Search results for: scientific data mining

Authors: K. Tunde Olagunju, C. Scott Allen, Freek Van Der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization are only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two (2) operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the hydrocarbon spectral slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven (7) different hydrocarbon oils (crude and refined oil) taken on ten (10) different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon-substrate combination, Sentinel-2, WorldView-3

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

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The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: Olga Shuvaeva, Tamara Romanova, Sergey Volynkin, Valentina Podolinnaya

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Green chemistry concept is focused on the prevention of environmental pollution caused by human activity. However, there are a lot of contaminated areas in the world which pose a serious threat to ecosystems in terms of their conservation. Therefore in accordance with the principles of green chemistry, it should not be forgotten about the need to clean these areas. Furthermore, the waste material often contains the valuable components, the extraction of which by traditional wet chemical technologies is inefficient both from the economic and environmental protection standpoint. Wherein, the plants may be successfully used to ‘scavenge’ a range of metals from polluted land sites in an approach allowing to carry out both of these processes – phytoremediation and phytomining in conjunction. The goal of the present work was to study bioaccumulation ability of floating macrophytes such as water hyacinth and pondweed toward Hg, Ba, Cd, Mo and Pb as pollutants in aquatic medium and terrestrial plants (birch, reed, and cane) towards gold and silver as valuable components. The peculiarity of ongoing research was that the plants grew under extreme conditions (pH of drainage and pore waters was about 2.5). The study was conducted at the territory of Ursk tailings (Southwestern Siberia, Russia) formed as a result of primary polymetallic ores cyanidation. The waste material is mainly presented (~80%) by pyrite (FeS₂) and barite (BaSO₄), the raw minerals included FeAsS, HgS, PbS, Ag₂S as minor ones. It has been shown that water hyacinth demonstrates high ability to accumulate different metals, and what is especially important – to remove mercury from polluted waters with BCF value more than 1000. As for the gold, its concentrations in reed and cane growing near the waste material were estimated as 500 and 900 μg∙kg⁻¹ respectively. It was also found that the plants can survive under extreme conditions of acidic environment and hence we can assume that there is a principal opportunity to use them for the valuable substances extraction from an area of the mining waste dumps burial.

Keywords: bioaccumulation, gold, heavy metals, mine tailing

Procedia PDF Downloads 177

Authors: Sajjad Jafari

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Background and Aim: The use of herbal medicines has a long history. Today, due to the resistance of microorganisms to antibiotics and antimicrobial substances, herbal medicines have attracted attention due to their significant antimicrobial effects and low toxicity. This study aims to systematically review the antimicrobial effects of different plant extracts (Quercus infectoria) as possible candidates for treating infectious diseases. Material and Methods: The present study is a review study by searching reputable scientific databases such as PubMed, Google Scholar, Scopus, and Web of Science from 2000 to 2023 using the keywords Antimicrobial, Quercus infectoria, Medicinal herbal, Infectious diseases the latest information obtained. Results: In this study, 45 articles were found and reviewed. Quercus infectoria is a small tree native to Greece, Asia Minor, and Iran. Quercus is a plant genus in the family of Fagaceae. This species is generally known under the name ‘‘baloot” in Iran and is commonly used as a medicinal plant. The extracts used included water, hydro-alcoholic, ethanol, methanol. This plant had high inhibition activity and a lethal effect on gram-positive and gram-negative bacteria of ATCC strains, hospital, and resistant strains. Therefore, in addition to antibacterial effects, antiparasitic and antifungal effects. The seed of the plant was the most used and the most effective antimicrobial extract among the ethanol and methanol extracts. Conclusion: The findings of this study suggest that Quercus infectoria has significant antimicrobial effects against a wide range of microorganisms. This makes it a potential candidate for the development of new antimicrobial drugs. Further research is needed to confirm the efficacy and safety of Quercus infectoria in clinical trials.

Keywords: antimicrobial, Quercus infectoria, medicinal herbal, infectious diseases

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Authors: Khaled Shehata, Hanady Hussien, Sara Yehia

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Securing the data stored on E-passport is a very important issue. RSA encryption algorithm is suitable for such application with low data size. In this paper the design and implementation of 1024 bit-key RSA encryption and decryption module on an FPGA is presented. The module is verified through comparing the result with that obtained from MATLAB tools. The design runs at a frequency of 36.3 MHz on Virtex-5 Xilinx FPGA. The key size is designed to be 1024-bit to achieve high security for the passport information. The whole design is achieved through VHDL design entry which makes it a portable design and can be directed to any hardware platform.

