Search results for: object detection with multimodal inputs
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5195

Search results for: object detection with multimodal inputs

3005 Application of Random Forest Model in The Prediction of River Water Quality

Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

Abstract:

Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

Procedia PDF Downloads 192
3004 Considering Climate Change in Food Security: A Sociological Study Investigating the Modern Agricultural Practices and Food Security in Bangladesh

Authors: Hosen Tilat Mahal, Monir Hossain

Abstract:

Despite being a food-sufficient country after revolutionary changes in agricultural inputs, Bangladesh still has food insecurity and undernutrition. This study examines the association between agricultural practices (as social practices) and food security concentrating on the potential impact of sociodemographic factors and climate change. Using data from the 2012 Bangladesh Integrated Household Survey (BIHS), this study shows how modifiedagricultural practices are strongly associated with climate change and different sociodemographic factors (land ownership, religion, gender, education, and occupation) subsequently affect the status of food security in Bangladesh. We used linear and logistic regression models to analyze the association between modified agricultural practices and food security. The findings indicate that socioeconomic statuses are significant predictors of determining agricultural practices in a society like Bangladesh and control food security at the household level. Moreover, climate change is adversely impactingeven the modified agricultural and food security association version. We conclude that agricultural practices must consider climate change while boosting food security. Therefore, future research should integrate climate change into the agriculture and food-related mitigation and resiliency models.

Keywords: food security, agricultural productivity, climate change, bangladesh

Procedia PDF Downloads 114
3003 Multi-Level Meta-Modeling for Enabling Dynamic Subtyping for Industrial Automation

Authors: Zoltan Theisz, Gergely Mezei

Abstract:

Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead

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3002 Contemporary Materialities

Authors: Fabian Saptouw

Abstract:

In the past decade there was a resurgence of interest in the value of ‘process’ and ‘craft’ within the social and artistic community. Theorist like Barbara Bolt and Paul Carter have eloquently argued for the importance of ‘theorizing out of practice’ and ‘material thinking’ in response to this trend. Time and labour intensive artistic production processes are however not generally included in this bracket and often labelled as either obsessive or absurd. Neither of these terms adequately conveys the conceptual importance of labour in relation to ‘process’ as manifested through this production method. This issue will be addressed by critically assessing the work of eight South African artists through the lens of contemporary process-based production. This will result in a more integrated view of the art-object, its art-historical trajectory, its materialisation as well as its production process. This paper will conclude by tying the characteristics of these artworks to international trends and provide a platform for the overall reconsideration of unalienated artistic labour.

Keywords: materiality, process art, practice-led research, unalienated labour

Procedia PDF Downloads 329
3001 Motivation and Criteria as Determinant Factors in Accepting New Talents on User-Generated Content (UGC): Youtube as a Platform

Authors: Shereen Nadira Binti Jasney, Mohd Syuhaidi Bin Abu Bakar, Hafizah Binti Rosli

Abstract:

This quantitative study explored factors that motivate the public to use YouTube; and the elements of criteria, which the public are looking for to accept new talents on User-Generated Content (UGC). There are mass inputs on the net but the publics are still being very selective in accepting new talents. Thus, it is important to identify determinant factors that contribute to the acceptance of new talents on UGC. A total number of 236 respondents have participated in this study using Simple Random Sampling and they were analyzed with descriptive analysis. The findings of this paper advocate that tremendous expansion; and diversification YouTube music offers are main factors that motivated public viewers in using YouTube on accepting new talents. It is also found that by being relatable and concurrently providing interesting contents, having the artist name and song title in the YouTube talent’s title video and the number of views and likes of the video are some of the criteria that the public are looking for in accepting new talents on the UGC. This paper introduces YouTube as a mean of discovering new talents in the music industry where the public, especially the younger generations, whom are actively engaged with current digital landscape that they’ve been presently silver-plated.

