Search results for: data utilization

Authors: Zaw Z Aung

Abstract:

Background: High-risk groups for hepatitis B infection (HBV) are people who injected drugs (PWID), men who have sex with men (MSM), people living with HIV (PLHIV) and persons with hepatitis C (HCV), etc. HBV/HCV coinfected patients are at increased risk of cirrhosis, hepatic decompensation and hepatocellular carcinoma. To the best of author’s knowledge, there is currently no data for hepatitis B vaccine utilization in HCV positive patients and their antibody response. Methodology: From February 2018 to May 2018, consented participants at or above 18 years who came to the clinic in Mandalay were tested with the anti-HCV rapid test. Those who tested HCV positive (n=168) were further tested with hepatitis B profile and asked about their previous hepatitis B vaccination history and risk factors. Results: Out of 168 HCV positive participants, three were excluded for active HBV infections. The remaining 165 were categorized into previously vaccinated 64% (n=106) and unvaccinated 36% (n=59) There were three characteristics groups- PWID monoinfected (n=77), General Population (GP) monoinfected (n=22) and HIV/HCV coinfected participants (n=66). Unvaccinated participants were highest in HIV/HCV, with 68%(n=45) followed by GP (23%, n=5) and PWID (12%, n=9). Among previously vaccinated participants, the highest percentage was PWID (88%, n=68), the second highest was GP (77%, n=17) and lowest in HIV/HCV patients (32%, n=21). 63 participants completed third doses of vaccination (PWID=36, GP=13, HIV/HCV=14). 53% of participants who completed 3 dose of hepatitis B were non-responders (n=34): HIV/HCV (86%, n=12), PWID (44%, n=16), and GP (46%, n=6) Conclusion: Even in the presence of effective and safe hepatitis B vaccine, uptake is low among high risk groups especially PLHIV that needs to be improved. Integration or collaboration of hepatitis B vaccination program, HIV/AIDS and hepatitis C treatment centers is desirable. About half of vaccinated participants were non-responders so that optimal doses, schedule and follow-up testing need to be addressed carefully for those groups.

Keywords: Hepatitis B vaccine, Hepatitis C, HIV, Myanmar

Procedia PDF Downloads 139

Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

Abstract:

This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

Procedia PDF Downloads 344

Authors: Lucas B. Naves, Maria José Abreu

Abstract:

Reprocessing single-use device has attracted interesting on the medical environment over the last decades. The reprocessing technique was sought in order to reduce the cost of purchasing the new medical device, which can achieve almost double of the price of the reprocessed product. In this manuscript, we have done a literature review, aiming the reuse of medical device that was firstly designed for single use only, but has become, more and more, effective on its reprocessing procedure. We also show the regulation, the countries which allows this procedure, the classification of these device and also the most important issue concerning the re-utilization of medical device, how to minimizing the risk of gram positive and negative bacteria, avoid cross-contamination, hepatitis B (HBV), and C (HCV) virus, and also human immunodeficiency virus (HIV).

Keywords: reusing, reprocessing, single-use medical device, HIV, hepatitis B and C

Procedia PDF Downloads 385

Authors: Ashima Anurag Sharma

Abstract:

Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 521

Authors: Fuad M. Alkoot

Abstract:

Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

Procedia PDF Downloads 556

Authors: Abhinay Puvvala, Veerendra Kumar Rai

Abstract:

A bottleneck situation arises when the outflow is lesser than the inflow in a pipe-like setup. A more practical interpretation of bottlenecks emphasizes on the realization of Service Level Objectives (SLOs) at given workloads. Our approach detects two key aspects of bottlenecks – when and where. To identify ‘when’ we continuously poll on certain key metrics such as resource utilization, processing time, request backlog and throughput at a system level. Further, when the slope of the expected sojourn time at a workload is greater than ‘K’ times the slope of expected sojourn time at the previous step of the workload while the workload is being gradually increased in discrete steps, a bottleneck situation arises. ‘K’ defines the threshold condition and is computed based on the system’s service level objectives. The second aspect of our approach is to identify the location of the bottleneck. In multi-tier systems with a complex network of layers, it is a challenging problem to locate bottleneck that affects the overall system performance. We stage the system by varying workload incrementally to draw a correlation between load increase and system performance to the point where Service Level Objectives are violated. During the staging process, multiple metrics are monitored at hardware and application levels. The correlations are drawn between metrics and the overall system performance. These correlations along with the Service Level Objectives are used to arrive at the threshold conditions for each of these metrics. Subsequently, the same method used to identify when a bottleneck occurs is used on metrics data with threshold conditions to locate bottlenecks.

