Search results for: covering machine
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3486

Search results for: covering machine

966 Cutting Performance of BDD Coating on WC-Co Tools

Authors: Feng Xu, Zhaozhi Liu, Junhua Xu, Xiaolong Tang, Dunwen Zuo

Abstract:

Chemical vapor deposition (CVD) diamond coated cutting tool has excellent cutting performance, it is the most ideal tool for the processing of nonferrous metals and alloys, composites, nonmetallic materials and other difficult-to-machine materials efficiently and accurately. Depositing CVD diamond coating on the cemented carbide with high cobalt content can improve its toughness and strength, therefore, it is very important to research on the preparation technology and cutting properties of CVD diamond coated cemented carbide cutting tool with high cobalt content. The preparation technology of boron-doped diamond (BDD) coating has been studied and the coated drills were prepared. BDD coating were deposited on the drills by using the optimized parameters and the SEM results show that there are no cracks or collapses in the coating. Cutting tests with the prepared drills against the silumin and aluminum base printed circuit board (PCB) have been studied. The results show that the wear amount of the coated drill is small and the machined surface has a better precision. The coating does not come off during the test, which shows good adhesion and cutting performance of the drill.

Keywords: cemented carbide with high cobalt content, CVD boron-doped diamond, cutting test, drill

Procedia PDF Downloads 440
965 Evaluating Urban City Indices: A Study for Investigating Functional Domains, Indicators and Integration Methods

Authors: Fatih Gundogan, Fatih Kafali, Abdullah Karadag, Alper Baloglu, Ersoy Pehlivan, Mustafa Eruyar, Osman Bayram, Orhan Karademiroglu, Wasim Shoman

Abstract:

Nowadays many cities around the world are investing their efforts and resources for the purpose of facilitating their citizen’s life and making cities more livable and sustainable by implementing newly emerged phenomena of smart city. For this purpose, related research institutions prepare and publish smart city indices or benchmarking reports aiming to measure the city’s current ‘smartness’ status. Several functional domains, various indicators along different selection and calculation methods are found within such indices and reports. The selection criteria varied for each institution resulting in inconsistency in the ranking and evaluating. This research aims to evaluate the impact of selecting such functional domains, indicators and calculation methods which may cause change in the rank. For that, six functional domains, i.e. Environment, Mobility, Economy, People, Living and governance, were selected covering 19 focus areas and 41 sub-focus (variable) areas. 60 out of 191 indicators were also selected according to several criteria. These were identified as a result of extensive literature review for 13 well known global indices and research and the ISO 37120 standards of sustainable development of communities. The values of the identified indicators were obtained from reliable sources for ten cities. The values of each indicator for the selected cities were normalized and standardized to objectively investigate the impact of the chosen indicators. Moreover, the effect of choosing an integration method to represent the values of indicators for each city is investigated by comparing the results of two of the most used methods i.e. geometric aggregation and fuzzy logic. The essence of these methods is assigning a weight to each indicator its relative significance. However, both methods resulted in different weights for the same indicator. As a result of this study, the alternation in city ranking resulting from each method was investigated and discussed separately. Generally, each method illustrated different ranking for the selected cities. However, it was observed that within certain functional areas the rank remained unchanged in both integration method. Based on the results of the study, it is recommended utilizing a common platform and method to objectively evaluate cities around the world. The common method should provide policymakers proper tools to evaluate their decisions and investments relative to other cities. Moreover, for smart cities indices, at least 481 different indicators were found, which is an immense number of indicators to be considered, especially for a smart city index. Further works should be devoted to finding mutual indicators representing the index purpose globally and objectively.

Keywords: functional domain, urban city index, indicator, smart city

Procedia PDF Downloads 149
964 Role of Institutional Quality as a Key Determinant of FDI Flows in Developing Asian Economies

Authors: Bikash Ranjan Mishra, Lopamudra D. Satpathy

Abstract:

In the wake of the phenomenal surge in international business in the last decades or more, both the developed and developing economies around the world are in massive competition to attract more and more FDI flows. While the developed countries have marched ahead in the race, the developing countries, especially those of Asian economies, have followed them at a rapid pace. While most of the previous studies have analysed the role of institutional quality in the promotion of FDI flows in developing countries, very few studies have taken an integrated approach of examining the comprehensive impact of institutional quality, globalization pattern and domestic financial development on FDI flows. In this context, the paper contributes to the literature in two important ways. Firstly, two composite indices of institutional quality and domestic financial development for the Asian countries are constructed in comparison to earlier studies that resort to a single variable for indicating the institutional quality and domestic financial development. Secondly, the impact of these variables on FDI flows through their interaction with geographical region is investigated. The study uses panel data covering the time period of 1996 to 2012 by selecting twenty Asian developing countries by emphasizing the quality of institutions from the geographical regions of eastern, south-eastern, southern and western Asia. Control of corruption, better rule of law, regulatory quality, effectiveness of the government, political stability and voice and accountability are used as indicators of institutional quality. Besides these, the study takes into account the domestic credits in the hands of public, private sectors and in stock markets as domestic financial indicators. First in the specification of model, a factor analysis is performed to reduce the vast determinants, which are highly correlated with each other, to a manageable size. Afterwards, a reduced version of the model is estimated with the extracted factors in the form of index as independent variables along with a set of control variables. It is found that the institutional quality index and index of globalization exert a significant effect on FDI inflows of the host countries; in contrast, the domestic financial index does not seem to play much worthy role. Finally, some robustness tests are performed to make sure that the results are not sensitive to temporal and spatial unobserved heterogeneity. On the basis of the above study, one general inference can be drawn from the policy prescription point of view that the government of these developing countries should strengthen their domestic institution, both financial and non-financial. In addition to these, welfare policies should also target for rapid globalization. If the financial and non-financial institutions of these developing countries become sound and grow more globalized in the economic, social and political domain, then they can appeal to more amounts of FDI inflows that will subsequently result in advancement of these economies.

Keywords: Asian developing economies, FDI, institutional quality, panel data

Procedia PDF Downloads 315
963 Implementation of a Photo-Curable 3D Additive Manufacturing Technology with Grey Capability by Using Piezo Ink-jets

Authors: Ming-Jong Tsai, Y. L. Cheng, Y. L. Kuo, S. Y. Hsiao, J. W. Chen, P. H. Liu, D. H. Chen

Abstract:

The 3D printing is a combination of digital technology, material science, intelligent manufacturing and control of opto-mechatronics systems. It is called the third industrial revolution from the view of the Economist Journal. A color 3D printing machine may provide the necessary support for high value-added industrial and commercial design, architectural design, personal boutique, and 3D artist’s creation. The main goal of this paper is to develop photo-curable color 3D manufacturing technology and system implementation. The key technologies include (1) Photo-curable color 3D additive manufacturing processes development and materials research (2) Piezo type ink-jet head control and Opto-mechatronics integration technique of the photo-curable color 3D laminated manufacturing system. The proposed system is integrated with single Piezo type ink-jet head with two individual channels for two primary UV light curable color resins which can provide for future colorful 3D printing solutions. The main research results are 16 grey levels and grey resolution of 75 dpi.

Keywords: 3D printing, additive manufacturing, color, photo-curable, Piezo type ink-jet, UV Resin

Procedia PDF Downloads 562
962 Examines the Proportionality between the Needs of Industry and Technical and Vocational Training of Male and Female Vocational Schools

Authors: Khalil Aryanfar, Pariya Gholipor, Elmira Hafez

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This study examines the proportionality between the needs of industry and technical and vocational training of male and female vocational schools. The research method was descriptive that was conducted in two parts: documentary analysis and needs assessment and Delphi method was used in the need assessment. The statistical population of the study included 312 individuals from the industry sector employers and 52 of them were selected through stratified random sampling. Methods of data collection in this study, upstream documents include: document of the development of technical and vocational training, Statistical Yearbook 1393 in Tehran, the available documents in Isfahan Planning Department, the findings indicate that there is an almost proportionality between the needs of industry and Vocational training of male and female vocational schools in fields of welding, industrial electronics, electro technique, industrial drawing, auto mechanics, design, packaging, machine tool, metalworking, construction, accounting, computer graphics and the Administrative Affairs. The findings indicate that there is no proportionality between the needs of industry and Vocational training of male and female vocational schools in fields of Thermal - cooling systems, building electricity, building drawing, interior architecture, car electricity and motor repair.

Keywords: needs assessment, technical and vocational training, industry

Procedia PDF Downloads 455
961 Modification of Unsaturated Fatty Acids Derived from Tall Oil Using Micro/Mesoporous Materials Based on H-ZSM-22 Zeolite

