Search results for: food composition data

Authors: Aissa Belmeguenai, Khaled Mansouri

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In this work, an efficient implementation of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written by MATLAB.7.5. At first two different original images are used for validate the proposed design. Then our developed program was used to transform the original images data into image digits file. Finally, we used our implemented program to encrypt and decrypt images data. Several tests are done for proving the design performance including visual tests and security analysis; we discuss the security analysis of the proposed image encryption scheme including some important ones like key sensitivity analysis, key space analysis, and statistical attacks.

Keywords: Achterbahn-128, stream cipher, image encryption, security analysis

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Authors: O. Abramova, L. Abukova, A. Goreva, G. Isaeva

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The present work was made for the purpose of evaluating the interstitial water’s role in the mobilization of metal elements of clay deposits and occurrences in sedimentary formation in the hydro-geological basins. The experiments were performed by using a special facility, which allows adjusting the pressure, temperature, and the frequency of the acoustic vibrations. The dates for study were samples of the oil shales (Baltic career, O₂kk) and clay rocks, mainly montmorillonite composition (Borehole SG-12000, the depth of selection 1000–3600 m, the Azov-Kuban trough, N₁). After interstitial water squeezing from the rock samples, decrease in the original content of the rock forming components including trace metals V, Cr, Co, Ni, Cu, Zn, Zr, Mo, Pb, W, Ti, and others was recorded. The experiments made it possible to evaluate the ore elements output and organic matters with the interstitial waters. Calculations have shown that, in standard conditions, from each ton of the oil shales, 5-6 kg of ore elements and 9-10 kg of organic matter can be escaped. A quantity of matter, migrating from clays in the process of solidification, is changed depending on the lithogenesis stage: more recent unrealized deposits lose more ore and organic materials than the clay rocks, selected from depth over 3000 m. Each ton of clays in the depth interval 1000-1500 m is able to generate 3-5 kg of the ore elements and 6-8 kg of the organic matters. The interstitial waters are a freight forwarder over transferring these matters in the reservoir beds. It was concluded that the interstitial waters which escaped from the study samples are solutions with abnormal high concentrations of the metals and organic matters. In the discharge zones of the sediment basins, such fluids can create paragenetic associations of the sedimentary-catagenetic ore and hydrocarbon mineral resources accumulations.

Keywords: hydrocarbons, ore genesis, paragenesis, pore water

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Authors: Shobha Kumari Yadav, Yubaraj Satyal, Ajaya Dixit

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In addressing groundwater depletion, it is important to develop evidence base so to be used in assessing the state of its degradation. Groundwater data is limited compared to meteorological data, which impedes the groundwater use and management plan. Monitoring of groundwater levels provides information base to assess the condition of aquifers, their responses to water extraction, land-use change, and climatic variability. It is important to maintain a network of spatially distributed, long-term monitoring wells to support groundwater management plan. Monitoring involving local community is a cost effective approach that generates real time data to effectively manage groundwater use. This paper presents the relationship between rainfall and spring flow, which are the main source of freshwater for drinking, household consumptions and agriculture in hills of Nepal. The supply and withdrawal of water from springs depends upon local hydrology and the meteorological characteristics- such as rainfall, evapotranspiration and interflow. The study offers evidence of the use of scientific method and community based initiative for managing groundwater and springshed. The approach presents a method to replicate similar initiative in other parts of the country for maintaining integrity of springs.

Keywords: citizen science, groundwater, water resource management, Nepal

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Authors: Jose Funes, Jeff Sauer, Laixiang Sun

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This research examines determinants of multifamily housing development and spillovers in the District of Columbia. A range of socioeconomic factors related to income distribution, productivity, and land use policies are thought to influence the development in contemporary U.S. multifamily housing markets. The analysis leverages data from the American Community Survey to construct panel datasets spanning from 2010 to 2019. Using spatial regression, we identify several socioeconomic measures and land use policies both positively and negatively associated with new housing supply. We contextualize housing estimates related to race in relation to uneven development in the contemporary D.C. housing supply.