Keywords: bottleneck, workload, service level objectives (SLOs), throughput, system performance

Procedia PDF Downloads 225

Authors: Matthew Kostawich, Mohammed Elmorsy, Mohamed Sayed Sifat, Shoukry Shams, Mahmoud Elsaadany

Abstract:

6G communication systems represent the nominal future extension of current wireless technology, where its impact is extended to touch upon all human activities, including medical, security, and entertainment applications. As a result, human needs are allocated among the highest priority aspects of the system design and requirements. 6G communications is expected to replace all the current video conferencing with interactive virtual reality meetings involving high data-rate transmission merged with massive distributed computing resources. In addition, the current expansion of IoT applications must be mitigated with significant network changes to provide a reasonable Quality of Service (QoS). This directly implies a high demand for Human-Computer Interaction (HCI) through mobile computing modules in future wireless communication systems. This article proposes the utilization of a Printed Ridge Gap Waveguide (PRGW) to host the wearable nodes. To the best of our knowledge, we propose for the first time a physical layer analysis within the context of a complete architecture. A thorough study is provided on the impact of the distortion of the guiding structure on the overall system performance. The proposed structure shows small latency and small losses, highlighting its compatibility with future applications.

Keywords: ridge gap waveguide, edge computing module, 6G, multimedia IoT applications

Procedia PDF Downloads 64

Authors: Fei Gao, Rodolfo C. Raga Jr.

Abstract:

This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

Procedia PDF Downloads 66

Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini

Abstract:

Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.

Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling

Procedia PDF Downloads 88

Authors: Sumitra Sharma, Christina Parker, Kathleen Finlayson, Clint Douglas, Niall Higgins

Abstract:

Background: Telehealth services have potential to increase accessibility, utilization, and effectiveness of healthcare services. As the telehealth services are yet to integrate within regular hospital services in Nepal, the use of the telehealth services among adults with diabetes is scarce. Prior to implementation of telehealth services for adults with diabetes, it is necessary to examine influencing factors of telehealth services. Objective: This study aimed to investigate factors influencing telehealth services for diabetes care in Nepal. Methods: This study used a mixed-method study design which included a cross-sectional survey among adults with diabetes and semi-structured interviews among key healthcare professionals of Nepal. The study was conducted in a medical out-patient department of a tertiary hospital of Nepal. The survey adapted a previously validated questionnaire, while semi-structured questions for interviews were developed from literature review and experts consultation. All interviews were audio-recorded, and inductive content analysis was used to code transcripts and develop themes. For a survey, a descriptive analysis, chi-square test, and Mann Whitney U test were used to analyze the data. Results: One hundred adults with diabetes were participated in a survey, and seven healthcare professionals were recruited for interviews. In a survey, just over half of the participants (53%) were male, and others were female. Almost all participants (98%) owned a mobile phone, and 67% of them had a computer with internet access at home. Majority of participants had experience in using Facebook messenger (95%), followed by Viber (60%) and Zoom (26%). Almost all of the participants (96%) were willing to use telehealth services. There were significant associations between female sex and participants living 10 km away from the hospital with their willingness to use telehealth services. There was a significant association between participants' self-perception of good health status with their willingness to use video-conference calls and phone calls to use telehealth services. Seven themes were developed from interview data which are related to predisposing, reinforcing, and enabling factors influencing telehealth services for diabetes care in Nepal. Conclusion: In summary, several factors were found to influence the use of telehealth services for diabetes care in Nepal. For effective implementation of a sustainable telehealth services for adults with diabetes in Nepal, these factors need to be considered.

Keywords: contributing factors, diabetes mellitus, developing countries, telemedicine, telecare

Procedia PDF Downloads 67

Authors: Fang-Bo Yu, Li-Bo Guan, Sheng-Dao Shan

Abstract:

Biogas slurry was mixed with six commercial fungicides and screening against 11 phytopathogens was carried out. Results showed that inhibition of biogas slurry was different for the test strains and no significant difference between treatments of Didymella bryoniae, Fusarium oxysporum f. sp. vasinfectum, Aspergillus niger, Rhizoctonia cerealis, F. graminearum and Septoria tritici was observed. However, significant differences were found among Penicillium sp., Botrytis cinerea, Alternaria sonali, F. oxysporum F. sp. melonis and Sclerotinia sclerotiorum. The approach described here presents a promising alternative to current manipulation although some issues still need further examination. This study could contribute to the development of sustainable agriculture and better utilization of biogas slurry.

