Search results for: network intrusion detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7720

Search results for: network intrusion detection

880 The Influence of Travel Experience within Perceived Public Transport Quality

Authors: Armando Cartenì, Ilaria Henke

Abstract:

The perceived public transport quality is an important driver that influences both customer satisfaction and mobility choices. The competition among transport operators needs to improve the quality of the services and identify which attributes are perceived as relevant by passengers. Among the “traditional” public transport quality attributes there are, for example: travel and waiting time, regularity of the services, and ticket price. By contrast, there are some “non-conventional” attributes that could significantly influence customer satisfaction jointly with the “traditional” ones. Among these, the beauty/aesthetics of the transport terminals (e.g. rail station and bus terminal) is probably one of the most impacting on user perception. Starting from these considerations, the point stressed in this paper was if (and how munch) the travel experience of the overall travel (e.g. how long is the travel, how many transport modes must be used) influences the perception of the public transport quality. The aim of this paper was to investigate the weight of the terminal quality (e.g. aesthetic, comfort and service offered) within the overall travel experience. The case study was the extra-urban Italian bus network. The passengers of the major Italian terminal bus were interviewed and the analysis of the results shows that about the 75% of the travelers, are available to pay up to 30% more for the ticket price for having a high quality terminal. A travel experience effect was observed: the average perceived transport quality varies with the characteristic of the overall trip. The passengers that have a “long trip” (travel time greater than 2 hours) perceived as “low” the overall quality of the trip even if they pass through a high quality terminal. The opposite occurs for the “short trip” passengers. This means that if a traveler passes through a high quality station, the overall perception of that terminal could be significantly reduced if he is tired from a long trip. This result is important and if confirmed through other case studies, will allow to conclude that the “travel experience impact" must be considered as an explicit design variable for public transport services and planning.

Keywords: transportation planning, sustainable mobility, decision support system, discrete choice model, design problem

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879 New Suspension Mechanism for a Formula Car using Camber Thrust

Authors: Shinji Kajiwara

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The basic ability of a vehicle is the ability to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle is vital in automotive engineering. Stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswind and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle especially with the worrying increase of vehicle collision every day. With better safety performance on a vehicle, every driver will be more confidence driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in four-wheel vehicle especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on performance of both suspension systems.

Keywords: automobile, camber thrust, cornering force, suspension

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878 Analyzing the Performance of Different Cost-Based Methods for the Corrective Maintenance of a System in Thermal Power Plants

Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

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877 Cultural Regeneration and Social Impacts of Industrial Heritage Transformation: The Case of Westergasfabriek Cultural Park, Netherland

Authors: Hsin Hua He

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The purpose of this study is to strengthen the social cohesion of the local community by injecting the cultural and creative concept into the industrial heritage transformation. The paradigms of industrial heritage research tend to explore from the perspective of space analysis, which concerned less about the cultural regeneration and the development of local culture. The paradigms of cultural quarter research use to from the perspective of creative economy and urban planning, concerned less about the social impacts and the interaction between residents and industrial sites. This research combines these two research areas of industrial heritage and cultural quarter, and focus on the social and cultural aspects. The transformation from the industrial heritage into a cultural park not only enhances the cultural capital and the quality of residents’ lives, but also preserves the unique local values. Internally it shapes the local identity, while externally establishes the image of the city. This paper uses Westergasfabriek Cultural Park in Amsterdam as the case study, through literature analysis, field work, and depth interview to explore how the cultural regeneration transforms industrial heritage. In terms of the planners’ and residents’ point of view adopt the theory of community participation, social capital, and sense of place to analyze the social impact of the industrial heritage transformation. The research finding is through cultural regeneration policies like holding cultural activities, building up public space, social network and public-private partnership, and adopting adaptive reuse to fulfil the people’s need and desire and reach the social cohesion. Finally, the study will examine the transformation of Taiwan's industrial heritage into cultural and creative quarters. The results are expected to use the operating experience of the Amsterdam cases and provide directions for Taiwan’s industrial heritage management to meet the cultural, social, economic symbiosis.

