Search results for: food composition data

Authors: Sahil Imtiyaz

Abstract:

One of the biggest challenges has emerged from the ever-expanding, dynamic, and instantaneously changing space-Big Data; and to find a data point and inherit wisdom to this space is a hard task. In this paper, we reduce the space of big data in Hamiltonian formalism that is in concordance with Ising Model. For this formulation, we simulate the system using dye laser in FORTRAN and analyse the dynamics of the data point in energy well of rhodium atom. After mapping the photon intensity and pulse width with energy and potential we concluded that as we increase the energy there is also increase in probability of tunnelling up to some point and then it starts decreasing and then shows a randomizing behaviour. It is due to decoherence with the environment and hence there is a loss of ‘quantumness’. This interprets the efficiency parameter and the extent of quantum evolution. The results are strongly encouraging in favour of the use of ‘Topological Property’ as a source of information instead of the qubit.

Keywords: big data, optimization, quantum evolution, hamiltonian, dye laser, fermionic computations

Procedia PDF Downloads 182

Authors: Muhammad Muhammad Suleiman

Abstract:

Cloud Computing is a versatile concept that refers to a service that allows users to outsource their data without having to worry about local storage issues. However, the most pressing issues to be addressed are maintaining a secure and reliable data repository rather than relying on untrustworthy service providers. In this study, we look at how stenography approaches and collaboration with Digital Watermarking can greatly improve the system's effectiveness and data security when used for Cloud Computing. The main requirement of such frameworks, where data is transferred or exchanged between servers and users, is safe data management in cloud environments. Steganography is the cloud is among the most effective methods for safe communication. Steganography is a method of writing coded messages in such a way that only the sender and recipient can safely interpret and display the information hidden in the communication channel. This study presents a new text steganography method for hiding a loaded hidden English text file in a cover English text file to ensure data protection in cloud computing. Data protection, data hiding capability, and time were all improved using the proposed technique.

Keywords: cloud computing, steganography, information hiding, cloud storage, security

Procedia PDF Downloads 172

Authors: Farhad Asadi, Mohammad Javad Mollakazemi

Abstract:

In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

Procedia PDF Downloads 412

Authors: İbrahi̇m Kara, Seher Arslankaya

Abstract:

Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

Procedia PDF Downloads 343

Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

Abstract:

Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

Procedia PDF Downloads 105

Authors: John Gaber

Abstract:

Planners regularly use citizen input as empirical data to help them better understand community issues they know very little about. This type of community data is based on the lived experiences of local residents and is known as "emic" data. What is becoming more common practice for planners is their use of data from local experts and stakeholders (known as "etic" data or the outsider perspective) to help them fill in the gaps in their analysis of applied planning research projects. Utilizing international Health Impact Assessment (HIA) data, I look at who planners invite to their citizen input investigations. Research presented in this paper shows that planners access a wide range of emic and etic community perspectives in their search for the “community’s view.” The paper concludes with how planners can chart out a new empirical path in their execution of emic/etic citizen participation strategies in their applied planning research projects.

Keywords: citizen participation, emic data, etic data, Health Impact Assessment (HIA)

Procedia PDF Downloads 473

Authors: Vincent Mokoka, Kai Behn, Edwin Mudongo, Jan Ruppert, Kingsley Ayisi, Anja Linstädter

Abstract:

Severe drought may trigger a transition of vegetation composition in dryland grasslands, with productive perennial grasses often being replaced by annual grasses. Grazing pressure is thought to exacerbate drought effects, but little is known on the joint effects of grazing and drought on the functional and taxonomic composition of the herbaceous vegetation in African savannas. This study thus aimed to elucidate which herbaceous species and plant functional types (PFTs) are most resistant to prolonged drought and grazing and whether resting plays a role in this context. Thus, we performed a six-year field experiment in South Africa’s Limpopo province, combining drought and grazing treatments. Aboveground herbaceous biomass was harvested annually and separated into species. We grouped species into five PFTs, i.e. very broad-leaved perennial grasses, broad-leaved perennial grasses, narrow-leaved perennial grasses, annual grasses, and forbs. For all species, we also recorded three-leaf traits (leaf area - LA, specific leaf area – SLA, and leaf dry matter content – LDM) to describe their resource acquisition strategies. We used generalized linear models to test for treatment effects and their interaction. Association indices were used to detect the relationship between species and treatments. We found that there were no absolute winner species or PFTs, as the six-year severe drought had a pronounced negative impact on the biomass production of all species and PFTs. However, we detected relative winners with increases in relative abundances, mainly forbs and less palatable narrow-leafed grasses with comparatively low LA and high LDMC, such as Aristida stipidata Hack. These species and PFTs also tended to be favored by grazing. Although few species profited from resting, for most species, the combination of drought and resting proved to be particularly unfavorable. Winners and losers can indicate ecological transition and may be used to guide management decisions.