Keywords: anaerobic digestion, biogas slurry, phytopathogen, sustainable agriculture

Procedia PDF Downloads 324

Authors: Waziri Victor Onomza, John K. Alhassan, Idris Ismaila, Noel Dogonyaro Moses

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute theoretical presentations in high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, homomorphic, homomorphic encryption scheme

Procedia PDF Downloads 372

Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

Abstract:

The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

Procedia PDF Downloads 74

Authors: Umego Chukwudi T., Ntui Valentine O., Uyoh Edak A.

Abstract:

Phosphorus (P) deficiency has been identified as a major hindrance to rice production the world over. Eleven (11) rice genotypes predominantly used by local farmers in Nigeria were studied for their responses to P deficient conditions. The characterization was based on morpho-physiologic parameters. The genotypes were screened using a hydroponic system in a modified Hoagland’s solution. Morphological and physiologic parameters, including Plant height (PH), number of tillers per plant, shoot dry weight (SDW), shoot phosphate concentration (SPC), and chlorophyll content, were recorded after exposure to three levels of phosphate concentration (0µM, 400 µM, and 800 µM). The data obtained were subjected to analysis of variance (ANOVA), and the means were separated using least significance difference tests. The results obtained showed that P starvation caused a significant (p≤0.05) reduction in PH, SDW, and tillering and also triggered a significant (p≤0.05) increase in root length among the genotypes. The Pearsons correlation coefficient was used to estimate the relationships among studied parameters, and a significant negative correlation was observed between plant height and root length. FARO63 was identified as a highly tolerant genotype to P deficiency with a low (0.24) SPC and higher (4.81) phosphate utilization efficiency (PUE). This study has identified FARO63 as a true tolerant genotype to Phosphate deficiency, which will be useful in breeding for phosphate deficiency tolerance in rice and thus combating food insecurity.

Keywords: phosphate deficiency, rice genotypes, hydroponic system, food security

Procedia PDF Downloads 99

Authors: Bilquis Ferdousi

Abstract:

With the exponential growth of the online business, the threat to consumers’ privacy and data security has become a serious challenge. This literature review-based study focuses on a better understanding of those threats and what legislative measures have been taken to address those challenges. Research shows that people are increasingly involved in online business using different digital devices and platforms, although this practice varies based on age groups. The threat to consumers’ privacy and data security is a serious hindrance in developing trust among consumers in online businesses. There are some legislative measures taken at the federal and state level to protect consumers’ privacy and data security. The study was based on an extensive review of current literature on protecting consumers’ privacy and data security and legislative measures that have been taken.

Keywords: privacy, data security, legislation, online business

Procedia PDF Downloads 97

Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

Abstract:

This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

Procedia PDF Downloads 214

Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

Abstract:

The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

Procedia PDF Downloads 377

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

Abstract:

Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

Procedia PDF Downloads 390

Authors: Xinge Liao, Francesc Xavier Roige Ventura, Dolores Sanchez Aguilera

Abstract:

With the development of the Internet, the study of tourism behavior has rapidly expanded from the traditional physical market to the online market. Data on the Internet is characterized by dynamic changes, and new data appear all the time. In recent years the generation of a large volume of data was characterized, such as forums, blogs, and other sources, which have expanded over time and space, together they constitute large-scale Internet data, known as Big Data. This data of technological origin that derives from the use of devices and the activity of multiple users is becoming a source of great importance for the study of geography and the behavior of tourists. The study will focus on cultural heritage tourist practices in the context of Big Data. The research will focus on exploring the characteristics and behavior of Chinese tourists in relation to the cultural heritage of Catalonia. Geographical information, target image, perceptions in user-generated content will be studied through data analysis from Weibo -the largest social networks of blogs in China. Through the analysis of the behavior of heritage tourists in the Big Data environment, this study will understand the practices (activities, motivations, perceptions) of cultural tourists and then understand the needs and preferences of tourists in order to better guide the sustainable development of tourism in heritage sites.