Keywords: motivation, criteria, new talents, UGC, YouTube

Procedia PDF Downloads 279
3000 Human Behavior Modeling in Video Surveillance of Conference Halls

Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

Abstract:

In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: activity modeling, clustering, PLSA, video representation

Procedia PDF Downloads 386
2999 A Visual Analytics Tool for the Structural Health Monitoring of an Aircraft Panel

Authors: F. M. Pisano, M. Ciminello

Abstract:

Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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2998 The Bloom of 3D Printing in the Health Care Industry

Authors: Mihika Shivkumar, Krishna Kumar, C. Perisamy

Abstract:

3D printing is a method of manufacturing wherein materials, such as plastic or metal, are deposited in layers one on top of the other to produce a three dimensional object. 3D printing is most commonly associated with creating engineering prototypes. However, its applications in the field of human health care have been frequently disregarded. Medical applications for 3D printing are expanding rapidly and are envisaged to revolutionize health care. Medical applications for 3D printing, both present and its potential, can be categorized broadly, including: creation of customized prosthetics tissue and organ fabrication; creation of implants, and anatomical models and pharmaceutical research regarding drug dosage forms. This piece breaks down bioprinting in the healthcare sector. It focuses on the better subtle elements of every particular point, including how 3D printing functions in the present, its impediments, and future applications in the health care sector.

Keywords: bio-printing, prototype, drug delivery, organ regeneration

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2997 Non-Revenue Water Management in Palestine

Authors: Samah Jawad Jabari

Abstract:

Water is the most important and valuable resource not only for human life but also for all living things on the planet. The water supply utilities should fulfill the water requirement quantitatively and qualitatively. Drinking water systems are exposed to both natural (hurricanes and flood) and manmade hazards (risks) that are common in Palestine. Non-Revenue Water (NRW) is a manmade risk which remains a major concern in Palestine, as the NRW levels are estimated to be at a high level. In this research, Hebron city water distribution network was taken as a case study to estimate and audit the NRW levels. The research also investigated the state of the existing water distribution system in the study area by investigating the water losses and obtained more information on NRW prevention and management practices. Data and information have been collected from the Palestinian Water Authority (PWA) and Hebron Municipality (HM) archive. In addition to that, a questionnaire has been designed and administered by the researcher in order to collect the necessary data for water auditing. The questionnaire also assessed the views of stakeholder in PWA and HM (staff) on the current status of the NRW in the Hebron water distribution system. The important result obtained by this research shows that NRW in Hebron city was high and in excess of 30%. The main factors that contribute to NRW were the inaccuracies in billing volumes, unauthorized consumption, and the method of estimating consumptions through faulty meters. Policy for NRW reduction is available in Palestine; however, it is clear that the number of qualified staff available to carry out the activities related to leak detection is low, and that there is a lack of appropriate technologies to reduce water losses and undertake sufficient system maintenance, which needs to be improved to enhance the performance of the network and decrease the level of NRW losses.

Keywords: non-revenue water, water auditing, leak detection, water meters

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2996 Non-Destructive Technique for Detection of Voids in the IC Package Using Terahertz-Time Domain Spectrometer

Authors: Sung-Hyeon Park, Jin-Wook Jang, Hak-Sung Kim

Abstract:

In recent years, Terahertz (THz) time-domain spectroscopy (TDS) imaging method has been received considerable interest as a promising non-destructive technique for detection of internal defects. In comparison to other non-destructive techniques such as x-ray inspection method, scanning acoustic tomograph (SAT) and microwave inspection method, THz-TDS imaging method has many advantages: First, it can measure the exact thickness and location of defects. Second, it doesn’t require the liquid couplant while it is very crucial to deliver that power of ultrasonic wave in SAT method. Third, it didn’t damage to materials and be harmful to human bodies while x-ray inspection method does. Finally, it exhibits better spatial resolution than microwave inspection method. However, this technology couldn’t be applied to IC package because THz radiation can penetrate through a wide variety of materials including polymers and ceramics except of metals. Therefore, it is difficult to detect the defects in IC package which are composed of not only epoxy and semiconductor materials but also various metals such as copper, aluminum and gold. In this work, we proposed a special method for detecting the void in the IC package using THz-TDS imaging system. The IC package specimens for this study are prepared by Packaging Engineering Team in Samsung Electronics. Our THz-TDS imaging system has a special reflection mode called pitch-catch mode which can change the incidence angle in the reflection mode from 10 o to 70 o while the others have transmission and the normal reflection mode or the reflection mode fixed at certain angle. Therefore, to find the voids in the IC package, we investigated the appropriate angle as changing the incidence angle of THz wave emitter and detector. As the results, the voids in the IC packages were successfully detected using our THz-TDS imaging system.

