Search results for: feature selection feature subset selection feature extraction/transformation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7129

Search results for: feature selection feature subset selection feature extraction/transformation

6139 Removal Cobalt (II) and Copper (II) by Solvent Extraction from Sulfate Solutions by Capric Acid in Chloroform

Authors: A. Bara, D. Barkat

Abstract:

Liquid-liquid extraction is one of the most useful techniques for selective removal and recovery of metal ions from aqueous solutions, applied in purification processes in numerous chemical and metallurgical industries. In this work, The liquid-liquid extraction of cobalt (II) and copper (II) from aqueous solution by capric acid (HL) in chloroform at 25°C has been studied. Our interest in this paper is to study the effect of concentration of capric acid on the extraction of Co(II) and Cu(II) to see the complexes could be formed in the organic phase using various concentration of capric acid. The extraction of cobalt (II) and copper (II) is extracted as the complex CoL2 (HL )2, CuL2 (HL)2.

Keywords: capric acid, Cobalt(II), copper(II), liquid-liquid extraction

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6138 Adaptive Threshold Adjustment of Clear Channel Assessment in LAA Down Link

Authors: Yu Li, Dongyao Wang, Xiaobao Sun, Wei Ni

Abstract:

In long-term evolution (LTE), the carriers around 5GHz are planned to be utilized without licenses to further enlarge system capacity. This feature is termed licensed assisted access (LAA). The channel sensing (clean channel assessment, CCA) is required before any transmission on these unlicensed carriers, in order to make sure the harmonious co-existence of LAA with other radio access technology in the unlicensed band. Obviously, the CCA threshold is very critical, which decides whether the transmission right following CCA is delivered in time and without collisions. An improper CCA threshold may cause buffer overflow of some eNodeBs if the eNodeBs are heavily loaded with the traffic. Thus, to solve these problems, we propose an adaptive threshold adjustment method for CCA in the LAA downlink. Both the load and transmission opportunities are concerned. The trend of the LAA throughput as the threshold varies is obtained, which guides the threshold adjustment. The co-existing between LAA and Wi-Fi is particularly tested. The results from system-level simulation confirm the merits of our design, especially in heavy traffic cases.

Keywords: LTE, LAA, CCA, threshold adjustment

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6137 A Review of In-Vehicle Network for Cloud Connected Vehicle

Authors: Hanbhin Ryu, Ilkwon Yun

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Automotive industry targets to provide an improvement in safety and convenience through realizing fully autonomous vehicle. For partially realizing fully automated driving, Current vehicles already feature varieties of advanced driver assistance system (ADAS) for safety and infotainment systems for the driver’s convenience. This paper presents Cloud Connected Vehicle (CCV) which connected vehicles with cloud data center via the access network to control the vehicle for achieving next autonomous driving form and describes its features. This paper also describes the shortcoming of the existing In-Vehicle Network (IVN) to be a next generation IVN of CCV and organize the 802.3 Ethernet, the next generation of IVN, related research issue to verify the feasibility of using Ethernet. At last, this paper refers to additional considerations to adopting Ethernet-based IVN for CCV.

Keywords: autonomous vehicle, cloud connected vehicle, ethernet, in-vehicle network

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6136 Controlling Excitons Complexes in Two Dimensional MoS₂ Monolayers

Authors: Arslan Usman, Abdul Sattar, Hamid Latif, Afshan Ashfaq, Muhammad Rafique, Martin Koch

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Two-dimensional materials have promising applications in optoelectronic and photonics; MoS₂ is the pioneer 2D material in the family of transition metal dichalcogenides. Its optical, optoelectronic, and structural properties are of practical importance along with its exciton dynamics. Exciton, along with exciton complexes, plays a vital role in realizing quantum devices. MoS₂ monolayers were synthesized using chemical vapour deposition (CVD) technique on SiO₂ and hBN substrates. Photoluminescence spectroscopy (PL) was used to identify the monolayer, which also reflects the substrate based peak broadening due to screening effects. In-plane and out of plane characteristic vibrational modes E¹₂g and A₁g, respectively, were detected in a different configuration on the substrate. The B-excitons and trions showed a dominant feature at low temperatures due to electron-phonon coupling effects, whereas their energies are separated by 100 meV.