Keywords: aboveground net primary production, drought, functional diversity, winner and loser species

Procedia PDF Downloads 153

Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

Abstract:

As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

Procedia PDF Downloads 167

Authors: S. Ravindran, Y.Liu, I. Gratchev, D.Jeng

Abstract:

Rainfall-induced shallow landslides are more common in the northern New South Wales (NSW), Australia. From 2009 to 2017, around 105 rainfall-induced landslides occurred along the road corridors and caused temporary road closures in the northern NSW. Rainfall causing shallow landslides has different distributions of rainfall varying from uniform, normal, decreasing to increasing rainfall intensity. The duration of rainfall varied from one day to 18 days according to historical data. The objective of this research is to analyse slope instability of some of the sites in the northern NSW by varying cumulative rainfall using SLOPE/W and SEEP/W and compare with field data of rainfall causing shallow landslides. The rainfall data and topographical data from public authorities and soil data obtained from laboratory tests will be used for this modelling. There is a likelihood of shallow landslides if the cumulative rainfall is between 100 mm to 400 mm in accordance with field data.

Keywords: landslides, modelling, rainfall, suction

Procedia PDF Downloads 150

Authors: Nicholas Milburn, Yu Liang, Dalei Wu

Abstract:

Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence

Procedia PDF Downloads 130

Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

Procedia PDF Downloads 133

Authors: Vasile Caunii, Andreea D. Serban, Mihaela Ivancia

Abstract:

The paper presents a new approach in terms of the circular economy of technologies for feeding and aeration of accumulations and water basins for fish farming and aquaculture. Because fish is and will be one of the main foods on the planet, the use of bio-eco-technologies is a priority for all producers. The technologies proposed in the paper want to reduce by a substantial percentage the costs of operation of ponds and water accumulation, using non-polluting technologies with minimal impact on the environment. The paper proposes two innovative, intelligent systems, fully automated that use a common platform, completely eco-friendly. One system is intended to aerate the water of the fish pond, and the second is intended to feed the fish by dispersing an optimal amount of fodder, depending on population size, age and habits. Both systems use a floating platform, regenerative energy sources, are equipped with intelligent and innovative systems, and in addition to fully automated operation, significantly reduce the costs of aerating water accumulations (natural or artificial) and feeding fish. The intelligent system used for feeding, in addition, to reduce operating costs, optimizes the amount of food, thus preventing water pollution and the development of bacteria, microorganisms. The advantages of the systems are: increasing the yield of fish production, these are green installations, with zero pollutant emissions, can be arranged anywhere on the water surface, depending on the user's needs, can operate autonomously or remotely controlled, if there is a component failure, the system provides the operator with accurate data on the issue, significantly reducing maintenance costs, transmit data about the water physical and chemical parameters.

Keywords: bio-eco-technologies, economy, environment, fish

Procedia PDF Downloads 132

Authors: Matthew Montebello

Abstract:

Student engagement within a virtual learning environment generates masses of data points that can significantly contribute to the learning analytics that lead to decision support. Ideally, similar data is collected during student interaction with a physical learning space, and as a consequence, data is present at a large scale, even in relatively small classes. In this paper, we report of such an occurrence during classes held in a HiFlex modality as we investigate the advantages of adopting such a methodology. We plan to take full advantage of the learner-generated data in an attempt to further enhance the effectiveness of the adopted learning environment. This could shed crucial light on operating modalities that higher education institutions around the world will switch to in a post-COVID era.