Keywords: cultural regeneration, community participation, social capital, sense of place, industrial heritage transformation

Procedia PDF Downloads 500
876 A Benchmark System for Testing Medium Voltage Direct Current (MVDC-CB) Robustness Utilizing Real Time Digital Simulation and Hardware-In-Loop Theory

Authors: Ali Kadivar, Kaveh Niayesh

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The integration of green energy resources is a major focus, and the role of Medium Voltage Direct Current (MVDC) systems is exponentially expanding. However, the protection of MVDC systems against DC faults is a challenge that can have consequences on reliable and safe grid operation. This challenge reveals the need for MVDC circuit breakers (MVDC CB), which are in infancies of their improvement. Therefore will be a lack of MVDC CBs standards, including thresholds for acceptable power losses and operation speed. To establish a baseline for comparison purposes, a benchmark system for testing future MVDC CBs is vital. The literatures just give the timing sequence of each switch and the emphasis is on the topology, without in-depth study on the control algorithm of DCCB, as the circuit breaker control system is not yet systematic. A digital testing benchmark is designed for the Proof-of-concept of simulation studies using software models. It can validate studies based on real-time digital simulators and Transient Network Analyzer (TNA) models. The proposed experimental setup utilizes data accusation from the accurate sensors installed on the tested MVDC CB and through general purpose input/outputs (GPIO) from the microcontroller and PC Prototype studies in the laboratory-based models utilizing Hardware-in-the-Loop (HIL) equipment connected to real-time digital simulators is achieved. The improved control algorithm of the circuit breaker can reduce the peak fault current and avoid arc resignation, helping the coordination of DCCB in relay protection. Moreover, several research gaps are identified regarding case studies and evaluation approaches.

Keywords: DC circuit breaker, hardware-in-the-loop, real time digital simulation, testing benchmark

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875 Identification of Damage Mechanisms in Interlock Reinforced Composites Using a Pattern Recognition Approach of Acoustic Emission Data

Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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874 A Study of the Attitude Towards Marriage among Young Adults in Indian and Tibetan Society Which Impacted in Social Learning and Cross-Cultural Behavior

Authors: Meenakshi Chaubey

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A principle proposed in the cross-cultural adaption of behavior among Indian and Tibetan societies in which there are not any great variations between their young adults on the mindset of day-to-day marriage, Marriage plays a dominant position in constructing the society, which in large part comprises underneath the domain of lifestyle. Way of life is a social behavior and norm located in human societies where an extensive range of phenomena can be transmitted thru social studying. It acts characteristic of the individual has been the diploma day-to-day which they have got cultivated a specific stage of class in arts, science, architecture. The existing studies preliminarily on young adults of each community, wherein we carried out a comparative observe of the mindset of daily marriage among Indian and Tibetan teens. Further, we studied statistics comprehensively on the mindset closer day by day the marriage between Indian adult males and Tibetan younger males. With the extension of a complete look, we considered the mindset of an everyday marriage of Indian girls and Tibetan young ladies. Studies 1 showed that there might be no sizable distinction within the attitude of the day-to-day marriage of Indian and Tibetan teenagers. It, in addition, showed that they followed each different marriage beliefs and customs. Studies 2 showed that there might be no important difference in the attitude toward the everyday marriage of Indian and Tibetan young males. It similarly showcased that day-to-day secular schooling gadget in Tibetan society complements their clinical approach and changes their point of view on distinct social issues along with marriage. Research three confirmed that there is no substantial difference in the mindset of the daily marriage of Indian and Tibetan younger females. It similarly spread out the strict authorities' recommendations that they may no longer be allowed day-to-day comply with their marriage practices, including polygamy and polyandry. Thus, the information showed that there's a shift of lifestyle from one network every day to some other community because of social every day, which affects the conduct and results of daily past cultural adaptation.

Keywords: culture, marriage, attitude, society, young adults, Indian, Tibetan

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873 Platelet Volume Indices: Emerging Markers of Diabetic Thrombocytopathy