Keywords: neighborhood effect, sorting, spatial spillovers, multifamily housing

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Authors: M. Soltani, K. Pakzad, A. Haghigh-Khiyabani, M. Alavi, R. Naderi, M. Castex

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Effect of probiotic Bactocell (Pediococcus acidilactici) as a supplementary diet was studied on post-larvae 12-15 of white leg shrimp (Litopenaeus vannamei) (150000 PL/0.5 h pond, average body weight=0.02 g) growth performance under farm condition for 102 days at water quality parameters consisting of temperature at 30.5-36οC, dissolved oxygen 4.1-6.6 mg/l, salinity 40-54 g/l, turbidity 35-110 cm, ammonia 0.1-0.8 mg/l and nitrite 0.1-0.9 mg/l. Also, the resistance level of the treated shrimps was assessed against a virulent strain of Vibrio paraheamolyticus as intramuscular injection route at 1.4 x 106 cells/shrimp. Significantly higher growth rate (11.3±1.54 g) and lower feed conversion ratio (1.1) were obtained in shrimps fed diets supplemented with Bactocell at 350 g/ tone feed compared to other treatments of 250 g Bactocell/ton feed (10.8±2 g, 1.3), 500 g Bactocell/ton feed (10.3±1.7 g, 1.3) and untreated control (10.1±2 g, 1.4). Also, thermal growth coefficient (0.057%) and protein efficiency ratio (2.13) were significantly improved in shrimps fed diets supplemented with Bactocell at 350 g/ton feed compare to other groups. Shrimps fed diet supplemented with Bactocell at 350 g/tone feed showed significantly higher protein content (72.56%) in their carcass composition than treatments of 250 g/ton feed (65.9%), 500 g/ton feed (67.5%) and control group (65.9%), while the carcass contents of moisture, lipid and ash in all shrimp groups were not significantly affected by different concentrations of Bactocell. No mortality occurred in the experimentally infected shrimps fed with Bactocell at 500 g/tone feed after 7 hours post-challenge with V. parahemolyticus. The mortality levels of 100%, 40%, 50% and 70% were obtained in shrimps fed with 0.0, 500 g/tone feed, 350 g/ton feed and 250 g/ton feed, respectively 14 hours post-infection. Also, the cumulative mortalities were achieved in 100%, 92% and 81% in shrimps few with Bactocell at 500 g/ton feed, 250 g/ton feed and 350 g/ton feed, respectively.

Keywords: litopenaeus vannamei, vibrio paraheamolyticus, pediococcus acidilactici, growth performance, bactocell

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Authors: Alexey Yu. Postnikov, Nikolay T. Kazakovskiy, Valery V. Mokrushin, Irina A. Tsareva, Andrey A. Potekhin, Valentina N. Golubeva, Yuliya V. Potekhina, Maxim V. Tsarev

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The development of tritium and deuterium targets for neutron tubes and generators is a part of the activities in All-Russia Research Institute of Experimental Physics (RFNC-VNIIEF). These items contain a metal substrate (for example, copper) with a titanium film with a few microns thickness deposited on it. Then these metal films are saturated with tritium, deuterium or their mixtures. The significant problem in neutron tubes and neutron generators is the characterization of substrate surface before a deposition of titanium film on it, and analysis of the deposited titanium film’s surface before hydrogenation and after a saturation of the film with hydrogen isotopes. The performance effectiveness of neutron tube and generator also depends on upon the quality parameters of the surface of the initial substrate, deposited metal film and hydrogenated target. The objective of our work is to study the target prototype samples, that have differ by various approaches to the preliminary chemical processing of a copper substrate, and to analyze the integrity of titanium film after its saturation with deuterium. The research results of copper substrate and the surface of deposited titanium film with the use of electron microscopy, X-ray spectral microanalysis and laser-spark methods of analyses are presented. The causes of surface defects appearance have been identified. The distribution of deuterium and some impurities (oxygen and nitrogen) along the surface and across the height of the hydrogenated film in the target has been established. This allows us to evaluate the composition homogeneity of the samples and consequently to estimate the quality of hydrogenated samples. As the result of this work the propositions on the advancement of production technology and characterization of target’s surface have been presented.