Keywords: 2D materials, photoluminescence, AFM, excitons

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6135 Drugstore Control System Design and Realization Based on Programmable Logic Controller (PLC)

Authors: Muhammad Faheem Khakhi, Jian Yu Wang, Salman Muhammad, Muhammad Faisal Shabir

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Population growth and Chinese two-child policy will boost pharmaceutical market, and it will continue to maintain the growth for a period of time in the future, the traditional pharmacy dispensary has been unable to meet the growing medical needs of the peoples. Under the strong support of the national policy, the automatic transformation of traditional pharmacies is the inclination of the Times, the new type of intelligent pharmacy system will continue to promote the development of the pharmaceutical industry. Under this background, based on PLC control, the paper proposed an intelligent storage and automatic drug delivery system; complete design of the lower computer's control system and the host computer's software system has been present. The system can be applied to dispensing work for Chinese herbal medicinal and Western medicines. Firstly, the essential of intelligent control system for pharmacy is discussed. After the analysis of the requirements, the overall scheme of the system design is presented. Secondly, introduces the software and hardware design of the lower computer's control system, including the selection of PLC and the selection of motion control system, the problem of the human-computer interaction module and the communication between PC and PLC solves, the program design and development of the PLC control system is completed. The design of the upper computer software management system is described in detail. By analyzing of E-R diagram, built the establish data, the communication protocol between systems is customize, C++ Builder is adopted to realize interface module, supply module, main control module, etc. The paper also gives the implementations of the multi-threaded system and communication method. Lastly, each module of the lower computer control system is tested. Then, after building a test environment, the function test of the upper computer software management system is completed. On this basis, the entire control system accepts the overall test.

Keywords: automatic pharmacy, PLC, control system, management system, communication

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6134 Optimizing Design Parameters for Efficient Saturated Steam Production in Fire Tube Boilers: A Cost-Effective Approach

Authors: Yoftahe Nigussie Worku

Abstract:

This research focuses on advancing fire tube boiler technology by systematically optimizing design parameters to achieve efficient saturated steam production. The main objective is to design a high-performance boiler with a production capacity of 2000kg/h at a 12-bar design pressure while minimizing costs. The methodology employs iterative analysis, utilizing relevant formulas, and considers material selection and production methods. The study successfully results in a boiler operating at 85.25% efficiency, with a fuel consumption rate of 140.37kg/hr and a heat output of 1610kW. Theoretical importance lies in balancing efficiency, safety considerations, and cost minimization. The research addresses key questions on parameter optimization, material choices, and safety-efficiency balance, contributing valuable insights to fire tube boiler design.

Keywords: safety consideration, efficiency, production methods, material selection

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6133 Novel Bioinspired Design to Capture Smoky CO2 by Reactive Absorption with Aqueous Scrubber

Authors: J. E. O. Hernandez

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In the next 20 years, energy production by burning fuels will increase and so will the atmospheric concentration of CO2 and its well-known threats to life on Earth. The technologies available for capturing CO2 are still dubious and this keeps fostering an interest in bio-inspired approaches. The leading one is the application of carbonic anhydrase (CA) –a superfast biocatalyst able to convert up to one million molecules of CO2 into carbonates in water. However, natural CA underperforms when applied to real smoky CO2 in chimneys and, so far, the efforts to create superior CAs in the lab rely on screening methods running under pristine conditions at the micro level, which are far from resembling those in chimneys. For the evolution of man-made enzymes, selection rather than screening would be ideal but this is challenging because of the need for a suitable artificial environment that is also sustainable for our society. Herein we present the stepwise design and construction of a bioprocess (from bench-scale to semi-pilot) for evolutionary selection experiments. In this bioprocess, reaction and adsorption took place simultaneously at atmospheric pressure in a spray tower. The scrubbing solution was fed countercurrently by reusing municipal pressure and it was mainly prepared with water, carbonic anhydrase and calcium chloride. This bioprocess allowed for the enzymatic carbonation of smoky CO2; the reuse of process water and the recovery of solid carbonates without cooling of smoke, pretreatments, solvent amines and compression of CO2. The average yield of solid carbonates was 0.54 g min-1 or 12-fold the amount produced in serum bottles at lab bench scale. This bioprocess could be used as a tailor-made environment for driving the selection of superior CAs. The bioprocess and its match CA could be sustainably used to reduce global warming by CO2 emissions from exhausts.