Authors: Xinyu Wei, Mingming Peng, Kenji Kamiya, Eika Qian

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Iso-stearic acid as a saturated fatty acid with a branched chain shows a low pour point, high oxidative stability and great biodegradability. The industrial production of iso-stearic acid involves first isomerizing unsaturated fatty acids into branched-chain unsaturated fatty acids (BUFAs), followed by hydrogenating the branched-chain unsaturated fatty acids to obtain iso-stearic acid. However, the production yield of iso-stearic acid is reportedly less than 30%. In recent decades, extensive research has been conducted on branched fatty acids. Most research has replaced acidic clays with zeolites due to their high selectivity, good thermal stability, and renewability. It was reported that isomerization of unsaturated fatty acid occurred mainly inside the zeolite channel. In contrast, the production of by-products like dimer acid mainly occurs at acid sites outside the surface of zeolite. Further, the deactivation of catalysts is attributed to the pore blockage of zeolite. In the present study, micro/mesoporous ZSM-22 zeolites were developed. It is clear that the synthesis of a micro/mesoporous ZSM-22 zeolite is regarded as the ideal strategy owing to its ability to minimize coke formation. Different mesoporosities micro/mesoporous H-ZSM-22 zeolites were prepared through recrystallization of ZSM-22 using sodium hydroxide solution (0.2-1M) with cetyltrimethylammonium bromide template (CTAB). The structure, morphology, porosity, acidity, and isomerization performance of the prepared catalysts were characterized and evaluated. The dissolution and recrystallization process of the H-ZSM-22 microporous zeolite led to the formation of approximately 4 nm-sized mesoporous channels on the outer surface of the microporous zeolite, resulting in a micro/mesoporous material. This process increased the weak Brønsted acid sites at the pore mouth while reducing the total number of acid sites in ZSM-22. Finally, an activity test was conducted using oleic acid as a model compound in a fixed-bed reactor. The activity test results revealed that micro/mesoporous H-ZSM-22 zeolites exhibited a high isomerization activity, reaching >70% selectivity and >50% yield of BUFAs. Furthermore, the yield of oligomers was limited to less than 20%. This demonstrates that the presence of mesopores in ZSM-22 enhances contact between the feedstock and the active sites within the catalyst, thereby increasing catalyst activity. Additionally, a portion of the dissolved and recrystallized silica adhered to the catalyst's surface, covering the surface-active sites, which reduced the formation of oligomers. This study offers distinct insights into the production of iso-stearic acid using a fixed-bed reactor, paving the way for future research in this area.

Keywords: Iso-stearic acid, oleic acid, skeletal isomerization, micro/mesoporous, ZSM-22

Procedia PDF Downloads 26
960 Push-Out Bond Strength of Two Root-End Filling Materials in Root-End Cavities Prepared by Er,Cr: YSGG Laser or Ultrasonic Technique

Authors: Noushin Shokouhinejad, Hasan Razmi, Reza Fekrazad, Saeed Asgary, Ammar Neshati, Hadi Assadian, Sanam Kheirieh

Abstract:

This study compared the push-out bond strength of mineral trioxide aggregate (MTA) and a new endodontic cement (NEC) as root-end filling materials in root-end cavities prepared by ultrasonic technique (US) or Er,Cr:YSGG laser (L). Eighty single-rooted extracted human teeth were endodontically treated, apicectomised and randomly divided into four following groups (n = 20): US/MTA, US/NEC, L/MTA and L/NEC. In US/MTA and US/NEC groups, rooted cavities were prepared with ultrasonic retrotip and filled with MTA and NEC, respectively. In L/MTA and L/NEC groups, root-end cavities were prepared using Er, Cr:YSGG laser and filled with MTA and NEC, respectively. Each root was cut apically to create a 2 mm-thick root slice for measurement of bond strength using a universal testing machine. Then, all slices were examined to determine the mode of bond failure. Data were analysed using two-way ANOVA. Root-end filling materials showed significantly higher bond strength in root-end cavities prepared using the ultrasonic technique (US/MTA and US/NEC) (P < 0.001). The bond strengths of MTA and NEC did not differ significantly. The failure modes were mainly adhesive for MTA, but cohesive for NEC. In conclusion, bond strengths of MTA and NEC to root-end cavities were comparable and higher in ultrasonically prepared cavities.

Keywords: bond strength, Er, Cr:YSGG laser, MTA, NEC, root-end cavity

Procedia PDF Downloads 347
959 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

Procedia PDF Downloads 421
958 Analysis and Detection of Facial Expressions in Autism Spectrum Disorder People Using Machine Learning

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

Abstract:

Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

Procedia PDF Downloads 176
957 Using Deep Learning in Lyme Disease Diagnosis

Authors: Teja Koduru

Abstract:

Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

Procedia PDF Downloads 242
956 Automatic Verification Technology of Virtual Machine Software Patch on IaaS Cloud

Authors: Yoji Yamato

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In this paper, we propose an automatic verification technology of software patches for user virtual environments on IaaS Cloud to decrease verification costs of patches. In these days, IaaS services have been spread and many users can customize virtual machines on IaaS Cloud like their own private servers. Regarding to software patches of OS or middleware installed on virtual machines, users need to adopt and verify these patches by themselves. This task increases operation costs of users. Our proposed method replicates user virtual environments, extracts verification test cases for user virtual environments from test case DB, distributes patches to virtual machines on replicated environments and conducts those test cases automatically on replicated environments. We have implemented the proposed method on OpenStack using Jenkins and confirmed the feasibility. Using the implementation, we confirmed the effectiveness of test case creation efforts by our proposed idea of 2-tier abstraction of software functions and test cases. We also evaluated the automatic verification performance of environment replications, test cases extractions and test cases conductions.

