Search results for: resolution digital data

Authors: Caroline F. Moeser

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The skin-gut axis defines the relationship between the intestinal microbiota and the development of pathological skin diseases. Low diversity within the gut can predispose to the development of allergic skin conditions, and a greater diversity of the gastrointestinal microflora has been associated with a reduction of skin flares in people with atopic dermatitis. Manipulation of the gut microflora has been used as a treatment option for several conditions in people, but there is limited data available on the use of faecal transplantation as a preventative measure in either people or dogs. Six, 4-month-old pups from a litter of ten were presented for diarrhea and/or signs of skin disease (chronic scratching, otitis externa). Of these pups, two were given probiotics with a resultant resolution of diarrhea. The other four pups were given faecal transplantation, either as a sole treatment or in combination with other treatments. Follow-up on the litter of ten pups was performed at 18 months of age. At this stage, the four pups that had received faecal transplantation had resolved all clinical signs and had no recurrence of either skin or gastrointestinal symptoms. Of the remaining six pups from the litter, all had developed at least one episode of Malassezia otitis externa within the period of 5 months to 18 months of age. Two pups had developed two Malassezia otitis infections, and one had developed three Malassezia otitis infections during this period. Favrot’s criteria for the diagnosis of canine atopic dermatitis include chronic or recurrent Malassezia infections by the age of three years. Early results from this litter predict a reduction in the development of canine atopic disease in dogs given faecal microbial transplantation. Follow-up studies at three years of age and within a larger population of dogs can enhance understanding of the impact of early faecal transplantation in the prevention of canine atopic dermatitis.

Keywords: canine atopic dermatitis, faecal microbial transplant, skin-gut axis, otitis

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Authors: Chinelle van der Westhuizen

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The introduction of cryptocurrencies as an alternative payment system have placed governments in a challenging position in relation to the regulatory status of cryptocurrencies and the money laundering activities associated with it. In April 2018, the Australian government amended its Anti-Money Laundering laws to regulate digital currency exchanges in an attempt to regulate money laundering activities and the introduction of ‘know-your-customer’ policies within the digital currency sector. Part one of this paper explores the use of cryptocurrencies for money laundering purposes and its significance to money launderers. Part two studies the efficacy of the current Australian Anti-Money Laundering laws and whether more can be done on a regulatory level. This paper will, therefore, highlight recent court decisions and legislation in terms of money laundering activities within these alternative payment systems in Australia and the United Kingdom. Part three of the paper will further analyze recent case studies by the Australian Transaction Reports and Analysis Centre and the Office for Professional Body Anti-Money Laundering Supervision in the United Kingdom as the regulatory bodies for money laundering activities. The case studies and research will explore the legal disputes and future regulation concerning the use of cryptocurrencies and money laundering on a national as well as international level. This paper intends to highlight that although cryptocurrency is viewed as an innovative global phenomenon and an alternative method of payment, there are a number of legal issues associated with its use that indicate the need for regulatory reform. It is recommended in this paper that the Financial Action Task Force, International Monetary Fund as well as concerned governments have ongoing discussions on these regulatory issues and how to address it appropriately, whether through legislation or universal guidelines. Therefore, the conclusion of this paper will emphasize the benefits of a regulatory regime for money laundering activities within the cryptocurrency space and that the lack of such a regime may be detrimental to countries.

Keywords: cryptocurrency, know-your-customer policy, money laundering, regulation

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Authors: Ana Gavardashvili

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The field-and-scientific studies to evaluate the modern ecological state in the water area of the estuaries of the major water-abundant rivers in the coastal line of the Black Sea (Chorokhi, Kintrishi, Natanebi, Supsa, Khobistskali, Rioni and Enguri) and sea ports (Batumi, Poti) and sea terminals of the oil pipeline (Baku-Tbilisi-Supsa, Kulevi) were accomplished in the months of June and July of 2015. GPS coordinates and GIS programs were used to fix the areas of the estuaries of the above-listed rivers on a digital map, with their values varying within the limits of 0,861 and 20,390 km2. Water samples from the Black Sea were taken from the river estuaries and sea ports during the field works, with their statistical series of 125 points. The temperatures of air (t2) and water in the Black Sea (t1) were measured locally, and their relative value is (t1 /t2 ) = 0,69 – 0,92. 125 water samples taken from the study object in the Black Sea coastal line were subject to laboratory analysis, and it was established that the Black Sea acidity (pH) changes within the limits of 7,71 – 8,22 in the river estuaries and within 8,42 - 8,65 in the port water areas and at oil terminals. As for the Sea water salinity index (TDS), it changes within the limits of 6,15 – 12,67 in the river estuaries, and (TDS) = 11,80 – 13,67 in the port water areas and at oil terminals. By taking the gained data and climatic changes into account, by using the theories of reliability and risk at the following stage, the nature of the changes of the function of the Black Sea ecological parameters will be established.