Keywords: biological carbon capture and sequestration, carbonic anhydrase, directed evolution, global warming

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6132 Me and My Selfie: Identity Building Through Self Representation in Social Media

Authors: Revytia Tanera

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This research is a pilot study to examine the rise of selfie trend in dealing with individual self representation and identity building in social media. The symbolic interactionism theory is used as the concept of the desired self image, and Cooley’s looking glass-self concept is used to analyze the mechanical reflection of ourselves; how do people perform their “digital self” in social media. In-depth interviews were conducted in the study with a non-random sample who owns a smartphone with a front camera feature and are active in social media. This research is trying to find out whether the selfie trend brings any influence on identity building on each individual. Through analysis of interview results, it can be concluded that people take selfie photos in order to express themselves and to boost their confidence. This study suggests a follow up and more in depth analysis on identity and self representation from various age groups.

Keywords: self representation, selfie, social media, symbolic interaction, looking glass-self

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6131 Identifying Applicant Potential Through Admissions Testing

Authors: Belinda Brunner

Abstract:

Objectives: Communicate common test constructs of well-known higher education admissions tests. Discuss influences on admissions test construct definition and design and discuss research on related to factors influencing success in academic study. Discuss how admissions tests can be used to identify relevant talent. Examine how admissions test can be used to facilitate educational mobility and inform selection decisions when the prerequisite curricula is not standardized Observations: Generally speaking, constructs of admissions tests can be placed along a continuum from curriculum-related knowledge to more general reasoning abilities. For example, subject-specific achievement tests are more closely aligned to a prescribed curriculum, while reasoning tests are typically not associated with a specific curriculum. This session will draw reference from the test-constructs of well-known international higher education admissions tests, such as the UK clinical aptitude test (UKCAT) which is used for medicine and dentistry admissions. Conclusions: The purpose of academic admissions testing is to identify potential students with the prerequisite skills set needed to succeed in the academic environment, but how can the test construct help achieve this goal? Determination of the appropriate test construct for tests used in the admissions selection decisions should be influenced by a number of factors, including the preceding academic curricula, other criteria influencing the admissions decision, and the principal purpose for testing. Attendees of this session will learn the types of aptitudes and knowledge that are assessed higher education admissions tests and will have the opportunity to gain insight into how careful and deliberate consideration of the desired test constructs can aid in identifying potential students with the greatest likelihood of success in medical school.

Keywords: admissions, measuring success, selection, identify skills

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6130 The Examination of Prospective ICT Teachers’ Attitudes towards Application of Computer Assisted Instruction

Authors: Agâh Tuğrul Korucu, Ismail Fatih Yavuzaslan, Lale Toraman

Abstract:

Nowadays, thanks to development of technology, integration of technology into teaching and learning activities is spreading. Increasing technological literacy which is one of the expected competencies for individuals of 21st century is associated with the effective use of technology in education. The most important factor in effective use of technology in education institutions is ICT teachers. The concept of computer assisted instruction (CAI) refers to the utilization of information and communication technology as a tool aided teachers in order to make education more efficient and improve its quality in the process of educational. Teachers can use computers in different places and times according to owned hardware and software facilities and characteristics of the subject and student in CAI. Analyzing teachers’ use of computers in education is significant because teachers are the ones who manage the course and they are the most important element in comprehending the topic by students. To accomplish computer-assisted instruction efficiently is possible through having positive attitude of teachers. Determination the level of knowledge, attitude and behavior of teachers who get the professional knowledge from educational faculties and elimination of deficiencies if any are crucial when teachers are at the faculty. Therefore, the aim of this paper is to identify ICT teachers' attitudes toward computer-assisted instruction in terms of different variables. Research group consists of 200 prospective ICT teachers studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education CEIT department. As data collection tool of the study; “personal information form” developed by the researchers and used to collect demographic data and "the attitude scale related to computer-assisted instruction" are used. The scale consists of 20 items. 10 of these items show positive feature, while 10 of them show negative feature. The Kaiser-Meyer-Olkin (KMO) coefficient of the scale is found 0.88 and Barlett test significance value is found 0.000. The Cronbach’s alpha reliability coefficient of the scale is found 0.93. In order to analyze the data collected by data collection tools computer-based statistical software package used; statistical techniques such as descriptive statistics, t-test, and analysis of variance are utilized. It is determined that the attitudes of prospective instructors towards computers do not differ according to their educational branches. On the other hand, the attitudes of prospective instructors who own computers towards computer-supported education are determined higher than those of the prospective instructors who do not own computers. It is established that the departments of students who previously received computer lessons do not affect this situation so much. The result is that; the computer experience affects the attitude point regarding the computer-supported education positively.

