriorated buildings that fails to satisfy with the minimum thickness. In this experimental study, the vibration scale by impact sound was calibrated and compared with ISO and AIJ standard for vibration. The results show that vibration in slab with thickness used in existing building reach human perception levels.

Keywords: vibration, frequency, accelerometer, concrete slab

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: Khedidja Bouhadef, Imene Said Kouadri, Omar Rahli

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In this paper numerical investigation is performed to analyze natural convection heat transfer characteristics within a wavy-wall enclosure filled with fluid-saturated porous medium. The bottom wall which has the wavy geometry is maintained at a constant high temperature, while the top wall is straight and is maintained at a constant lower temperature. The left and right walls of the enclosure are both straight and insulated. The governing differential equations are solved by Finite-volume approach and grid generation is used to transform the physical complex domain to a computational regular space. The aim is to examine flow field, temperature distribution and heat transfer evolutions inside the cavity when Darcy number, Rayleigh number and undulations number values are varied. The results mainly indicate that the heat transfer is rather affected by the permeability and Rayleigh number values since increasing these values enhance the Nusselt number; although the exchanges are not highly affected by the undulations number.

Keywords: grid generation, natural convection, porous medium, wavy wall enclosure

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Authors: V. Geza, J. Vencels, G. Zageris, S. Pavlovs

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One of the most perspective methods to produce SoG-Si is refinement via metallurgical route. The most critical part of this route is refinement from boron and phosphorus. Therefore, a new approach could address this problem. We propose an approach of creating surface waves on silicon melt’s surface in order to enlarge its area and accelerate removal of boron via chemical reactions and evaporation of phosphorus. A two dimensional numerical model is created which includes coupling of electromagnetic and fluid dynamic simulations with free surface dynamics. First results show behaviour similar to experimental results from literature.

Keywords: numerical modelling, silicon refinement, surface waves, VOF method

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Authors: M. Aruna, Uma Gunasilan

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Hospitals play an ample role in securing the health of a country. Nevertheless, they also have an unhealthy side. Ecological issues strengthen ill-health throughout the domain which subsequently puts pressure on hospital supply chains. Medical waste indeed is hazardous for environment and subsequently for human. The hospital waste management is of immense prominence due to its infectious and hazardous nature that can source many effects on human health and the environment. Government regulations and public cognizance regarding hospital waste issues have imposed hospital units to admit these strategies. The innovative technologies and instruments have been developed to handle hospital wastes. Green supply chain management practices are common in the United States. In India, Green Supply Chain management (GSCM) has just started to be recognized and practiced. GSCM are green, integrated and ecologically optimized. In Green supply chain management environmental sustainability is found to be an important driver. Eleven barriers are identified in this work. Interpretive Structural Modeling (ISM) technique is used for ranking the obstructions.

Keywords: green supply chain management (GSCM), hospital waste management (HWM), interpretive structural modeling (ISM), medical waste (MW)

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Authors: H. Imad, Y. Cheah, O. Aamera

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The aims of this research are to study the mitochondrial non-coding region by using the Sanger sequencing technique and establish the degree of variation characteristics of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. A portion of a non-coding region encompassing positions 37 to 340 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and detected by using the ABI 3730xL DNA Analyzer. New polymorphic positions 57, 63, and 101 are described may in future be suitable sources for identification purpose. The data obtained can be used to identify variable nucleotide positions characterized by frequent occurrence most promising for identification variants.

Keywords: encompassing nucleotide positions 37 to 340, HVII, Iraq, mitochondrial DNA, polymorphism, frequency

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Ali Abdullah Albezaghi

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This article aims to introduce a conceptual framework that can facilitate investigations concerning the role of risk management practices in the relationship between construction risks and the construction project's performance. This article is structured based on the extant literature; it reviews theoretical perspectives, highlights the gaps, and illustrates the significance of developing a framework of suggested relationships. Despite growing interest in the role of risks in construction project performance, previous studies have paid little attention to investigating the moderating role of risk management practices on the risk-performance link. This has left researchers and construction project managers with minimal information to explain the conditions under which risk management practices can reduce the impact of project-related risks and improve performance. In this context, this article suggests a viable research model with propositions that assess risk-performance relationships and discusses the potential moderating effects on the domain relationship. This paper adds to the risk management literature by focusing on risk variables that directly impact performance. Further, it also considers the moderating role of risk management practices in such relationships.

Keywords: risk management practices, external risks, internal risks, project risks, project performance

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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

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Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

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Authors: Erzen Muharemi, Emmanuel De Jaeger, Jos Knockaert

Abstract:

The work presented here investigates the modeling of power electronics converters in terms of their harmonic production. Specifically, it addresses high-frequency emissions in the range of 2-150 kHz, referred to as supraharmonics. This paper models a conventional converter, namely the boost converter used as an active power factor corrector (APFC). Furthermore, the modeling is extended to the case of the interleaved boost converter, which offers advantages such as halving the emissions. Finally, a comparison between the theoretical, numerical, and experimental results will be provided.