Keywords: acidity, estuary, salinity, sea

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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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

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Authors: Raphael Palucci Rosa, Giuseppe Rosace

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Stereolithography (SLA) is one of the 3D-printing technologies that has been steadily growing in popularity for both industrial and personal applications due to its versatility, high accuracy, and low cost. Its printing process consists of using a light emitter to solidify photosensitive liquid resins layer-by-layer to produce solid objects. However, the majority of the resins used in SLA are derived from petroleum and characterized by toxicity, stability, and recalcitrance to degradation in natural environments. Aiming to develop an eco-friendly resin, in this work, different combinations of a standard commercial SLA resin (Peopoly UV professional) with a vegetable-based resin were investigated. To reach this goal, different mass concentrations (varying from 10 to 50 wt%) of acrylated epoxidized soybean oil (AESO), a vegetable resin produced from soyabean oil, were mixed with a commercial acrylate-based resin. 1.0 wt% of Diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO) was used as photo-initiator, and the samples were printed using a Peopoly moai 130. The machine was set to operate at standard configurations when printing commercial resins. After the print was finished, the excess resin was drained off, and the samples were washed in isopropanol and water to remove any non-reacted resin. Finally, the samples were post-cured for 30 min in a UV chamber. FT-IR analysis was used to confirm the UV polymerization of the formulated resin with different AESO/Peopoly ratios. The signals from 1643.7 to 1616, which corresponds to the C=C stretching of the AESO acrylic acids and Peopoly acrylic groups, significantly decreases after the reaction. The signal decrease indicates the consumption of the double bonds during the radical polymerization. Furthermore, the slight change of the C-O-C signal from 1186.1 to 1159.9 decrease of the signals at 809.5 and 983.1, which corresponds to unsaturated double bonds, are both proofs of the successful polymerization. Mechanical analyses showed a decrease of 50.44% on tensile strength when adding 10 wt% of AESO, but it was still in the same range as other commercial resins. The elongation of break increased by 24% with 10 wt% of AESO and swelling analysis showed that samples with a higher concentration of AESO mixed absorbed less water than their counterparts. Furthermore, high-resolution prototypes were printed using both resins, and visual analysis did not show any significant difference between both products. In conclusion, the AESO resin was successful incorporated into a commercial resin without affecting its printability. The bio-based resin showed lower tensile strength than the Peopoly resin due to network loosening, but it was still in the range of other commercial resins. The hybrid resin also showed better flexibility and water resistance than Peopoly resin without affecting its resolution. Finally, the development of new types of SLA resins is essential to provide new sustainable alternatives to the commercial petroleum-based ones.

Keywords: 3D-printing, bio-based, resin, soybean, stereolithography

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Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

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Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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Authors: Shahab Zomorodbakhsh, Hayron Nesa Motevasel

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Water soluble compoundes were attached to single-walled carbon nanotubes (SWNTs) to form water-soluble nano pigments. functionalized SWNTs were then characterized by Fourier Transform Infrared spectroscopy (FT-IR), Raman spectroscopy, UV analysis, Transmission electron microscopy (TEM)and defunctionalization test and Representative results concerning the solubility. The product can be dissolved in water and High-resolution transmission electron microscope images showed that the SWNTs were efficiently functionalized, thus the p-stacking interaction between aromatic rings and COOH of SWNTs was considered responsible for the high solubility and High transmission electron in singlewall nanotubes.

