Search results for: wireless body area networks (WBANs)

Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Norbert Csizmadia

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The 21st Century's main power centers are the cities. More than 52% of the world’s population lives in cities, in particular in the megacities which have a population over 10 million people and is still growing. According to various research and forecasts, the main economic concentration will be in 40 megacities and global centers. Based on various competitiveness analyzes and indices, global city centers, and city networks are outlined, but if we look at other aspects of urban development like complexity, connectivity, creativity, technological development, viability, green cities, pedestrian and child friendly cities, creative and cultural centers, cultural spaces and knowledge centers, we get a city competitiveness index with quite new complex indicators. The research shows this result. In addition to the megacities and the global centers, with the investigation of functionality, we got 64 so-called ‘fusiononopolis’ (i.e., fusion-polis) which stand for the most decisive economic power centers of the 21st century. In this city competition Asian centers considerably rise, as the world's functional city competitiveness index is being formed.

Keywords: economic geography, human geography, technological development, urbanism

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Authors: Sibel Daglilar, Isil Kerti, Murat Karagoz, Fatih Dumludag, Oguzhan Gunduz, Faik Nuzhet Oktar

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Hydroxyapatite (HA) materials have common use in bone repairing due to its ability to accelerate the bone growth around the implant. In spite of being a biocompatible and bioactive material, HA has a limited usage as an implant material because of its weak mechanical properties. HA based composites are required to improve the strength and toughness properties of the implant materials without compromising of biocompatibility. The excellent mechanical properties and higher biocompatibilities are expected from each of biomedical composites. In this study, HA composites were synthesized by using bovine bone reinforced doped with different amount of (wt.%) Li2O. The pressed pellets were sintered at various sintering temperatures between 1000ºC and 1300°C, and mechanical, electrical properties of the obtained products were characterized. In addition to that, in vitro stimulated body fluid (SBF) tests for these samples were conducted. The most suitable composite composition for biomedical applications was discussed among the composites studied.

Keywords: biocomposites, sintering temperature, biocompatibility, electrical property, conductivity, mechanical property

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Authors: Saurabh Parkhedkar, Rajanikant Tenguria

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The paper proposes revamping the public transportation system in Mumbai with the use of Radio Frequency Identification (RFID) technology in order to provide better integration and compatibility across various modes of transport. In Mumbai, mass transport system suffers from poor inter-compatible ticketing system, subpar money collection techniques, and lack of planning for optimum utilization of resources. Development of suburbs and growth in population will result in growing demand for mass transportation networks. Hence, the growing demand for the already overburdened public transportation system is only going to worsen the scenario. Thus, a superior system is essential in order to regulate, manage and supervise future transportation needs. The proposed RFID based system integrates Mumbai Suburban Railway, BEST (Brihanmumbai Electric Supply and Transport Undertaking transport wing) Bus, Mumbai Monorail and Mumbai Metro systems into a Unified Public Transportation System (UPTS). The UTPS takes into account various drawbacks of the present day system and offers solution, suitable for the modern age Mumbai.

Keywords: urbanization, transportation, RFID, Mumbai, public transportation, smart city.