Keywords: APFC, boost converter, converter modeling, double fourier series, supraharmonics

Procedia PDF Downloads 27

Authors: Ravi Inder Singh

Abstract:

Due to high heat transfer rate, high carbon utilizing efficiency, fuel flexibilities and other advantages numerous circulating fluidized bed boilers have grown up in India in last decade. Many companies like BHEL, ISGEC, Thermax, Cethar Limited, Enmas GB Power Systems Projects Limited are making CFBC and installing the units throughout the India. Due to complexity many problems exists in CFBC units and only few have been reported. Agglomeration i.e clinker formation in riser, loop seal leg and stripper ash coolers is one of problem industry is facing. Proper documentation is rarely found in the literature. Circulating fluidized bed (CFB) boiler bottom ash contains large amounts of physical heat. While the boiler combusts the low-calorie fuel, the ash content is normally more than 40% and the physical heat loss is approximately 3% if the bottom ash is discharged without cooling. In addition, the red-hot bottom ash is bad for mechanized handling and transportation, as the upper limit temperature of the ash handling machinery is 200 °C. Therefore, a bottom ash cooler (BAC) is often used to treat the high temperature bottom ash to reclaim heat, and to have the ash easily handled and transported. As a key auxiliary device of CFB boilers, the BAC has a direct influence on the secure and economic operation of the boiler. There are many kinds of BACs equipped for large-scale CFB boilers with the continuous development and improvement of the CFB boiler. These ash coolers are water cooled ash cooling screw, rolling-cylinder ash cooler (RAC), fluidized bed ash cooler (FBAC).In this study prototype of a novel stripper ash cooler is studied. The Circulating Fluidized bed Ash Coolers (CFBAC) combined the major technical features of spouted bed and bubbling bed, and could achieve the selective discharge on the bottom ash. The novel stripper ash cooler is bubbling bed and it is visible cold test rig. The reason for choosing cold test is that high temperature is difficult to maintain and create in laboratory level. The aim of study to know the flow pattern inside the stripper ash cooler. The cold rig prototype is similar to stripper ash cooler used industry and it was made after scaling down to some parameter. The performance of a fluidized bed ash cooler is studied using a cold experiment bench. The air flow rate, particle size of the solids and air distributor type are considered to be the key parameters of the operation of a fluidized bed ash cooler (FBAC) are studied in this.

Keywords: CFD, Eulerian-Eulerian, Eulerian-Lagraingian model, parallel simulations

Procedia PDF Downloads 506

Authors: Xin-Yu Shih, Yue-Qu Liu, Hong-Ru Chou

Abstract:

This paper presents a low-area and fully-reconfigurable Fast Fourier Transform (FFT) hardware design for 3GPP-LTE communication standard. It can fully support 32 different FFT sizes, up to 2048 FFT points. Besides, a special processing element is developed for making reconfigurable computing characteristics possible, while first-in first-out (FIFO) scheduling scheme design technique is proposed for hardware-friendly FIFO resource arranging. In a synthesis chip realization via TSMC 40 nm CMOS technology, the hardware circuit only occupies core area of 0.2325 mm² and dissipates 233.5 mW at maximal operating frequency of 250 MHz.

Keywords: reconfigurable, fast Fourier transform (FFT), single-path delay feedback (SDF), 3GPP-LTE

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Authors: Stephen Orimoloye, Jose Horrillo-Caraballo, Harshinie Karunarathna, Dominic E. Reeve

Abstract:

Prediction of wave overtopping is an essential component of coastal seawall designing and management. Not only that excessive overtopping is reported for impermeable seawalls under bimodal waves, but overtopping is also showing a high sensitivity to the peakedness of the random wave propagation patterns. In the present study, we present a comprehensive analysis of the effects of peakedness of bimodal wave patterns of the overtopping of sloping seawalls. An energy-conserved bimodal spectrum with four different spectra peak periods and swell percentages was applied to estimate wave overtopping in both numerical and experimental flumes. Results of incident surface elevations and bimodal spectra were accurately captured across the flume domain using sets of well-positioned resistant-type wave gauges. Peakedness characteristics of the wave patterns were extracted to derive a relationship between the non-dimensional overtopping and the peakedness across the wave groups in the wave series. The full paper will briefly describe the development of the spectrum and present a comprehensive results analysis leading to the derivation of the relationship between dimensionless overtopping and peakedness of bimodal waves.

Keywords: wave overtopping, peakedness, bimodal waves, swell percentages

Procedia PDF Downloads 178