Keywords: functionalized CNTs, singlewalled carbon nanotubes, water soluble compoundes, nano pigments

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Authors: Parsa Keyvani, Alistair Phillips, David Warwick

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Background: The current process for gaining patient consent for hand and wrist surgery at University Hospital Southampton (UHS) is paper-based and makes use of generic forms provided by the NHS and no patient information leaflet is available relating to hand and wrist surgery. Aims: To evaluate the process of obtaining clinical consent and suggest ways in which the service can be improved. Methods: A log-book review of four orthopaedic surgeons at UHS was carried out over a three-month period in order to identify the 10 most common types of elective hand and wrist surgeries performed. A literature review was carried out to identify the complications of these surgeries. The surgeries were then divided into 6 types: nerve, bone, ligament, joint, tendon and dupuytren’s surgery. A digitised consent form was created covering the complications of all 6 surgery types. Finally, the surgeons at the orthopaedic department of UHS were asked whether they prefer the old paper-based or the digitised consent form. Results: All of the surgeons felt that the procedure type-based form was easier to read, use and understand. Conclusion: This research highlights a number of problems related to the use of current NHS consent forms. The proposed solution is to use a set of digitised, procedure type-based consent forms. Digital consent forms can be filled in in advance and sent to the patient electronically along with any relevant information leaflets, thus giving them time to absorb the information and come up with any questions before they have their pre-procedure discussion with their doctor. This would allow the doctor to focus the consultation on the patient rather than writing out the consent form and would ultimately be a step forward in making the NHS a global digital leader and fully embrace the opportunity offered by technology.

Keywords: digitised consent form, elective surgery, hand surgery complications, informed consent, procedure type-based consent form

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Authors: Manal Sultan Alhussein, Xiang Michelle Liu

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Telehealth is an advanced technology using digital information and telecommunication facilities that provide access to health services from a distance. It slows the transmission factor of COVID-19, especially for elderly patients and patients with chronic diseases during the pandemic. Therefore, understanding patient perspectives on telehealth services and the factors impacting their option of telehealth service will shed light on the measures that healthcare providers can take to improve the quality of telehealth services. This study aimed to evaluate perceptions of telehealth services among different patient groups and explore various aspects of telehealth utilization in the United States during the COVID-19 pandemic. An online survey distributed via social media platforms was used to collect research data. In addition to the descriptive statistics, both correlation and regression analyses were conducted to test research hypotheses. The empirical results highlighted that the factors such as accessibility to telehealth services and the type of specialty clinics that the patients required play important roles in the effectiveness of telehealth services they received. However, the results found that patients’ waiting time to receive telehealth services and their annual income did not significantly influence their desire to select receiving healthcare services via telehealth. The limitations of the study and future research directions are discussed.

Keywords: telehealth, patient satisfaction, pandemic, healthcare, survey

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

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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

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Authors: Masood Hussain, Erol Pehlivan, Ahmet Avci, Ecem Guder

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Green synthesis of silver nanoparticles (AgNPs) was carried out by using echinacea flower extract as reducing/protecting agent. The effects of various operating parameters and additives on the dimensions such as stirring rate, temperature, pH of the solution, the amount of extract and concentration of silver nitrate were optimized in order to achieve monodispersed spherical and small size echinacea protected silver nanoparticles (echinacea-AgNPs) through biosynthetic method. The surface roughness and topography of synthesized metal nanoparticles were confirmed by using Atomic Force Microscopy (AFM). High-Resolution Transmission Electron Microscopic (HRTEM) results elaborated the formation of uniformly distributed Echinacea protected AgNPs (Echinacea-AgNPs) having an average size of 30.2±2nm.

Keywords: Echinacea flower extract, green synthesis, silver nanoparticles, morphology

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Authors: D. Diaz, C. Guevara, P. Rey

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This paper contains information about designing, shielding and protocols building in order to avoid ionizing radiation in X-Rays imaging areas as generated by X-Ray, mammography equipment, computed tomography equipment and digital subtraction angiography equipment, according to global standards. Furthermore, tools and elements about infrastructure to improve protection over patients, physicians and staff involved in a diagnostic imaging area are presented. In addition, technical parameters about each machine and the architecture designs and maps are described.