Keywords: RSA, VHDL, FPGA, modular multiplication, modular exponential

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Authors: Shamsulhaq Amin

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Drought can arise from several hydrometeorological phenomena that result in insufficient precipitation, soil moisture, and surface and groundwater flow, leading to conditions that are considerably drier than the usual water content or availability. Drought is often assessed using indices that are associated with meteorological, agricultural, and hydrological phenomena. In order to effectively handle drought disasters, it is essential to accurately determine the kind, intensity, and extent of the drought using drought characterization. This information is critical for managing the drought before, during, and after the rehabilitation process. Over a hundred drought assessments have been created in literature to evaluate drought disasters, encompassing a range of factors and variables. Some models utilise solely hydrometeorological drivers, while others employ remote sensing technology, and some incorporate a combination of both. Comprehending the entire notion of drought and taking into account drought indices along with their calculation processes are crucial for researchers in this discipline. Examining several drought metrics in different studies requires additional time and concentration. Hence, it is crucial to conduct a thorough examination of approaches used in drought indices in order to identify the most straightforward approach to avoid any discrepancies in numerous scientific studies. In case of practical application in real-world, categorizing indices relative to their usage in meteorological, agricultural, and hydrological phenomena might help researchers maximize their efficiency. Users have the ability to explore different indexes at the same time, allowing them to compare the convenience of use and evaluate the benefits and drawbacks of each. Moreover, certain indices exhibit interdependence, which enhances comprehension of their connections and assists in making informed decisions about their suitability in various scenarios. This study provides a comprehensive assessment of various drought indices, analysing their types and computation methodologies in a detailed and systematic manner.

Keywords: drought classification, drought severity, drought indices, agriculture, hydrological

Procedia PDF Downloads 51

Authors: Shashank Gupta, Iteash Agarwal, Vijayalaxmi Mogiligidda, Rajesh Kumar Krishnan, Sruthi Chennuri, Deepika Aggarwal, Anwesha Hoodati, Sheroy Cooper, Ranjan, Mohammad Bilal Sheik, Bhavya K. M., Manasa Hegde, M. Naveen Krishna, Amit Kumar Chauhan, Mallikarjun Korrapati, Sumit Singh, J. B. Singh, Sunil Sud, Sunil Gupta, Sidhartha Pant, Sankar, Neha Agrawal, Ashish Ranjan, Piyush Mohapatra, Roopak T., Arsh Ahmad, Nanjunda M., Dilip Singh

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Major research interests on quantum key distribution (QKD) are primarily focussed on increasing 1. point-to-point transmission distance (1000 Km), 2. secure key rate (Mbps), 3. security of quantum layer (device-independence). It is great to push the boundaries on these fronts, but these isolated approaches are neither scalable nor cost-effective due to the requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different sets of challenges apart from distance, key rate, and quantum security. In this regard, we present ChaQra -a sub-quantum network with core features as 1) Crypto agility (integration in the already deployed telecommunication fibres), 2) Software defined networking (SDN paradigm for routing different nodes), 3) reliability (addressing denial-of-service with hybrid quantum safe cryptography), 4) upgradability (modules upgradation based on scientific and technological advancements), 5) Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under the national quantum mission.

Keywords: quantum network, quantum key distribution, quantum security, quantum information

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Authors: Jean Marie Ntaganda, Froduald Minani, Wellars Banzi, Lydie Mpinganzima, Japhet Niyobuhungiro, Jean Bosco Gahutu, Vincent Dusabejambo, Immaculate Kambutse

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In this paper, we present a nonlinear dynamic model for the interactive mechanism of the cardiovascular and respiratory system. The model is designed and analyzed for human during physical exercises. In order to verify the adequacy of the designed model, data collected in Rwanda are used for validation. We have simulated the impact of heart rate and alveolar ventilation as controls of cardiovascular and respiratory system respectively to steady state response of the main cardiovascular hemodynamic quantities i.e., systemic arterial and venous blood pressures, arterial oxygen partial pressure and arterial carbon dioxide partial pressure, to the stabilised values of controls. We used data collected in Rwanda for both male and female during physical activities. We obtained a good agreement with physiological data in the literature. The model may represent an important tool to improve the understanding of exercise physiology.