Keywords: tritium and deuterium targets, titanium film, laser-spark methods, electron microscopy

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Authors: Rahmayanti, Theresia Simatupang, Ronald H. Sianturi

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Corruption criminal act develops rapidly since in the transition era there is weakness in law. Consequently, there is an opportunity for a few people to do fraud and illegal acts and to misuse their positions and formal functions in order to make them rich, and the criminal acts are done systematically and sophisticatedly. Some people believe that legal provisions which specifically regulate the corruption criminal act; namely, Law No. 31/1999 in conjunction with Law No. 20/2001 on the Eradication of Corruption Criminal Act are not effective any more, especially in onus probandi (the burden of proof) on corruptors. The research was a descriptive analysis, a research method which is used to obtain description on a certain situation or condition by explaining the data, and the conclusion is drawn through some analyses. The research used judicial normative approach since it used secondary data as the main data by conducting library research. The system of the burden of proof, which follows the principles of reversal of the burden of proof stipulated in Article 12B, paragraph 1 a and b, Article 37A, and Article 38B of Law No. 20/2001 on the Amendment of Law No. 31/1999, is used only as supporting evidence when the principal case is proved. Meanwhile, how to maximize the implementation of the burden of proof on the perpetrators of corruption criminal act in which the public prosecutor brings a corruption case to Court, depends upon the nature of the case and the type of indictment. The system of burden of proof can be used to eradicate corruption in the Court if some policies and general principles of justice such as independency, impartiality, and legal certainty, are applied.

Keywords: burden of proof, perpetrator, corruption criminal act

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Background: Avian influenza, more commonly known as Bird flu, is a viral zoonotic respiratory disease stemming from various species of poultry, including pets and migratory birds. Researchers have purported that the accessibility of health information online, in addition to the low-cost data collection methods the internet provides, has revolutionized the methods in which epidemiological and disease surveillance data is utilized. This paper examines the feasibility of using internet data sources, such as Twitter and livestock forums, for the early detection of the avian flu outbreak, through the use of text mining algorithms and social network analysis. Methods: Social media mining was conducted on Twitter between the period of 01/01/2021 to 31/12/2021 via the Twitter API in Python. The results were filtered firstly by hashtags (#avianflu, #birdflu), word occurrences (avian flu, bird flu, H5N1), and then refined further by location to include only those results from within the UK. Analysis was conducted on this text in a time-series manner to determine keyword frequencies and topic modeling to uncover insights in the text prior to a confirmed outbreak. Further analysis was performed by examining clinical signs (e.g., swollen head, blue comb, dullness) within the time series prior to the confirmed avian flu outbreak by the Animal and Plant Health Agency (APHA). Results: The increased search results in Google and avian flu-related tweets showed a correlation in time with the confirmed cases. Topic modeling uncovered clusters of word occurrences relating to livestock biosecurity, disposal of dead birds, and prevention measures. Conclusions: Text mining social media data can prove to be useful in relation to analysing discussed topics for epidemiological surveillance purposes, especially given the lack of applied research in the veterinary domain. The small sample size of tweets for certain weekly time periods makes it difficult to provide statistically plausible results, in addition to a great amount of textual noise in the data.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, avian influenza, social media

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Authors: Nur Azreena Idris, Soh Kheang Loh, Harrison Lau Lik Nang, Yuen May Choo, Eminour Muzalina Mustafa, Vijaysri Vello, Cheng Yau Tan, Siew Moi Phang

