Search results for: high-speed data transmission

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Muhammad Arshad, Ghulam Hussain Bhatti, Abdul Qayyum

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Zinc-doped silica oxide nanoparticles having size 7.93nm were synthesized by the deposition precipitation method by using different solvents (acetonitrile, n-hexane, isoamylalchol). Biological potential such as antibacterial activities against Bacillussubtilusand Escherichia coli, and antifungal activities against Candida parapsilosis and Aspergilusniger were also investigated by Disc diffusion method. Different characterizations techniques including Fournier Transmission Infrared Spectroscopy (FT-IR), X-ray diffraction (XRD), Scanning Electron Microscope (SEM), Transmission Electron Microscope (TEM), Thermo-gravimeteric Analysis (TGA), Atomic forced microscopy (AFM), and Dynamic Light Scattering (DLS) were used. FT-IR characterization confirmed the presence of metal oxide bond (SiO2) while XRD showed the hexagonal structure. SEM and TEM characterization showed the morphology of nanoparticles. AFM study showed good particle size distribution as depicted by a histogram. DLS study showed the gradual decease in the size of nanoparticles from 24.86nm to 13.24 nm. Highest antibacterial activities revealed by acetonitrile solvents (6%and 4.5%) followed by isoamylalchol (3% and 2.4%) while n-hexane solvent showed the lowest activity (2%and 1%) respectively. Higher antifungal activities exhibited by n-hexane (0.34 % and 0.43%) followed by isoamylalchol (0.27% and 0.19%) solvent while acetonitrile (0.21% and 0.17%) showed least activity respectively. Statistical analysis by using one-way ANOVA also indicated the significant results of both biological activities.

Keywords: nanoparticles, precipitation methods, antibacterial, antifungal, characterizations

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Authors: Ali Asmari, Alex Symington, Htaik Than, Austin Caradonna, John Senft

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This paper presents the collaborative effort between ULC Technologies and Con Edison in developing a groundbreaking robotic cable splicing machine. The focus is on the machine's design, which integrates advanced robotics and automation to enhance safety and efficiency in power network maintenance. The paper details the operational steps of the machine, including cable grounding, cutting, and removal of different insulation layers, and discusses its novel technological approach. The significant benefits over traditional methods, such as improved worker safety and reduced outage times, are highlighted based on the field data collected during the validation phase of the project. The paper also explores the future potential and scalability of this technology, emphasizing its role in transforming the landscape of power network maintenance.

Keywords: cable splicing machine, power network maintenance, electric distribution, electric transmission, medium voltage cable

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Authors: Jugoslav Jokovic, Tijana Dimitrijevic, Nebojsa Doncov

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The goal of this paper is to investigate the possibilities and effectiveness of the TLM (Transmission Line Matrix) method for modelling of up-to-date microstrip antennas with circular geometry that have significant application in modern wireless communication systems. The coaxially fed microstrip antenna configurations with circular patch are analyzed by using the in-house 3DTLMcyl_cw solver based on computational electromagnetic TLM method adapted to the cylindrical grid and enhanced with the compact wire model. Opposed to the widely used rectangular TLM mesh, where a staircase approximation has to be used to describe curved boundaries, precise modelling of circular boundaries can be accomplished in the cylindrical grid irrespective of the mesh resolution. Using the compact wire model incorporated in cylindrical mesh, it is possible to model coaxial feed and include the influence of the real excitation in the antenna model. The conventional and inverted configuration of a coaxially fed circular patch antenna are considered, comparing the resonances obtained using TLM cylindrical model with results reached by the corresponding model in a rectangular grid as well as with experimental ones. Bearing in mind that accuracy of simulated results depends on a relevantly created model, besides structure geometry and dimensions, it is important to consider additional modelling issues, regarding appropriate mesh resolution and a relevant extension of a mesh around the considered structure that would provide convergence of the results.