Keywords: Barcelona, Big Data, Catalonia, cultural heritage, Chinese tourism market, tourists’ behavior

Procedia PDF Downloads 133

Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

Abstract:

Media has revealed a variety of corruption cases in the regional and local governments all over the world. Many governments pursued many anti-corruption reforms and have created a system of checks and balances. Three types of corruption are faced by citizens; administrative corruption, collusion and extortion. Accountability is one of the benchmarks for building transparent government. The public sector is required to report the results of the programs that have been implemented so that the citizen can judge whether the institution has been working such as economical, efficient and effective. Open Data is offering solutions for the implementation of good governance in organizations who want to be more transparent. In addition, Open Data can create transparency and accountability to the community. The objective of this paper is to build a framework of open data for accountability to combating corruption. This paper will investigate the relationship between open data, and accountability as part of anti-corruption initiatives. This research will investigate the impact of open data implementation on public organization.

Keywords: open data, accountability, anti-corruption, framework

Procedia PDF Downloads 324

Authors: H. S. Assaedi, F. U. A. Shaikh, I. M. Low

Abstract:

Geopolymer composites reinforced with flax fabrics and nano-clay are fabricated and studied for physical and mechanical properties using X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM). Nanoclay platelets at a weight of 1.0%, 2.0%, and 3.0% were added to geopolymer pastes. Nanoclay at 2.0 wt.% was found to improve density and decrease porosity while improving flexural strength and post-peak toughness. A microstructural analysis indicated that nanoclay behaves as filler and as an activator supporting geopolymeric reaction while producing a higher content geopolymer gel improving the microstructure of binders. The process enhances adhesion between the geopolymer matrix and flax fibres.

Keywords: flax fibres, geopolymer, mechanical properties, nanoclay

Procedia PDF Downloads 241

Authors: Tewodros Abate Alemayehu, Abebe Getahun, Akewake Geremew, Dawit Solomon Demeke, John Recha, Dawit Solomon, Gebremedihin Ambaw, Fasil Dawit Moges

Abstract:

The purpose of this study was to examine the effects of supplementation of zinc oxide (ZnO) nanoparticles and Mannan-oligosaccharide (MOS) on growth performance, feed utilization, fatty acid profiles, hematology, and intestinal morphology of Chamo strain Nile tilapia Oreochromis niloticus (L.) fry reared at optimal temperature (28.62 ± 0.11 ⁰C). Nile tilapia fry (initial weight 1.45 ± 0.01g) were fed basal diet/control diet (Diet-T1), 6 g kg-¹ MOS supplemented diet (Diet-T2), 4 mg ZnO-NPs supplemented diet (Diet-T3), 4 mg ZnO-Bulk supplemented diet (Diet-T4), a combination of 6 g kg-¹ MOS and 4 mg ZnO-Bulk supplemented diet (Diet-T5) and combination of 6 g kg-¹ MOS and 4 mg ZnO-NPs supplemented diet (Diet-T6). Randomly, duplicate aquariums for each diet were assigned and hand-fed to apparent satiation three times daily (08:00, 12:00, and 16:00) for 12 weeks. Fish fed MOS, ZnO-NPs, and a combination of MOS and ZnO-Bulk supplemented diet had higher weight gain, Daily Growth Rate (DGR), and Specific Growth Rate (SGR) than fish fed the basal diet and other feeding groups, although the effect was not significant. According to the GC analysis, Nile tilapia was supplemented with 6 g kg-¹ MOS, 4 mg ZnO-NPs, or a combination of ZnO-NPs, and MOS showed the highest content of EPA, DHA, and higher ratios of PUFA/SFA than other feeding groups. Mean villi length in the proximal and middle portion of the Nile tilapia intestine was affected significantly (p<0.05) by diet. Fish fed Diet-T2 and Diet-T3 had significantly higher villi lengths in the proximal and middle portions of the intestine compared to other feeding groups. The inclusion of additives significantly improved goblet numbers at the proximal, middle, and distal portions of the intestine. Supplementation of additives had also improved some hematological parameters compared with control groups. In conclusion, dietary supplementation of additives MOS and ZnO-NPs could confer benefits on growth performance, fatty acid profiles, hematology, and intestinal morphology of Chamo strain Nile tilapia.