Keywords: terahertz, non-destructive technique, void, IC package

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2995 Location Tracking of Human Using Mobile Robot and Wireless Sensor Networks

Authors: Muazzam A. Khan

Abstract:

In order to avoid dangerous environmental disasters, robots are being recognized as good entrants to step in as human rescuers. Robots has been gaining interest of many researchers in rescue matters especially which are furnished with advanced sensors. In distributed wireless robot system main objective for a rescue system is to track the location of the object continuously. This paper provides a novel idea to track and locate human in disaster area using stereo vision system and ZigBee technology. This system recursively predict and updates 3D coordinates in a robot coordinate camera system of a human which makes the system cost effective. This system is comprised of ZigBee network which has many advantages such as low power consumption, self-healing low data rates and low cost.

Keywords: stereo vision, segmentation, classification, human tracking, ZigBee module

Procedia PDF Downloads 485
2994 Feasibility of Small Hydropower Plants Odisha

Authors: Sanoj Sahu, Ramakar Jha

Abstract:

Odisha (India) is in need of reliable, cost-effective power generation. A prolonged electricity crisis and increasing power demand have left over thousands of citizens without access to electricity, and much of the population suffers from sporadic outages. The purpose of this project is to build a methodology to evaluate small hydropower potential, which can be used to alleviate the Odisha’s energy problem among rural communities. This project has three major tasks: the design of a simple SHEP for a single location along a river in the Odisha; the development of water flow prediction equations through a linear regression analysis; and the design of an ArcGIS toolset to estimate the flow duration curves (FDCs) at locations where data do not exist. An explanation of the inputs to the tool, as well has how it produces a suitable output for SHEP evaluation will be presented. The paper also gives an explanation of hydroelectric power generation in the Odisha, SHEPs, and the technical and practical aspects of hydroelectric power. Till now, based on topographical and rainfall analysis we have located hundreds of sites. Further work on more number of site location and accuracy of location is to be done.

Keywords: small hydropower, ArcGIS, rainfall analysis, Odisha’s energy problem

Procedia PDF Downloads 444
2993 Nearest Neighbor Investigate Using R+ Tree

Authors: Rutuja Desai

Abstract:

Search engine is fundamentally a framework used to search the data which is pertinent to the client via WWW. Looking close-by spot identified with the keywords is an imperative concept in developing web advances. For such kind of searching, extent pursuit or closest neighbor is utilized. In range search the forecast is made whether the objects meet to query object. Nearest neighbor is the forecast of the focuses close to the query set by the client. Here, the nearest neighbor methodology is utilized where Data recovery R+ tree is utilized rather than IR2 tree. The disadvantages of IR2 tree is: The false hit number can surpass the limit and the mark in Information Retrieval R-tree must have Voice over IP bit for each one of a kind word in W set is recouped by Data recovery R+ tree. The inquiry is fundamentally subordinate upon the key words and the geometric directions.

Keywords: information retrieval, nearest neighbor search, keyword search, R+ tree

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2992 Control of an SIR Model for Basic Reproduction Number Regulation

Authors: Enrique Barbieri

Abstract:

The basic disease-spread model described by three states denoting the susceptible (S), infectious (I), and removed (recovered and deceased) (R) sub-groups of the total population N, or SIR model, has been considered. Heuristic mitigating action profiles of the pharmaceutical and non-pharmaceutical types may be developed in a control design setting for the purpose of reducing the transmission rate or improving the recovery rate parameters in the model. Even though the transmission and recovery rates are not control inputs in the traditional sense, a linear observer and feedback controller can be tuned to generate an asymptotic estimate of the transmission rate for a linearized, discrete-time version of the SIR model. Then, a set of mitigating actions is suggested to steer the basic reproduction number toward unity, in which case the disease does not spread, and the infected population state does not suffer from multiple waves. The special case of piecewise constant transmission rate is described and applied to a seventh-order SEIQRDP model, which segments the population into four additional states. The offline simulations in discrete time may be used to produce heuristic policies implemented by public health and government organizations.