Keywords: exercise, cardiovascular/respiratory, hemodynamic quantities, numerical simulation, physical activity, sportsmen in Rwanda, system

Procedia PDF Downloads 247

Authors: Yener Ekiz

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Knowledge development is a proactive process that covers collection, analysis, storage and distribution of information that helps to contribute the understanding of the environment. To transfer knowledge correctly and fastly, you have to use new emerging information system technologies. Actionable knowledge is only of value if it is understandable and usable by target users. The purpose of the paper is to enlighten how technology eases and affects the process of knowledge development. While preparing the paper, literature review, survey and interview methodology will be used. The hypothesis is that the technology and knowledge development are inseparable and the technology will formalize the DIKW hierarchy again. As a result, today there is huge data. This data must be classified sharply and quickly.

Keywords: DIKW hierarchy, knowledge development, technology

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Authors: Marcello De Falco, Gianluca Natrella, Mauro Capocelli

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CO₂ capture and utilization (CCU) is a promising approach to reduce GHG(greenhouse gas) emissions. Many technologies in this field are recently attracting attention. However, since CO₂ is a very stable compound, its utilization as a reagent is energetic intensive. As a consequence, it is unclear whether CCU processes allow for a net reduction of environmental impacts from a life cycle perspective and whether these solutions are sustainable. Among the tools to apply for the quantification of the real environmental benefits of CCU technologies, exergy analysis is the most rigorous from a scientific point of view. The exergy of a system is the maximum obtainable work during a process that brings the system into equilibrium with its reference environment through a series of reversible processes in which the system can only interact with such an environment. In other words, exergy is an “opportunity for doing work” and, in real processes, it is destroyed by entropy generation. The exergy-based analysis is useful to evaluate the thermodynamic inefficiencies of processes, to understand and locate the main consumption of fuels or primary energy, to provide an instrument for comparison among different process configurations and to detect solutions to reduce the energy penalties of a process. In this work, the exergy analysis of a process for the production of Dimethyl Ether (DME) from green hydrogen generated through an electrolysis unit and pure CO₂ captured from flue gas is performed. The model simulates the behavior of all units composing the plant (electrolyzer, carbon capture section, DME synthesis reactor, purification step), with the scope to quantify the performance indices based on the II Law of Thermodynamics and to identify the entropy generation points. Then, a plant optimization strategy is proposed to maximize the exergy efficiency.

Keywords: green DME production, exergy analysis, energy penalties, exergy efficiency

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Authors: Yu-Hsuan Liu, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the laser metal deposition (LMD) process and to estimate particle concentrations deposited in the head (H), that the tracheobronchial (TB) and alveolar (A) regions, respectively. The studied LMD chamber (3.6m × 3.8m × 2.9m) is installed with a robot laser metal deposition machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling inside the chamber for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L / min, respectively. The resultant size distributions were used to predict depositions of nanoparticles at the H, TB, and A regions of the respiratory tract using the UK National Radiological Protection Board’s (NRPB’s) LUDEP Software. Result that the number concentrations of nanoparticles in indoor background and LMD chamber were 4.8×10³ and 4.3×10⁵ # / cm³, respectively. However, the nanoparticles emitted from the LMD process was in the form of the uni-modal with number median diameter (NMD) and geometric standard deviation (GSD) as 142nm and 1.86, respectively. The fractions of the nanoparticles deposited on the alveolar region (A: 69.8%) were higher than the other two regions of the head region (H: 10.9%), tracheobronchial region (TB: 19.3%). This study conducted static sampling to measure the nanoparticles in the LMD process, and the results show that the fraction of particles deposited on the A region was higher than the other two regions. Therefore, applying the characteristics of nanoparticles emitted from LMD process could be provided valuable scientific-based evidence for exposure assessments in the future.