Keywords: OpenStack, cloud computing, automatic verification, jenkins

Procedia PDF Downloads 491
955 A Study of Traditional Mode in the Framework of Sustainable Urban Transportation

Authors: Juanita, B. Kombaitan, Iwan Pratoyo Kusumantoro

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The traditional mode is a non-motorized vehicle powered by human or animal power. The objective of the study was to define the strategy of using traditional modes by the framework of sustainable urban transport in support of urban tourism activities. The study of the traditional mode does not include a modified mode using the engine power as motor tricycles are often called ‘bentor ‘in Indonesia. The use of non-motorized traditional mode in Indonesia has begun to shift, and its use began to be eliminated by the change of propulsion using the machine. In an effort to push back the use of traditional mode one of them with tourism activities. Strategies for the use of traditional modes within the framework of sustainable urban transport are seen from three dimensions: social, economic and environmental. The social dimension related to accessibility and livability, an economic dimension related to traditional modes can promote products and tourist attractions, while the environmental dimension related to the needs of the users/groups with respect to safety, comfort. The traditional mode is rarely noticed by the policy makers, and public opinion in its use needs attention. The involvement of policy-making between stakeholders and the community is needed in the development of sustainable traditional mode strategies in support of urban tourism activities.

Keywords: traditional mode, sustainable, urban, transportation

Procedia PDF Downloads 267
954 Massively Parallel Sequencing Improved Resolution for Paternity Testing

Authors: Xueying Zhao, Ke Ma, Hui Li, Yu Cao, Fan Yang, Qingwen Xu, Wenbin Liu

Abstract:

Massively parallel sequencing (MPS) technologies allow high-throughput sequencing analyses with a relatively affordable price and have gradually been applied to forensic casework. MPS technology identifies short tandem repeat (STR) loci based on sequence so that repeat motif variation within STRs can be detected, which may help one to infer the origin of the mutation in some cases. Here, we report on one case with one three-step mismatch (D18S51) in family trios based on both capillary electrophoresis (CE) and MPS typing. The alleles of the alleged father (AF) are [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₁₅. The mother’s alleles are [AGAA]₁₉ and [AGAA]₉AGGA[AGAA]₃. The questioned child’s (QC) alleles are [AGAA]₁₉ and [AGAA]₁₂. Given that the sequence variants in repeat regions of AF and mother are not observed in QC’s alleles, the QC’s allele [AGAA]₁₂ was likely inherited from the AF’s allele [AGAA]₁₅ by loss of three repeat [AGAA]. Besides, two new alleles of D18S51 in this study, [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₉AGGA[AGAA]₃, have not been reported before. All the results in this study were verified using Sanger-type sequencing. In summary, the MPS typing method can offer valuable information for forensic genetics research and play a promising role in paternity testing.

Keywords: family trios analysis, forensic casework, ion torrent personal genome machine (PGM), massively parallel sequencing (MPS)

Procedia PDF Downloads 302
953 Process Safety Management Digitalization via SHEQTool based on Occupational Safety and Health Administration and Center for Chemical Process Safety, a Case Study in Petrochemical Companies

Authors: Saeed Nazari, Masoom Nazari, Ali Hejazi, Siamak Sanoobari Ghazi Jahani, Mohammad Dehghani, Javad Vakili

Abstract:

More than ever, digitization is an imperative for businesses to keep their competitive advantages, foster innovation and reduce paperwork. To design and successfully implement digital transformation initiatives within process safety management system, employees need to be equipped with the right tool, frameworks, and best practices. we developed a unique full stack application so-called SHEQTool which is entirely dynamic based on our extensive expertise, experience, and client feedback to help business processes particularly operations safety management. We use our best knowledge and scientific methodologies published by CCPS and OSHA Guidelines to streamline operations and integrated them into task management within Petrochemical Companies. We digitalize their main process safety management system elements and their sub elements such as hazard identification and risk management, training and communication, inspection and audit, critical changes management, contractor management, permit to work, pre-start-up safety review, incident reporting and investigation, emergency response plan, personal protective equipment, occupational health, and action management in a fully customizable manner with no programming needs for users. We review the feedback from main actors within petrochemical plant which highlights improving their business performance and productivity as well as keep tracking their functions’ key performance indicators (KPIs) because it; 1) saves time, resources, and costs of all paperwork on our businesses (by Digitalization); 2) reduces errors and improve performance within management system by covering most of daily software needs of the organization and reduce complexity and associated costs of numerous tools and their required training (One Tool Approach); 3) focuses on management systems and integrate functions and put them into traceable task management (RASCI and Flowcharting); 4) helps the entire enterprise be resilient to any change of your processes, technologies, assets with minimum costs (through Organizational Resilience); 5) reduces significantly incidents and errors via world class safety management programs and elements (by Simplification); 6) gives the companies a systematic, traceable, risk based, process based, and science based integrated management system (via proper Methodologies); 7) helps business processes complies with ISO 9001, ISO 14001, ISO 45001, ISO 31000, best practices as well as legal regulations by PDCA approach (Compliance).

Keywords: process, safety, digitalization, management, risk, incident, SHEQTool, OSHA, CCPS

Procedia PDF Downloads 69
952 A Review on Parametric Optimization of Casting Processes Using Optimization Techniques

Authors: Bhrugesh Radadiya, Jaydeep Shah

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In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

Procedia PDF Downloads 729
951 Design and Implementation a Platform for Adaptive Online Learning Based on Fuzzy Logic

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 197
950 Mind Care Assistant - Companion App

Authors: Roshani Gusain, Deep Sinha, Karan Nayal, Anmol Kumar Mishra, Manav Singh

Abstract:

In this research paper, we introduce "Mind Care Assistant - Companion App", which is a Flutter and Firebase-based mental health monitor. The app wants to improve and monitor the mental health of its users, it uses noninvasive ways to check for a change in their emotional state. By responding to questions, the app will provide individualized suggestions ᅳ tasks and mindfulness exercises ᅳ for users who are depressed or anxious. The app features a chat-bot that incorporates cognitive behavioural therapy (CBT) principles and combines natural language processing with machine learning to develop personalised responses. The feature of the app that makes it easy for us to choose between iOS and Android is cross-platform, which allows users from both mobile systems to experience almost no changes in their interfaces. With Firebase integration synchronized and real-time data storage, security is easily possible. The paper covers the architecture of the app, how it was developed and some important features. The primary research result presents the promise of a "Mind Care Assistant" in mental health care using new wait-for-health technology, proposing a full stack application to be able to manage depression/anxiety and overall Mental well-being very effectively.

Keywords: mental health, mobile application, flutter, firebase, Depression, Anxiety

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949 Nilsson Model Performance in Estimating Bed Load Sediment, Case Study: Tale Zang Station

Authors: Nader Parsazadeh

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The variety of bed sediment load relationships, insufficient information and data, and the influence of river conditions make the selection of an optimum relationship for a given river extremely difficult. Hence, in order to select the best formulae, the bed load equations should be evaluated. The affecting factors need to be scrutinized, and equations should be verified. Also, re-evaluation may be needed. In this research, sediment bed load of Dez Dam at Tal-e Zang Station has been studied. After reviewing the available references, the most common formulae were selected that included Meir-Peter and Muller, using MS Excel to compute and evaluate data. Then, 52 series of already measured data at the station were re-measured, and the sediment bed load was determined. 1. The calculated bed load obtained by different equations showed a great difference with that of measured data. 2. r difference ratio from 0.5 to 2.00 was 0% for all equations except for Nilsson and Shields equations while it was 61.5 and 59.6% for Nilsson and Shields equations, respectively. 3. By reviewing results and discarding probably erroneous measured data measurements (by human or machine), one may use Nilsson Equation due to its r value higher than 1 as an effective equation for estimating bed load at Tal-e Zang Station in order to predict activities that depend upon bed sediment load estimate to be determined. Also, since only few studies have been conducted so far, these results may be of assistance to the operators and consulting companies.