Keywords: control of SIR, observer, SEIQRDP, disease spread

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2991 Rough Neural Networks in Adapting Cellular Automata Rule for Reducing Image Noise

Authors: Yasser F. Hassan

Abstract:

The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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2990 The Effect of Pulsator on Washing Performance in a Front-Loading Washer

Authors: Eung Ryeol Seo, Hee Tae Lim, Eunsuk Bang, Soon Cheol Kweon, Jeoung-Kyo Jeoung, Ji-Hoon Choic

Abstract:

The object of this study is to investigate the effect of pulsator on washing performance quantitatively for front-loading washer. The front-loading washer with pulsator shows washing performance improvement of 18% and the particle-based body simulation technique has been applied to figure out the relation between washing performance and mechanical forces exerted on textile during washing process. As a result, the mechanical forces, such as collision force and strain force, acting on the textile have turned out to be about twice numerically. The washing performance improvement due to additional pulsate system has been utilized for customers to save 50% of washing time.

Keywords: front-loading washer, mechanical force, fabric movement, pulsator, time-saving

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2989 Problems and Solutions in the Application of ICP-MS for Analysis of Trace Elements in Various Samples

Authors: Béla Kovács, Éva Bódi, Farzaneh Garousi, Szilvia Várallyay, Áron Soós, Xénia Vágó, Dávid Andrási

Abstract:

In agriculture for analysis of elements in different food and food raw materials, moreover environmental samples generally flame atomic absorption spectrometers (FAAS), graphite furnace atomic absorption spectrometers (GF-AAS), inductively coupled plasma optical emission spectrometers (ICP-OES) and inductively coupled plasma mass spectrometers (ICP-MS) are routinely applied. An inductively coupled plasma mass spectrometer (ICP-MS) is capable for analysis of 70-80 elements in multielemental mode, from 1-5 cm3 volume of a sample, moreover the detection limits of elements are in µg/kg-ng/kg (ppb-ppt) concentration range. All the analytical instruments have different physical and chemical interfering effects analysing the above types of samples. The smaller the concentration of an analyte and the larger the concentration of the matrix the larger the interfering effects. Nowadays there is very important to analyse growingly smaller concentrations of elements. From the above analytical instruments generally the inductively coupled plasma mass spectrometer is capable of analysing the smallest concentration of elements. The applied ICP-MS instrument has Collision Cell Technology (CCT) also. Using CCT mode certain elements have better (smaller) detection limits with 1-3 magnitudes comparing to a normal ICP-MS analytical method. The CCT mode has better detection limits mainly for analysis of selenium, arsenic, germanium, vanadium and chromium. To elaborate an analytical method for trace elements with an inductively coupled plasma mass spectrometer the most important interfering effects (problems) were evaluated: 1) Physical interferences; 2) Spectral interferences (elemental and molecular isobaric); 3) Effect of easily ionisable elements; 4) Memory interferences. Analysing food and food raw materials, moreover environmental samples an other (new) interfering effect emerged in ICP-MS, namely the effect of various matrixes having different evaporation and nebulization effectiveness, moreover having different quantity of carbon content of food and food raw materials, moreover environmental samples. In our research work the effect of different water-soluble compounds furthermore the effect of various quantity of carbon content (as sample matrix) were examined on changes of intensity of the applied elements. So finally we could find “opportunities” to decrease or eliminate the error of the analyses of applied elements (Cr, Co, Ni, Cu, Zn, Ge, As, Se, Mo, Cd, Sn, Sb, Te, Hg, Pb, Bi). To analyse these elements in the above samples, the most appropriate inductively coupled plasma mass spectrometer is a quadrupole instrument applying a collision cell technique (CCT). The extent of interfering effect of carbon content depends on the type of compounds. The carbon content significantly affects the measured concentration (intensities) of the above elements, which can be corrected using different internal standards.

Keywords: elements, environmental and food samples, ICP-MS, interference effects

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2988 Onmanee Prajuabjinda, Pakakrong Thondeeying, Jipisute Chunthorng-Orn, Bhanuz Dechayont, Arunporn Itharat

Authors: Ekrem Erdem, Can Tansel Tugcu

Abstract:

Improved resource efficiency of production is a key requirement for sustainable growth, worldwide. In this regards, by considering the energy and tourism as the extra inputs to the classical Coub-Douglas production function, this study aims at investigating the efficiency changes in the North African countries. To this end, the study uses panel data for the period 1995-2010 and adopts the Malmquist index based on the data envelopment analysis. Results show that tourism increases technical and scale efficiencies, while it decreases technological and total factor productivity changes. On the other hand, when the production function is augmented by the energy input, technical efficiency change decreases, while the technological change, scale efficiency change and total factor productivity change increase. Thus, in order to satisfy the needs for sustainable growth, North African governments should take some measures for increasing the contribution that the tourism makes to economic growth and some others for efficient use of resources in the energy sector.