Authors: Mitakshara Sharma, S. K. Nema

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Diabetes mellitus (DM) is metabolic disorder prevalent in pandemic proportions, incurring significant morbidity and mortality due to associated vascular angiopathies. Platelet related thrombogenesis plays key role in pathogenesis of these complications. Most patients with type II DM suffer from preventable vascular complications and early diagnosis can help manage these successfully. These complications are attributed to platelet activation which can be recognised by the increase in Platelet Volume Indices(PVI) viz. Mean Platelet Volume(MPV) and Platelet Distribution Width(PDW). This study was undertaken with the aim of finding a relationship between PVI and vascular complications of Diabetes mellitus, their importance as a causal factor in these complications and use as markers for early detection of impending vascular complications in patients with poor glycaemic status. This is a cross-sectional study conducted for 2 years with total 930 subjects. The subjects were segregated in 03 groups on basis of glycosylated haemoglobin (HbA1C) as: - (a) Diabetic, (b) Non-Diabetic and (c) Subjects with Impaired fasting glucose(IFG) with 300 individuals in IFG and non-diabetic group & 330 individuals in diabetic group. The diabetic group was further divided into two groups: - (a) Diabetic subjects with diabetes related vascular complications (b) Diabetic subjects without diabetes related vascular complications. Samples for HbA1C and platelet indices were collected using Ethylene diamine tetracetic acid(EDTA) as anticoagulant and processed on SYSMEX-XS-800i autoanalyser. The study revealed stepwise increase in PVI from non-diabetics to IFG to diabetics. MPV and PDW of diabetics, IFG and non diabetics were 17.60 ± 2.04, 11.76 ± 0.73, 9.93 ± 0.64 and 19.17 ± 1.48, 15.49 ± 0.67, 10.59 ± 0.67 respectively with a significant p value 0.00 and a significant positive correlation (MPV-HbA1c r = 0.951; PDW-HbA1c r = 0.875). However, significant negative correlation was found between glycaemic levels and total platelet count (PC- HbA1c r =-0.164). MPV & PDW of subjects with and without diabetes related complications were (15.14 ± 1.04) fl & (17.51±0.39) fl and (18.96 ± 0.83) fl & (20.09 ± 0.98) fl respectively with a significant p value 0.00.The current study demonstrates raised platelet indices & reduced platelet counts in association with rising glycaemic levels and diabetes related vascular complications across various study groups & showed that platelet morphology is altered with increasing glycaemic levels. These changes can be known by measurements of PVI which are important, simple, cost effective, effortless tool & indicators of impending vascular complications in patients with deranged glycaemic control. PVI should be researched and explored further as surrogate markers to develop a clinical tool for early recognition of vascular changes related to diabetes and thereby help prevent them. They can prove to be more useful in developing countries with limited resources. This study is multi-parameter, comprehensive with adequately powered study design and represents pioneering effort in India on account of the fact that both Platelet indices (MPV & PDW) along with platelet count have been evaluated together for the first time in Diabetics, non diabetics, patients with IFG and also in the diabetic patients with and without diabetes related vascular complications.

Keywords: diabetes, HbA1C, IFG, MPV, PDW, PVI

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872 Authentic and Transformational Leadership Model of the Directors of Tambon Health Promoting Hospitals Effecting to the Effectiveness of Southern Tambon Health Promoting Hospitals: The Interaction and Invariance Tests of Gender Factor

Authors: Suphap Sikkhaphan, Muwanga Zake, Johnnie Wycliffe Frank

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The purposes of the study included a) investigating the authentic and transformational leadership model of the directors of tambon health promoting hospitals b) evaluating the relation between the authentic and transformation leadership of the directors of tambon health promoting hospitals and the effectiveness of their hospitals and c) assessing the invariance test of the authentic and transformation leadership of the directors of tambon health promoting hospitals. All 400 southern tambon health promoting hospital directors were enrolled into the study. Half were males (200), and another half were females (200). They were sampled via a stratified method. A research tool was a questionnaire paper containing 4 different sections. The Alpha-Cronbach’s Coefficient was equally to .98. Descriptive analysis was used for demographic data, and inferential statistics was used for the relation and invariance tests of authentic and transformational leadership of the directors of tambon health promoting hospitals. The findings revealed overall the authentic and transformation leadership model of the directors of tambon health promoting hospitals has the relation to the effectiveness of the hospitals. Only the factor of “strong community support” was statistically significantly related to the authentic leadership (p < .05). However, there were four latent variables statistically related to the transformational leadership including, competency and work climate, management system, network cooperation, and strong community support (p = .01). Regarding the relation between the authentic and transformation leadership of the directors of tambon health promoting hospitals and the effectiveness of their hospitals, four casual variables of authentic leadership were not related to those latent variables. In contrast, all four latent variables of transformational leadership has statistically significantly related to the effectiveness of tambon health promoting hospitals (p = .001). Furthermore, only management system variable was significantly related to those casual variables of the authentic leadership (p < .05). Regarding the invariance test, the result found no statistical significance of the authentic and transformational leadership model of the directors of tambon health promoting hospitals, especially between male and female genders (p > .05).

Keywords: authentic leadership, transformational leadership, tambon health promoting hospital

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871 A Framework of Dynamic Rule Selection Method for Dynamic Flexible Job Shop Problem by Reinforcement Learning Method

Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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870 Design of Nanoreinforced Polyacrylamide-Based Hybrid Hydrogels for Bone Tissue Engineering