Keywords: computational electromagnetic, coaxial feed, microstrip antenna, TLM modelling

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Authors: S. Melvin Samuel, Jayanta Bhattacharya

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In the present study, a graphene oxide/chitosan (GO-CS) composite material was prepared and used as an adsorbent for the removal of methylene blue (MB) from aqueous solution. The synthesized GO-CS adsorbent was characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopes (SEM), transmission electron microscopy (TEM), Raman spectroscopy and thermogravimetric analysis (TGA). The removal of MB was conducted in batch mode. The effect of parameters influencing the adsorption of MB such as pH of the solution, initial MB concentration, shaking speed, contact time and adsorbent dosage were studied. The results showed that the GO-CS composite material has high adsorption capacity of 196 mg/g of MB solution at pH 9.0. Further, the adsorption of MB on GO-CS followed pseudo second order kinetics and equilibrium adsorption data well fitted by the Langmuir isotherm model. The study suggests that the GO-CS is a favorable adsorbent for the removal of MB from aqueous solution.

Keywords: Methylene blue, Graphene oxide-chitosan, Isotherms, Kinetics.

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Authors: Behailu Bezabih Ayele

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Illustrative expressions in art education and in overall learning are being given increasing attention in the transmission of knowledge. The objective of this paper, therefore, is to present an analysis of graffiti on school desks-a way of smuggling knowledge on the edge of classroom education and learning. The methodological approach focuses on the systematic collection and selection of desk graffiti. Four schools are chosen to reflect socioeconomic status and gender composition. The analysis focused on the categorization of graffiti by genre. This was followed by an analysis of the style, intensity as well as content of the messages in terms of overall social impacts. The paper grounds the analysis by reviewing the literature on modern education and art education in the Ethiopian context, as well as the place of desk graffiti. The findings generally show that the school desks and the school environment, by and large, have managed to serve as vessels through which formal and informal knowledge is acquired, transmitted, engrained into the students and transformed into messages by the students. The desks have also apparently served as a springboard to maximize the interfaces between several ideas and disciplines and communications. However, the very fact that the desks serve as massive channels of expression and knowledge transmission also points to a lack of breadth availability of channels of expression, perhaps confounding the ability of classrooms as means of outlet of expression and documentation for the students. This points to the need for efforts in education policy and funding of artistic endeavors for young students.

Keywords: artistic expression, desk graffiti, education, school children, Ethiopia

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Nazli Hardy

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Multidisciplinary application of computer science, interactive database-driven web application, the Internet of Things (IoT) represents a digital ecosystem that has pervasive technological, social, and economic, impact on the human population. It is a long-term technology, and its development is built around the connection of everyday objects, to the Internet. It is estimated that by 2020, with billions of people connected to the Internet, the number of connected devices will exceed 50 billion, and thus IoT represents a paradigm shift in in our current interconnected ecosystem, a communication shift that will unavoidably affect people, businesses, consumers, clients, employees. By nature, in order to provide a cohesive and integrated service, connected devices need to collect, aggregate, store, mine, process personal and personalized data on individuals and corporations in a variety of contexts and environments. A significant factor in this paradigm shift is the necessity for secure and appropriate transmission, processing and storage of the data. Thus, while benefits of the applications appear to be boundless, these same opportunities are bounded by concerns such as trust, privacy, security, loss of control, and related issues. This poster and presentation look at a multi-factor authentication (MFA) mechanisms that need to change from the login-password tuple to an Identity and Access Management (IAM) model, to the more cohesive to Identity Relationship Management (IRM) standard. It also compares and contrasts messaging protocols that are appropriate for the IoT ecosystem.