Keywords: data envelopment analysis, economic efficiency, North African countries, sustainable growth

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2987 Botulinum Toxin type A for Lower Limb Lengthening and Deformity Correction: A Systematic Review and Meta-analysis

Authors: Jawaher F. Alsharef, Abdullah A. Ghaddaf, Mohammed S. Alomari, Abdullah A. Al Qurashi, Ahmed S. Abdulhamid, Mohammed S. Alshehri, Majed Alosaimi

Abstract:

Botulinum toxin type A (BTX-A) is the most popular therapeutic agent for muscle relaxation and pain control. Lately, BTX-A injection received great interest as a part of multimodal pain management for lower limb lengthening and deformity correction. This systematic review aimed to determine the role of BTX-A injection in pain management for during lower limb lengthening and/or deformity correction. We searched Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared the BTX-A injection to placebo for individuals undergoing lower limb lengthening and/or deformity correction. We sought to evaluate the following outcomes: pain on visual analogue scale (VAS), range of motion parameters, average opioid consumption, and adverse events. The standardized mean difference (SMD) was used to represent continuous outcomes while risk ratio (RR) was used to represent dichotomous outcomes. A total of 4 RCTs that enrolled 257 participants (337 limbs) deemed eligible. Adjuvant BTX-A injection showed a significant reduction in post-operative pain compared to placebo (SMD=–0.28, 95% CI –0.53 to –0.04). No difference was found between BTX-A injection and placebo in terms of range of motion parameters, average opioid consumption, or adverse events after surgical limb lengthening and/or deformity correction (RR= 0.77, 95% CI –0.58 to 1.03). Conclusions: Adjuvant BTX-A injection conferred a discernible reduction in post-operative pain during surgical limb lengthening and/or deformity without increasing the risk of adverse events.

Keywords: botulinum toxin type A, limb lengthening, distraction osteogenesis, deformity correction, pain management

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2986 South African Breast Cancer Mutation Spectrum: Pitfalls to Copy Number Variation Detection Using Internationally Designed Multiplex Ligation-Dependent Probe Amplification and Next Generation Sequencing Panels

Authors: Jaco Oosthuizen, Nerina C. Van Der Merwe

Abstract:

The National Health Laboratory Services in Bloemfontien has been the diagnostic testing facility for 1830 patients for familial breast cancer since 1997. From the cohort, 540 were comprehensively screened using High-Resolution Melting Analysis or Next Generation Sequencing for the presence of point mutations and/or indels. Approximately 90% of these patients stil remain undiagnosed as they are BRCA1/2 negative. Multiplex ligation-dependent probe amplification was initially added to screen for copy number variation detection, but with the introduction of next generation sequencing in 2017, was substituted and is currently used as a confirmation assay. The aim was to investigate the viability of utilizing internationally designed copy number variation detection assays based on mostly European/Caucasian genomic data for use within a South African context. The multiplex ligation-dependent probe amplification technique is based on the hybridization and subsequent ligation of multiple probes to a targeted exon. The ligated probes are amplified using conventional polymerase chain reaction, followed by fragment analysis by means of capillary electrophoresis. The experimental design of the assay was performed according to the guidelines of MRC-Holland. For BRCA1 (P002-D1) and BRCA2 (P045-B3), both multiplex assays were validated, and results were confirmed using a secondary probe set for each gene. The next generation sequencing technique is based on target amplification via multiplex polymerase chain reaction, where after the amplicons are sequenced parallel on a semiconductor chip. Amplified read counts are visualized as relative copy numbers to determine the median of the absolute values of all pairwise differences. Various experimental parameters such as DNA quality, quantity, and signal intensity or read depth were verified using positive and negative patients previously tested internationally. DNA quality and quantity proved to be the critical factors during the verification of both assays. The quantity influenced the relative copy number frequency directly whereas the quality of the DNA and its salt concentration influenced denaturation consistency in both assays. Multiplex ligation-dependent probe amplification produced false positives due to ligation failure when ligation was inhibited due to a variant present within the ligation site. Next generation sequencing produced false positives due to read dropout when primer sequences did not meet optimal multiplex binding kinetics due to population variants in the primer binding site. The analytical sensitivity and specificity for the South African population have been proven. Verification resulted in repeatable reactions with regards to the detection of relative copy number differences. Both multiplex ligation-dependent probe amplification and next generation sequencing multiplex panels need to be optimized to accommodate South African polymorphisms present within the genetically diverse ethnic groups to reduce the false copy number variation positive rate and increase performance efficiency.