Keywords: exposure assessment, laser metal deposition process, nanoparticle, respiratory region

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Authors: Chin-Yuan Hsieh, Wei-Chun Lu, Yu-Hong Zeng

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The situation of a group of fish die is frequently found due to the fish disease caused by the deterioration of aquaculture water quality. The toxic ammonia is produced by animals as a byproduct of protein. The system is designed by the smart sensor technology and developed by the mathematical model to monitor the water parameters 24 hours a day and predict the relationship among twelve water quality parameters for monitoring the water quality in aquaculture. All data measured are stored in cloud server. In productive ponds, the daytime pH may be high enough to be lethal to the fish. The sudden change of the aquaculture conditions often results in the increase of PH value of water, lack of oxygen dissolving content, water quality deterioration and yield reduction. From the real measurement, the system can send the message to user’s smartphone successfully on the bad conditions of water quality. From the data comparisons between measurement and model simulation in fish aquaculture site, the difference of parameters is less than 2% and the correlation coefficient is at least 98.34%. The solubility rate of oxygen decreases exponentially with the elevation of water temperature. The correlation coefficient is 98.98%.

Keywords: aquaculture, sensor, ammonia, dissolved oxygen

Procedia PDF Downloads 287

Authors: Siah Koka, Rony Swennen

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Arumeru district is located in Arusha region in Upper Pangani basin in Tanzania. Economically it is dominated with agricultural activities. Banana, coffee, maize, beans, tomatoes, and cassava are the most important food and cash crops. This paper characterized the banana-based farming system of Arumeru district, evaluates its sustainability as well as research needs. The household questionnaire was performed on-site and on farm observation. Transect walk also involved to identify different agro- ecological zones. Results show that farm holdings (home gardens) are smaller than a hectare (0.7 ha) and continue to fragment as population continues to grow. Banana cultivation is the backbone of the farming systems present both in the upland and plains. In the upper belt banana found their place in the forest, which form the home garden structure typical to East African highland banana production systems. However, in the plains, cultivation is done in monoculture and depends heavily on irrigation. We found slightly less cultivars present and hypothetically more pest and disease pressure. This was mainly seen for Fusarium oxysporum species, which eradicates susceptible cultivars such as Mchare cultivars rapidly given the method of irrigation. The smaller permanent upland home garden plots provide thus a more suitable environment where banana perform better. It should be noted that findings indicated good performance to occur in the less suitable plains too. Good management is believed to be the most influencing factor, although our survey failed in identifying them. Population pressure is currently pushing the sustainable system in the uplands to its boundaries. Nutrient mining, deforestation and changing rain patterns threat production not only on Mt. Meru but on a global scale.

Keywords: Arumeru district, banana-based farming system, Tanzania, Arumeru district

Procedia PDF Downloads 182

Authors: Maria Ukolova

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Social and cultural processes over the past decades have largely affected the understanding of conventional female beauty all over the world. Fine arts and design tendencies could not remain unchanged and show a dynamic interplay with female rights, gender equality, and other social processes. As of now, the area lacks comprehensive academic research on the tendencies of understanding female beauty in contemporary art. This article makes an attempt to outline and analyse the main tendencies of contemporary works of art that turn to the image of a woman, including photography, digital art, and various forms of design. The research bases itself on paintings, performing arts, photography, digital art, and various forms of design, mainly on the principle of the most broadly resonated in society, as an empirical basis, and on existing researches in the sphere. The results of the research show a general trend that the concept of female beauty in art is either challenged as such or its understanding has shifted to individuality, diversity, and the state of mental health. However, some categories of art, such as digital art in the gaming industry, remain resistant to change and retain the appearance-based understanding of beauty. Specific tendencies are, firstly, aestheticization of all types of appearances; secondly, a ubiquitous interest in mental health issues and understanding the state of mental health as a part of beauty; thirdly, a certain infantilization of the image of the woman is observed as compared to previous decades. The significance of the findings of the research is to contribute to a scientific understanding of the concept of beauty in contemporary art and to give ground for prospective further related research in sociology, phycology, etc. The findings might be perceived not only by academics but also by artists and practitioners in the spheres of art and society.

Keywords: fine arts, history of art, contemporary art, concept of beauty

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

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Authors: Suresh Kumar Reddy Narala, Rakesh Kumar Gunda