Keywords: Internet of Things (IoT), authentication, protocols, survey

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Minwuyelet Maru, Solomon Habtemariam, Endalamaw Gadissa, Abraham Aseffa

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Background: Tuberculosis is a major public health problem in Ethiopia. The burden of TB is aggravated by emergence and expansion of drug resistant tuberculosis and different lineages of Mycobacterium tuberculosis (M. tuberculosis) have been reported in many parts of the country. Describing strains of Mycobacterial isolates and drug susceptibility pattern is necessary. Method: Sputum samples were collected from smear positive pulmonary TB patients age >= 7 years between October 1, 2012 to September 30, 2013 and Mycobacterial strains isolated on Loweensten Jensen (LJ) media. Each strain was characterized by deletion typing and Spoligotyping. Drug sensitivity testing was determined with the indirect proportion method using Middle brook 7H10 media and association to determine possible risk factors to drug resistance was done. Result: A total of 144 smear positive pulmonary tuberculosis patients were enrolled. The age of participants ranged from 7 to 78 with mean age of 29.22 (±10.77) years. In this study 82.2% (n=97) of the isolates were sensitive to the four first line anti-tuberculosis drugs and resistance to any of the four drugs tested was 17.8% (n=21). A high frequency of any resistance was observed in isoniazid, 13.6%, (n=16) followed by streptomycin, 11.8% (n=14). No significant association of isoniazid resistance with HIV, sex and history of previous TB treatment was observed but there was significant association with age, high between 31-35 years of age (p=0.01). Majority, 89.9% (n=128) of participants were new cases and only 11.1% (n=16) had history of previous TB treatment. No MDR-TB from new cases and 2 MDRTB (13.3%) was isolated from re-treatment cases which was significantly associated with previous TB treatment (p<0.01). Thirty two different types of spoligotype patterns were identified and 74.1% were grouped in to 13 clusters. The dominant strains were SIT 25, 18.1% (n=21), SIT 53, 17.2% (n=20) and SIT 149, 8.6% (n=10). Lineage 4 is the predominant lineage followed by lineage 3 and lineage 7 comprising 65.5% (n=76), 28.4% (n=33) and 6% (n=7) respectively. Majority of strains from lineage 3 and 4 were SIT 25 (63.6%) and SIT 53 (26.3%) whereas SIT 343 was the dominant strain from lineage 7 (71.4%). Conclusion: Wide spread of lineage 3 and lineage 4 of the modern lineage and high number of strain cluster indicates high ongoing transmission. The high proportion resistance to any of the first line anti-tuberculosis drugs may be a potential source in the emergence of MDR-TB. Wide spread of SIT 25 and SIT 53 having a tendency of ease transmission and presence of higher resistance of isoniazid in working and mobile age group, 31-35 years of age may increase risk of drug resistant strains transmission.

Keywords: tuberculosis, drug susceptibility, strain diversity, lineage, Ethiopia, spoligotyping

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Giovanni Matheus Rech, Gilberto Zan, Filipe P. Aguiar

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The current pandemic scenario raises questions that many times would have previously gone unnoticed. One of these issues is the quality of the air we breathe in the most diverse environments in which we are inserted in an everyday. It is plausible to suppose that, at times like this, there is apprehension regarding the possibility of contamination by pathological agents such as viruses and bacterias through the airways. However, the renewal of indoor air, combined with a properly sanitized air conditioning system, are important tools for the prevention of viral diseases, as is the case with COVID-19. The bus is an example of an environment where renovation is applied to improve the quality of indoor air, helping to reduce the possibility of spreading pathological agents. Together with other care, such as an alcohol gel dispenser, curtains to separate the passengers, cleaning the environment more frequently, and mandatory use of masks, help to reduce the transmission of pathologies, such as COVID-19. Knowing the reality of a large part of the population regarding the need for public transport, there are standards and devices dedicated to promoting air quality, ensuring greater comfort and safety for users. This paper seeks to present such standards and recommendations to improve the quality of indoor air, as well as the equipment responsible for the renewal of the air in the body of a bus. Experimental measurement of the flow rates of the renewal devices present in the bus body allows quantifying the average volume of external air admitted in each type of body. This way, it was possible to compare, in terms of airflow per person, the values of a bus in relation to a series of other environments, using recommendations for air renewal are described through the Brazilian standard ABNT NBR 16401.