Authors: Anuj Kumar, Kummara M. Rao, Sung S. Han

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Bone tissue engineering has emerged as a potentially alternative method for localized bone defects or diseases, congenital deformation, and surgical reconstruction. The designing and the fabrication of the ideal scaffold is a great challenge, in restoring of the damaged bone tissues via cell attachment, proliferation, and differentiation under three-dimensional (3D) biological micro-/nano-environment. In this case, hydrogel system composed of high hydrophilic 3D polymeric-network that is able to mimic some of the functional physical and chemical properties of the extracellular matrix (ECM) and possibly may provide a suitable 3D micro-/nano-environment (i.e., resemblance of native bone tissues). Thus, this proposed hydrogel system is highly permeable and facilitates the transport of the nutrients and metabolites. However, the use of hydrogels in bone tissue engineering is limited because of their low mechanical properties (toughness and stiffness) that continue to posing challenges in designing and fabrication of tough and stiff hydrogels along with improved bioactive properties. For this purpose, in our lab, polyacrylamide-based hybrid hydrogels were synthesized by involving sodium alginate, cellulose nanocrystals and silica-based glass using one-step free-radical polymerization. The results showed good in vitro apatite-forming ability (biomineralization) and improved mechanical properties (under compression in the form of strength and stiffness in both wet and dry conditions), and in vitro osteoblastic (MC3T3-E1 cells) cytocompatibility. For in vitro cytocompatibility assessment, both qualitative (attachment and spreading of cells using FESEM) and quantitative (cell viability and proliferation using MTT assay) analyses were performed. The obtained hybrid hydrogels may potentially be used in bone tissue engineering applications after establishment of in vivo characterization.

Keywords: bone tissue engineering, cellulose nanocrystals, hydrogels, polyacrylamide, sodium alginate

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869 The Singapore Innovation Web and Facilitation of Knowledge Processes

Authors: Ola Jon Mork, Irina Emily Hansen

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The European Growth Strategy Program calls for more efficient methods for knowledge creation and innovation. This study contributes with new insights into the Singapore Innovation System; more precisely how knowledge processes are facilitated. The research material is collected by visiting the different innovation locations in Singapore and depth interview with key persons. The different innovation actors web sites and brochures have been studied. Governmental reports and figures have also been studied. The findings show that facilitation of Knowledge Processes in the Singapore Innovation System has a basic structure with three processes, which is 1) Idea capturing – 2)Technology and Business Execution – 3)Idea Realization. Dedicated innovation parks work with the most promising entrepreneurs; more precisely: finding the persons with the motivation to 'change the world'. The innovation park will facilitate these entrepreneurs for 100 days, where they also will be connected to a global network of venture capital. And, the entrepreneurs will have access to mentors from these venture companies. Research institutes parks work with the development of world leading technology. To facilitate knowledge development they connect with industrial companies which are the most promising applicators of their technology. Knowledge facilitation is the main purpose, but this cooperation/testing is also serving as a platform for funding. Probably this is cooperation is also attractive for world leading companies. Dedicated innovation parks work with facilitation of innovators of new applications and perfection of products for the end- user. These parks can be specialized in special areas, like health products and life science products. Another example of this is automotive companies giving research call for these parks to develop and innovate new products and services upon their technology. Common characteristics for the knowledge facilitation in the Singapore Innovation System are a short trial period for promising actors, normally 100 days. It is also a strong focus on training of the entrepreneurs. Presentations and diffusion of knowledge is an important part of the facilitation. Funding will be available for the most successful entrepreneurs and innovators.

Keywords: knowledge processes, facilitation, innovation, Singapore innovation web

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868 Body Fluids Identification by Raman Spectroscopy and Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Authors: Huixia Shi, Can Hu, Jun Zhu, Hongling Guo, Haiyan Li, Hongyan Du

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The identification of human body fluids during forensic investigations is a critical step to determine key details, and present strong evidence to testify criminal in a case. With the popularity of DNA and improved detection technology, the potential question must be revolved that whether the suspect’s DNA derived from saliva or semen, menstrual or peripheral blood, how to identify the red substance or aged blood traces on the spot is blood; How to determine who contribute the right one in mixed stains. In recent years, molecular approaches have been developing increasingly on mRNA, miRNA, DNA methylation and microbial markers, but appear expensive, time-consuming, and destructive disadvantages. Physicochemical methods are utilized frequently such us scanning electron microscopy/energy spectroscopy and X-ray fluorescence and so on, but results only showing one or two characteristics of body fluid itself and that out of working in unknown or mixed body fluid stains. This paper focuses on using chemistry methods Raman spectroscopy and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to discriminate species of peripheral blood, menstrual blood, semen, saliva, vaginal secretions, urine or sweat. Firstly, non-destructive, confirmatory, convenient and fast Raman spectroscopy method combined with more accurate matrix-assisted laser desorption/ionization time-of-flight mass spectrometry method can totally distinguish one from other body fluids. Secondly, 11 spectral signatures and specific metabolic molecules have been obtained by analysis results after 70 samples detected. Thirdly, Raman results showed peripheral and menstrual blood, saliva and vaginal have highly similar spectroscopic features. Advanced statistical analysis of the multiple Raman spectra must be requested to classify one to another. On the other hand, it seems that the lactic acid can differentiate peripheral and menstrual blood detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, but that is not a specific metabolic molecule, more sensitivity ones will be analyzed in a forward study. These results demonstrate the great potential of the developed chemistry methods for forensic applications, although more work is needed for method validation.

