Search results for: open source data

Authors: Bouchou Aïssa, Mohamed Akbi

Abstract:

Contact materials used for electrical breakers are often made with silver alloys. Mechanical and thermo dynamical properties as well as electron emission of such complicated alloys present a lack of reliable and accurate experimental data. This paper deals mainly with electron work function (EWF) measurements about silver-metal oxide (Ag-MeO) electrical contacts (Ag-ZnO (92/8), before and after surface heat treatments at 296 K  813 K, under UHV conditions (residual gas pressure of 1.4 x 10-7 mbar). The electron work function (EWF) of silver zinc oxide materials was measured photoelectrically, using both Fowler’s method of isothermal curves and linearized Fowler plots. In this paper, we present the development of a method for measuring photoelectric work function of contact materials. Also reported in this manuscript are the results of experimental work whose purpose has been the buildup of a reliable photoelectric system and associated monochromatic ultra-violet radiations source, and the photoelectric measurement of the electron work functions (EWF) of contact materials. In order to study the influence of annealing temperature on the EWF, a vacuum furnace was used for heating the metallic samples up to 800 K. The EWF of the silver – zinc oxide materials were investigated to study the influence of annealing temperature on the EWF. In the present study, the photoelectric measurements about Ag-ZnO(92/8) contacts have shown a linear decrease of the EWF with increasing temperature, i.e. the temperature coefficient is constant and negative: for the first annealing # 1, in the temperature range [299 K  823 K]. On the contrary, a linear increase was observed with increasing temperature (i.e. , being constant and positive), for the next annealing # 2, in the temperature range [296 K  813 K]. The EWFs obtained for silver-zinc oxide Ag-ZnO(92/8) show an obvious dependence on the annealing temperature which is strongly associated with the evolution of the arrangement on ZnO nano particles on the Ag-ZnO contact surface as well as surface charge distribution.

Keywords: Photoemission, Electron work function, Fowler methods, Ag-ZnO contact materials, Vacuum heat treatment

Procedia PDF Downloads 416

Authors: Tuji Jemal Ahmed, Hussen Beker Yusuf

Abstract:

Food safety is a major concern worldwide, with microbial contamination being one of the leading causes of foodborne illnesses. In Ethiopia, drinking water and untreated groundwater are a primary source of microbial contamination, leading to significant health risks. East Hararghe, Oromia, is one of the regions in Ethiopia that has been affected by this problem. This paper provides an overview of the impact of untreated groundwater on human health in Haramaya Rural District, East Hararghe and highlights the urgent need for sustained efforts to address the water sanitation supply problem. The use of untreated groundwater for drinking and household purposes in Haramaya Rural District, East Hararghe is prevalent, leading to high rates of waterborne illnesses such as diarrhea, typhoid fever, and cholera. The impact of these illnesses on human health is significant, resulting in significant morbidity and mortality, especially among vulnerable populations such as children and the elderly. In addition to the direct health impacts, waterborne illnesses also have indirect impacts on human health, such as reduced productivity and increased healthcare costs. Groundwater sources are susceptible to microbial contamination due to the infiltration of surface water, human and animal waste, and agricultural runoff. In Haramaya Rural District, East Hararghe, poor water management practices, inadequate sanitation facilities, and limited access to clean water sources contribute to the prevalence of untreated groundwater as a primary source of drinking water. These underlying causes of microbial contamination highlight the need for improved water sanitation infrastructure, including better access to safe drinking water sources and the implementation of effective treatment methods. The paper emphasizes the need for regular water quality monitoring, especially for untreated groundwater sources, to ensure safe drinking water for the population. The implementation of effective preventive measures, such as the use of effective disinfectants, proper waste disposal methods, and regular water quality monitoring, is crucial to reducing the risk of contamination and improving public health outcomes in the region. Community education and awareness-raising campaigns can also play a critical role in promoting safe water practices and reducing the risk of contamination. These campaigns can include educating the population on the importance of boiling water before drinking, the use of water filters, and proper sanitation practices. In conclusion, the use of untreated groundwater as a primary source of drinking water in East Hararghe, Oromia, Ethiopia, has significant impacts on human health, leading to widespread waterborne illnesses and posing a significant threat to public health. Sustained efforts are urgently needed to address the root causes of contamination, such as poor sanitation and hygiene practices, improper waste management, and the water sanitation supply problem, including the implementation of effective preventive measures and community-based education programs, ultimately improving public health outcomes in the region. A comprehensive approach that involves community-based water management systems, point-of-use water treatment methods, and awareness-raising campaigns can contribute to reducing the incidence of microbial contamination in the region.