Keywords: imaging area, X-ray, shielding, dose

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

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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

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

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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

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Authors: Bayonle Abiola Omoniyi

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In turbidite reservoirs with volumetrically significant thin-bedded turbidites (TBTs), thin-pay intervals may be underestimated during calculation of reserve volume due to poor vertical resolution of conventional well logs. This paper demonstrates the strong control of bed-scale sedimentary heterogeneity on oil recovery using six facies distribution scenarios that were generated from outcrop data from the Eocene Itzurun Formation, Basque Basin (northern Spain). The variable net sand volume in these scenarios serves as a primary source of sedimentary heterogeneity impacting sandstone-mudstone ratio, sand and shale geometry and dimensions, lateral and vertical variations in bed thickness, and attribute indices. The attributes provided input parameters for modeling the scenarios. The models are 20-m (65.6 ft) thick. Simulation of the scenarios reveals that oil production is markedly enhanced where degree of sedimentary heterogeneity and resultant permeability contrast are low, as exemplified by Scenarios 1, 2, and 3. In these scenarios, bed architecture encourages better apparent vertical connectivity across intervals of laterally continuous beds. By contrast, low net-to-gross Scenarios 4, 5, and 6, have rapidly declining oil production rates and higher water cut with more oil effectively trapped in low-permeability layers. These scenarios may possess enough lateral connectivity to enable injected water to sweep oil to production well; such sweep is achieved at a cost of high-water production. It is therefore imperative to consider not only net-to-gross threshold but also facies stack pattern and related attribute indices to better understand how to effectively manage water production for optimum oil recovery from basin-plain reservoirs.

Keywords: architecture, connectivity, modeling, turbidites

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Authors: Sang Yeong Choi, Woo Sung Park

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This paper presents the architecture design of the robot operability assessment simulation testbed (called "ROAST") for the resolution of robot operability problems occurred during interactions between human operators and robots. The basic idea of the ROAST architecture design is to enable the easy composition of legacy or new simulation models according to its purpose. ROAST architecture is based on IEEE1516 High Level Architecture (HLA) of defense modeling and simulation. The ROAST architecture is expected to provide the foundation framework for the easy construction of a simulation testbed to order to assess the robot operability during the robotic system design. Some of ROAST implementations and its usefulness are demonstrated through a simple illustrative example.

Keywords: robotic system, modeling and simulation, simulation architecture, operability assessment

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Authors: Gustavo Cruz-Bello

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Progreso is a coastal community in Yucatan, Mexico, highly exposed to floods produced by severe storms and tropical cyclones. A participatory cartography approach was conducted to help to reduce floods disasters and assess social vulnerability within the community. The first step was to engage local authorities in risk management to facilitate the process. Two workshop were conducted, in the first, a poster size printed high spatial resolution satellite image of the town was used to gather information from the participants: eight women and seven men, among them construction workers, students, government employees and fishermen, their ages ranged between 23 and 58 years old. For the first task, participants were asked to locate emblematic places and place them in the image to familiarize with it. Then, they were asked to locate areas that get flooded, the buildings that they use as refuges, and to list actions that they usually take to reduce vulnerability, as well as to collectively come up with others that might reduce disasters. The spatial information generated at the workshops was digitized and integrated into a GIS environment. A printed version of the map was reviewed by local risk management experts, who validated feasibility of proposed actions. For the second workshop, we retrieved the information back to the community for feedback. Additionally a survey was applied in one household per block in the community to obtain socioeconomic, prevention and adaptation data. The information generated from the workshops was contrasted, through T and Chi Squared tests, with the survey data in order to probe the hypothesis that poorer or less educated people, are less prepared to face floods (more vulnerable) and live near or among higher presence of floods. Results showed that a great majority of people in the community are aware of the hazard and are prepared to face it. However, there was not a consistent relationship between regularly flooded areas with people’s average years of education, house services, or house modifications against heavy rains to be prepared to hazards. We could say that the participatory cartography intervention made participants aware of their vulnerability and made them collectively reflect about actions that can reduce disasters produced by floods. They also considered that the final map could be used as a communication and negotiation instrument with NGO and government authorities. It was not found that poorer and less educated people are located in areas with higher presence of floods.