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It is estimated that about 0.65-0.67 m3 of palm oil mill effluent (POME) is generated when one tonne of fresh fruit bunches is processed. Owning to the high content of nutrients in POME, it has high potential as a medium for microalgae growth. This study attempted determining the growth rate, biomass productivity and biochemical composition of microalgae (Chlorella sp.) grown in different POME concentrations i.e. 6.25%, 12.5%, 25% and 50% at outdoor conditions using a 200-mL capacity high rate algae pond (HRAP) and 2 closed photobioreactors (PBRs) i.e. annular and flat panel. The strain, Chlorella sp. grown on 12.5% of POME in flat panel PBR exhibited the highest specific growth rate of 0.32/day and biomass productivity (27.1 mg/L/day) followed by those in HRAP and annular PBR. It further showed that a good growth of Chlorella sp. in 12.5% of POME could sufficiently reduce the nutrients of POME such as phosphate (PO4), nitrate (NO3), nitrite (NO2) and chemical oxygen demand (COD). The extracted algal oil from POME culture showed that the saturated fatty acids decreased while polyunsaturated fatty acids increased compared to those cultured in standard culture medium (Bold’s Basal medium). The biochemical compositions of the algae grown in flat panel PBR were the highest with lipid, protein and carbohydrate productivity of 17.91 mg/L/day, 34.65 mg/L/day and 21.44 mg/L/day, respectively. The microalgae cultivation in diluted POME had not only shown potential as biodiesel feedstock based on the fatty acids profile but also the ability to reduce pollutants e.g. PO4, NO3, NO2 and COD in biological wastewater treatment.

Keywords: wastewater treatment, photobioreactors, biomass productivity, specific growth rate

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Authors: Rajkumar Ghosh

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Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.

Keywords: earthquake, out-of-sequence thrust, disaster, human life

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Bassem Nassar, Wessam Hussein, Medhat Mokhtar

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The crucial concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems in order to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important in order to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the aforementioned problem coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions and the results shows that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: space telemetry monitoring, multivariate analysis, PCA algorithm, space operations

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Authors: Freddy Munzhelele

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Setting: the empirical research has shown that the life cycle theory has an impact on the firms’ financing decisions, particularly the dividend pay-outs. Accordingly, the life cycle theory posits that as a firm matures, it gets to a level and capacity where it distributes more cash as dividends. On the other hand, the young firms prioritise investment opportunities sets and their financing; thus, they pay little or no dividends. The research on firms’ financing decisions also demonstrated, among others, the adoption of trade-off and pecking order theories on the dynamics of firms capital structure. The trade-off theory talks to firms holding a favourable position regarding debt structures particularly as to the cost and benefits thereof; and pecking order is concerned with firms preferring a hierarchical order as to choosing financing sources. The case of life cycle hypothesis explaining the financial managers’ decisions as regards the firms’ capital structure dynamics appears to be an interesting link, yet this link has been neglected in corporate finance research. If this link is to be explored as an empirical research, the financial decision-making alternatives will be enhanced immensely, since no conclusive evidence has been found yet as to the dynamics of capital structure. Aim: the aim of this study is to examine the impact of life cycle theory on the capital structure dynamics trade-off and pecking order theories of firms listed in retail, industrial and mining sectors of the JSE. These sectors are among the key contributors to the GDP in the South African economy. Design and methodology: following the postpositivist research paradigm, the study is quantitative in nature and utilises secondary data obtainable from the financial statements of sampled firm for the period 2010 – 2022. The firms’ financial statements will be extracted from the IRESS database. Since the data will be in panel form, a combination of the static and dynamic panel data estimators will used to analyse data. The overall data analyses will be done using STATA program. Value add: this study directly investigates the link between the life cycle theory and the dynamics of capital structure decisions, particularly the trade-off and pecking order theories.