Keywords: food safety, health risks, microbial contamination, untreated groundwater

Procedia PDF Downloads 114

Authors: Kayode Balogun, Femi Ayoola

Abstract:

Crime is at alarming rate in this part of world and there are many factors that are contributing to this antisocietal behaviour both among the youths and old. In this work, principal component analysis (PCA) was used as a tool to reduce the dimensionality and to really know those variables that were crime prone in the study region. Data were collected on twenty-eight crime variables from National Bureau of Statistics (NBS) databank for a period of fifteen years, while retaining as much of the information as possible. We use PCA in this study to know the number of major variables and contributors to the crime in the Southwest Nigeria. The results of our analysis revealed that there were eight principal variables have been retained using the Scree plot and Loading plot which implies an eight-equation solution will be appropriate for the data. The eight components explained 93.81% of the total variation in the data set. We also found that the highest and commonly committed crimes in the Southwestern Nigeria were: Assault, Grievous Harm and Wounding, theft/stealing, burglary, house breaking, false pretence, unlawful arms possession and breach of public peace.

Keywords: crime rates, data, Southwest Nigeria, principal component analysis, variables

Procedia PDF Downloads 444

Authors: Chang Lee Shu-Jung, Mei-Se Chien, Chien-Chiang Lee, Hui-Ting Hu

Abstract:

This paper applies recursive cointegration analysis to examine the dynamic changes in Feldstein-Horioka saving-investment (S-I) coefficients across China and the ASEAN-5 countries over time. To the extent that the S-I coefficients measure international capital mobility, the main empirical results are as follows. The recursive trace statistics show that the investment- savings nexus varies in these six countries. There is no cointegration between investment and savings in three countries (China, Malaysia, and Singapore), which means that the mobility of the capital markets in the three is high and that domestic investment in them will be financed by the global pool of capital. As to the other three countries (Indonesia, Thailand, and Philippines), there is cointegration between investment and savings for part of the sample period in the three, including before 2002 for Thailand, before 2001 for Indonesia, and before 2002 for Philippines. This shows these three countries achieved highly mobile and open capital markets later.

Keywords: investment, savings, recursive cointegration test, ASEAN, China

Procedia PDF Downloads 552

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

Procedia PDF Downloads 356

Authors: P. Mormile, M. Rippa, G. Bonanomi, F. Scala, Changrong Yan, L. Petti

Abstract:

Photo-reflective films represent, in the panorama of agricultural films, a valid support for Spring and Summer cultivations, both in open field and under greenhouse. In fact, thanks to the high reflectivity of these films, thermal aggression, that causes serious problems to plants when traditional black mulch films are used, is avoided. Yellow or silver colored photo-reflective films protect plants from damages, assure the mulching effect, give a valid support to Integrated Pest Management and, according to recent trials, greatly contribute in saving water. This further advantage is determined by the high water condensation under the mulch film and this gives rise to reduction of irrigation. Water saving means also energy saving for electric system of water circulation. Trials performed at different geographic and ambient context confirm that the use of photo-reflective mulch films during the hot season allows to save water up to 30%.

Keywords: photo-selective mulches, saving water, water circulation, irrigation

Procedia PDF Downloads 516

Authors: Rupali Bhardwaj

Abstract:

Cryptography is the science of using mathematics to encrypt and decrypt data; the data are converted into some other gibberish form, and then the encrypted data are transmitted. The primary purpose of this paper is to provide two levels of security through a two-step process, rather than transmitted the message bits directly, first encrypted it using 2D cellular automata and then scrambled with Arnold Cat Map transformation; it provides an additional layer of protection and reduces the chance of the transmitted message being detected. A comparative analysis on effectiveness of scrambling technique is provided by scrambling degree measurement parameters i.e. Gray Difference Degree (GDD) and Correlation Coefficient.

Keywords: scrambling, cellular automata, Arnold cat map, game of life, gray difference degree, correlation coefficient

Procedia PDF Downloads 377

Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

Abstract:

The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

Procedia PDF Downloads 105

Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

Abstract:

New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

Procedia PDF Downloads 139

Authors: Naveed Ghani, Samreen Javed

Abstract:

In today’s heterogeneous network environment, there is a growing demand for distrust clients to jointly execute secure network to prevent from malicious attacks as the defining task of propagating malicious code is to locate new targets to attack. Residual risk is always there no matter what solutions are implemented or whet so ever security methodology or standards being adapted. Security is the first and crucial phase in the field of Computer Science. The main aim of the Computer Security is gathering of information with secure network. No one need wonder what all that malware is trying to do: It's trying to steal money through data theft, bank transfers, stolen passwords, or swiped identities. From there, with the help of our survey we learn about the importance of white listing, antimalware programs, security patches, log files, honey pots, and more used in banks for financial data protection but there’s also a need of implementing the IPV6 tunneling with Crypto data transformation according to the requirements of new technology to prevent the organization from new Malware attacks and crafting of its own messages and sending them to the target. In this paper the writer has given the idea of implementing IPV6 Tunneling Secessions on private data transmission from financial organizations whose secrecy needed to be safeguarded.