Keywords: bed load, empirical relation ship, sediment, Tale Zang Station

Procedia PDF Downloads 363
948 The Impact of Physical Exercise on Gestational Diabetes and Maternal Weight Management: A Meta-Analysis

Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Physiological changes during pregnancy, such as alterations in the circulatory, respiratory, and musculoskeletal systems, can negatively impact daily physical activity. This reduced activity is often associated with an increased risk of adverse maternal health outcomes, particularly gestational diabetes mellitus (GDM) and excessive weight gain. This meta-analysis aims to evaluate the effectiveness of structured physical exercise interventions during pregnancy in reducing the risk of GDM and managing maternal weight gain. A comprehensive search was conducted across six major databases: PubMed, Cochrane Library, EMBASE, Web of Science, ScienceDirect, and ClinicalTrials.gov, covering the period from database inception until 2023. Randomized controlled trials (RCTs) that explored the effects of physical exercise programs on pregnant women with low physical activity levels were included. The search was performed using EndNote and results were managed using RevMan (Review Manager) for meta-analysis. RCTs involving healthy pregnant women with low levels of physical activity or sedentary lifestyles were selected. These RCTs must have incorporated structured exercise programs during pregnancy and reported on outcomes related to GDM and maternal weight gain. From an initial pool of 5,112 articles, 65 RCTs (involving 11,400 pregnant women) met the inclusion criteria. Data extraction was performed, followed by a quality assessment of the selected studies using the Cochrane Risk of Bias tool. The meta-analysis was conducted using RevMan software, where pooled relative risks (RR) and weighted mean differences (WMD) were calculated using a random-effects model to address heterogeneity across studies. Sensitivity analyses, subgroup analyses (based on factors such as exercise intensity, duration, and pregnancy stage), and publication bias assessments were also conducted. Structured physical exercise during pregnancy led to a significant reduction in the risk of developing GDM (RR = 0.68; P < 0.001), particularly when the exercise program was performed throughout the pregnancy (RR = 0.62; P = 0.035). In addition, maternal weight gain was significantly reduced (WMD = −1.18 kg; 95% CI −1.54 to −0.85; P < 0.001). There were no significant adverse effects reported for either the mother or the neonate, confirming that exercise interventions are safe for both. This meta-analysis highlights the positive impact of regular moderate physical activity during pregnancy in reducing the risk of GDM and managing maternal weight gain. These findings suggest that physical exercise should be encouraged as a routine part of prenatal care. However, more research is required to refine exercise recommendations and determine the most effective interventions based on individual risk factors and pregnancy stages.

Keywords: gestational diabetes, maternal weight management, meta-analysis, randomized controlled trials

Procedia PDF Downloads 18
947 FLIME - Fast Low Light Image Enhancement for Real-Time Video

Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

Procedia PDF Downloads 208
946 Short-Term Operation Planning for Energy Management of Exhibition Hall

Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

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945 Laying Hens' Feed Fortified with Pectin, Xanthan Gum and Guar Gum Aims to Reduce the Cholesterol in Muscle and Egg Yolk

Authors: Novia Dwi Prabandari, Diah Ayu Asmarani

Abstract:

Soluble fiber can accelerate the metabolism of cholesterol. Pectin and gum has been used in the form of substance additive for material stabilizer and emulsifier. Pectin supplementation in laying hens can decimate the cholesterol content in egg yolk and muscle. Therefore, this laying hens’ feed is regular feed chickens enriched with soluble fiber (Pectin, Xanthan gum, and Guar gum) to produce eggs and muscle with lower cholesterol than usual.The ingredients are mixed in the ratio of concentrate 45%, corn flour 25%, soybean meal 20%, and extract of soluble fiber 10%. Once all the ingredients are mixed and then evaporated with temperature < 80 °C. Then put in the grinding machine resulting in a circular shape with holes 2-3 mm in diameter, after it dried up the water content in the feed is less than 14%. Eggs from laying hen with soluble fiber fortification feed intake will have lower cholesterol levels in eggs than regular feed. So even with the cholesterol content in the muscle, it is because chicken feed fortified with soluble fiber will accelerate the metabolism of cholesterol and cause cholesterol deposits in the chicken less. The use of this kind of laying hens feed is produce eggs with high protein content can be consumed more for people who have hypercholesterolemia.

Keywords: pectin, xanthan gum, guar gum, laying hen, cholesterol

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944 Heavy Metal Contamination in Soils: Detection and Assessment Using Machine Learning Algorithms Based on Hyperspectral Images

Authors: Reem El Chakik

Abstract:

The levels of heavy metals in agricultural lands in Lebanon have been witnessing a noticeable increase in the past few years, due to increased anthropogenic pollution sources. Heavy metals pose a serious threat to the environment for being non-biodegradable and persistent, accumulating thus to dangerous levels in the soil. Besides the traditional laboratory and chemical analysis methods, Hyperspectral Imaging (HSI) has proven its efficiency in the rapid detection of HMs contamination. In Lebanon, a continuous environmental monitoring, including the monitoring of levels of HMs in agricultural soils, is lacking. This is due in part to the high cost of analysis. Hence, this proposed research aims at defining the current national status of HMs contamination in agricultural soil, and to evaluate the effectiveness of using HSI in the detection of HM in contaminated agricultural fields. To achieve the two main objectives of this study, soil samples were collected from different areas throughout the country and were analyzed for HMs using Atomic Absorption Spectrophotometry (AAS). The results were compared to those obtained from the HSI technique that was applied using Hyspex SWIR-384 camera. The results showed that the Lebanese agricultural soils contain high contamination levels of Zn, and that the more clayey the soil is, the lower reflectance it has.