Keywords: body fluids, identification, Raman spectroscopy, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

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867 Grid and Market Integration of Large Scale Wind Farms using Advanced Predictive Data Mining Techniques

Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

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866 Antenatal Monitoring of Pre-Eclampsia in a Low Resource Setting

Authors: Alina Rahim, Joanne Moffatt, Jessica Taylor, Joseph Hartland, Tamer Abdelrazik

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Background: In 2011, 15% of maternal deaths in Uganda were due to hypertensive disorders (pre-eclampsia and eclampsia). The majority of these deaths are avoidable with optimum antenatal care. The aim of the study was to evaluate how antenatal monitoring of pre-eclampsia was carried out in a low resource setting and to identify barriers to best practice as recommended by the World Health Organisation (WHO) as part of a 4th year medical student External Student Selected component field trip. Method: Women admitted to hospital with pre-eclampsia in rural Uganda (Villa Maria and Kitovu Hospitals) over a year-long period were identified using the maternity register and antenatal record book. It was not possible to obtain notes for all cases identified on the maternity register. Therefore a total of thirty sets of notes were reviewed. The management was recorded and compared to Ugandan National Guidelines and WHO recommendations. Additional qualitative information on routine practice was established by interviewing staff members from the obstetric and midwifery teams. Results: From the records available, all patients in this sample were managed according to WHO recommendations during labour. The rate of Caesarean section as a mode of delivery was noted to be high in this group of patients; 56% at Villa Maria and 46% at Kitovu. Antenatally two WHO recommendations were not routinely met: aspirin prophylaxis and calcium supplementation. This was due to lack of resources, and lack of attendance at antenatal clinic leading to poor detection of high-risk patients. Medical management of pre-eclampsia varied between individual patients, overall 93.3% complied with Ugandan national guidelines. Two patients were treated with diuretics, which is against WHO guidance. Discussion: Antenatal monitoring of pre-eclampsia is important in reducing severe morbidity, long-term disability and mortality amongst mothers and their babies 2 . Poor attendance at antenatal clinic is a barrier to healthcare in low-income countries. Increasing awareness of the importance of these visits for women should be encouraged. The majority of cases reviewed in this sample of women were treated according to Ugandan National Guidelines. It is recommended to commence the use of aspirin prophylaxis for women at high-risk of developing pre-eclampsia and the creation of detailed guidelines for Uganda which would allow for standardisation of care county-wide.

Keywords: antenatal monitoring, low resource setting, pre-eclampsia, Uganda

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865 Safety Tolerance Zone for Driver-Vehicle-Environment Interactions under Challenging Conditions

Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

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864 Statistical Modeling and by Artificial Neural Networks of Suspended Sediment Mina River Watershed at Wadi El-Abtal Gauging Station (Northern Algeria)

Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

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863 Remote Sensing-Based Prediction of Asymptomatic Rice Blast Disease Using Hyperspectral Spectroradiometry and Spectral Sensitivity Analysis

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

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Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

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862 Multi-Criterial Analysis: Potential Regions and Height of Wind Turbines, Rio de Janeiro, Brazil

Authors: Claudio L. M. Souza, Milton Erthal, Aldo Shimoya, Elias R. Goncalves, Igor C. Rangel, Allysson R. T. Tavares, Elias G. Figueira

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The process of choosing a region for the implementation of wind farms involves factors such as the wind regime, economic viability, land value, topography, and accessibility. This work presents results obtained by multi-criteria decision analysis, and it establishes a hierarchy, regarding the installation of wind farms, among geopolicy regions in the state of ‘Rio de Janeiro’, Brazil: ‘Regiao Norte-RN’, ‘Regiao dos Lagos-RL’ and ‘Regiao Serrana-RS’. The wind regime map indicates only these three possible regions with an average annual wind speed of above of 6.0 m/s. The method applied was the Analytical Hierarchy Process-AHP, designed to prioritize and rank the three regions based on four criteria as follows: 1) potential of the site and average wind speeds of above 6.0 ms-¹, 2) average land value, 3) distribution and interconnection to electric network with the highest number of electricity stations, and 4) accessibility with proximity and quality of highways and flat topography. The values of energy generation were calculated for wind turbines 50, 75, and 100 meters high, considering the production of site (GWh/Km²) and annual production (GWh). The weight of each criterion was attributed by six engineers and by analysis of Road Map, the Map of the Electric System, the Map of Wind Regime and the Annual Land Value Report. The results indicated that in 'RS', the demand was estimated at 2,000 GWh, so a wind farm can operate efficiently in 50 m turbines. This region is mainly mountainous with difficult access and lower land value. With respect to ‘RL’, the wind turbines have to be installed at a height of 75 m high to reach a demand of 6,300 GWh. This region is very flat, with easy access, and low land value. Finally, the ‘NR’ was evaluated as very flat and with expensive lands. In this case, wind turbines with 100 m can reach an annual production of 19,000 GWh. In this Region, the coast area was classified as of greater logistic, productivity and economic potential.