Keywords: network worms, malware infection propagating malicious code, virus, security, VPN

Procedia PDF Downloads 358

Authors: Abdallah Al-ZoubI, Mamoun Dmour

Abstract:

The spectrum of IoT devices is becoming widely diversified, entering almost all possible fields and finding applications in industry, health, finance, logistics, education, to name a few. The IoT active endpoint sensors and devices exceeded the 12 billion mark in 2021 and are expected to reach 27 billion in 2025, with over $34 billion in total market value. This sheer rise in numbers and use of IoT devices bring with it considerable concerns regarding data storage, analysis, manipulation and protection. IoT Blockchain-based systems have recently been proposed as a decentralized solution for large-scale data storage and protection. COVID-19 has actually accelerated the desire to utilize IoT devices as it impacted both demand and supply and significantly affected several regions due to logistic reasons such as supply chain interruptions, shortage of shipping containers and port congestion. An IoT-blockchain system is proposed to handle big data generated by a distributed network of sensors and controllers in an interactive manner. The system is designed using the Ethereum platform, which utilizes smart contracts, programmed in solidity to execute and manage data generated by IoT sensors and devices. such as Raspberry Pi 4, Rasbpian, and add-on hardware security modules. The proposed system will run a number of applications hosted by a local machine used to validate transactions. It then sends data to the rest of the network through InterPlanetary File System (IPFS) and Ethereum Swarm, forming a closed IoT ecosystem run by blockchain where a number of distributed IoT devices can communicate and interact, thus forming a closed, controlled environment. A prototype has been deployed with three IoT handling units distributed over a wide geographical space in order to examine its feasibility, performance and costs. Initial results indicated that big IoT data retrieval and storage is feasible and interactivity is possible, provided that certain conditions of cost, speed and thorough put are met.

Keywords: IoT devices, blockchain, Ethereum, big data

Procedia PDF Downloads 150

Authors: Soo Im Chung, Lara Marie Pangan Lo, Yao Cheng Zhang, Su Jin Nam, Xingyue Jin, Mi Young Kang

Abstract:

Rice (Oryza sativa L.) is one of the most widely consumed grains. Due to the growing number of demand as a potential functional food and nutraceutical source and the increasing awareness of people towards healthy diet and good quality of living, more researches dwell upon the development of new rice cultivars for population consumption. However, studies on the antioxidant capacities of newly developed rice were limited as well as the effects of germination in these rice cultivars. Therefore, this study aimed to focus on analysis of the antioxidant potential of pre-germinated and germinated pigmented rice cultivars in South Korea such as purple cultivar Superjami (SJ) and red cultivar Super hongmi (SH) in comparison with the non-pigmented Normal Brown (NB) Rice. The powdered rice grain samples were extracted with 80% methanol and their antioxidant activities were determined. The Results showed that pre-germinated pigmented rice cultivars have higher Fe2+ Chelating Ability (Fe2+), Reducing Power (RP), 2,2´-azinobis[3-ethylbenzthiazoline]-6-sulfonic acid (ABTS) radical scavenging and Superoxide Dismutase activity than the control NB rice. Moreover, it is revealed that germination process induced a significant increased in the antioxidant activities of all the rice samples regardless of their strains. Purple rice SJ showed greater Fe2+ (88.82 + 0.53%), RP (0.82 + 0.01) , ABTS (143.63 + 2.38 mg VCEAC/100 g) and SOD (59.31 + 0.48%) activities than the red grain SH and the control NB having the lowest antioxidant potential among the three (3) rice samples examined. The Effective concentration at 50% (EC50) of 1, 1-Diphenyl-2-picrylhydrazyl (DPPH) and Hydroxyradical (-OH) Scavenging activity for the rice samples were also obtained. SJ showed lower EC50 in terms of its DPPH (3.81 + 0.15 mg/mL) and –OH (5.19 + 0.08 mg/mL) radical scavenging activities than the red grain SH and control NB rice indicating that at lower concentrations, it can readily exhibit antioxidant effects against reactive oxygen species (ROS). These results clearly suggest the higher antioxidant potential of pigmented rice varieties as compared with the widely consumed NB rice. Also, it is revealed in the study that even at lower concentrations, pigmented rice varieties can exhibit their antioxidant activities. Germination process further enhanced the antioxidant capacities of the rice samples regardless of their types. With these results at hand, these new rice varieties can be further developed as a good source of bio functional elements that can help alleviate the growing number of cases of metabolic disorders.