Keywords: life cycle theory, trade-off theory, pecking order theory, capital structure, JSE listed firms

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Authors: David Edgar

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To understand how the brain’s subconscious and conscious functions, we must conquer the physics of Unity, which leads to duality’s algorithm. Where the subconscious (bottom-up) and conscious (top-down) processes function together to produce and consume intelligence, we use terms like ‘time is relative,’ but we really do understand the meaning. In the brain, there are different processes and, therefore, different observers. These different processes experience time at different rates. A sensory system such as the eyes cycles measurement around 33 milliseconds, the conscious process of the frontal lobe cycles at 300 milliseconds, and the subconscious process of the thalamus cycle at 5 milliseconds. Three different observers experience time differently. To bridge observers, the thalamus, which is the fastest of the processes, maintains a synchronous state and entangles the different components of the brain’s physical process. The entanglements form a synchronous cohesion between the brain components allowing them to share the same state and execute in the same measurement cycle. The thalamus uses the shared state to control the firing sequence of the brain’s linear subconscious process. Sharing state also allows the brain to cheat on the amount of sensory data that must be exchanged between components. Only unpredictable motion is transferred through the synchronous state because predictable motion already exists in the shared framework. The brain’s synchronous subconscious process is entirely based on energy conservation, where prediction regulates energy usage. So, the eyes every 33 milliseconds dump their sensory data into the thalamus every day. The thalamus is going to perform a motion measurement to identify the unpredictable motion in the sensory data. Here is the trick. The thalamus conducts its measurement based on the original observation time of the sensory system (33 ms), not its own process time (5 ms). This creates a data payload of synchronous motion that preserves the original sensory observation. Basically, a frozen moment in time (Flat 4D). The single moment in time can then be processed through the single state maintained by the synchronous process. Other processes, such as consciousness (300 ms), can interface with the synchronous state to generate awareness of that moment. Now, synchronous data traveling through a separate faster synchronous process creates a theoretical time tunnel where observation time is tunneled through the synchronous process and is reproduced on the other side in the original time-relativity. The synchronous process eliminates time dilation by simply removing itself from the equation so that its own process time does not alter the experience. To the original observer, the measurement appears to be instantaneous, but in the thalamus, a linear subconscious process generating sensory perception and thought production is being executed. It is all just occurring in the time available because other observation times are slower than thalamic measurement time. For life to exist in the physical universe requires a linear measurement process, it just hides by operating at a faster time relativity. What’s interesting is time dilation is not the problem; it’s the solution. Einstein said there was no universal time.

Keywords: neural synchronization, natural intelligence, 99.95% IoT data transmission savings, artificial subconscious intelligence (ASI)

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Authors: Olusola Abiodun Arinde

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This research work was prompted by the very important role e-commerce plays in every organization, be it private or public. The underlying objective of this study is to have a critical appraisal of the extent to which e-commerce impacts on organizational effectiveness. This research was carried out using Zenith Bank Plc as a case study. Relevant data were collected through structured questionnaire, oral interview, journals, newspapers, and textbooks. The data collected were analyzed and hypotheses were tested. Based on the result of the hypotheses, it was observed that e-commerce is significant to every organization. Through e-commerce, fast services delivery would be guaranteed to customers, this would lead to higher productivity and profit for organizations. E-commerce should be managed in such a way that it does not alienate customers; it should also prevent enormous risks that are associated with e-commerce.

Keywords: e-commerce, fast service, productivity, profit

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Authors: Garry Gorman, Nigel McKelvey, James Connolly

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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

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Authors: R. Dubey, M. Sarwan, S. Singh

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We have investigated the phase transition pressure and associated volume collapse in Sm1– X EuX S alloy (0≤x≤1) which shows transition from discontinuous to continuous as x is reduced. The calculated results from present approach are in good agreement with experimental data available for the end point members (x=0 and x=1). The results for the alloy counter parts are also in fair agreement with experimental data generated from the vegard’s law. An improved interaction potential model has been developed which includes coulomb, three body interaction, polarizability effect and overlap repulsive interaction operative up to second neighbor ions. It is found that the inclusion of polarizability effect has improved our results.