Keywords: AHP, renewable energy, wind energy

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861 Data Mining Model for Predicting the Status of HIV Patients during Drug Regimen Change

Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

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860 Verification of a Simple Model for Rolling Isolation System Response

Authors: Aarthi Sridhar, Henri Gavin, Karah Kelly

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Rolling Isolation Systems (RISs) are simple and effective means to mitigate earthquake hazards to equipment in critical and precious facilities, such as hospitals, network collocation facilities, supercomputer centers, and museums. The RIS works by isolating components acceleration the inertial forces felt by the subsystem. The RIS consists of two platforms with counter-facing concave surfaces (dishes) in each corner. Steel balls lie inside the dishes and allow the relative motion between the top and bottom platform. Formerly, a mathematical model for the dynamics of RISs was developed using Lagrange’s equations (LE) and experimentally validated. A new mathematical model was developed using Gauss’s Principle of Least Constraint (GPLC) and verified by comparing impulse response trajectories of the GPLC model and the LE model in terms of the peak displacements and accelerations of the top platform. Mathematical models for the RIS are tedious to derive because of the non-holonomic rolling constraints imposed on the system. However, using Gauss’s Principle of Least constraint to find the equations of motion removes some of the obscurity and yields a system that can be easily extended. Though the GPLC model requires more state variables, the equations of motion are far simpler. The non-holonomic constraint is enforced in terms of accelerations and therefore requires additional constraint stabilization methods in order to avoid the possibility that numerical integration methods can cause the system to go unstable. The GPLC model allows the incorporation of more physical aspects related to the RIS, such as contribution of the vertical velocity of the platform to the kinetic energy and the mass of the balls. This mathematical model for the RIS is a tool to predict the motion of the isolation platform. The ability to statistically quantify the expected responses of the RIS is critical in the implementation of earthquake hazard mitigation.

Keywords: earthquake hazard mitigation, earthquake isolation, Gauss’s Principle of Least Constraint, nonlinear dynamics, rolling isolation system

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859 LHCII Proteins Phosphorylation Changes Involved in the Dark-Chilling Response in Plant Species with Different Chilling Tolerance

Authors: Malgorzata Krysiak, Anna Wegrzyn, Maciej Garstka, Radoslaw Mazur

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Under constantly fluctuating environmental conditions, the thylakoid membrane protein network evolved the ability to dynamically respond to changing biotic and abiotic factors. One of the most important protective mechanism is rearrangement of the chlorophyll-protein (CP) complexes, induced by protein phosphorylation. In a temperate climate, low temperature is one of the abiotic stresses that heavily affect plant growth and productivity. The aim of this study was to determine the role of LHCII antenna complex phosphorylation in the dark-chilling response. The study included an experimental model based on dark-chilling at 4 °C of detached chilling sensitive (CS) runner bean (Phaseolus coccineus L.) and chilling tolerant (CT) garden pea (Pisum sativum L.) leaves. This model is well described in the literature as used for the analysis of chilling impact without any additional effects caused by light. We examined changes in thylakoid membrane protein phosphorylation, interactions between phosphorylated LHCII (P-LHCII) and CP complexes, and their impact on the dynamics of photosystem II (PSII) under dark-chilling conditions. Our results showed that the dark-chilling treatment of CS bean leaves induced a substantial increase of phosphorylation of LHCII proteins, as well as changes in CP complexes composition and their interaction with P-LHCII. The PSII photochemical efficiency measurements showed that in bean, PSII is overloaded with light energy, which is not compensated by CP complexes rearrangements. On the contrary, no significant changes in PSII photochemical efficiency, phosphorylation pattern and CP complexes interactions were observed in CT pea. In conclusion, our results indicate that different responses of the LHCII phosphorylation to chilling stress take place in CT and CS plants, and that kinetics of LHCII phosphorylation and interactions of P-LHCII with photosynthetic complexes may be crucial to chilling stress response. Acknowledgments: presented work was financed by the National Science Centre, Poland grant No.: 2016/23/D/NZ3/01276

Keywords: LHCII, phosphorylation, chilling stress, pea, runner bean

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858 A Study on the Quantitative Evaluation Method of Asphalt Pavement Condition through the Visual Investigation