Keywords: antioxidant capacity, germinated rice, pigmented rice, super hongmi, superjami

Procedia PDF Downloads 444

Authors: Abdul-Rahman Al-Ali

Abstract:

As the number of mobile devices is growing exponentially, it is estimated to connect about 50 million devices to the Internet by the year 2020. At the end of this decade, it is expected that an average of eight connected devices per person worldwide. The 50 billion devices are not mobile phones and data browsing gadgets only, but machine-to-machine and man-to-machine devices. With such growing numbers of devices the Internet of Things (I.o.T) concept is one of the emerging technologies as of recently. Within the smart grid technologies, smart home appliances, Intelligent Electronic Devices (IED) and Distributed Energy Resources (DER) are major I.o.T objects that can be addressable using the IPV6. These objects are called the smart grid internet of things (SG-I.o.T). The SG-I.o.T generates big data that requires high-speed computing infrastructure, widespread computer networks, big data storage, software, and platforms services. A company’s utility control and data centers cannot handle such a large number of devices, high-speed processing, and massive data storage. Building large data center’s infrastructure takes a long time, it also requires widespread communication networks and huge capital investment. To maintain and upgrade control and data centers’ infrastructure and communication networks as well as updating and renewing software licenses which collectively, requires additional cost. This can be overcome by utilizing the emerging computing paradigms such as cloud computing. This can be used as a smart grid enabler to replace the legacy of utilities data centers. The talk will highlight the role of I.o.T, cloud computing services and their development models within the smart grid technologies.

Keywords: intelligent electronic devices (IED), distributed energy resources (DER), internet, smart home appliances

Procedia PDF Downloads 324

Authors: Shishen Xie, Yingda L. Xie

Abstract:

Tuberculosis (TB) is a potentially serious infectious disease that remains a health concern. The Interferon Gamma Release Assay (IGRA) is a blood test to find out if an individual is tuberculous positive or negative. This study applies statistical analysis to the clinical data of interferon-gamma levels of seventy-three subjects who diagnosed pulmonary TB in an anti-tuberculous treatment. Data analysis is performed to determine if there is a significant decline in interferon-gamma levels for the subjects during a period of six months, and to infer if the anti-tuberculous treatment is effective.

Keywords: data analysis, interferon gamma release assay, statistical methods, tuberculosis infection

Procedia PDF Downloads 306

Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

Abstract:

Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

Procedia PDF Downloads 142

Authors: Jinghui Peng, Shanyu Tang, Jia Li

Abstract:

Steganalysis seeks to detect the presence of secret data embedded in cover objects, and there is an imminent demand to detect hidden messages in streaming media. This paper shows how a steganalysis algorithm based on Fast Fourier Transform (FFT) can be used to detect the existence of secret data embedded in streaming media. The proposed algorithm uses machine parameter characteristics and a network sniffer to determine whether the Internet traffic contains streaming channels. The detected streaming data is then transferred from the time domain to the frequency domain through FFT. The distributions of power spectra in the frequency domain between original VoIP streams and stego VoIP streams are compared in turn using t-test, achieving the p-value of 7.5686E-176 which is below the threshold. The results indicate that the proposed FFT-based steganalysis algorithm is effective in detecting the secret data embedded in VoIP streaming media.

Keywords: steganalysis, security, Fast Fourier Transform, streaming media

Procedia PDF Downloads 147

Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

Abstract:

Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

Procedia PDF Downloads 321

Authors: Shlomit Paz, Meir Broza

Abstract:

Cholera is an acute intestinal infection caused by ingestion of food or water contaminated with the bacterium Vibrio cholerae. It has a short incubation period and produces an enterotoxin that causes copious, painless, watery diarrhoea that can quickly lead to severe dehydration and death if treatment is not promptly given. In an epidemic, the source of the contamination is usually the feces of an infected person. The disease can spread rapidly in areas with poor treatment of sewage and drinking water. Cholera remains a global threat and is one of the key indicators of social development. An estimated 3-5 million cases and over 100,000 deaths occur each year around the world. The relevance of climatic events as causative factors for cholera epidemics is well known. However, the examination of the involvement of winds in intra-continental disease distribution is new. The study explore the hypothesis that the spreading of cholera epidemics may be related to the dominant wind direction over land by presenting the influence of the wind direction on windborn dissemination by flying insects, which may serve as vectors. Chironomids ("non-biting midges“) exist in the majority of freshwater aquatic habitats, especially in estuarine and organic-rich water bodies typical to Vibrio cholerae. Chironomid adults emerge into the air for mating and dispersion. They are highly mobile, huge in number and found frequently in the air at various elevations. The huge number of chironomid egg masses attached to hard substrate on the water surface, serve as a reservoir for the free-living Vibrio bacteria. Both male and female, while emerging from the water, may carry the cholera bacteria. In experimental simulation, it was demonstrated that the cholera-bearing adult midges are carried by the wind, and transmit the bacteria from one body of water to another. In our previous study, the geographic diffusions of three cholera outbreaks were examined through their linkage with the wind direction: a) the progress of Vibrio cholerae O1 biotype El Tor in Africa during 1970–1971 and b) again in 2005–2006; and c) the rapid spread of Vibrio cholerae O139 over India during 1992–1993. Using data and map of cholera dissemination (WHO database) and mean monthly SLP and geopotential data (NOAA NCEP-NCAR database), analysis of air pressure data at sea level and at several altitudes over Africa, India and Bangladesh show a correspondence between the dominant wind direction and the intra-continental spread of cholera. The results support the hypothesis that aeroplankton (the tiny life forms that float in the air and that may be caught and carried upward by the wind, landing far from their origin) carry the cholera bacteria from one body of water to an adjacent one. In addition to these findings, the current follow-up study will present new results regarding the possible involvement of winds in the spreading of cholera in recent outbreaks (2010-2013). The findings may improve the understanding of how climatic factors are involved in the rapid distribution of new strains throughout a vast continental area. Awareness of the aerial transfer of Vibrio cholerae may assist health authorities by improving the prediction of the disease’s geographic dissemination.

Keywords: cholera, Vibrio cholerae, wind direction, Vibrio cholerae dissemination

Procedia PDF Downloads 367

Authors: Jose Gonzalez, Fai Cheng, Ivy Fan

Abstract:

Shipping has a mature and ever expanding worldwide market. The future of the marine industry itself is not only irrevocably linked with the global economic, social, and political landscape; it is also subject to the technological developments in different fields. Some of them may have never been linked to the marine industry before. Companies in the marine sector are getting more dependent on technologies to achieve competitive advantage in an increasing open market. Technologies can be fused across different business functions and geopolitical influences. A successful marine business should be prepared to embrace such potential changes that lie ahead. The present paper intends to articulate long-term marine technology strategies from an industrial perspective. Methodology and current development are introduced. The paper will also provide insight into future technological trends demand for major commercial ship types. It may also assist different stakeholders in tailoring their long-term strategies to achieve a Sea Change and to uncap opportunity.

Keywords: commercial sector, marine, trends, technology

Procedia PDF Downloads 409

Authors: Sidi Yang, Haiyi Zhang

Abstract:

Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: text mining, Twitter, topic model, sentiment analysis

Procedia PDF Downloads 179

Authors: N. N. Lingaraju, A. Sathish, K. N. Geetha, C. A. Srinivasamurthy, S. Bhaskar

Abstract:

Studies on spent wash utilization as a nutrient source through 'Effect of distillery spentwash application on soil properties and yield of maize (Zea may L.) and finger millet (Eleusine coracana (L.) G)' was carried out in Malavalli Taluk, Mandya District, Karnataka State, India. The study was conducted in fourteen different locations of Malavalli (12) and Maddur taluk (2) involving maize and finger millet as a test crop. The spentwash was characterized for various parameters like pH, EC, total NPK, Na, Ca, Mg, SO₄, Fe, Zn, Cu, Mn and Cl content. It was observed from the results that the pH was slightly alkaline (7.45), EC was excess (23.3 dS m⁻¹), total NPK was 0.12, 0.02, and 1.31 percent respectively, Na, Ca, Mg and SO₄ concentration was 664, 1305, 745 and 618 (mg L⁻¹) respectively, total solid content was quite high (6.7%), Fe, Zn, Cu, Mn, values were 23.5, 5.70, 3.64, 4.0 mg L⁻¹, respectively. The crops were grown by adopting different crop management practices after application of spentwash at 100 m³ ha⁻¹ to the identified farmer fields. Soil samples were drawn at three stages i.e., before sowing of crop, during crop growth stage and after harvest of the crop at 2 depths (0-30 and 30-60 cm) and analyzed for pH, EC, available K and Na parameters by adopting standard procedures. The soil analysis showed slightly acidic reaction (5.93), normal EC (0.43 dS m⁻¹), medium available potassium (267 kg ha⁻¹) before application of spentwash. Application of spentwash has enhanced pH level of soil towards neutral (6.97), EC 0.25 dS m⁻¹, available K2O to 376 kg ha⁻¹ and sodium content of 0.73 C mol (P+) kg⁻¹ during the crop growth stage. After harvest of the crops soil analysis data indicated a decrease in pH to 6.28, EC of 0.22 dS m⁻¹, available K₂O to 316 kg ha⁻¹ and Na 0.52 C mol (P⁺) kg⁻¹ compared with crop growth stage. The study showed that, there will be enhancement of potassium levels if the spentwash is applied once to dryland. The yields of both the crops were quantified and found to be in the range of 35.65 to 65.55 q ha⁻¹ and increased yield to the extent of 13.36-22.36 percent as compared to control field (11.36-22.33 q ha⁻¹) in maize crop. Also, finger millet yield was increased with the spentwash application to the extent of 14.21-20.49 percent (9.5-17.73 q ha⁻¹) higher over farmers practice (8.15-14.15 q ha⁻¹).

Keywords: distillery spentwash, finger millet, maize, waste water

Procedia PDF Downloads 358

Authors: Kwaku Damoah

Abstract:

This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

Procedia PDF Downloads 70

Authors: Seonjae Lee, Sungjoo Lee

Abstract:

Excavation is necessary to remain competitive in the current business environment. The company survived the rapidly changing industry conditions by adapting new business strategy and reducing technology challenges. Traditionally, the two methods are conducted excavations for new businesses. The first method is, qualitative analysis of expert opinion, which is gathered through opportunities and secondly, new technologies are discovered through quantitative data analysis of method patents. The second method increases time and cost. Patent data is restricted for use and the purpose of discovering business opportunities. This study presents the company's characteristics (sector, size, etc.), of new business opportunities in customized form by reviewing the value chain perspective and to contributing to creating new business opportunities in the proposed model. It utilizes the trademark database of the Korean Intellectual Property Office (KIPO) and proprietary company information database of the Korea Enterprise Data (KED). This data is key to discovering new business opportunities with analysis of competitors and advanced business trademarks (Module 1) and trading analysis of competitors found in the KED (Module 2).

Keywords: value chain, trademark, trading analysis, new business opportunity

Procedia PDF Downloads 372

Authors: Thassanant Unnanantn, Suttipong Boonphadung

Abstract:

This research study aimed to survey and analyze the attitudes of pre-service teachers’ the analytical thinking development based on Miller’s Model. The informants of this study were 22 third year teacher students majoring in Thai. The course where the instruction was conducted was English for Academic Purposes in Thai Language 2. The instrument of this research was an open-ended questionnaire with two dimensions of questions: academic and satisfaction dimensions. The investigation revealed the positive attitudes. In the academic dimension, the majority of 12 (54.54%), the highest percentage, reflected that the method of teaching analytical thinking and language simultaneously was their new knowledge and the similar percentage also belonged to text cohesion in writing. For the satisfaction, the highest frequency count was from 17 of them (77.27%) and this majority favored the openness or friendliness of the teacher.

Keywords: analytical thinking development, Miller’s Model, attitudes, pre-service teachers

Procedia PDF Downloads 309

Authors: Federico Garrido, Mostafa El Hayani, Ahmed Shams

Abstract:

The exploration of the potential of artificial intelligence (AI) in architecture is still embryonic, however, its latent capacity to change design disciplines is significant. 'Synthetic Classism' is a research project that questions the underlying aspects of classically organized architecture not just in aesthetic terms but also from a geometrical and morphological point of view, intending to generate new architectural information using historical examples as source material. The main aim of this paper is to explore the uses of artificial intelligence and machine learning algorithms in architectural design while creating a coherent narrative to be contained within a design process. The purpose is twofold: on one hand, to develop and train machine learning algorithms to produce architectural information of small pavilions and on the other, to synthesize new information from previous architectural drawings. These algorithms intend to 'interpret' graphical information from each pavilion and then generate new information from it. The procedure, once these algorithms are trained, is the following: parting from a line profile, a synthetic 'front view' of a pavilion is generated, then using it as a source material, an isometric view is created from it, and finally, a top view is produced. Thanks to GAN algorithms, it is also possible to generate Front and Isometric views without any graphical input as well. The final intention of the research is to produce isometric views out of historical information, such as the pavilions from Sebastiano Serlio, James Gibbs, or John Soane. The idea is to create and interpret new information not just in terms of historical reconstruction but also to explore AI as a novel tool in the narrative of a creative design process. This research also challenges the idea of the role of algorithmic design associated with efficiency or fitness while embracing the possibility of a creative collaboration between artificial intelligence and a human designer. Hence the double feature of this research, both analytical and creative, first by synthesizing images based on a given dataset and then by generating new architectural information from historical references. We find that the possibility of creatively understand and manipulate historic (and synthetic) information will be a key feature in future innovative design processes. Finally, the main question that we propose is whether an AI could be used not just to create an original and innovative group of simple buildings but also to explore the possibility of fostering a novel architectural sensibility grounded on the specificities on the architectural dataset, either historic, human-made or synthetic.