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Authors: Yinsheng Zhang

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Changes in the extent and amount of snow cover in Eurasia are of great interest because of their vital impacts on the global climate system and regional water resource management. This study investigated the spatial and temporal variability of the snow cover extent (SCE) and snow water equivalent (SWE) of continental Eurasia using the Northern Hemisphere Equal-Area Scalable Earth Grid (EASE-Grid) Weekly SCE data for 1972–2006 and the Global Monthly EASE-Grid SWE data for 1979–2004. The results indicated that, in general, the spatial extent of snow cover significantly decreased during spring and summer, but varied little during autumn and winter over Eurasia in the study period. The date at which snow cover began to disappear in spring has significantly advanced, whereas the timing of snow cover onset in autumn did not vary significantly during 1972–2006. The snow cover persistence period declined significantly in the western Tibetan Plateau as well as the partial area of Central Asia and northwestern Russia but varied little in other parts of Eurasia. ‘Snow-free breaks’ (SFBs) with intermittent snow cover in the cold season were mainly observed in the Tibetan Plateau and Central Asia, causing a low sensitivity of snow cover persistence period to the timings of snow cover onset and disappearance over the areas with shallow snow. The averaged SFBs were 1–14 weeks in the Tibetan Plateau during 1972–2006 and the maximum intermittence could reach 25 weeks in some extreme years. At a seasonal scale, the SWE usually peaked in February or March but fell gradually since April across Eurasia. Both annual mean and annual maximum SWE decreased significantly during 1979–2004 in most parts of Eurasia except for eastern Siberia as well as northwestern and northeastern China.

Keywords: Eurasia, snow cover extent, snow cover persistence period, snow-free breaks, onset and disappearance timings, snow water equivalent

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Authors: Fariba Ebrahimi, Mehdi Ghorbani

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Achieving to integrated Water management fundamentally needs to effective relation, coordination, collaboration and synergy among various actors who have common but different responsibilities. In this sense, the foundation of comprehensive and integrated management is not compatible with centralization and top-down strategies. The aim of this paper is analysis institutional network of water relevant stakeholders and water policy monitoring in Shemiranat. In this study collaboration networks between informal and formal institutions co-management process have been investigated. Stakeholder network analysis as a quantitative method has been implicated in this research. The results of this study indicate that institutional cohesion is medium; sustainability of institutional network is about 40 percent (medium). Additionally the core-periphery index has measured in this study according to reciprocity index. Institutional capacities for integrated natural resource management in regional level are measured in this study. Furthermore, the necessity of centrality reduction and promote stakeholders relations and cohesion are emphasized to establish a collaborative natural resource governance.

Keywords: policy monitoring, water management, social network, stakeholder, shemiranat

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Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Sombol Mokhles

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Tackling climate change requires expanding networking opportunities between a diverse range of cities to accelerate climate actions. Existing climate city networks have limitations in actively engaging “ordinary” cities in networking processes between cities, as they encourage a few powerful cities to be followed by the many “ordinary” cities. To reimagine the networking opportunities between cities beyond global cities, this paper incorporates “cosmopolitan comparison” to expand our knowledge of a diverse range of cities using a data-driven approach. Through a cosmopolitan perspective, a framework is presented on how to utilise large data to expand knowledge of cities beyond global cities to reimagine the existing hierarchical networking practices. The contribution of this framework is beyond urban climate governance but inclusive of different fields which strive for a more inclusive and cosmopolitan comparison attentive to the differences across cities.

Keywords: cosmopolitan city comparison, data-driven approach, climate city networking, urban climate governance

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Kleiner Marques Marra, Tércio Pedrosa

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This paper reports the production of uranium-molybdenum alloys, which have been considered promising fuel for test and research nuclear reactors. U-Mo alloys were produced in three molybdenum contents: 5 wt.%, 7 wt.%, and 10 wt.%, using an electric vacuum induction furnace. A boron nitride-coated graphite crucible was employed in the production of the alloys and, after melting, the material was immediately poured into a boron nitride-coated graphite mold. The incorporation of carbon was observed, but it happened in a lower intensity than in the case of the non-coated crucible/mold. It is observed that the carbon incorporation increased and alloys density decreased with Mo addition. It was also noticed that the increase in the carbon or molybdenum content did not seem to change the as-cast structure in terms of granulation. The three alloys presented body-centered cubic crystal structure (g phase), after solidification, besides a seeming negative microsegregation of molybdenum, from the center to the periphery of the grains. There were signs of macrosegregation, from the base to the top of the ingots.