Keywords: elastic constants, high pressure, phase transition, rare earth compound

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Authors: Ontima Yamchuti, Waruntorn Kanitpanyacharoen, Chakkaphan Sutthirat, Wantana Klysuban, Penphitcha Amonpattarakit

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Natural corundum occurs in various colors due to impurities or trace elements in its structure. Sapphire and ruby are essentially the same mineral, corundum, but valued differently due to their red and blue varieties, respectively. Color is one of the critical factors used to determine the value of natural and synthetic corundum. Despite the abundance of research on impurities in natural corundum, little is known about trace elements in synthetic corundum. This project thus aims to quantify trace elements and identify their oxidation states in synthetic corundum. A total of 15 corundum samples in red, blue, and yellow, synthesized by melt growth process, were first investigated by X-ray diffraction (XRD) analysis to determine the composition. Electron probe micro-analyzer (EPMA) was used to identify the types of trace elements. Results confirm that all synthetic corundums contain crystalline Al₂O₃ and a wide variety type of trace element, particularly Cr, Fe, and Ti. In red, yellow, and blue corundums respectively. To further determine their oxidation states, synchrotron X-ray absorption near edge structure spectrometry (XANES) was used to observe absorbing energy of each element. XANES results show that red synthetic corundum has Cr³⁺ as a major trace element (62%). The pre-edge absorption energy of Cr³⁺ is at 6001 eV. In addition, Fe²⁺ and Fe³⁺ are dominant oxidation states of yellow synthetic corundum while Ti³⁺and Ti⁴⁺ are dominant oxidation states of blue synthetic corundum. the average absorption energy of Fe and Ti is 4980 eV and 7113 eV respectively. The presence of Fe²⁺, Fe³⁺, Cr³⁺, Ti³⁺, and Ti⁴⁺ in synthetic corundums in this study is governed by comparison absorption energy edge with standard transition. The results of oxidation states in this study conform with natural corundum. However yellow synthetic corundums show difference oxidation state of trace element compared with synthetic in electron spin resonance spectrometer method which found that Ni³⁺ is a dominant oxidation state.

Keywords: corundum, trace element, oxidation state, XANES technique

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Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

Procedia PDF Downloads 35

Authors: W. M. Buba, J. G. Nangbes, J. P. Butven

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This research was undertaken to evolve community based awareness on the arsenic contamination from agricultural practices in Communities of Bokkos local government area. Contaminated farmland soil samples were collected from the surface for tailings and at various depths (50, 100, 150 cm intervals) in eight holes drilled in each farm at different locations using hand auger. A total of sixty- four (64) soil samples were collected from eight (8) different communities. A standard titrimetric method was applied for the determination of arsenic. It was found that the average concentration of arsenic in the surface soil (0-150cm) for the entire study areas was 0.0525mg/kg with range 0.0425 -0.0601mg/kg which is well above the recommended the soil to plant concentration guideline range of 2.3 – 4.3 x10-4 mg/kg value. This indicates that the arsenic concentration in the study areas does pose health risk for agricultural practices via potential bioaccumulation in plant food crops. However, some risks measures could follow the arsenic occurrence through direct exposure such as those resulting from the inhalation, oral or dermal intake of arsenic during agricultural practices and in the course of stay on the contaminated soil.