Authors: Sungho Kim, Jaechoul Shin, Yujin Baek

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In recent years, due to the environmental impacts and time factor, etc., various type of pavement deterioration is increasing rapidly such as crack, pothole, rutting and roughness degradation. The Ministry of Land, Infrastructure and Transport maintains regular pavement condition of the highway and the national highway using the pavement condition survey equipment and structural survey equipment in Korea. Local governments that maintain local roads, farm roads, etc. are difficult to maintain the pavement condition using the pavement condition survey equipment depending on economic conditions, skills shortages and local conditions such as narrow roads. This study presents a quantitative evaluation method of the pavement condition through the visual inspection to overcome these problems of roads managed by local governments. It is difficult to evaluate rutting and roughness with the naked eye. However, the condition of cracks can be evaluated with the naked eye. Linear cracks (m), area cracks (m²) and potholes (number, m²) were investigated with the naked eye every 100 meters for survey the cracks. In this paper, crack ratio was calculated using the results of the condition of cracks and pavement condition was evaluated by calculated crack ratio. The pavement condition survey equipment also investigated the pavement condition in the same section in order to evaluate the reliability of pavement condition evaluation by the calculated crack ratio. The pavement condition was evaluated through the SPI (Seoul Pavement Index) and calculated crack ratio using results of field survey. The results of a comparison between 'the SPI considering only crack ratio' and 'the SPI considering rutting and roughness either' using the equipment survey data showed a margin of error below 5% when the SPI is less than 5. The SPI 5 is considered the base point to determine whether to maintain the pavement condition. It showed that the pavement condition can be evaluated using only the crack ratio. According to the analysis results of the crack ratio between the visual inspection and the equipment survey, it has an average error of 1.86%(minimum 0.03%, maximum 9.58%). Economically, the visual inspection costs only 10% of the equipment survey and will also help the economy by creating new jobs. This paper advises that local governments maintain the pavement condition through the visual investigations. However, more research is needed to improve reliability. Acknowledgment: The author would like to thank the MOLIT (Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: asphalt pavement maintenance, crack ratio, evaluation of asphalt pavement condition, SPI (Seoul Pavement Index), visual investigation

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857 Polymer Impregnated Sulfonated Carbon Composite as a Solid Acid Catalyst for the Dehydration of Xylose to Furfural

Authors: Praveen K. Khatri, Neha Karanwal, Savita Kaul, Suman L. Jain

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Conversion of biomass through green chemical routes is of great industrial importance as biomass is considered to be most widely available inexpensive renewable resource that can be used as a raw material for the production of bio fuel and value-added organic products. In this regard, acid catalyzed dehydration of biomass derived pentose sugar (mainly D-xylose) to furfural is a process of tremendous research interest in current scenario due to the wider industrial applications of furfural. Furfural is an excellent organic solvent for refinement of lubricants and separation of butadiene from butene mixture in synthetic rubber fabrication. In addition it also serve as a promising solvent for many organic materials, such as resins, polymers and also used as a building block for synthesis of various valuable chemicals such as furfuryl alcohol, furan, pharmaceutical, agrochemicals and THF. Here in a sulfonated polymer impregnated carbon composite solid acid catalyst (P-C-SO3H) was prepared by the pyrolysis of a polymer matrix impregnated with glucose followed by its sulfonation and used for the dehydration of xylose to furfural. The developed catalyst exhibited excellent activity and provided almost quantitative conversion of xylose with the selective synthesis of furfural. The higher catalytic activity of P-C-SO3H may be due to the more even distribution of polycyclic aromatic hydrocarbons generated from incomplete carbonization of glucose along the polymer matrix network, leading to more available sites for sulfonation which resulted in greater sulfonic acid density in P-C-SO3H as compared to sulfonated carbon catalyst (C-SO3H). In conclusion, we have demonstrated sulfonated polymer impregnated carbon composite (P-C-SO3H) as an efficient and selective solid acid catalyst for the dehydration of xylose to furfural. After completion of the reaction, the catalyst was easily recovered and reused for several runs without noticeable loss in its activity and selectivity.