Keywords: uranium-molybdenum alloys, incorporation of carbon, solidification, macrosegregation and microsegregation

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

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Authors: Chang Hung Chen

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Typically the Cause-Related Marketing (CRM) is effective for promoting products, and is also accepted as a role of communication tool for creating a positive image of the corporate. Today, companies are taking Corporate Social Responsibility (CSR) as core activities to build a goal of sustainable development. CRM is not a synonym of CSR. Actually, CRM is a part of CSR, or a type of marketing strategy in CSR framework. This article focuses on the relationship between CSR and CRM, and how the CRM improves the CSR performance of the corporate. The research was conducted through review of literature on the subject area.

Keywords: cause-related marketing, corporate social responsibility, corporate image, consumer behavior

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Authors: F. U. Rahman, R. Q. Zhang

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This work aims to develop a systematic numerical technique which can be easily extended to many-body problem. The Lippmann Schwinger equation (integral form of the Schrodinger wave equation) is solved for the nonrelativistic radial wave of hydrogen atom using iterative integration scheme. As the unknown wave function appears on both sides of the Lippmann Schwinger equation, therefore an approximate wave function is used in order to solve the equation. The Green’s function is obtained by the method of Laplace transform for the radial wave equation with excluded potential term. Using the Lippmann Schwinger equation, the product of approximate wave function, the Green’s function and the potential term is integrated iteratively. Finally, the wave function is normalized and plotted against the standard radial wave for comparison. The outcome wave function converges to the standard wave function with the increasing number of iteration. Results are verified for the first fifteen states of hydrogen atom. The method is efficient and consistent and can be applied to complex systems in future.

Keywords: Green’s function, hydrogen atom, Lippmann Schwinger equation, radial wave

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Luke Taylor, Samantha J. Hall, Kenneth I. Cumming, Jakki Bardsley, Scott S. P. Wildman

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Medway School of Pharmacy, as part of an Equality Diversity and Inclusivity (EDI) initiative run by the University of Kent, decided to take steps to try and negate disparities in numeracy competencies within students undertaking the Master of Pharmacy degree in order to combat a trend in pharmacy students’ numerical abilities upon entry. This included a research driven project 1) to identify if pharmacy students are aware of weaknesses in their numeracy capabilities, and 2) recognise where their numeracy skillset is lacking. In addition to gaining this student perspective, a number of actions have been implemented to support students in improving their numeracy competencies. Reflective and quantitative analysis has shown promising improvements for the final year cohort of 2014/15 when compared to previous years. The method of involving student feedback into the structure of numeracy teaching/support has proven to be extremely beneficial to both students and teaching staff alike. Students have felt empowered and in control of their own learning requirements, leading to increased engagement and attainment. School teaching staff have received quality data to help improve existing initiatives and to innovate further in the area of numeracy teaching. In light of the recognised improvements, further actions are currently being trialled in the area of numeracy support. This involves utilising Virtual Learning Environment platforms to provide individualised support as a supplement to the increased numeracy mentoring (staff and peer) provided to students. Mentors who provide group or one-to-one sessions are now given significant levels of training in dealing with situations that commonly arise from mentoring schemes. They are also provided with continued support throughout the life of their degree. Following results from this study, Medway School of Pharmacy hopes to drive increasing numeracy standards within Pharmacy (primarily through championing peer mentoring) as well as other healthcare professions including Midwifery and Nursing.

Keywords: attainment, ethnicity, numeracy, pharmacy, support

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Authors: Anil Saini, Jatinder Kumar Ratan