Keywords: agrochemicals, arsenic, bokkos, contamination, soil

Procedia PDF Downloads 333

Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Abolfazl Kamkar

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Vegetable oils and fats are recognized as important components of our diet. They provide essential fatty acids, which are precursors of important hormones and control many physiological factors such as blood pressure, cholesterol level, and the reproductive system.Vegetable oils with higher contents of unsaturated fatty acids, especially polyunsaturated fatty acids (PUFAs) are more susceptible to oxidation.Protective effects of Sature jahortensis(SE) extracts in stabilizing soybean oil at different concentrations (200 and 400 ppm) were tested. Results showed that plant extracts could significantly (P< 0.05) lower the peroxide value and thiobarbituric acid value of oil during storage at 60 oC. The IC50 values for methanol and ethanol extracts were 31.5 ± 0.7 and 37.00 ± 0 µg/ml, respectively. In the β- carotene/linoleic acid system, methanol and ethanol extracts exhibited 87.5 ± 1.41% and 74.0 ±2.25 % inhibition against linoleic acid oxidation. The total phenolic and flavonoid contents of methanol and ethanol extracts were (101.58 ± 0. 26m g/ g) and (96.00 ± 0.027 mg/ g), (44.91 ± 0.14 m g/ g) and (14.30 ± 0.12 mg/ g) expressed in Gallic acid and Quercetin equivalents, respectively.These findings suggest that Satureja extracts may have potential application as natural antioxidants in the edible oil and food industry.

Keywords: satureja hortensis, antioxidant activity, oxidative stability, vegetable oil, extract

Procedia PDF Downloads 355

Authors: Nurlaili E. P., Astuti M., Marsono Y., Naruki S.

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Iron is an essential nutrient with limited bioavailability. Nutritional anemia caused mainly by iron deficiency is the most recognized nutritional problem in both countries as well as affluent societies. Rice (Oryza sativa L.) has become the most important cereal crop for the improvement of human health due to the starch, protein, oil, and the majority of micronutrients, particularly in Asian countries. In this study, the iron availability and profile lipid were evaluated for the extracts from Cibeusi varieties (black rices) of ancient rice brans. Results: The quality of K, B, R, E diets groups shows the same effect on the growth of rats. This indicate that groups is as efficiently utilized by the body as E diets. Hematocrit and MCHC levels of rats fed K, B, R and E diets were not significantly (P< 0.05). MCV and MCH levels of rats K, B, R were significantly (P< 0.05) with E groups but rats K, B, R were not significantly (P< 0.05). The iron content in the serum of rats fed with K, B, R and E diets were not significantly (P< 0.05). The highest level of iron in the serum was founded in the B group. The iron content in the liver of rats fed with K, B, R and E diets were not significantly (P< 0.05). The highest level of iron in the liver was founded in the R group. HDL cholesterol levels were significantly (P< 0.05) between rats of fed B, E with K, R, but K and R were not significantly (P< 0.05). LDL cholesterol levels of rats fed K and E significantly (P< 0.05) with B and R. Conclusions: the bran of pigmented rice varieties has, with some exceptions, greater antioxidant and free-radical scavenging activities. The results also show that pigmented rice extracts acted as pro-oxidants in the lipid peroxidation assay, possibly by mechanisms described for the pro-oxidant activities of tocopherol and ascorbic. Pigmented rice bran extracts more effectively increases iron stores and reduces the prevalence of iron deficiency. And reduces cholesterol, TG and LDL cholesterol and increses HDL cholesterol.

Keywords: anemia, black rice bran extract, iron, profile lipid

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Authors: Zahid Khalil, Saad Ul Haque, Asif Khan

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Decision making about identifying suitable sites for any project by considering different parameters is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30-meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pairwise comparison method, also known as Analytical Hierarchy Process (AHP) is taken into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision-making about suitable sites analysis for small dams using geospatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

Keywords: Remote sensing, GIS, AHP, RWH

Procedia PDF Downloads 372

Authors: Hong-Yi Lin, Feng-Tyan Lin

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In a Bike-sharing system (BSS), users can easily rent bikes from any station in the city for mid-range or short-range trips. BSS can also be integrated with other types of transport system, especially Green Transportation system, such as rail transport, bus etc. Since BSS records time and place of each pickup and return, the operational data can reflect more authentic and dynamic state of user behaviors. Furthermore, land uses around docking stations are highly associated with origins and destinations for the BSS users. As urban researchers, what concerns us more is to take BSS into consideration during the urban planning process and enhance the quality of urban life. This research focuses on the simulation of travel behavior of BSS users in Kaohsiung. First, rules of users’ behavior were derived by analyzing operational data and land use patterns nearby docking stations. Then, integrating with Monte Carlo method, these rules were embedded into a travel behavior simulation model, which was implemented by NetLogo, an agent-based modeling tool. The simulation model allows us to foresee the rent-return behaviour of BSS in order to choose potential locations of the docking stations. Also, it can provide insights and recommendations about planning and policies for the future BSS.