Keywords: agricultural soils in Lebanon, atomic absorption spectrophotometer, hyperspectral imaging., heavy metals contamination

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943 Covid-19, Diagnosis with Computed Tomography and Artificial Intelligence, in a Few Simple Words

Authors: Angelis P. Barlampas

Abstract:

Target: The (SARS-CoV-2) is still a threat. AI software could be useful, categorizing the disease into different severities and indicate the extent of the lesions. Materials and methods: AI is a new revolutionary technique, which uses powered computerized systems, to do what a human being does more rapidly, more easily, as accurate and diagnostically safe as the original medical report and, in certain circumstances, even better, saving time and helping the health system to overcome problems, such as work overload and human fatigue. Results: It will be given an effort to describe to the inexperienced reader (see figures), as simple as possible, how an artificial intelligence system diagnoses computed tomography pictures. First, the computerized machine learns the physiologic motives of lung parenchyma by being feeded with normal structured images of the lung tissue. Having being used to recognizing normal structures, it can then easily indentify the pathologic ones, as their images do not fit to known normal picture motives. It is the same way as when someone spends his free time in reading magazines with quizzes, such as <> and <>. General conclusion: The AI mimics the physiological processes of the human mind, but it does that more efficiently and rapidly and provides results in a few seconds, whereas an experienced radiologist needs many days to do that, or even worse, he is unable to accomplish such a huge task.

Keywords: covid-19, artificial intelligence, automated imaging, CT, chest imaging

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942 Inter Laboratory Comparison with Coordinate Measuring Machine and Uncertainty Analysis

Authors: Tugrul Torun, Ihsan A. Yuksel, Si̇nem On Aktan, Taha K. Vezi̇roglu

Abstract:

In the quality control processes in some industries, the usage of CMM has increased in recent years. Consequently, the CMMs play important roles in the acceptance or rejection of manufactured parts. For parts, it’s important to be able to make decisions by performing fast measurements. According to related technical drawing and its tolerances, measurement uncertainty should also be considered during assessment. Since uncertainty calculation is difficult and time-consuming, most companies ignore the uncertainty value in their routine inspection method. Although studies on measurement uncertainty have been carried out on CMM’s in recent years, there is still no applicable method for analyzing task-specific measurement uncertainty. There are some standard series for calculating measurement uncertainty (ISO-15530); it is not possible to use it in industrial measurement because it is not a practical method for standard measurement routine. In this study, the inter-laboratory comparison test has been carried out in the ROKETSAN A.Ş. with all dimensional inspection units. The reference part that we used is traceable to the national metrology institute TUBİTAK UME. Each unit has measured reference parts according to related technical drawings, and the task-specific measuring uncertainty has been calculated with related parameters. According to measurement results and uncertainty values, the En values have been calculated.

Keywords: coordinate measurement, CMM, comparison, uncertainty

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941 Structural Analysis and Evolution of 18th Century Ottoman Imperial Mosques (1750-1799) in Comparison with the Classical Period Examples

Authors: U. Demir

Abstract:

18th century which is the period of 'change' in the Ottoman Empire, affects the architecture as well, where the Classical period is left behind, architecture is differentiated in the form language. This change is especially noticeable in monumental buildings and thus manifested itself in the mosques. But, is it possible to talk about the structural context of the 'change' which has been occurred in decoration? The aim of this study is to investigate the changes and classical relations of the 18th century mosques through plan schedules and structure systems. This study focuses on the monumental mosques constructed during the reign of the three sultans who ruled in the second half of the century (Mustafa the 3rd 1757-1774, Abdülhamid the 1st 1774-1789 and Selim the 3rd). According to their construction years these are 'Ayazma, Laleli, Zeyneb Sultan, Fatih, Beylerbeyi, Şebsefa Kadın, Eyüb Sultan, Mihrişah Valide Sultan and Üsküdar-Selimiye' mosques. As a plan scheme, four mosques have a square or close to a rectangular square scheme, while the others have a rectangle scheme and showing the longitudinal development of the mihrab axis. This situation is widespread throughout the period. In addition to the longitudinal development plan, which is the general characteristic of the 18th century mosques, the use of the classical plan schemes continued in the same direction. Spatialization of the mihrab area was applied to the five mosques while other mosques were applied as niches on the wall surface. This situation is widespread in the period of the second half of the century. In the classical period, the lodges may be located at the back of the mosques interior, not interfering with the main worship area. In the period, the lodges were withdrawn from the main worship area. They are separated from the main interior with their own structural and covering systems. The plans seem to be formed as a result of the addition of lodge parts to the northern part of the Classical period mosques. The 18th century mosques are the constructions where the change of the architectural language and style can be observed easily. This change and the break from the classical period manifest themselves quickly in the structural elements, wall surface decorations, pencil work designs, small scale decor elements, motifs. The speed and intensity of change in the decor does not occur the same as in structural context. The mosque construction rules from the traditional and classical era still continues in the century. While some mosque structures have a plan which is inherited from the classical successor, some of were constructed with the same classical period rules. Nonetheless, the location and transformation of the lodges, which are affecting the interior design, are noteworthy. They provide a significant transition on the way to the new language of the mosque design that will be experienced in the next century. It is intended to draw attention to the structural evolution of the 18th century Ottoman architecture through the royal mosques within the scope of this conference.

Keywords: mosque structure, Ottoman architecture, structural evolution, 18th century architecture

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940 Analysis of Noodle Production Process at Yan Hu Food Manufacturing: Basis for Production Improvement

Authors: Rhadinia Tayag-Relanes, Felina C. Young

Abstract:

This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: continuous improvement, process, operations, PDCA

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939 Iot Device Cost Effective Storage Architecture and Real-Time Data Analysis/Data Privacy Framework

Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

Abstract:

This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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938 The Administration of Infection Diseases During the Pandemic COVID-19 and the Role of the Differential Diagnosis with Biomarkers VB10

Authors: Sofia Papadimitriou

Abstract:

INTRODUCTION: The differential diagnosis between acute viral and bacterial infections is an important cost-effectiveness parameter at the stage of the treatment process in order to achieve the maximum benefits in therapeutic intervention by combining the minimum cost to ensure the proper use of antibiotics.The discovery of sensitive and robust molecular diagnostic tests in response to the role of the host in infections has enhanced the accurate diagnosis and differentiation of infections. METHOD: The study used a sample of six independent blood samples (total=756) which are associated with human proteins-proteins, each of which at the transcription stage expresses a different response in the host network between viral and bacterial infections.Τhe individual blood samples are subjected to a sequence of computer filters that identify a gene panel corresponding to an autonomous diagnostic score. The data set and the correspondence of the gene panel to the diagnostic patents a new Bangalore -Viral Bacterial (BL-VB). FINDING: We use a biomarker based on the blood of 10 genes(Panel-VB) that are an important prognostic value for the detection of viruses from bacterial infections with a weighted average AUROC of 0.97(95% CL:0.96-0.99) in eleven independent samples (sets n=898). We discovered a base with a patient score (VB 10 ) according to the table, which is a significant diagnostic value with a weighted average of AUROC 0.94(95% CL: 0.91-0.98) in 2996 patient samples from 56 public sets of data from 19 different countries. We also studied VB 10 in a new cohort of South India (BL-VB,n=56) and found 97% accuracy in confirmed cases of viral and bacterial infections. We found that VB 10 (a)accurately identifies the type of infection even in unspecified cases negative to the culture (b) shows its clinical condition recovery and (c) applies to all age groups, covering a wide range of acute bacterial and viral infectious, including non-specific pathogens. We applied our VB 10 rating to publicly available COVID 19 data and found that our rating diagnosed viral infection in patient samples. RESULTS: Τhe results of the study showed the diagnostic power of the biomarker VB 10 as a diagnostic test for the accurate diagnosis of acute infections in recovery conditions. We look forward to helping you make clinical decisions about prescribing antibiotics and integrating them into your policies management of antibiotic stewardship efforts. CONCLUSIONS: Overall, we are developing a new property of the RNA-based biomarker and a new blood test to differentiate between viral and bacterial infections to assist a physician in designing the optimal treatment regimen to contribute to the proper use of antibiotics and reduce the burden on antimicrobial resistance, AMR.

Keywords: acute infections, antimicrobial resistance, biomarker, blood transcriptome, systems biology, classifier diagnostic score

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937 Detection of Cyberattacks on the Metaverse Based on First-Order Logic

Authors: Sulaiman Al Amro

Abstract:

There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies and is therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and, thus, the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: security, privacy, metaverse, cyberattacks, detection, first-order logic

Procedia PDF Downloads 41