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Now a day, the key issue for the scientific community is to devise the innovative technologies for sustainable control of urban pollution. In urban cities, a large surface area of the masonry structures, buildings, and pavements is exposed to the open environment, which may be utilized for the control of air pollution, if it is built from the photocatalytically active cement-based constructional materials such as concrete, mortars, paints, and blocks, etc. The photocatalytically active cement is formulated by incorporating a photocatalyst in the cement matrix, and such cement is generally known as self-cleaning cement In the literature, self-cleaning cement has been synthesized by incorporating nanosized-TiO₂ (n-TiO₂) as a photocatalyst in the formulation of the cement. However, the utilization of n-TiO₂ for the formulation of self-cleaning cement has the drawbacks of nano-toxicity, higher cost, and agglomeration as far as the commercial production and applications are concerned. The use of microsized-TiO₂ (m-TiO₂) in place of n-TiO₂ for the commercial manufacture of self-cleaning cement could avoid the above-mentioned problems. However, m-TiO₂ is less photocatalytically active as compared to n- TiO₂ due to smaller surface area, higher band gap, and increased recombination rate. As such, the use of m-TiO₂ in the formulation of self-cleaning cement may lead to a reduction in photocatalytic activity, thus, reducing the self-cleaning, depolluting, and antimicrobial abilities of the resultant cement material. So improvement in the photoactivity of m-TiO₂ based self-cleaning cement is the key issue for its practical applications in the present scenario. The current work proposes the use of surface-fluorinated m-TiO₂ for the formulation of self-cleaning cement to enhance its photocatalytic activity. The calcined dolomite, a constructional material, has also been utilized as co-adsorbent along with the surface-fluorinated m-TiO₂ in the formulation of self-cleaning cement to enhance the photocatalytic performance. The surface-fluorinated m-TiO₂, calcined dolomite, and the formulated self-cleaning cement were characterized using diffuse reflectance spectroscopy (DRS), X-ray diffraction analysis (XRD), field emission-scanning electron microscopy (FE-SEM), energy dispersive x-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), BET (Brunauer–Emmett–Teller) surface area, and energy dispersive X-ray fluorescence spectrometry (EDXRF). The self-cleaning property of the as-prepared self-cleaning cement was evaluated using the methylene blue (MB) test. The depolluting ability of the formulated self-cleaning cement was assessed through a continuous NOX removal test. The antimicrobial activity of the self-cleaning cement was appraised using the method of the zone of inhibition. The as-prepared self-cleaning cement obtained by uniform mixing of 87% clinker, 10% calcined dolomite, and 3% surface-fluorinated m-TiO₂ showed a remarkable self-cleaning property by providing 53.9% degradation of the coated MB dye. The self-cleaning cement also depicted a noteworthy depolluting ability by removing 5.5% of NOx from the air. The inactivation of B. subtiltis bacteria in the presence of light confirmed the significant antimicrobial property of the formulated self-cleaning cement. The self-cleaning, depolluting, and antimicrobial results are attributed to the synergetic effect of surface-fluorinated m-TiO₂ and calcined dolomite in the cement matrix. The present study opens an idea and route for further research for acile and economical formulation of self-cleaning cement.

Keywords: microsized-titanium dioxide (m-TiO₂), self-cleaning cement, photocatalysis, surface-fluorination

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Authors: Neha Adsul, Rohit Shah