Keywords: familial breast cancer, multiplex ligation-dependent probe amplification, next generation sequencing, South Africa

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2985 Exploring Dynamics of Regional Creative Economy

Authors: Ari Lindeman, Melina Maunula, Jani Kiviranta, Ronja Pölkki

Abstract:

The aim of this paper is to build a vision of the utilization of creative industry competences in industrial and services firms connected to Kymenlaakso region, Finland, smart specialization focus areas. Research indicates that creativity and the use of creative industry’s inputs can enhance innovation and competitiveness. Currently creative methods and services are underutilized in regional businesses and the added value they provide is not well grasped. Methodologically, the research adopts a qualitative exploratory approach. Data is collected in multiple ways including a survey, focus groups, and interviews. Theoretically, the paper contributes to the discussion about the use creative industry competences in regional development, and argues for building regional creative economy ecosystems in close co-operation with regional strategies and traditional industries rather than as treating regional creative industry ecosystem initiatives separate from them. The practical contribution of the paper is the creative vision for the use of regional authorities in updating smart specialization strategy as well as boosting industrial and creative & cultural sectors’ competitiveness. The paper also illustrates a research-based model of vision building.

Keywords: business, cooperation, creative economy, regional development, vision

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2984 The Study of Fine and Nanoscale Gold in the Ores of Primary Deposits and Gold-Bearing Placers of Kazakhstan

Authors: G. Omarova, S. Assubayeva, S. Tugambay, K. Bulegenov

Abstract:

The article discusses the problem of developing a methodology for studying thin and nanoscale gold in ores and placers of primary deposits, which will allow us to develop schemes for revealing dispersed gold inclusions and thus improve its recovery rate to increase the gold reserves of the Republic of Kazakhstan. The type of studied gold, is characterized by a number of features. In connection with this, the conditions of its concentration and distribution in ore bodies and formations, as well as the possibility of reliably determining it by "traditional" methods, differ significantly from that of fine gold (less than 0.25 microns) and even more so from that of larger grains. The mineral composition of rocks (metasomatites) and gold ore and the mineralization associated with them was studied in detail on the Kalba ore field in Kazakhstan. Mineralized zones were identified and samples were taken from them for analytical studies. The research revealed paragenetic relationships of newly formed mineral formations at the nanoscale, which makes it possible to clarify the conditions for formation of deposits with a particular type of mineralization. This will provide significant assistance in developing a scheme for study. Typomorphic features of gold were revealed, and mechanisms of formation and aggregation of gold nanoparticles were proposed. The presence of a large number of particles isolated at the laboratory stage from concentrates of gravitational enrichment can serve as an indicator of the presence of even smaller particles in the object. Even the most advanced devices based on gravitational methods for gold concentration provide extraction of metal at a level of around 50%, while pulverized metal is extracted much worse, and gold of less than 1 micron size is extracted at only a few percent. Therefore, when particles of gold smaller than 10 microns are detected, their actual numbers may be significantly higher than expected. In particular, at the studied sites, enrichment of slurry and samples with volumes up to 1 m³ was carried out using a screw lock or separator to produce a final concentrate weighing up to several kilograms. Free gold particles were extracted from the concentrates in the laboratory using a number of processes (magnetic and electromagnetic separation, washing with bromoform in a cup to obtain an ultracontentrate, etc.) and examined under electron microscopes to investigate the nature of their surface and chemical composition. The main result of the study was the detection of gold nanoparticles located on the surface of loose metal grains. The most characteristic forms of gold secretions are individual nanoparticles and aggregates of different configurations. Sometimes, aggregates form solid dense films, deposits, and crusts, all of which are confined to the negative forms of the nano- and microrelief on the surfaces of golden. The results will provide significant knowledge about the prevalence and conditions for the distribution of fine and nanoscale gold in Kazakhstan deposits, as well as the development of methods for studying it, which will minimize losses of this type of gold during extraction.