Keywords: computer based instruction, teacher candidate, attitude, technology based instruction, information and communication technologies

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6129 Gaming Tools for Efficient Low Cost Urban Planning Using Nature Based Solutions

Authors: Ioannis Kavouras, Eftychios Protopapadakis, Emmanuel Sardis, Anastasios Doulamis

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In this paper, we investigate the appropriateness and usability of three different free and open-source rendering tools for urban planning visualizations. The process involves the selection of a map area, the 3D rendering transformation, the addition of nature-based solution placement, and the evaluation and assessment of the suggested applied interventions. The manuscript uses a case study involved at Dilaveri Coast, Piraeus region, Greece. Research outcomes indicate that a Blender-OSM implementation is an appropriate tool capable of supporting high-fidelity urban planning, with quick and accurate visibility of related results for end users and involved in NBS transformations.

Keywords: urban planning, nature based solution, 3D gaming tools, game engine, free and open source

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6128 Knowledge Management in the Interactive Portal for Decision Makers on InKOM Example

Authors: K. Marciniak, M. Owoc

Abstract:

Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge - for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers–InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We will focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.

Keywords: business intelligence, decision support systems, knowledge management, knowledge transformation, knowledge validation, managerial systems

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6127 A Study of Effective Stereo Matching Method for Long-Wave Infrared Camera Module

Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

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In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

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6126 Online Authenticity Verification of a Biometric Signature Using Dynamic Time Warping Method and Neural Networks

Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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6125 Optimized Weight Selection of Control Data Based on Quotient Space of Multi-Geometric Features

Authors: Bo Wang

Abstract:

The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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6124 A Study of Electrowetting-Assisted Mold Filling in Nanoimprint Lithography

Authors: Wei-Hsuan Hsu, Yi-Xuan Huang

Abstract:

Nanoimprint lithography (NIL) possesses the advantages of sub-10-nm feature and low cost. NIL patterns the resist with physical deformation using a mold, which can easily reproduce the required nano-scale pattern. However, the variation of process parameters and environmental conditions seriously affect reproduction quality. How to ensure the quality of imprinted pattern is essential for industry. In this study, the authors used the electrowetting technology to assist mold filling in the NIL process. A special mold structure was designed to cause electrowetting. During the imprinting process, when a voltage was applied between the mold and substrate, the hydrophilicity/hydrophobicity of the surface of the mold can be converted. Both simulation and experiment confirmed that the electrowetting technology can assist mold filling and avoid incomplete filling rate. The proposed method can also reduce the crack formation during the de-molding process. Therefore, electrowetting technology can improve the process quality of NIL.

Keywords: electrowetting, mold filling, nano-imprint, surface modification

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6123 Twitter's Impact on Print Media with Respect to Real World Events

Authors: Basit Shahzad, Abdullatif M. Abdullatif

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Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.

Keywords: twitter trends, text mining, effectiveness of trends, print media

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6122 2.5D Face Recognition Using Gabor Discrete Cosine Transform

Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao

Abstract:

In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.

Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose

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6121 The Effects of Virtual Reality Technology in Maternity Delivery: A Systematic Review and Meta-Analysis