Keywords: architecture, central pavilions, classicism, machine learning

Procedia PDF Downloads 140

Authors: Mousouris Spiridon, Kavakli Evangelia

Abstract:

This paper focuses on Digital Libraries (DLs) that contain and geovisualise cultural data, highlighting the need to define them as a separate category termed Cultural Mapping Libraries, based on their inherent connection of culture with geographic location and their design requirements in support of visual representation of cultural data on the map. An exploratory analysis of DLs that conform to the above definition brought forward the observation that existing Cultural Mapping Libraries fail to geovisualise the entirety of cultural data per point of interest thus resulting in a Cultural Snapshot phenomenon. The existence of this phenomenon was reinforced by the results of a systematic bibliographic research. In order to address the Cultural Snapshot, this paper proposes the use of the Semantic Web principles to efficiently interconnect spatial cultural data through time, per geographic location. In this way points of interest are transformed into scenery where culture evolves over time. This evolution is expressed as occurrences taking place chronologically, in an event oriented approach, a conceptualization also endorsed by the CIDOC Conceptual Reference Model (CIDOC CRM). In particular, we posit the use of CIDOC CRM as the baseline for defining the logic of Cultural Mapping Libraries as part of the Culture Domain in accordance with the Digital Library Reference Model, in order to define the rules of cultural data management by the system. Our future goal is to transform this conceptual definition in to inferencing rules that resolve the Cultural Snapshot and lead to a more complete geovisualisation of cultural data.

Keywords: digital libraries, semantic web, geovisualization, CIDOC-CRM

Procedia PDF Downloads 109

Authors: Najia Zulfiqar

Abstract:

Imparting moral education is the need of time, considering the obvious moral decline in society. Recent research shows the downfall of moral competence among university students. The main objective of the present study was to develop moral development intervention strategies for undergraduate students of Sports and Physical Education. Using an interpretative phenomenological approach, insight into field-specific moral issues was gained through interviews with 7 subject experts and a focus-group discussion session with 8 students. Two research assistants who were trained in qualitative interviewing collected, transcribed and analyzed data into the MAXQDA software using content and discourse analyses. The identified moral issues in Sports and Physical Education were sports gambling and betting, pay-for-play, doping, coach misconduct, tampering, cultural bias, gender equity/nepotism, bullying/discrimination, and harassment. Next, intervention modules were developed for each moral issue based on hypothetical situations, and followed by guided reflection and dilemma discussion questions. The third moral development strategy was community services that included posture screening, diet plan for different age groups, open fitness ground training, exercise camps for physical fitness, balanced diet awareness camp, gymnastic camp, shoe assessment as per health standards, and volunteering for public awareness at the playground, gymnasium, stadium, park, etc. The intervention modules were given to four subject specialists for expert validation who were from different backgrounds within Sport Sciences. Upon refinement and finalization, four students were presented with these intervention modules and questioned about accuracy, relevance, comprehension, and content organization. Iterative changes were made in the content of the intervention modules to tailor them to the moral development needs of undergraduate students. This intervention will strengthen positive moral values and foster mature decision-making about right and wrong acts. As this intervention is easy to apply as a remedial tool, academicians and policymakers can use this to promote students’ moral development.

Keywords: community service, dilemma discussion, morality, physical education, university students.