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In modern industry, mechanical parts are subjected to friction and wear, leading to heat generation, which affects the reliability, life and power consumption of machinery. To overcome the tribological losses due to friction and wear, a significant portion of lubricant with high viscous properties allows very smooth relative motion between two sliding surfaces. Advancement in modern tribology has facilitated the use of applying solid lubricants in various industrial applications. Solid lubricant additives with high viscous thin film formation between the sliding surfaces can adequately wet and adhere to a work surface. In the present investigation, an attempt has been made to investigate and evaluate the tribological studies of various solid lubricants like MoS¬2, graphite, and boric acid at different sliding conditions. The base oil used in this study was SAE 40 oil with a viscosity of 220 cSt at 400C. The tribological properties were measured on pin-on-disc tribometer. An experimental set-up has been developed for effective supply of solid lubricants to the pin-disc interface zone. The results obtained from the experiments show that the friction coefficient increases with increase in applied load for all the considered environments. The tribological properties with MoS2 solid lubricant exhibit larger load carrying capacity than that of graphite and boric acid. The present research work also contributes to the understanding of the behavior of film thickness distribution of solid lubricant using potential contact technique under different sliding conditions. The results presented in this research work are expected to form a scientific basis for selecting the best solid lubricant in various industrial applications for possible minimization of friction and wear.

Keywords: friction, wear, temperature, solid lubricant

Procedia PDF Downloads 351

Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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Authors: L. Maiza, A. Cantagrel, M. Forestier, G. Laucoin, T. Regali

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Evaluation of High Frequency Trading (HFT) impact on financial markets is very important for traders who use market analysis to detect winning transaction opportunity. Analysis of HFT data on tobacco commodity market is discussed here and interesting linear relationship has been shown between trading frequency and difference between averaged trading prices above and below considered trading frequency. This may open new perspectives on markets data understanding and could provide possible interpretation of Adam Smith invisible hand.

Keywords: financial market, high frequency trading, analysis, impacts, Adam Smith invisible hand

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Authors: Xue Wang, Liwei Fan

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Renewable energy technology innovation is an important way to realize the energy transformation. Our government has issued a series of policies to guide and support the development of renewable energy. The implementation of these policies will affect the further development, utilization and technological innovation of renewable energy. In this context, it is of great significance to systematically sort out and evaluate the renewable energy technology innovation policy for improving the existing policy system. Taking the 190 renewable energy technology innovation policies issued during 2005-2021 as a sample, from the perspectives of policy issuing departments and policy keywords, it uses text mining and content analysis methods to analyze the current situation of the policies and conduct a semantic network analysis to identify the core issuing departments and core policy topic words; A PMC (Policy Modeling Consistency) index model is built to quantitatively evaluate the selected policies, analyze the overall pros and cons of the policy through its PMC index, and reflect the PMC value of the model's secondary index The core departments publish policies and the performance of each dimension of the policies related to the core topic headings. The research results show that Renewable energy technology innovation policies focus on synergy between multiple departments, while the distribution of the issuers is uneven in terms of promulgation time; policies related to different topics have their own emphasis in terms of policy types, fields, functions, and support measures, but It still needs to be improved, such as the lack of policy forecasting and supervision functions, the lack of attention to product promotion, and the relatively single support measures. Finally, this research puts forward policy optimization suggestions in terms of promoting joint policy release, strengthening policy coherence and timeliness, enhancing the comprehensiveness of policy functions, and enriching incentive measures for renewable energy technology innovation.

Keywords: renewable energy technology innovation, content analysis, policy evaluation, PMC index model

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Moses Banda Aron, Julia Higgins, Manuel Mulwafu, Kondwani Mpinga, Mwayi Chunga, Grace Momba, Enock Ndarama, Dickson Sumphi, Atupere Phiri, Fabien Munyaneza