Authors: Nuo Xu, Sijing Chen

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Background: Childbirth is considered a critical traumatic event throughout our lives, positively or negatively impacting the mother's physiology, psychology, and even the whole family. Adverse birth experiences, such as labor pain, anxiety, and fear can negatively impact the mother. Studies had shown that the immersive nature of VR can distract attention from pain and increase focus on interventions for pain relief. However, the existing studies that applied VR to maternal delivery were still in their infancy and showed disparate results, and the small sample size is not representative, so this review analyzed the effects of VR in labor, such as on maternal pain and anxiety, with a view to providing a basis for future applications. Search strategy: We searched Pubmed, Embase, Web of Science, the Cochrane Library, CINAHL, China National Knowledge Infrastructure, Wan-Fang database from the building to November 17, 2021. Selection Criteria: Randomized controlled trials (RCTs) that intervened the pregnant women aged 18-35 years with gestational >34 weeks and without complications with VR technology were contained within this review. Data Collection and Analysis: Two researchers completed the study selection, data extraction, and assessment of study quality. For quantitative data we used MD or SMD, and RR (risk ratio) for qualitative data. Random-effects model and 95% confidence interval (95% CI) were used. Main Results: 12 studies were included. Using VR could relieve pain during labor (MD=-1.81, 95% CI (-2.04, -1.57), P< 0.00001) and active period (SMD=-0.41, 95% CI (-0.68, -0.14), P= 0.003), reduce anxiety (SMD=-1.39, 95% CI (-1.99, -0.78), P< 0.00001) and improve satisfaction (RR = 1.32; 95% CI (1.10, 1.59); P = 0.003), but the effect on the duration of first (SMD=-1.12, 95% CI (-2.38, 0.13), P=0.08) and second (SMD=-0.22, 95% CI (-0.67, 0.24), P=0.35) stage of labor was not statistically significant. Conclusions: Compared with conventional care, VR technology can relieve labor pain and anxiety and improve satisfaction. However, extensive experimental validation is still needed.

Keywords: virtual reality, delivery, labor pain, anxiety, meta-analysis, systematic review

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6120 The Feasibility Evaluation Of The Compressed Air Energy Storage System In The Porous Media Reservoir

Authors: Ming-Hong Chen

Abstract:

In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

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6119 The Molecular Bases of Δβ T-Cell Mediated Antigen Recognition

Authors: Eric Chabrol, Sidonia B.G. Eckle, Renate de Boer, James McCluskey, Jamie Rossjohn, Mirjam H.M. Heemskerk, Stephanie Gras

Abstract:

αβ and γδ T-cells are disparate T-cell lineages that, via their use of either αβ or γδ T-cell antigen receptors (TCRs) respectively, can respond to distinct antigens. Here we characterise a new population of human T-cells, term δβ T-cells, that express TCRs comprising a TCR-δ variable gene fused to a Joining-α/Constant-α domain, paired with an array of TCR-β chains. We characterised the cellular, functional, biophysical and structural characteristic feature of this new T-cells population that reveal some new insight into TCR diversity. We provide molecular bases of how δβ T-cells can recognise viral peptide presented by Human Leukocyte Antigen (HLA) molecule. Our findings highlight how components from αβ and γδTCR gene loci can recombine to confer antigen specificity thus expanding our understanding of T-cell biology and TCR diversity.

Keywords: new delta-beta TCR, HLA, viral peptide, structural immunology

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6118 Comparative Life Cycle Assessment of High Barrier Polymer Packaging for Selecting Resource Efficient and Environmentally Low-Impact Materials

Authors: D. Kliaugaitė, J. K, Staniškis

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In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE). All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging. Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH. The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: life cycle assessment, polymer packaging, resource efficiency, materials extraction, polyethylene terephthalate

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6117 Active Learning Techniques in Engineering Education

Authors: H. M. Anitha, Anusha N. Rao

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The current developments in technology and ideas have given entirely new dimensions to the field of research and education. New delivery methods are proposed which is an added feature to the engineering education. Particularly, more importance is given to new teaching practices such as Information and Communication Technologies (ICT). It is vital to adopt the new ICT methods which lead to the emergence of novel structure and mode of education. The flipped classroom, think pair share and peer instruction are the latest pedagogical methods which give students to learn the course. This involves students to watch video lectures outside the classroom and solve the problems at home. Students are engaged in group discussions in the classroom. These are the active learning methods wherein the students are involved diversely to learn the course. This paper gives a comprehensive study of past and present research which is going on with flipped classroom, thinks pair share activity and peer instruction.