Procedia PDF Downloads 72

Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

Abstract:

The relation between stock price volatility and trading volume represents a controversial issue which has received a remarkable attention over the past decades. In fact, an extensive literature shows a positive relation between price volatility and trading volume in the financial markets, but the causal relationship which originates such association is an open question, from both a theoretical and empirical point of view. In this regard, various models, which can be considered as complementary rather than competitive, have been introduced to explain this relationship. They include the long debated Mixture of Distributions Hypothesis (MDH); the Sequential Arrival of Information Hypothesis (SAIH); the Dispersion of Beliefs Hypothesis (DBH); the Noise Trader Hypothesis (NTH). In this work, we analyze whether stock market efficiency can explain the diversity of results achieved during the years. For this purpose, we propose an alternative measure of market efficiency, based on the pointwise regularity of a stochastic process, which is the Hurst–H¨older dynamic exponent. In particular, we model the stock market by means of the multifractional Brownian motion (mBm) that displays the property of a time-changing regularity. Mostly, such models have in common the fact that they locally behave as a fractional Brownian motion, in the sense that their local regularity at time t0 (measured by the local Hurst–H¨older exponent in a neighborhood of t0 equals the exponent of a fractional Brownian motion of parameter H(t0)). Assuming that the stock price follows an mBm, we introduce and theoretically justify the Hurst–H¨older dynamical exponent as a measure of market efficiency. This allows to measure, at any time t, markets’ departures from the martingale property, i.e. from efficiency as stated by the Efficient Market Hypothesis. This approach is applied to financial markets; using data for the SP500 index from 1978 to 2017, on the one hand we find that when efficiency is not accounted for, a positive contemporaneous relationship emerges and is stable over time. Conversely, it disappears as soon as efficiency is taken into account. In particular, this association is more pronounced during time frames of high volatility and tends to disappear when market becomes fully efficient.

Keywords: volume–volatility relationship, efficient market hypothesis, martingale model, Hurst–Hölder exponent

Procedia PDF Downloads 78

Authors: Suyong Kim

Abstract:

Recently because of the rise in the price of rare earth magnet, interest of non-rare earth or less-rare earth motor is growing. Especially to achieve the high power density, Spoke-Type BLDC (Brushless Permanent Magnet) Motor with ferrite permanent magnet are spotlighted. But Spoke-Type Ferrite BLDC Motor has much of magnetic flux leakage in the direction of rotor shaft. In order to solve this problem, there are two conventional ways. But conventional ways bring the increases of product cost or the decreases of the power density. Therefore, this paper proposes new Spoke-Type BLDC Rotor shape that has the advantages of both conventional methods. The new shape is consists of a one-piece core. The inside and the outside of the rotor are open alternately. So it can take reduced production cost and high power density.

Keywords: motor, BLDC, spoke, ferrite

Procedia PDF Downloads 573

Authors: Niyi Awofeso, Yunes Gaber, Moyosola Bamidele

Abstract:

Since most social media platforms are accessible anytime and anywhere where Internet connections and smartphones are available, the invisibility of the reader raises questions about accuracy, appropriateness and comprehensibility of social media communication. Furthermore, the identity and motives of individuals and organizations who post articles on social media sites are not always transparent. In the health sector, through socially networked platforms constitute a common source of health-related information, given their purported wealth of information. Nevertheless, fake blogs and sponsored postings for marketing 'natural cures' pervade most commonly used social media platforms, thus complicating readers’ abilities to access and understand trustworthy health-related information. This purposive sampling study of 120 participants aged 18-35 year in UAE was conducted between September and December 2017, and explored commonly used social media platforms, frequency of use of social media for accessing health related information, and approaches for assessing the trustworthiness of health information on social media platforms. Results indicate that WhatsApp (95%), Instagram (87%) and Youtube (82%) were the most commonly used social media platforms among respondents. Majority of respondents (81%) indicated that they regularly access social media to get health-associated information. More than half of respondents (55%) with non-chronic health status relied on unsolicited messages to obtain health-related information. Doctors’ health blogs (21%) and social media sites of international healthcare organizations (20%) constitute the most trusted source of health information among respondents, with UAE government health agencies’ social media accounts trusted by 15% of respondents. Cardiovascular diseases, diabetes, and hypertension were the most commonly searched topics on social media (29%), followed by nutrition (20%) and skin care (16%). Majority of respondents (41%) rely on reliability of hits on Google search engines, 22% check for health information only from 'reliable' social media sites, while 8% utilize 'logic' to ascertain reliability of health information. As social media has rapidly become an integral part of the health landscape, it is important that health care policy makers, healthcare providers and social media companies collaborate to promote the positive aspects of social media for young people, whilst mitigating the potential negatives. Utilizing popular social media platforms for posting reader-friendly health information will achieve high coverage. Improving youth digital literacy will facilitate easier access to trustworthy information on the internet.

Keywords: social media, United Arab Emirates, youth engagement, digital literacy

Procedia PDF Downloads 119