Keywords: electron microscopy, microminerology, placers, thin and nanoscale gold

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2983 Coagulase Negative Staphylococci: Phenotypic Characterization and Antimicrobial Susceptibility Pattern

Authors: Lok Bahadur Shrestha, Narayan Raj Bhattarai, Basudha Khanal

Abstract:

Introduction: Coagulase-negative staphylococci (CoNS) are the normal commensal of human skin and mucous membranes. The study was carried out to study the prevalence of CoNS among clinical isolates, to characterize them up to species level and to compare the three conventional methods for detection of biofilm formation. Objectives: to characterize the clinically significant coagulase-negative staphylococci up to species level, to compare the three phenotypic methods for the detection of biofilm formation and to study the antimicrobial susceptibility pattern of the isolates. Methods: CoNS isolates were obtained from various clinical samples during the period of 1 year. Characterization up to species level was done using biochemical test and study of biofilm formation was done by tube adherence, congo red agar, and tissue culture plate method. Results: Among 71 CoNS isolates, seven species were identified. S. epidermidis was the most common species followed by S. saprophyticus, S. haemolyticus. Antimicrobial susceptibility pattern of CoNS documented resistance of 90% to ampicillin. Resistance to cefoxitin and ceftriaxone was observed in 55% of the isolates. We detected biofilm formation in 71.8% of isolates. The sensitivity of tube adherence method was 82% while that of congo red agar method was 78%. Conclusion: Among 71 CoNS isolated, S. epidermidis was the most common isolates followed by S. saprophyticus and S. haemolyticus. Biofilm formation was detected in 71.8% of the isolates. All of the methods were effective at detecting biofilm-producing CoNS strains. Biofilm former strains are more resistant to antibiotics as compared to biofilm non-formers.

Keywords: CoNS, congo red agar, bloodstream infections, foreign body-related infections, tissue culture plate

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2982 Non-parametric Linear Technique for Measuring the Efficiency of Winter Road Maintenance in the Arctic Area

Authors: Mahshid Hatamzad, Geanette Polanco

Abstract:

Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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2981 Inclusive Cities Decision Matrix Based on a Multidimensional Approach for Sustainable Smart Cities

Authors: Madhurima S. Waghmare, Shaleen Singhal

Abstract:

The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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2980 Penetration Analysis for Composites Applicable to Military Vehicle Armors, Aircraft Engines and Nuclear Power Plant Structures

Authors: Dong Wook Lee

Abstract:

This paper describes a method for analyzing penetration for composite material using an explicit nonlinear Finite Element Analysis (FEA). This method may be used in the early stage of design for the protection of military vehicles, aircraft engines and nuclear power plant structures made of composite materials. This paper deals with simple ballistic penetration tests for composite materials and the FEA modeling method and results. The FEA was performed to interpret the ballistic field test phenomenon regarding the damage propagation in the structure subjected to local foreign object impact.

Keywords: computer aided engineering, finite element analysis, impact analysis, penetration analysis, composite material

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2979 Classifying Affective States in Virtual Reality Environments Using Physiological Signals

Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

Abstract:

Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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2978 Horse Exposition to Coxiella burnetii in France: Antibody Dynamics in Serum, Environmental Risk Assessment and Potential Links with Symptomatology

Authors: Joulié Aurélien, Isabelle Desjardins, Elsa Jourdain, Sophie Pradier, Dufour Philippe, Elodie Rousset, Agnès Leblond

Abstract:

Q fever is a worldwide zoonosis caused by the bacterium Coxiella burnetii. It may infect a broad range of host species, including horses. Although the role of horses in C. burnetii infections remains unknown, their use as sentinel species may be interesting to better assess the human risk exposure. Thus, we aimed to assess the C. burnetii horse exposition in a French endemic area by describing the antibody dynamics detected in serum; investigating the pathogen circulation in the horse environment, and exploring potential links with unexplained syndromes. Blood samples were collected in 2015 and 2016 on 338 and 294 horses, respectively and analyzed by ELISA. Ticks collected on horses were identified, and C. burnetii DNA detection was performed by qPCR targeting the IS1111 gene. Blood sample analyses revealed a significant increase of the seroprevalence in horses between both years, from 11% [7.67; 14.43] to 25% [20.06; 29.94]. On 36 seropositive horses in 2015 and 73 in 2016, 5 and four respectively showed clinical signs compatible with a C. burnetii infection (i.e., chronic fever or respiratory disorders, unfitness and unexplained weight loss). DNA was detected in almost 40% of ticks (n=59/148 in 2015 and n=103/305 in 2016) and exceptionally in dust samples (n=2/46 in 2015 and n=1/14 in 2016) every year. The C. burnetti detection in both the serum and the environment of horses confirm their exposure to the bacterium. Therefore, consideration should be given to target a relevant sentinel species to better assess the Q fever surveillance depending on the epidemiological context.