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Background: The global history of nursing is exclusively a history of deep contradictions as it seeks to negotiate inclusion in an already gendered world. Although a powerful 'clinical gaze exists, nurses have toiled to re-negotiate and subvert the 'medical gaze' by practicing the 'therapeutic gaze' to tether back 'care into nursing practice.' This helps address the duality of the 'body' and 'mind' wherein the patient is not just limited to being an object of medical inquiry. Nevertheless, there has been a consistent effort to fit 'nursing' into being an art or an emerging science over the years. Especially with advances in hospital-based techno-centric medical practices, the boundaries between technology and nursing practices are becoming more blurred as the technical process becomes synonymous with nursing, eroding the essence of nursing care. Aim: This paper examines the history of nursing and offers insights into how gendered relations and the ideological belief of 'nursing as gendered work' have propagated to the subjugation of the nursing profession. It further aims to provide insights into the patriarchally imbibed techno-centrism that negates the gendered caregiving which lies at the crux of a nurse's work. Method: A literature search was carried out using Google Scholar, Web of Science and PubMed databases. Search words included: technology and nursing, medical technology and nursing, history of nursing, sociology and nursing and nursing care. The history of nursing is presented in a discussion that weaves together the historical events of the 'Birth of the Clinic' and the shift from 'bed-side medicine' to 'hospital-based medicine' that legitimizes exploitation of the bodies of patients to the 'medical gaze while the emergence of nursing as acquiescent to instrumental, technical, positivist and dominant views of medicine. The resultant power asymmetries, wherein in contemporary nursing, the constant struggle of nurses to juggle between being the physicians "operational right arm" to harboring that subjective understanding of the patients to refrain from de-humanizing nursing-care. Findings: The nursing profession suffers from being rendered invisible due to gendered relations having patrifocal societal roots. This perpetuates a notion rooted in the idea that emphasizes empiricism and has resulted in theoretical and epistemological fragmentation of the understanding of body and mind as separate entities. Nurses operate within this structure while constantly being at the brink of being pushed beyond the legitimate professional boundaries while being labeled as being 'unscientific' as the work does not always corroborate and align with the existing dominant positivist lines of inquiries. Conclusion: When understood in this broader context of how nursing as a practice has evolved over the years, it provides a particularly crucial testbed for understanding contemporary gender relations. Not because nurses like to live in a gendered work trap but because the gendered relations at work are written in a covert narcissistic patriarchal milieu that fails to recognize the value of intangible yet utmost necessary 'caring work in nursing. This research urges and calls for preserving and revering the humane aspect of nursing care alongside the emerging tech-savvy expectations from nursing work.

Keywords: nursing history, technocentric, power relations, scientific duality

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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Authors: Yousef Abu Nahleh, Alhasan Hakami, Arun Kumar, Fugen Daver

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This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data.

Keywords: Emergency Safety Stocks, safety stocks, Order Quantity Model, supply chain

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Authors: In-Sung Lee, Un-Hwan Park, Jun-Hyeok Heo, Tae-Hyeon Oh, Dae-Gyu Park

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Statistical Energy Analysis is to be the most effective CAE Method for air-born noise analysis in the Automotive area. This study deals with a method to predict the noise level inside of the car under the steady-state condition using the SEA model of car for air-born noise analysis. We can identify weakened part due to the acoustic material properties using it. Therefore, it is useful for the material structural design.

Keywords: air-born noise, material structural design, acoustic material properties, absorbing

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Authors: Shuting Ji, Yueming Zhang, Jing Zhao

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The output error of the globoidal cam mechanism can be considered as a relevant indicator of mechanism performance, because it determines kinematic and dynamical behavior of mechanical transmission. Based on the differential geometry and the rigid body transformations, the mathematical model of surface geometry of the globoidal cam is established. Then we present the analytical expression of the output error (including the transmission error and the displacement error along the output axis) by considering different manufacture and assembly errors. The effects of the center distance error, the perpendicular error between input and output axes and the rotational angle error of the globoidal cam on the output error are systematically analyzed. A globoidal cam mechanism which is widely used in automatic tool changer of CNC machines is applied for illustration. Our results show that the perpendicular error and the rotational angle error have little effects on the transmission error but have great effects on the displacement error along the output axis. This study plays an important role in the design, manufacture and assembly of the globoidal cam mechanism.