Keywords: chamo strain nile tilapia, fatty acid profile, hematology, intestinal morphology, MOS, ZnO-Bulk, ZnO-NPs

Procedia PDF Downloads 69

Authors: Saadat Ali, Rashid Abdulla Ahmed Alshehhi

Abstract:

Cable faults are always probable and common during or after commissioning, causing significant delays and disrupting power distribution or transmission network, which is intolerable for the utilities&service providers being their reliability and business continuity measures. Therefore, the adoption of rapid localization & rectification methodology is the main concern for them. This paper explores the present techniques available for high voltage cable localization & rectification and which is preferable with regards to easier, faster, and also less harmful to cables. It also provides insight experience of high resistance fault locating by utilization of the Very Low Frequency (VLF) method.

Keywords: faults, VLF, real cases, cables

Procedia PDF Downloads 100

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 106

Authors: P. Valdez, M. Pelissero, A. Haim, F. Muiño, F. Galia, R. Tula

Abstract:

As a result of the studies performed on the wave energy resource worldwide, a research project was set up to harvest wave energy for its conversion into electrical energy. Within this framework, a theoretical model of the electromechanical energy harvesting system, developed with MATLAB’s Simulink software, will be provided. This tool recreates the site conditions where the device will be installed and offers valuable information about the amount of energy that can be harnessed. This research provides a deeper understanding of the utilization of wave energy in order to improve the efficiency of a 1:1 scale prototype of the device.

Keywords: electromechanical device, modeling, renewable energy, sea wave energy, simulation

Procedia PDF Downloads 477

Authors: Yuyun Wabula, B. J. Dewancker

Abstract:

In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: geolocation, Twitter, distribution analysis, human mobility

Procedia PDF Downloads 308

Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser

Abstract:

Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.

Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract

Procedia PDF Downloads 652

Authors: Amritee Bora, B. S. Mipun

Abstract:

Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

Procedia PDF Downloads 159

Authors: Sudipto Shanker Dasgupta

Abstract:

One of the largest mining companies wanted to look at health analytics for their driverless trucks. These trucks were the key to their supply chain logistics. The automated trucks had multi-level sub-assemblies which would send out sensor information. The use case that was worked on was to capture the sensor signal from the truck subcomponents and analyze the health of the trucks from repair and replacement purview. Open source software was used to stream the data into a clustered Hadoop setup in Amazon Web Services cloud and Apache Spark SQL was used to analyze the data. All of this was achieved through a 10 node amazon 32 core, 64 GB RAM setup real-time analytics was achieved on ‘300 million records’. To check the scalability of the system, the cluster was increased to 100 node setup. This talk will highlight how Open Source software was used to achieve the above use case and the insights on the high data throughput on a cloud set up.

Keywords: streaming analytics, data science, big data, Hadoop, high throughput, sensor data

Procedia PDF Downloads 400

Authors: Fred N. H. Parker, Nicola T. Fear, S. A. M. Stevelink, L. Rafferty

Abstract:

Purpose Auditory problems, such as hearing loss and tinnitus, have been associated with mental health problems and alcohol misuse in the UK general population and in the US Armed Forces; however, few studies have examined these associations within the UK Armed Forces. The present study examined the association between auditory problems and probable common mental disorders, post-traumatic stress disorder and alcohol misuse. Methods 5474 serving and ex-service personnel from the UK Armed Forces were examined, selected from those who responded to phase two (data collection 2007–09) and phase three (2014–16) of a military cohort study. Multivariable logistic regression was used to examine the association between auditory problems at phase two and mental health problems at phase three. Results 9.7% of participants reported ever experiencing hearing problems alone, 7.9% reported tinnitus within the last month alone, and 7.8% reported hearing problems with tinnitus. After adjustment, hearing problems with tinnitus at phase two was associated with increased odds of probable common mental disorders (AOR = 1.50, 95% CI 1.09–2.08), post-traumatic stress disorder (AOR = 2.30, 95% CI 1.41–3.76), and alcohol misuse (AOR = 1.94, 95% CI 1.28–2.96) at phase three. Tinnitus alone was associated with probable post-traumatic stress disorder (AOR = 1.80, 95% CI 1.03–3.15); however, hearing problems alone were not associated with any outcomes of interest. Conclusions The association between auditory problems and mental health problems emphasizes the importance of the prevention of auditory problems in the Armed Forces: through enhanced audiometric screening, improved hearing protection equipment, and greater levels of utilization of such equipment.

Keywords: armed forces, hearing problems, tinnitus, mental health, alcohol misuse

Procedia PDF Downloads 159