Keywords: HiFlex, big data in higher education, learning analytics, virtual learning environment

Procedia PDF Downloads 183

Authors: Shahzad Hassan, Kamran Saeed

Abstract:

People are always in search of Wi-Fi hotspots because Internet is a major demand nowadays. But like all other technologies, there is still room for improvement in the Wi-Fi technology with regards to the speed and quality of connectivity. In order to address these aspects, Harald Haas, a professor at the University of Edinburgh, proposed what we know as the Li-Fi (Light Fidelity). Li-Fi is a new technology in the field of wireless communication to provide connectivity within a network environment. It is a two-way mode of wireless communication using light. Basically, the data is transmitted through Light Emitting Diodes which can vary the intensity of light very fast, even faster than the blink of an eye. From the research and experiments conducted so far, it can be said that Li-Fi can increase the speed and reliability of the transfer of data. This paper pays particular attention on the assessment of the performance of this technology. In other words, it is a 5G technology which uses LED as the medium of data transfer. For coverage within the buildings, Wi-Fi is good but Li-Fi can be considered favorable in situations where large amounts of data are to be transferred in areas with electromagnetic interferences. It brings a lot of data related qualities such as efficiency, security as well as large throughputs to the table of wireless communication. All in all, it can be said that Li-Fi is going to be a future phenomenon where the presence of light will mean access to the Internet as well as speedy data transfer.

Keywords: communication, LED, Li-Fi, Wi-Fi

Procedia PDF Downloads 328

Authors: Madhu Sarwan, Ritu Dubey, Sadhna Singh

Abstract:

We have investigated the structural phase transition from Zinc-Blende (ZB) to Rock-Salt (RS) structure of TlxGa1-xAs by using Interaction Potential Model (IPM). The IPM consists of Coulomb interaction, Three-Body Interaction (TBI), Van Der Wall (vdW) interaction and overlap repulsive short range interaction. The structural phase transition has been computed by using the vegard’s law. The volume collapse is also computed for this alloy. We have also investigated the second order elastic constants with composition for the alloy TlxGa1-xAs.

Keywords: III-V alloy, elastic moduli, phase transition, semiconductors

Procedia PDF Downloads 527

Authors: Renata Kurpiewska-Korbut

Abstract:

Making an assumption that the use and sharing of data generated in humanitarian action constitute a core function of humanitarian organizations, the paper analyzes the position of the largest Polish humanitarian non-governmental organizations in the humanitarian data ecosystem in Ukraine and their approach to non-personal and personal data management since February of 2022. Both expert interviews and document analysis of non-profit organizations providing a direct response in the Ukrainian crisis context, i.e., the Polish Humanitarian Action, Caritas, Polish Medical Mission, Polish Red Cross, and the Polish Center for International Aid and the applicability of theoretical perspective of contingency theory – with its central point that the context or specific set of conditions determining the way of behavior and the choice of methods of action – help to examine the significance of data complexity and adaptive approach to data management by relief organizations in the humanitarian supply chain network. The purpose of this study is to determine how the existence of well-established and accurate internal procedures and good practices of using and sharing data (including safeguards for sensitive data) by the surveyed organizations with comparable human and technological capabilities are implemented and adjusted to Ukrainian humanitarian settings and data infrastructure. The study also poses a fundamental question of whether this crisis experience will have a determining effect on their future performance. The obtained finding indicate that Polish humanitarian organizations in Ukraine, which have their own unique code of conduct and effective managerial data practices determined by contingencies, have limited influence on improving the situational awareness of other assistance providers in the data ecosystem despite their attempts to undertake interagency work in the area of data sharing.

Keywords: humanitarian data ecosystem, humanitarian data management, polish NGOs, Ukraine

Procedia PDF Downloads 78

Authors: Kotomi Yamashita, Hiromi Kawasaki, Satoko Yamasaki, Susumu Fukita, Risako Sakai

Abstract:

Lifestyle-related diseases develop from the long-term accumulation of health consequences from a poor lifestyle. Thus, schoolchildren, who have not accumulated long-term lifestyle habits, are believed to be at a lower risk for lifestyle-related diseases. However, schoolchildren rarely receive blood tests unless they are under treatment for a serious disease; without such data on their blood, the impacts of their young lifestyle could not be known. Blood data from physical measurements can help in the implementation of more effective health education. Therefore, we examined the correlation between body mass index (BMI) and blood sugar/serum lipid (BS/SL) levels. From 2014 to 2016, we measured the blood data of fourth-grade students living in a city in Japan. The present study reported on the results of 281 fourth-grade boys only (80.3% of total). We analyzed their BS/SL levels by comparing the blood data against the criteria of the National Center for Child Health and Development in Japan. Next, we examined the correlation between BMI and BS/SL levels. IBM SPSS Statistics for Windows, Version 25 was used for analysis. A total of 69 boys (24.6%) were within the normal range for BMI (18.5–24), whereas 193 (71.5%) and 8 boys (2.8%) had lower and higher BMI, respectively. Regarding BS levels, 280 boys were within the normal range (70–90 mg/dl); 1 boy reported a higher value. All the boys were within the normal range for glycated Hemoglobin (HbA1c) (4.6–6.2%). Regarding SL levels, 271 boys were within the normal range (125–230 mg/dl) for total cholesterol (TC), whereas 5 boys (1.8%) had lower and 5 boys (1.8%) had higher levels. A total of 243 boys (92.7%) were within the normal range (36-138mg/dL) for triglycerides (TG), whereas 19 boys (7.3%) had lower and 19 boys (7.3%) had higher levels. Regarding high-density lipoprotein cholesterol (HDL-C), 276 boys (98.2%) were within the normal range (40-mg/dl), whereas 5 boys (1.8%) reported lower values. All but one boy (280, 99.6%) were within the normal range (-170 mg/dl) for low-density lipoprotein cholesterol (LDL-C); the exception (0.4%) had a higher level. BMI and BS didn’t show a correlation. BMI and HbA1c were moderately positively correlated (r = 0.139, ｐ＝0.019). We also observed moderate positive correlations between BMI and TG (r = 0.328, p < 0.01), TC (r=0.239, p< 0.01), LDL-C (r = 0.324, p < 0.01), respectively. BMI and HDL-C were low correlated (r = -0.185, p = 0.002). Most of the boys were within the normal range for BS/SL levels. However, some boys exceeded the normal TG range. Fourth graders with a high TG may develop a lifestyle-related disease in the future. Given its relation to TG, food habits should be improved in this group. Our findings suggested a positive correlation between BMI and BS/SL levels. Fourth-grade schoolboys with a high BMI may be at high risk for developing lifestyle-related diseases. Lifestyle improvement may be recommended to lower the BS/SL levels in this group.

Keywords: blood sugar level, lifestyle-related diseases, school students, serum lipid level

Procedia PDF Downloads 128

Authors: A. Guemache, M. Omari

Abstract:

Oxides with formula Ca1-xSrx MnO3(0≤x≤0.2) were synthesized using co precipitation method. The identification of the obtained phase was carried out using infrared spectroscopy and x-ray diffraction. Thermogravimetric and differential analysis was permitted to characterize different transformations of precursors which take place during one heating cycle. The study of electrochemical behavior was carried out by cyclic voltammetry and impedance spectroscopy. The obtained results show that apparent catalytic activity improved when increasing the concentration of strontium. Anodic current densities varies from 1.3 to 5.9 mA/cm2 at the rate scan of 20 mV.s-1 and a potential 0.8 V for oxides with composition x=0 to 0.2.

Keywords: oxide, co-precipitation, thermal analysis, electrochemical properties

Procedia PDF Downloads 343

Authors: Daniel C. Bonzo

Abstract:

Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

Procedia PDF Downloads 123

Authors: P. Rahnemoon, M. Sarabi Jamab, M. Javanmard Dakheli, A. Bostan

Abstract:

In recent years, tendency to use of natural antimicrobial agents in food industry has increased. Pomegranate peels containing phenolic compounds and anti-microbial agents, are counted as valuable source for extraction of these compounds. In this study, the extraction of pomegranate peel extract was carried out at different ethanol/water ratios (40:60, 60:40, and 80:20), temperatures (25, 40, and 55 ˚C), and time durations (20, 24, and 28 h). The extraction yield, phenolic compounds, flavonoids, and anthocyanins were measured. ‎Antimicrobial activity of pomegranate peel extracts were determined against some food-borne ‎microorganisms such as Salmonella enteritidis, Escherichia coli, Listeria monocytogenes, ‎‎Staphylococcus aureus, Aspergillus niger, and Saccharomyces cerevisiae by agar diffusion and MIC methods. Results showed that at ethanol/water ratio 60:40, 25 ˚C and 24 h maximum amount of phenolic compounds ‎‏(‎‏‎349.518‎‏ ‏mg gallic acid‏/‏g dried extract), ‎flavonoids (250.124 mg rutin‏/‏g dried extract), anthocyanins (252.047 ‎‏‏mg ‎cyanidin‏‎3‎‏glucoside‏/‏‎100 g dried extract), and the strongest antimicrobial activity were obtained. ‎All extracts’ antimicrobial activities were demonstrated against every tested ‎‎microorganisms‏.‎‏ Staphylococcus aureus showed the highest sensitivity among the tested ‎‎‎microorganisms.