Keywords: agent-based model, bike-sharing system, BSS operational data, simulation

Procedia PDF Downloads 315

Authors: Abdullah Al Mamoon, Ataur Rahman

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Due to climate change, future rainfall will change at many locations on earth; however, the spatial and temporal patterns of this change are not easy to predict. One approach of predicting such future changes is to examine the trends in the historical rainfall data at a given region and use the identified trends to make future prediction. For this, a statistical trend test is commonly applied to the historical data. This paper examines the trends of daily extreme rainfall events from 30 rain gauges located in the State of Qatar. Rainfall data covering from 1962 to 2011 were used in the analysis. A combination of four non-parametric and parametric tests was applied to identify trends at 10%, 5%, and 1% significance levels. These tests are Mann-Kendall (MK), Spearman’s Rho (SR), Linear Regression (LR) and CUSUM tests. These tests showed both positive and negative trends throughout the country. Only eight stations showed positive (upward) trend, which were however not statistically significant. In contrast, significant negative (downward) trends were found at the 5% and 10% levels of significance in six stations. The MK, SR and LR tests exhibited very similar results. This finding has important implications in the derivation/upgrade of design rainfall for Qatar, which will affect design and operation of future urban drainage infrastructure in Qatar.

Keywords: trends, extreme rainfall, daily rainfall, Mann-Kendall test, climate change, Qatar

Procedia PDF Downloads 546

Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

Procedia PDF Downloads 57

Authors: Shan-Ken Chine

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This research aims to a one-year course run of String Music Appreciation, an international online course launched on the British open education platform. It explains how to present music teaching videos with three main features. They are music lesson explanations, instrumental playing demonstrations, and live music performances. The plan of this course is with four major themes and a total of 97 steps. In addition, the paper also uses the testing data provided by the education platform to analyze the performance of learners and to understand the operation of the course. It contains three test data in the statistics dashboard. They are course-run measures, total statistics, and statistics by week. The paper ends with a review of the course's star rating in this one-year run. The result of this course run will be adjusted when it starts again in the future.

Keywords: music online courses, MOOCs, ubiquitous learning, string music, general music education

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Authors: Suliman A. I. Ali, Mory Mandiana Diakite, Saqib Ali, Man-Qun Wang

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Lesser grain borer, Rhyzopertha dominica, is a causing damages of stored grains all tropical and subtropical area in the global, according to the information of antenna cDNA library of R. dominica, three olfactory protein genes, including R.domica CSPs2, R.domica PBPs1, R.domica PBPs2 genes (GenBank accessions are KJ186798.1, KJ186830.1, KJ186831.1 separately.), were successfully cloned. For sequencing and phylogenetic analysis, R.domica CSPs1 and R.domica CSPs2 belonged to Minus-C CSPs showed that have 4 conserved cysteine residues, while R.domica PBPs1 and R.domica PBPs2 showed conserved amino acids in all PBPs six conserved cysteine residues. The results of transcription expression level of PBPs1 and PBPs2 of R. dominica showed that the expression level of R.domnica PBP2 is much higher than that of R.domnica PBP1. The variation transcription level at the different developmental time suggested the PBP1, and PBP2 had their particular job in searching food sources, mates and oviposition sites.

Keywords: Rhyzopertha dominica, CSPs, PBPs, molecular cloning

Procedia PDF Downloads 134