Keywords: Solid acid , Biomass conversion, Xylose Dehydration, Heterogeneous catalyst

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856 Bioanalytical Method Development and Validation of Aminophylline in Rat Plasma Using Reverse Phase High Performance Liquid Chromatography: An Application to Preclinical Pharmacokinetics

Authors: S. G. Vasantharaju, Viswanath Guptha, Raghavendra Shetty

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Introduction: Aminophylline is a methylxanthine derivative belonging to the class bronchodilator. From the literature survey, reported methods reveals the solid phase extraction and liquid liquid extraction which is highly variable, time consuming, costly and laborious analysis. Present work aims to develop a simple, highly sensitive, precise and accurate high-performance liquid chromatography method for the quantification of Aminophylline in rat plasma samples which can be utilized for preclinical studies. Method: Reverse Phase high-performance liquid chromatography method. Results: Selectivity: Aminophylline and the internal standard were well separated from the co-eluted components and there was no interference from the endogenous material at the retention time of analyte and the internal standard. The LLOQ measurable with acceptable accuracy and precision for the analyte was 0.5 µg/mL. Linearity: The developed and validated method is linear over the range of 0.5-40.0 µg/mL. The coefficient of determination was found to be greater than 0.9967, indicating the linearity of this method. Accuracy and precision: The accuracy and precision values for intra and inter day studies at low, medium and high quality control samples concentrations of aminophylline in the plasma were within the acceptable limits Extraction recovery: The method produced consistent extraction recovery at all 3 QC levels. The mean extraction recovery of aminophylline was 93.57 ± 1.28% while that of internal standard was 90.70 ± 1.30%. Stability: The results show that aminophylline is stable in rat plasma under the studied stability conditions and that it is also stable for about 30 days when stored at -80˚C. Pharmacokinetic studies: The method was successfully applied to the quantitative estimation of aminophylline rat plasma following its oral administration to rats. Discussion: Preclinical studies require a rapid and sensitive method for estimating the drug concentration in the rat plasma. The method described in our article includes a simple protein precipitation extraction technique with ultraviolet detection for quantification. The present method is simple and robust for fast high-throughput sample analysis with less analysis cost for analyzing aminophylline in biological samples. In this proposed method, no interfering peaks were observed at the elution times of aminophylline and the internal standard. The method also had sufficient selectivity, specificity, precision and accuracy over the concentration range of 0.5 - 40.0 µg/mL. An isocratic separation technique was used underlining the simplicity of the presented method.

Keywords: Aminophyllin, preclinical pharmacokinetics, rat plasma, RPHPLC

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855 Integrated Mass Rapid Transit System for Smart City Project in Western India

Authors: Debasis Sarkar, Jatan Talati

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This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.

Keywords: mass rapid transit systems, smart city, metro rail, bus rapid transit system, multiple linear regression, smart card, automated fare collection system

Procedia PDF Downloads 268
854 Extraction of Urban Building Damage Using Spectral, Height and Corner Information

Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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853 GIS Data Governance: GIS Data Submission Process for Build-in Project, Replacement Project at Oman Electricity Transmission Company

Authors: Rahma Al Balushi

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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS dept. This paper will describe in detail the GIS data submission process and the journey to develop the current process. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting, and data alterations salso aided to reduce the missing attributes of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the year 2017 and the year 2021. Overall, concluding that by governance, asset information & GIS department can control GIS data process; collect, properly record, and manage asset data and information within OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, geodatabase, NOC, CMMS

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852 Inkjet Printed Silver Nanowire Network as Semi-Transparent Electrode for Organic Photovoltaic Devices

Authors: Donia Fredj, Marie Parmentier, Florence Archet, Olivier Margeat, Sadok Ben Dkhil, Jorg Ackerman

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Transparent conductive electrodes (TCEs) or transparent electrodes (TEs) are a crucial part of many electronic and optoelectronic devices such as touch panels, liquid crystal displays (LCDs), organic light-emitting diodes (OLEDs), solar cells, and transparent heaters. The indium tin oxide (ITO) electrode is the most widely utilized transparent electrode due to its excellent optoelectrical properties. However, the drawbacks of ITO, such as the high cost of this material, scarcity of indium, and the fragile nature, limit the application in large-scale flexible electronic devices. Importantly, flexibility is becoming more and more attractive since flexible electrodes have the potential to open new applications which require transparent electrodes to be flexible, cheap, and compatible with large-scale manufacturing methods. So far, several materials as alternatives to ITO have been developed, including metal nanowires, conjugated polymers, carbon nanotubes, graphene, etc., which have been extensively investigated for use as flexible and low-cost electrodes. Among them, silver nanowires (AgNW) are one of the promising alternatives to ITO thanks to their excellent properties, high electrical conductivity as well as desirable light transmittance. In recent years, inkjet printing became a promising technique for large-scale printed flexible and stretchable electronics. However, inkjet printing of AgNWs still presents many challenges. In this study, a synthesis of stable AgNW that could compete with ITO was developed. This material was printed by inkjet technology directly on a flexible substrate. Additionally, we analyzed the surface microstructure, optical and electrical properties of the printed AgNW layers. Our further research focused on the study of all inkjet-printed organic modules with high efficiency.

Keywords: transparent electrodes, silver nanowires, inkjet printing, formulation of stable inks

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851 Improve Student Performance Prediction Using Majority Vote Ensemble Model for Higher Education

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 101