Keywords: globoidal cam mechanism, manufacture error, transmission error, automatic tool changer

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Authors: Safitri Nur Wulandari, M. Ivan Adi Perdana, Prathisto L. Panuntun Unggul, R. Dary Wira Mahadika

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In road construction on the soft soil, we need a soil improvement method to improve the soil bearing capacity of the land base so that the soil can withstand the traffic loads. Most of the land in Indonesia has a soft soil, where soft soil is a type of clay that has the consistency of very soft to medium stiff, undrained shear strength, Cu <0:25 kg/cm2, or the estimated value of NSPT <5 blows/ft. This study focuses on the analysis of the effect on preloading load (embarkment) to the amount of settlement ratio on the under of embarkment that will impact on the building cracks around of embarkment. The method used in this research is a superposition method for embarkment distribution on 27 locations with undisturbed soil samples at some borehole point in Java and Kalimantan, Indonesia. Then correlating the results of settlement plate monitoring on the field with Asaoka method. The results of settlement plate monitoring taken from an embarkment of Ahmad Yani airport in Semarang on 32 points. Where the value of Cc (index compressible) soil data based on some laboratory test results, while the value of Cc is not tested obtained from empirical formula Ardhana and Mochtar, 1999. From this research, the results of the field monitoring showed almost the same results with an empirical formulation with the standard deviation of 4% where the formulation of the empirical results of this analysis obtained by linear formula. Value empirical linear formula is to determine the effect of compression heap area as high as 4,25 m is 3,1209x + y = 0.0026 for the slope of the embankment 1: 8 for the same analysis with an initial height of embankment on the field. Provided that at the edge of the embankment settlement worth is not equal to 0 but at a quarter of embankment has a settlement ratio average 0.951 and at the edge of embankment has a settlement ratio 0,049. The influence areas around of embankment are approximately 1 meter for slope 1:8 and 7 meters for slope 1:2. So, it can cause the building cracks, to build in sustainable development.

Keywords: building cracks, influence area, settlement plate, soft soil, empirical formula, embankment

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Authors: Jens Ehm

Abstract:

Manufacturing in supply chains requires an efficient organisation of production and transport processes in order to guarantee the supply of all partners within the chain with the material that is needed for the reliable fulfilment of tasks. If one partner is not able to supply products for a certain period, these products might be missing as the working material for the customer to perform the next manufacturing step, potentially as supply for further manufacturing steps. This way, local disruptions can influence the whole supply chain. In order to avoid material shortages, an efficient scheduling of tasks is necessary. However, the occurrence of unexpected disruptions cannot be eliminated, so that a modification of the schedule should be arranged as fast as possible. This paper discusses the challenges for the implementation of real-time scheduling and control methods and presents a graph-based approach that enables the integrated scheduling of production and transport processes for multiple supply chain partners and offers the potential for quick adaptations to parts of the initial schedule.

Keywords: production, logistics, integrated scheduling, real-time scheduling

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Authors: Leo Laine, Morgan Johansson

Abstract:

To meet the civilizations future needs for safe living and low environmental footprint, the engineers designing the complex systems of tomorrow will need efficient ways to model and optimize these systems for their intended purpose. For example, a civil defence shelter and its subsystem components needs to withstand, e.g. airblast and ground shock from decided design level explosion which detonates with a certain distance from the structure. In addition, the complex civil defence shelter needs to have functioning air filter systems to protect from toxic gases and provide clean air, clean water, heat, and electricity needs to also be available through shock and vibration safe fixtures and connections. Similar complex building systems can be found in any concentrated living or office area. In this paper, the authors use a multidomain modelling language called Modelica to model a concrete wall as a single degree of freedom (SDOF) system with elastoplastic properties with the implemented option of plastic hardening. The elastoplastic model was developed and implemented in the open source tool OpenModelica. The simulation model was tested on the case with a transient equivalent reflected pressure time history representing an airblast from 100 kg TNT detonating 15 meters from the wall. The concrete wall is approximately regarded as a concrete strip of 1.0 m width. This load represents a realistic threat on any building in a city like area. The OpenModelica model results were compared with an Excel implementation of a SDOF model with an elastic-plastic spring using simple fixed timestep central difference solver. The structural displacement results agreed very well with each other when it comes to plastic displacement magnitude, elastic oscillation displacement, and response times.