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Background: Data is key to supporting health service delivery as stakeholders, including NGOs rely on it for effective service delivery, decision-making, and system strengthening. Several studies generated debate on data quality from national health management information systems (HMIS) in sub-Saharan Africa. This limits the utilization of data in resource-limited settings, which already struggle to meet standards set by the World Health Organization (WHO). We aimed to evaluate data quality improvement of Neno district HMIS over a 4-year period (2018 – 2021) following quarterly data reviews introduced in January 2020 by the district health management team and Partners In Health. Methods: Exploratory Mixed Research was used to examine report rates, followed by in-depth interviews using Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs). We used the WHO module desk review to assess the quality of HMIS data in the Neno district captured from 2018 to 2021. The metrics assessed included the completeness and timeliness of 34 reports. Completeness was measured as a percentage of non-missing reports. Timeliness was measured as the span between data inputs and expected outputs meeting needs. We computed T-Test and recorded P-values, summaries, and percentage changes using R and Excel 2016. We analyzed demographics for key informant interviews in Power BI. We developed themes from 7 FGDs and 11 KIIs using Dedoose software, from which we picked perceptions of healthcare workers, interventions implemented, and improvement suggestions. The study was reviewed and approved by Malawi National Health Science Research Committee (IRB: 22/02/2866). Results: Overall, the average reporting completeness rate was 83.4% (before) and 98.1% (after), while timeliness was 68.1% and 76.4 respectively. Completeness of reports increased over time: 2018, 78.8%; 2019, 88%; 2020, 96.3% and 2021, 99.9% (p< 0.004). The trend for timeliness has been declining except in 2021, where it improved: 2018, 68.4%; 2019, 68.3%; 2020, 67.1% and 2021, 81% (p< 0.279). Comparing 2021 reporting rates to the mean of three preceding years, both completeness increased from 88% to 99% (in 2021), while timeliness increased from 68% to 81%. Sixty-five percent of reports have maintained meeting a national standard of 90%+ in completeness while only 24% in timeliness. Thirty-two percent of reports met the national standard. Only 9% improved on both completeness and timeliness, and these are; cervical cancer, nutrition care support and treatment, and youth-friendly health services reports. 50% of reports did not improve to standard in timeliness, and only one did not in completeness. On the other hand, factors associated with improvement included improved communications and reminders using internal communication, data quality assessments, checks, and reviews. Decentralizing data entry at the facility level was suggested to improve timeliness. Conclusion: Findings suggest that data quality in HMIS for the district has improved following collaborative efforts. We recommend maintaining such initiatives to identify remaining quality gaps and that results be shared publicly to support increased use of data. These results can inform Ministry of Health and its partners on some interventions and advise initiatives for improving its quality.

Keywords: data quality, data utilization, HMIS, collaboration, completeness, timeliness, decision-making

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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Authors: Oktay Emir

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The objective of this study is to determine how entrepreneurs perceive the economic, social and physical impacts of tourism. The study was conducted in the city of Afyonkarahisar, Turkey, which is rich in thermal tourism resources and investments. A survey was used as the data collection method, and the questionnaire was applied to 472 entrepreneurs. A simple random sampling method was used to identify the sample. Independent sampling t-tests and ANOVA tests were used to analyse the data obtained. Additionally, some statistically significant differences (p<0.05) were found based on the participants’ demographic characteristics regarding their opinions about the social, economic and physical impacts of tourism activities.

Keywords: tourism, perception, entrepreneurship, entrepreneurs, structural equation modelling

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Authors: Jian-Heng Wu, Bor-Shen Lin

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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

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Authors: Jakob Krause

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Past Financial Crisis has shown that contemporary risk management models provide an unjustified sense of security and fail miserably in situations in which they are needed the most. In this paper, we start from the assumption that risk is a notion that changes over time and therefore past data points only have limited explanatory power for the current situation. Our objective is to derive the optimal amount of representative information by optimizing between the two adverse forces of estimator convergence, incentivizing us to use as much data as possible, and the aforementioned non-representativeness doing the opposite. In this endeavor, the cornerstone assumption of having access to identically distributed random variables is weakened and substituted by the assumption that the law of the data generating process changes over time. Hence, in this paper, we give a quantitative theory on how to perform statistical analysis in non-ergodic systems. As an application, we discuss the impact of a paragraph in the last iteration of proposals by the Basel Committee on Banking Regulation. We start from the premise that the severity of assumptions should correspond to the robustness of the system they describe. Hence, in the formal description of physical systems, the level of assumptions can be much higher. It follows that every concept that is carried over from the natural sciences to economics must be checked for its plausibility in the new surroundings. Most of the probability theory has been developed for the analysis of physical systems and is based on the independent and identically distributed (i.i.d.) assumption. In Economics both parts of the i.i.d. assumption are inappropriate. However, only dependence has, so far, been weakened to a sufficient degree. In this paper, an appropriate class of non-stationary processes is used, and their law is tied to a formal object measuring representativeness. Subsequently, that data set is identified that on average minimizes the estimation error stemming from both, insufficient and non-representative, data. Applications are far reaching in a variety of fields. In the paper itself, we apply the results in order to analyze a paragraph in the Basel 3 framework on banking regulation with severe implications on financial stability. Beyond the realm of finance, other potential applications include the reproducibility crisis in the social sciences (but not in the natural sciences) and modeling limited understanding and learning behavior in economics.