Keywords: climate change, floods, Mexico, participatory mapping, social vulnerability

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Authors: Steffon Campbell

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This research explores the potential of using artificial intelligence (AI) autoethnographies to study, document, explore, and understand aspects of Caribbean culture. As a digital research methodology, AI autoethnography merges computer science and technology with ethnography, providing a fresh approach to collecting and analyzing data to generate novel insights. This research investigates how AI autoethnography can best be applied to understanding the various complexities and nuances of Caribbean culture, as well as examining how technology can be a valuable tool for enriching study of the region. By applying AI autoethnography to Caribbean studies, the research aims to produce new and innovative ways of discovering, understanding, and appreciating the Caribbean. The study found that AI autoethnographies can offer a valuable method for exploring Caribbean culture. Specifically, AI autoethnographies can facilitate experiences of self-reflection, facilitate reconciliation with the past, and provide a platform to explore and understand the cultural, social, political, and economic concerns of Caribbean people. Findings also reveal that these autoethnographies can create a space for people to reimagine and reframe the conversation around Caribbean culture by enabling them to actively participate in the process of knowledge creation. The study also finds that AI autoethnography offers the potential for cross-cultural dialogue, allowing participants to connect with one another over cultural considerations and engage in meaningful discourse.

Keywords: artificial intelligence, autoethnography, caribbean, culture

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

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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

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

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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

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Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

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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

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Authors: Sheikh Nawaz Ali, Pratima Pandey, P. Morthekai, Jyotsna Dubey, Md. Firoze Quamar

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The high mountain glaciers are one of the most sensitive recorders of climate changes, because they have the tendency to respond to the combined effect of snow fall and temperature. The Himalayan glaciers have been studied with a good pace during the last decade. However, owing to its large ecological diversity and geographical vividness, major part of the Indian Himalaya is uninvestigated, and hence the palaeoclimatic patterns as well as the chronology of past glaciations in particular remain controversial for the entire Indian Himalayan transect. Although the Himalayan glaciers are nourished by two important climatic systems viz. the southwest summer monsoon and the mid-latitude westerlies, however, the influence of these systems is yet to be understood. Nevertheless, existing chronology (mostly exposure ages) indicate that irrespective of the geographical position, glaciers seem to grow during enhanced Indian summer monsoon (ISM). The Himalayan mountain glaciers are referred to the third pole or water tower of Asia as they form a huge reservoir of the fresh water supplies for the Asian countries. Mountain glaciers are sensitive probes of the local climate, and, thus, they present an opportunity and a challenge to interpret climates of the past as well as to predict future changes. The principle object of all the palaeoclimatic studies is to develop a futuristic models/scenario. However, it has been found that the glacial chronologies bracket the major phases of climatic events only, and other climatic proxies are sparse in Himalaya. This is the reason that compilation of data for rapid climatic change during the Holocene shows major gaps in this region. The sedimentation in proglacial lakes, conversely, is more continuous and, hence, can be used to reconstruct a more complete record of past climatic variability that is modulated by changing ice volume of the valley glacier. The Himalayan region has numerous proglacial lacustrine deposits formed during the late Quaternary period. However, there are only few such deposits which have been studied so far. Therefore, this is the high time when efforts have to be made to systematically map the moraines located in different climatic zones, reconstruct the local and regional moraine stratigraphy and use multiple dating techniques to bracket the events of glaciation. Besides this, emphasis must be given on carrying multiproxy studies on the lacustrine sediments that will provide a high resolution palaeoclimatic data from the alpine region of the Himalaya. Although the Himalayan glaciers fluctuated in accordance with the changing climatic conditions (natural forcing), however, it is too early to arrive at any conclusion. It is very crucial to generate multiproxy data sets covering wider geographical and ecological domains taking into consideration multiple parameters that directly or indirectly influence the glacier mass balance as well as the local climate of a region.