Keywords: air quality, air renewal, buses, Covid-19

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Authors: G. R. Kavitha, T. S. Indumathi

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With the constantly rising demands of the multimedia services, the requirements of long haul transport network are constantly changing in the area of optical network. Maximum data transmission using optimization of the communication channel poses the biggest challenge. Although there has been a constant focus on this area from the past decade, there was no evidence of a significant result that has been accomplished. Hence, after reviewing some potential design of optical network from literatures, it was understood that optical signal to noise ratio was one of the elementary attributes that can define the performance of the optical network. In this paper, we propose a framework termed as ECON (Enhanced Constraint-based Optical Network) that primarily optimize the optical signal to noise ratio using ROADM. The simulation is performed in Matlab and optical signal to noise ratio is extracted considering the system matrix. The outcome of the proposed study shows that optimized OSNR as compared to the existing studies.

Keywords: component, optical network, reconfigurable optical add-drop multiplexer, optical signal-to-noise ratio

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Ruth Muturi Wanjiku

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HIV/AIDS in Kenya for unborn and young kids. HIV/AIDS is a significant health concern in Kenya, with an estimated 1.5 million people living with the disease. Unfortunately, many of these individuals are unaware of their HIV status, and the disease continues to spread among the population or unborn kids. HIV/AIDS can be transmitted from an infected mother during pregnancy, childbirth, or breastfeeding. However, with early testing and treatment, the risk of mother-to-child transmission can be significantly reduced. Therefore, it is crucial for pregnant women to get tested and receive appropriate medical care. For young kids, HIV/AIDS education is critical to preventing the spread of the disease. It is essential to teach children about the importance of safe sex practices, avoiding risky behaviors such as sharing needles and getting tested regularly. Additionally, children should be taught about the stigma surrounding HIV/AIDS and encouraged to treat individuals living with the disease with compassion and respect. In conclusion, HIV/AIDS is a significant health concern in Kenya that affects individuals of all ages. For unborn kids, early testing and treatment are critical to reducing the risk of mother-to-child transmission. For young kids, education about HIV/AIDS and safe sex practices is essential to preventing the spread of the disease and reducing stigma. It is essential to promote awareness and encourage individuals to get tested and seek medical care if they believe they may be infected with HIV/AIDS.

Keywords: AIDS, HIV, children, pregnant

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Authors: Li Chen, Alex Skvortsov, Chris Norwood

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Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.

Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model

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Authors: Kumud Singh, Janvin Itteera, Priti Ukarde, Sanjay Malhotra, P. PMarathe, Ayan Bandyopadhay, Rakesh Meena, Vikram Rawat, L. M. Joshi

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Application of Permanent magnet technology to high frequency miniature klystron tubes to be utilized for space applications improves the efficiency and operational reliability of these tubes. But nevertheless the task of generating magnetic focusing forces to eliminate beam divergence once the beam crosses the electrostatic focusing regime and enters the drift region in the RF section of the tube throws several challenges. Building a high quality magnet focusing lens to meet beam optics requirement in cathode gun and RF interaction region is considered to be one of the critical issues for these high frequency miniature tubes. In this paper, electromagnetic design and particle trajectory studies in combined electric and magnetic field for optimizing the magnetic circuit using 3D finite element method (FEM) analysis software is presented. A rectangular configuration of the magnet was constructed to accommodate apertures for input and output waveguide sections and facilitate coupling of electromagnetic fields into the input klystron cavity and out from output klystron cavity through coupling loops. Prototype lenses have been built and have been tested after integration with the klystron tube. We discuss the design requirements and challenges, and the results from beam transmission of the prototype lens.