Keywords: antimicrobial agents, phenolic compounds, pomegranate peel, solvent extraction‎

Procedia PDF Downloads 244

Authors: Athar Mahmood, Asad Ali

Abstract:

Management considerations including harvesting time and nitrogen application considerably influence the biomass yield, quality and biogas production. Therefore, a field study was conducted to determine the effect of various harvesting times and nitrogen rates on the biomass yield, quality and biogas yield of maize crop. This experiment was consisted of various harvesting times i.e., harvesting after 45, 55 and 65 days of sowing (DAS) and nitrogen rates i.e., 0, 100, 150 and 200 kg ha-1 respectively. The data indicated that maximum plant height, leaf area, dry matter (DM) yield, protein, acid detergent fiber, neutral detergent fiber, crude fiber contents and biogas yield were recorded 65 days after sowing while lowest was recorded 45 days after sowing. In contrary to that significantly higher chlorophyll contents were observed at 45 DAS. In case of nitrogen rates maximum plant height, leaf area, and DM yield, protein contents, ash contents, acid detergent fiber, neutral detergent fiber, crude fiber contents and chlorophyll contents were determined with nitrogen at the rate of 200 kg ha-1, while minimum was observed when no N was applied. Therefore, harvesting 65 DAS and N application @ 200 kg ha-1 can be suitable for getting the higher biomass and biogas production.

Keywords: chemical composition, fiber contents, biogas, nitrogen, harvesting time

Procedia PDF Downloads 140

Authors: Martin A. Curry

Abstract:

Madeline Island is a small island community in Wisconsin, USA. Located in Lake Superior, it has been home to the Anishinaabe/Ojibway people for 1000s of years and is known as Moningwankuaning Minis-"The Island of the Golden Breasted Woodpecker". The community relies on summer tourism as its source of income, with a small population of 400 year-round residents. Supervisor Martin A. Curry (Ojibway/German descent) has been working on a fiscally responsible, environmentally principled and culturally centered approach to waste diversion and recycling. The tenets of this program encompass plastics, paper, food waste, local farming, energy production and art education. Through creative writing for the local newspaper and creative interactions, Martin has worked to engage the community in a more robust interest in waste diversion, including setting up a free-will donation store that incorporates elder volunteering opportunities, a compost program that works with the local community garden, biodiesel production and an art program that works with children from the local island school to make paper, grow local food and paint murals. The entirety of this program is based on the Ojibway concept of Mino-Bimadiiziwiin- "The Good Life" and benefits the community and its guests and represents a microcosm of the global dilemmas of waste and recycling.

Keywords: recycling, waste diversion, island, Native American, art

Procedia PDF Downloads 89

Authors: Celal Dudak, Aslı Utku, Burak Yağlioğlu

Abstract:

Uninterrupted and continuous satellite communication through the whole orbit time is becoming more indispensable every day. Data relay systems are developed and built for various high/low data rate information exchanges like TDRSS of USA and EDRSS of Europe. In these missions, a couple of task-dedicated communication satellites exist. In this regard, for Turkey a data relay system is attempted to be defined exchanging low data rate information (i.e. TTC) for Earth-observing LEO satellites appointing commercial GEO communication satellites all over the world. First, justification of this attempt is given, demonstrating duration enhancements in the link. Discussion of preference of RF communication is, also, given instead of laser communication. Then, preferred communication GEOs – including TURKSAT4A already belonging to Turkey- are given, together with the coverage enhancements through STK simulations and the corresponding link budget. Also, a block diagram of the communication system is given on the LEO satellite.

Keywords: communication, GEO satellite, data relay system, coverage

Procedia PDF Downloads 421

Authors: Tanawat Hongthai, Dusit Thanapatay

Abstract:

This paper presents the development of encrypted near field communication (NFC) data exchange format transmission in an NFC passive tag for the feasibility of implementing a genuine product authentication. We propose a research encryption and checking the genuine product into four major categories; concept, infrastructure, development and applications. This result shows the passive NFC-forum Type 2 tag can be configured to be compatible with the NFC data exchange format (NDEF), which can be automatically partially data updated when there is NFC field.