Keywords: glacial chronology, palaeoclimate, multiproxy, Himalaya

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Authors: Zebider Asire Munyelet, Yibeltal Chanie Manie

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In the modern digital landscape, the increase of social media platforms has become identical to the evolution of online consumer behavior. This study investigates the complicated relationship between social media and the purchasing decisions of online buyers. Through an extensive review of existing literature and empirical research, the aim is to comprehensively analyze the multidimensional impact that social media exerts on the various stages of the online buyer's journey. The investigation encompasses the exploration of how social media platforms serve as influential channels for information dissemination, product discovery, and consumer engagement. Additionally, the study investigates into the psychological aspects underlying the role of social media in shaping buyer preferences, perceptions, and trust in online transactions. The methodologies employed include both quantitative and qualitative analyses, incorporating surveys, interviews, and data analytics to derive meaningful insights. Statistical models are applied to distinguish patterns in online buyer behavior concerning product awareness, brand loyalty, and decision-making processes. The expected outcomes of this research contribute not only to the academic understanding of the dynamic interplay between social media and online buyer behavior but also offer practical implications for marketers, e-commerce platforms, and policymakers.

Keywords: consumer Behavior, social media, online purchasing, online transaction

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Authors: Vera Karla S. Caingles, Glen A. Lorenzo

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Soil, as the main material of landslides, plays a vital role in landslide assessment. An efficient and accurate method of doing an assessment is significantly important to prevent damage of properties and loss of lives. The study has two phases: to establish an empirical correlation of the residual soil thickness with the slope angle and to investigate the geotechnical characteristics of residual soil. Digital Elevation Model (DEM) in Geographic Information System (GIS) was used to establish the slope map and to program sampling points for field investigation. Physical and index property tests were undertaken on the 20 soil samples obtained from the area with Pliocene-Pleistocene geology and different slope angle in Kibawe, Bukidnon. The regression analysis result shows that the best fitting model that can describe the soil thickness-slope angle relationship is an exponential function. The physical property results revealed that soils contain a high percentage of clay and silts ranges from 41% - 99.52%. Based on the index properties test results, the soil exhibits a high degree of plasticity and expansion but not collapsible. It is deemed that this compendium will serve as primary data for slope stability analysis and deterministic landslide assessment.

Keywords: collapsibility, correlation, expansiveness, landslide, plasticity

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Authors: Mohan Singh Mehata, R. K. Ratnesh

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CdSe, CdSe/ZnS, and CdSe/CdS core-shell quantum dots (QDs) of 3-4 nm were developed by using chemical route and following successive ion layer adsorption and reaction (SILAR) methods. The prepared QDs have been examined by using X-ray diffraction, high-resolution electron microscopy and optical spectroscopy. The photoluminescence (PL) quantum yield (QY) of core-shell QDs increases with respect to the core, indicating that the radiative rate increases by the formation of shell around core, as evident by the measurement of PL lifetime. Further, the PL of bovine serum albumin is quenched strongly by the presence of core-shall QDs and follow the Stern-Volmer (S-V) relation, whereas the lifetime does not follow the S-V relation, demonstrating that the observed quenching is predominantly static in nature. Among all the QDs, the CdSe/ZnS QDs shows the least cytotoxicity hence most biocompatibility.

Keywords: biocompatibility, core-shell quantum dots, photoluminescence and lifetime, sensing ability

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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 116

Authors: Z. Ghorannevis, E. Akbarnejad, B. Aghazadeh, M. Ghoranneviss

Abstract:

Carbon nanotubes (CNTs) modified with semiconductor nanocrystalline particles may find wide applications due to their unique properties. Here Cadmium Sulfide (CdS) nanoparticles were successfully grown on Multi-Walled Carbon Nanotubes (MWNTs) via a magnetron sputtering method for the first time. The CdS/MWNTs sample was characterized with X-ray diffraction (XRD), Field Emission Scanning and High Resolution Transmission Electron Microscopies (SEM/TEM) and four point probe. The obtained images show clearly the decoration of the MWNTs by the CdS nanoparticles, and the XRD measurements indicate the CdS structure as hexagonal type. Moreover, the physical properties of the CdS/MWNTs were compared with the physical properties of the CdS nanoparticles grown on the silicon. Electrical measurements of CdS and CdS/MWNTs reveal that CdS/MWNTs has lower resistivity than the CdS sample which may be due to the higher carrier concentrations.

Keywords: CdS, MWNTs, HRTEM, magnetron sputtering

Procedia PDF Downloads 405

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 314

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 657

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 404