Keywords: flipped classroom, think pair share, peer instruction, active learning

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6116 A Family of Distributions on Learnable Problems without Uniform Convergence

Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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6115 Transducers for Measuring Displacements of Rotating Blades in Turbomachines

Authors: Pavel Prochazka

Abstract:

The study deals with transducers for measuring vibration displacements of rotating blade tips in turbomachines. In order to prevent major accidents with extensive economic consequences, it shows an urgent need for every low-pressure steam turbine stage being equipped with modern non-contact measuring system providing information on blade loading, damage and residual lifetime under operation. The requirement of measuring vibration and static characteristics of steam turbine blades, therefore, calls for the development and operational verification of both new types of sensors and measuring principles and methods. The task is really demanding: to measure displacements of blade tips with a resolution of the order of 10 μm by speeds up to 750 m/s, humidity 100% and temperatures up to 200 °C. While in gas turbines are used primarily capacitive and optical transducers, these transducers cannot be used in steam turbines. The reason is moisture vapor, droplets of condensing water and dirt, which disable the function of sensors. Therefore, the most feasible approach was to focus on research of electromagnetic sensors featuring promising characteristics for given blade materials in a steam environment. Following types of sensors have been developed and both experimentally and theoretically studied in the Institute of Thermodynamics, Academy of Sciences of the Czech Republic: eddy-current, Hall effect, inductive and magnetoresistive. Eddy-current transducers demand a small distance of 1 to 2 mm and change properties in the harsh environment of steam turbines. Hall effect sensors have relatively low sensitivity, high values of offset, drift, and especially noise. Induction sensors do not require any supply current and have a simple construction. The magnitude of the sensors output voltage is dependent on the velocity of the measured body and concurrently on the varying magnetic induction, and they cannot be used statically. Magnetoresistive sensors are formed by magnetoresistors arranged into a Wheatstone bridge. Supplying the sensor from a current source provides better linearity. The MR sensors can be used permanently for temperatures up to 200 °C at lower values of the supply current of about 1 mA. The frequency range of 0 to 300 kHz is by an order higher comparing to the Hall effect and induction sensors. The frequency band starts at zero frequency, which is very important because the sensors can be calibrated statically. The MR sensors feature high sensitivity and low noise. The symmetry of the bridge arrangement leads to a high common mode rejection ratio and suppressing disturbances, which is important, especially in industrial applications. The MR sensors feature high sensitivity, high common mode rejection ratio, and low noise, which is important, especially in industrial applications. Magnetoresistive transducers provide a range of excellent properties indicating their priority for displacement measurements of rotating blades in turbomachines.

Keywords: turbines, blade vibration, blade tip timing, non-contact sensors, magnetoresistive sensors

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6114 Automatic Seizure Detection Using Weighted Permutation Entropy and Support Vector Machine

Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

Abstract:

The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

Procedia PDF Downloads 373
6113 Advances of Image Processing in Precision Agriculture: Using Deep Learning Convolution Neural Network for Soil Nutrient Classification

Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

Abstract:

Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

Procedia PDF Downloads 318
6112 Thick Data Techniques for Identifying Abnormality in Video Frames for Wireless Capsule Endoscopy

Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

Abstract:

Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

Procedia PDF Downloads 156
6111 Selection of Intensity Measure in Probabilistic Seismic Risk Assessment of a Turkish Railway Bridge

Authors: M. F. Yilmaz, B. Ö. Çağlayan

Abstract:

Fragility curve is an effective common used tool to determine the earthquake performance of structural and nonstructural components. Also, it is used to determine the nonlinear behavior of bridges. There are many historical bridges in the Turkish railway network; the earthquake performances of these bridges are needed to be investigated. To derive fragility curve Intensity measures (IMs) and Engineering demand parameters (EDP) are needed to be determined. And the relation between IMs and EDP are needed to be derived. In this study, a typical simply supported steel girder riveted railway bridge is studied. Fragility curves of this bridge are derived by two parameters lognormal distribution. Time history analyses are done for selected 60 real earthquake data to determine the relation between IMs and EDP. Moreover, efficiency, practicality, and sufficiency of three different IMs are discussed. PGA, Sa(0.2s) and Sa(1s), the most common used IMs parameters for fragility curve in the literature, are taken into consideration in terms of efficiency, practicality and sufficiency.

Keywords: railway bridges, earthquake performance, fragility analyses, selection of intensity measures

Procedia PDF Downloads 360
6110 Analysis of the Significance of Multimedia Channels Using Sparse PCA and Regularized SVD

Authors: Kourosh Modarresi

Abstract:

The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

Procedia PDF Downloads 311