Keywords: banking regulation, non-ergodicity, risk management, semimartingale modeling

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Authors: Kalayanee Senasu

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This research investigates the influences of different factors on the happiness of Thai people, including both general factors and sustainable ones. Additionally, this study also monitors Thai people’s happiness via Thai Happiness Index developed in 2017. Besides reflecting happiness level of Thai people, this index also identifies related important issues. The data were collected by both secondary related data and primary survey data collected by interviewed questionnaires. The research data were from stratified multi-stage sampling in region, province, district, and enumeration area, and simple random sampling in each enumeration area. The research data cover 20 provinces, including Bangkok and 4-5 provinces in each region of the North, Northeastern, Central, and South. There were 4,960 usable respondents who were at least 15 years old. Statistical analyses included both descriptive and inferential statistics, including hierarchical regression and one-way ANOVA. The Alkire and Foster method was adopted to develop and calculate the Thai happiness index. The results reveal that the quality of household economy plays the most important role in predicting happiness. The results also indicate that quality of family, quality of health, and effectiveness of public administration in the provincial level have positive effects on happiness at about similar levels. For the socio-economic factors, the results reveal that age, education level, and household revenue have significant effects on happiness. For computing Thai happiness index (THaI), the result reveals the 2018 THaI value is 0.556. When people are divided into four groups depending upon their degree of happiness, it is found that a total of 21.1% of population are happy, with 6.0% called deeply happy and 15.1% called extensively happy. A total of 78.9% of population are not-yet-happy, with 31.8% called narrowly happy, and 47.1% called unhappy. A group of happy population reflects the happiness index THaI valued of 0.789, which is much higher than the THaI valued of 0.494 of the not-yet-happy population. Overall Thai people have higher happiness compared to 2017 when the happiness index was 0.506.

Keywords: happiness, quality of life, sustainability, Thai Happiness Index

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Authors: Shayan Rezvanigilkolaei, Shayesteh Vefaghnematollahi

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Electrical impedance tomography is a non-invasive medical imaging technique suitable for medical applications. This paper describes an electrical impedance tomography device with the ability to navigate a robotic arm to manipulate a target object. The design of the device includes various hardware and software sections to perform medical imaging and control the robotic arm. In its hardware section an image is formed by 16 electrodes which are located around a container. This image is used to navigate a 3DOF robotic arm to reach the exact location of the target object. The data set to form the impedance imaging is obtained by having repeated current injections and voltage measurements between all electrode pairs. After performing the necessary calculations to obtain the impedance, information is transmitted to the computer. This data is fed and then executed in MATLAB which is interfaced with EIDORS (Electrical Impedance Tomography Reconstruction Software) to reconstruct the image based on the acquired data. In the next step, the coordinates of the center of the target object are calculated by image processing toolbox of MATLAB (IPT). Finally, these coordinates are used to calculate the angles of each joint of the robotic arm. The robotic arm moves to the desired tissue with the user command.

Keywords: electrical impedance tomography, EIT, surgeon robot, image processing of electrical impedance tomography

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Authors: Afshin Azari, Farzad Peiravian, Nazila Yousefi

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Introduction: Community pharmacies have been always played an important role in public health. Therefore, having a decent service provided by these pharmacies is of paramount importance for the healthcare system. The issue of pharmacy ownership and its possible impact on the quality of services and amount of violations has been argued for many years, and there are different opinions around this debate. Since, so far, no scientific research has been performed to investigate this issue in Iran, this study aimed to examine the differences between these two types of pharmacies ownership in terms of violations and service quality. Method: This study investigates the impact of two different kinds of pharmacy ownership (pharmacists and non-pharmacist’s ownership) on the pharmacies’ amount of violations and services quality. Pharmacies’ amount of violations was examined using “pharmacy inspection reports” between September 2018 and September 2019, in their distinguishable categories: minor, major and critical violations. Then, service quality was examined using a questionnaire from the perspective of pharmacy customers. Results: Considering violations, there was no evidence to prove a significant relationship between critical violations and major violations with the type of pharmacy ownership. However, in minor violations, the average of violations was higher in pharmacies owned by pharmacists in comparison to their non-pharmacist owned counterparts. Regarding service quality, the results showed that there is no significant relationship between the quality of service and the type of pharmacy ownership. Discussion and Conclusion: In this study, no significant relationship was found between the amount of violations and the type of pharmacy ownership. This could indicate that the pharmacy ownership would not influence the rate of violations. Considering that more inspections have been carried out in non-pharmacist owned pharmacies, it can be concluded that these pharmacies are more under control, and in fact, this monitoring has reduced violations in these pharmacies. The quality of services in the two types of pharmacies were not significantly different from each other, and this shows that non-pharmacist-owned pharmacies also try to maintain the desired level of service in competition with their competitors.