Keywords: beam transmission, Brillouin, confined flow, miniature klystron

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Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

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Authors: Ravindra Raju, Vidhu Kampurath

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For smooth transition of the power from the engine to the transmission system, a clutch is used. In agricultural tractors, friction clutches are widely used in power transmission applications. To transmit the maximum torque in friction clutches, selection of materials is one of the important tasks. The present used material for friction disc is Asbestos, Ceramic etc. In this study, analysis is performed using composites materials. The composite materials are considered due to their high strength to weight ratio. Composite materials like kevlar49, kevlar 29U were used in the study. The paper presents a systematic approach to optimize the structural and thermal characteristics of the clutch friction pad. A single plate clutch is modeled using Creo 2.0 software and analyzed using ANSYS. Thermal analysis considers the reduction of heat generated between the friction surfaces and reducing the temperature rise during the steady state period. Structural analysis is done to minimize the stresses developed as a result of the loading contact between friction surfaces. Also, modal analysis is done to optimize the natural frequency of the friction plate to avoid being in resonance with the engine frequency range. The analysis carried out on ANSYS workbench to get the foremost appropriate friction material for clutch. From the analyzed results stress, strain / total deformation values and natural frequency of the materials were compared for all the composite materials and the best one was taken out. For the study purpose, specifications of the clutch are obtained from the MF1035 (47KW) Tractor model.

Keywords: ANSYS, clutch, composite materials, creo

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Authors: Emad Al-Abdallat, Faris G. Bakri, Azmi Mahafza, Rayyan Al Ali, Nidaa Ababneh, Ahmed Idhair

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Background: Morgues are high-risk areas for the spread of infection from the cadavers to the staff during the postmortem examination. Infection can spread from corpses to workers by the airborne route, by direct contact, or from needle and sharp object injuries. Objective: Knowledge about the prevalence of these infections among autopsies is prudent to appreciate any risk of transmission and to further enforce safety measures. Method: A total of 242 autopsies were tested. Age ranged from 3 days to 94 years (median 75.5 years, mean 45.3 (21.9 ± SD)). There were 172 (71%) males. Results: The cause of death was considered natural in 137 (56.6%) cases, accidental in 89 (36.8%), homicidal in 9 (3.7%), suicidal in 4 (1.7%), and unknown in 3 (1.2%). Hepatitis B surface antigen was positive in 5 (2.1%) cases. Hepatitis C virus antibody was detected in 5 (2.1%) cases and the hepatitis C virus polymerase chain reaction was positive in 2 of them (0.8%). HIV antibody was not detected in any of the cases. Conclusions: Autopsies can be associated with exposure to blood borne viruses. Autopsies performed during the study period were tested for hepatitis B surface antigen, hepatitis C virus antibody, and human immunodeficiency virus antibody. Positive tests were subsequently confirmed by polymerase chain reaction. There is low prevalence of infections with these viruses in our autopsy cases. However, the risk of transmission remains a threat. Healthcare workers in the forensic departments should adhere to standard precautions.

Keywords: autopsy, hepatitis B virus, hepatitis C virus, human immunodeficiency virus, Jordan

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Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Mojtaba Zabihi, Stephen Munro, Jonathan Little, Ri Li, Joshua Brinkerhoff, Sina Kheirkhah

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Occupational Safety and Health Administration (OSHA) identified dental workers at the highest risk of contracting COVID-19. This is because aerosol-generating procedures (AGP) during dental practices generate aerosols ( < 5µm) and droplets. These particles travel at varying speeds, in varying directions, and for varying durations. If these particles bear infectious viruses, their spreading causes airborne transmission of the virus in the dental room, exposing dentists, hygienists, dental assistants, and even other dental clinic clients to the infection risk. Computational fluid dynamics (CFD) simulation of two-phase flows based on a discrete phase model (DPM) is carried out to study the spreading of aerosol and droplets in a dental room. The simulation includes momentum, heat, and mass transfers between the particles and the airflow. Two simulations are conducted and compared. One simulation focuses on the effects of room ventilation in winter and summer on the particles' travel. The other simulation focuses on the control of aerosol and droplets' spreading. A suction collector is added near the source of aerosol and droplets, creating a flow sink in order to remove the particles. The effects of the suction flow on the aerosol and droplet travel are studied. The suction flow can remove aerosols and also reduce the spreading of droplets.

Keywords: aerosols, computational fluid dynamics, COVID-19, dental, discrete phase model, droplets, two-phase flow

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Authors: Thrivikraman Aswathi, S. Advaith

Abstract:

As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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