Keywords: near field communication, NFC data exchange format, checking the genuine product, encrypted NFC

Procedia PDF Downloads 264

Authors: Opeyemi Atiba-Oyewo, Taile Y. Leswfi, Maurice S. Onyango, Christian Wolkersdorfer

Abstract:

This paper describes the preparation of surface modified montmorillonite using hexadecyltrimethylammonium bromide (HDTMA-Br) for the removal of vanadium from mine water. The adsorbent before and after adsorption was characterised by Fourier transform infra-red (FT-IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM), while the amount of vanadium adsorbed was determined by ICP-OES. The batch adsorption method was employed using vanadium concentrations in solution ranging from 50 to 320 mg/L and vanadium tailings seepage water from a South African mine. Also, solution pH, temperature and sorbent mass were varied. Results show that the adsorption capacity was affected by solution pH, temperature, sorbent mass and the initial concentration. Electrical conductivity of the mine water before and after adsorption was measured to estimate the total dissolved solids in the mine water. Equilibrium isotherm results revealed that vanadium sorption follows the Freundlich isotherm, indicating that the surface of the sorbent was heterogeneous. The pseudo-second order kinetic model gave the best fit to the kinetic experimental data compared to the first order and Elovich models. The results of this study may be used to predict the uptake efficiency of South Africa montmorillonite in view of its application for the removal of vanadium from mine water. However, the choice of this adsorbent for the uptake of vanadium or other contaminants will depend on the composition of the effluent to be treated.

Keywords: adsorption, vanadium, modified montmorillonite, equilibrium, kinetics, mine water

Procedia PDF Downloads 412

Authors: Danutė Jablonskytė-Raščė, Vidas Damanauskas

Abstract:

The wheat (Triticum) genus is divided into many species, of which only two are widely distributed in the world - common wheat (Triticum aestivum L.) and durum wheat (Triticum durum Desf.). Common (soft) wheat is the most common type of wheat in the world and the most suitable for the harsh climate of Lithuania, but the grains have lower protein content and poorer nutritional properties. Durum wheat is characterized by a high protein content of the grain, but it is a crop of warmer climates grown in southern countries, Italy, Spain, the United States, Egypt, etc. Today's important issue is food, its resources and quality. The research focuses on healthier food grown in our conditions, the quality of which recently depends a lot not only on the cultivation technology but also on the warming climate conditions. Climatic conditions change the distribution of fungi and their hosts. Plants that have grown in our climate for many years have adapted to the use of fungicides, so the aim is to study cereal varieties grown in warmer climates and compare them with our country's varieties, studying their nutritional value and the spread of fungal diseases. The field experiments of different varieties of wheat were conducted at Joniškėlis Experimental Station of the Lithuanian Research Centre for Agriculture and Forestry in 2023. The soil of the experimental site was Endocalcari-Endohypogleyic Cambisol (CMg-n-w-can). The research was designed to identify the resistance to leaf diseases and the nutritional value of various wheat varieties. This research aims to focus on healthier food grown in our conditions, the quality of which recently depends a lot not only on the cultivation technology but also on the conditions of the warming climate. The study found that hot and humid summer weather led to the spread of foliar diseases in wheat. Tan spot (Pyrenophora tritici-repentis) is mostly spread in wheat crops. This disease had an average prevalence of 86.90%. The wheat crop was sparse, so this year was unfavorable for the spread of powdery mildew (Blumeria graminis). Dry weather prevailed during the period of flowering of cereals, which prevented the spread of ear diseases. Examining the qualitative indicators of grain, it was found that durum wheat had the best parameters.