Keywords: pharmacy ownership, quality of service, violation, community pharmacy

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Authors: Behrooz Khalilloo, Hamid Shahriari, Emad Roghanian

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Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices.

Keywords: multivariate process capability indices, robust M-estimator, outlier, multivariate quality control, statistical quality control

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Authors: Neliswa Dyosi

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Purpose - Using an integrated Technology-Organization-Environment (TOE) framework and the model of technology appropriation (MTA) as a theoretical lens, this interpretive qualitative study seeks to understand and explain the factors that influence the appropriation, non-appropriation, and disappropriation of bitcoin as a payment method by South African retailers. Design/methodology/approach –The study adopts the interpretivist philosophical paradigm. Multiple case studies will be adopted as a research strategy. For data collection, the study follows a qualitative approach. Qualitative data will be collected from the six retailers in various industries. Semi-structured interviews and documents will be used as the data collection techniques. Purposive and snowballing sampling techniques will be used to identify participants within the organizations. Data will be analyzed using thematic analysis. Originality/value - Using the deduction approach, the study seeks to provide a descriptive and explanatory contribution to theory. The study contributes to theory development by integrating the MTA and TOE frameworks as a means to understand technology adoption behaviors of organizations, in this case, retailers. This is also the first study that looks at an integrated approach of the Technology-Organization-Environment (TOE) framework and the MTA framework to understand the adoption and use of a payment method. South Africa is ranked amongst the top ten countries in the world on cryptocurrency adoption. There is, however, still a dearth of literature on the current state of adoption and usage of bitcoin as a payment method in South Africa. The study will contribute to the existing literature as bitcoin cryptocurrency is gaining popularity as an alternative payment method across the globe.

Keywords: cryptocurrency, bitcoin, payment methods, blockchain, appropriation, online retailers, TOE framework, disappropriation, non-appropriation

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Authors: Alex Fedoseyev

Abstract:

This study explores Generalized Hydrodynamic Equations (GHE) for the simulation of turbulent flows. The GHE was derived from the Generalized Boltzmann Equation (GBE) by Alexeev (1994). GBE was obtained by first principles from the chain of Bogolubov kinetic equations and considered particles of finite dimensions, Alexeev (1994). The GHE has new terms, temporal and spatial fluctuations compared to the Navier-Stokes equations (NSE). These new terms have a timescale multiplier τ, and the GHE becomes the NSE when τ is zero. The nondimensional τ is a product of the Reynolds number and the squared length scale ratio, τ=Re*(l/L)², where l is the apparent Kolmogorov length scale, and L is a hydrodynamic length scale. The turbulence phenomenon is not well understood and is not described by NSE. An additional one or two equations are required for the turbulence model, which may have to be tuned for specific problems. We show that, in the case of the GHE, no additional turbulence model is needed, and the turbulent velocity profile is obtained from the GHE. The 2D turbulent channel and circular pipe flows were investigated using a numerical solution of the GHE for several cases. The solutions are compared with the experimental data in the circular pipes and 2D channels by Nicuradse (1932, Prandtl Lab), Hussain and Reynolds (1975), Wei and Willmarth (1989), Van Doorne (2007), theory by Wosnik, Castillo and George (2000), and the relevant experiments on Superpipe setup at Princeton, data by Zagarola (1996) and Zagarola and Smits (1998), the Reynolds number is from Re=7200 to Re=960000. The numerical solution data compared well with the experimental data, as well as with the approximate analytical solution for turbulent flow in channel Fedoseyev (2023). The obtained results confirm that the Alexeev generalized hydrodynamic theory (GHE) is in good agreement with the experiments for turbulent flows. The proposed approach is limited to 2D and 3D axisymmetric channel geometries. Further work will extend this approach by including channels with square and rectangular cross-sections.

Keywords: comparison with experimental data. generalized hydrodynamic equations, numerical solution, turbulent boundary layer, turbulent flow in channel

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