Keywords: ELISA, Q fever, qPCR, syndromic surveillance

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2977 Machine Learning Based Anomaly Detection in Hydraulic Units of Governors in Hydroelectric Power Plants

Authors: Mehmet Akif Bütüner, İlhan Koşalay

Abstract:

Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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2976 Oxalate Method for Assessing the Electrochemical Surface Area for Ni-Based Nanoelectrodes Used in Formaldehyde Sensing Applications

Authors: S. Trafela, X. Xua, K. Zuzek Rozmana

Abstract:

In this study, we used an accurate and precise method to measure the electrochemically active surface areas (Aecsa) of nickel electrodes. Calculated Aecsa is really important for the evaluation of an electro-catalyst’s activity in electrochemical reaction of different organic compounds. The method involves the electrochemical formation of Ni(OH)₂ and NiOOH in the presence of adsorbed oxalate in alkaline media. The studies were carried out using cyclic voltammetry with polycrystalline nickel as a reference material and electrodeposited nickel nanowires, homogeneous and heterogeneous nickel films. From cyclic voltammograms, the charge (Q) values for the formation of Ni(OH)₂ and NiOOH surface oxides were calculated under various conditions. At sufficiently fast potential scan rates (200 mV s⁻¹), the adsorbed oxalate limits the growth of the surface hydroxides to a monolayer. Although the Ni(OH)₂/NiOOH oxidation peak overlaps with the oxygen evolution reaction, in the reverse scan, the NiOOH/ Ni(OH)₂ reduction peak is well-separated from other electrochemical processes and can be easily integrated. The values of these integrals were used to correlate experimentally measured charge density with an electrochemically active surface layer. The Aecsa of the nickel nanowires, homogeneous and heterogeneous nickel films were calculated to be Aecsa-NiNWs = 4.2066 ± 0.0472 cm², Aecsa-homNi = 1.7175 ± 0.0503 cm² and Aecsa-hetNi = 2.1862 ± 0.0154 cm². These valuable results were expanded and used in electrochemical studies of formaldehyde oxidation. As mentioned nickel nanowires, heterogeneous and homogeneous nickel films were used as simple and efficient sensor for formaldehyde detection. For this purpose, electrodeposited nickel electrodes were modified in 0.1 mol L⁻¹ solution of KOH in order to expect electrochemical activity towards formaldehyde. The investigation of the electrochemical behavior of formaldehyde oxidation in 0.1 mol L⁻¹ NaOH solution at the surface of modified nickel nanowires, homogeneous and heterogeneous nickel films were carried out by means of electrochemical techniques such as cyclic voltammetric and chronoamperometric methods. From investigations of effect of different formaldehyde concentrations (from 0.001 to 0.1 mol L⁻¹) on electrochemical signal - current we provided catalysis mechanism of formaldehyde oxidation, detection limit and sensitivity of nickel electrodes. The results indicated that nickel electrodes participate directly in the electrocatalytic oxidation of formaldehyde. In the overall reaction, formaldehyde in alkaline aqueous solution exists predominantly in form of CH₂(OH)O⁻, which is oxidized to CH₂(O)O⁻. Taking into account the determined (Aecsa) values we have been able to calculate the sensitivities: 7 mA mol L⁻¹ cm⁻² for nickel nanowires, 3.5 mA mol L⁻¹ cm⁻² for heterogeneous nickel film and 2 mA mol L⁻¹ cm⁻² for heterogeneous nickel film. The detection limit was 0.2 mM for nickel nanowires, 0.5 mM for porous Ni film and 0.8 mM for homogeneous Ni film. All of these results make nickel electrodes capable for further applications.

Keywords: electrochemically active surface areas, nickel electrodes, formaldehyde, electrocatalytic oxidation

Procedia PDF Downloads 154