Keywords: varieties, wheat, leaf disease, grain quality

Procedia PDF Downloads 22

Authors: Yung Gi Wu

Abstract:

With the growing of computer and network, digital data can be spread to anywhere in the world quickly. In addition, digital data can also be copied or tampered easily so that the security issue becomes an important topic in the protection of digital data. Digital watermark is a method to protect the ownership of digital data. Embedding the watermark will influence the quality certainly. In this paper, Vector Quantization (VQ) is used to embed the watermark into the image to fulfill the goal of data hiding. This kind of watermarking is invisible which means that the users will not conscious the existing of embedded watermark even though the embedded image has tiny difference compared to the original image. Meanwhile, VQ needs a lot of computation burden so that we adopt a fast VQ encoding scheme by partial distortion searching (PDS) and mean approximation scheme to speed up the data hiding process. The watermarks we hide to the image could be gray, bi-level and color images. Texts are also can be regarded as watermark to embed. In order to test the robustness of the system, we adopt Photoshop to fulfill sharpen, cropping and altering to check if the extracted watermark is still recognizable. Experimental results demonstrate that the proposed system can resist the above three kinds of tampering in general cases.

Keywords: data hiding, vector quantization, watermark, color image

Procedia PDF Downloads 347

Authors: Poonam Singh, Surendra Prasad, William Aalbersberg

Abstract:

Iron the most essential trace element in human nutrition. Its deficiency has serious health consequences and is a major public health threat worldwide. The common deficiencies in Fiji population reported are of Fe, Ca and Zn. It has also been reported that 40% of women in Fiji are iron deficient. Therefore, we have been studying the bioavailability of iron in commonly consumed Fiji foods. To study the bioavailability it is essential to assess the iron contents in raw foods. This paper reports the iron contents and its bioavailability in commonly consumed foods by multicultural population of Fiji. The food samples (rice, breads, wheat flour and breakfast cereals) were analyzed by atomic absorption spectrophotometer for total iron and its bioavailability. The white rice had the lowest total iron 0.10±0.03 mg/100g but had high bioavailability of 160.60±0.03%. The brown rice had 0.20±0.03 mg/100g total iron content but 85.00±0.03% bioavailable. The white and brown breads showed the highest iron bioavailability as 428.30±0.11 and 269.35 ±0.02%, respectively. The Weetabix and the rolled oats had the iron contents 2.89±0.27 and 1.24.±0.03 mg/100g with bioavailability of 14.19±0.04 and 12.10±0.03%, respectively. The most commonly consumed normal wheat flour had 0.65±0.00 mg/100g iron while the whole meal and the Roti flours had 2.35±0.20 and 0.62±0.17 mg/100g iron showing bioavailability of 55.38±0.05, 16.67±0.08 and 12.90±0.00%, respectively. The low bioavailability of iron in certain foods may be due to the presence of phytates/oxalates, processing/storage conditions, cooking method or interaction with other minerals present in the food samples.

Keywords: iron, bioavailability, Fiji foods, in vitro technique, human nutrition

Procedia PDF Downloads 512

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

Abstract:

Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 176

Authors: Muhammad Suhail Ibrahim, Muhammad Nadeem, Muhammad Sultan, Uzair Sajjad, Khalid Hamid, Tahir Mahmood Qureshi, Sadaf Javaria

Abstract:

Metabolic disorders, including hypertension, diabetes, cardiovascular disease etc., are major threats to public health and economy. Management and prevention of alarmingly increasing disorders have attracted researchers to explore natural barriers against these disorders. The objective of this study was to explore oats as a potential source of dietary fiber. Extraction of dietary was optimized by response surface methodology, and five indigenous oat cultivars, including SGD2011, Avon, SGD81, PD2LV65, and S2000, were also characterized for techno-functional characteristics, mineral composition and phytochemical quantification. These cultivars varied significantly (p < 0.05) for oil holding capacity, water saturation, and water holding capacity, respectively. SGD81 showed the highest oil-holding capacity, water-holding capacity, and water saturation due to the highest fraction of dietary fiber. The highest values of total phenolic contents, total flavonoid contents, total flavonol contents, 2, 2-Diphenyl-1-picrylhydrazyl radical scavenging activity, and anthocyanin were shown by SGD81, and SGD2011, respectively. All cultivars varied significantly (P<0.05) with respect to phytochemical quantification. Oat cultivars SGD81 and SGD2011 showed the best phenolic acid profile and can be effectively used as a source of nutraceuticals. Beyond the nutritional properties of oats, these also contribute and emerged as potential sources of dietary fiber and have gained attention as nutraceutical cereal crops. This approach offers oats as a natural means of dietary fiber to protect humans from alarmingly increasing metabolic disorders, and its extraction by sonication has made it a sustainable and eco-friendly strategy.

Keywords: oat cultivars, dietary fibers, mineral profile, antioxidant activity, color properties

Procedia PDF Downloads 14