Keywords: airblast from explosives, elastoplastic spring model, Modelica modelling language, SDOF, structural response of concrete structure

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Authors: Zhaoxin Luo, Michael Zhu

Abstract:

In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Proud Arunrangsiwed, Sarinya Kongtieng

Abstract:

Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: meta-regression analysis, social networking sites, academic Performances, multitasking, motivation

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Authors: Francesca Nicolosi, Teresa Cosola

Abstract:

Climate changes in Mediterranean areas, such as the increase of average seasonal temperatures, the urban heat island phenomenon, the intensification of solar radiation and the extreme weather threats, cause disruption events, so that climate adaptation has become a pressing issue. Due to the strategic role that the built heritage holds in terms of environmental impact and energy waste and its potentiality, it is necessary to assess the vulnerability and the adaptive capacity of the existing building to climate change, in order to define different mitigation scenarios. The aim of this research work is to define an optimized and integrated methodology for the assessment of resilience levels and adaptation scenarios for existing buildings in Mediterranean urban areas. Moreover, the study of resilience indicators allows us to define building environmental and energy performance in order to identify the design and technological solutions for the improvement of the building and its urban area potentialities. The methodology identifies step-by-step different phases, starting from the detailed study of characteristic elements of urban system: climatic, natural, human, typological and functional components are analyzed in their critical factors and their potential. Through the individuation of the main perturbing factors and the vulnerability degree of the system to the risks linked to climate change, it is possible to define mitigation and adaptation scenarios. They can be different, according to the typological, functional and constructive features of the analyzed system, divided into categories of intervention, and characterized by different analysis levels (from the single building to the urban area). The use of software simulations allows obtaining information on the overall behavior of the building and the urban system, to generate predictive models in the medium and long-term environmental and energy retrofit and to make a comparative study of the mitigation scenarios identified. The studied methodology is validated on a case study.

Keywords: climate impact mitigation, energy efficiency, existing building heritage, resilience

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Authors: Lise Alonso, Audrey Dubost, Patricia Luis, Thomas Pommier, Yvan Moënne-Loccoz

Abstract:

The Lascaux Cave in South-Est France is an archeological landmark renowned for its Paleolithic paintings dating back c.18.000 years. Extensive touristic frequenting and repeated chemical treatments have resulted in the development of microbial stains on cave walls, which is a major issue in terms of art conservation. Therefore, it is of prime importance to better understand the microbiology specific to the Lascaux Cave, in comparison to regional situations. To this end, we compared the microbial community (i.e. both prokaryotic and eukaryotic microbial populations) of Lascaux Cave with three other anthropized Périgord caves as well as three pristine caves from the same area. We used state-of-the-art metagenomic analyses of cave wall samples to obtain a global view of the composition of the microbial community colonizing cave walls. We measured the relative abundance and diversity of four DNA markers targeting different fractions of the ribosomal genes of bacteria (i.e. eubacteria), archaea (i.e. archeobacteria), fungi and other micro-eukaryotes. All groups were highly abundant and diverse in all Périgord caves, as several hundred genera of microorganisms were identified in each. However, Lascaux Cave displayed a specify microbial community, which differed from those of both pristine and anthropized caves. Comparison of stains versus non-stained samples from the Passage area of the Lascaux Cave indicated that a few taxa (e.g. the Sordiaromycetes amongst fungi) were more prevalent within than outside stains, yet the main difference was in the relative proportion of the different microbial taxonomic groups and genera, which supposedly supports the biological origin of the stains. Overall, metagenomic sequencing of cave wall samples was effective to evidence the large colonization of caves by a diversified range of microorganisms. It also showed that Lascaux Cave represented a very particular situation in comparison with neighboring caves, probably in relation to the extent of disturbance it had undergone. Our results provide key baseline information to guide conservation efforts in anthropized caves such as Lascaux and pave the way to modern monitoring of ornamented caves.

Keywords: cave conservation, Lascaux cave, microbes, paleolithic paintings

Procedia PDF Downloads 240