Search results for: food frequency and biomedical data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30071

Search results for: food frequency and biomedical data

25151 Information Communication Technology (ICT) Using Management in Nursing College under the Praboromarajchanok Institute

Authors: Suphaphon Udomluck, Pannathorn Chachvarat

Abstract:

Information Communication Technology (ICT) using management is essential for effective decision making in organization. The Concerns Based Adoption Model (CBAM) was employed as the conceptual framework. The purposes of the study were to assess the situation of Information Communication Technology (ICT) using management in College of Nursing under the Praboromarajchanok Institute. The samples were multi – stage sampling of 10 colleges of nursing that participated include directors, vice directors, head of learning groups, teachers, system administrator and responsible for ICT. The total participants were 280; the instrument used were questionnaires that include 4 parts, general information, Information Communication Technology (ICT) using management, the Stage of concern Questionnaires (SoC), and the Levels of Use (LoU) ICT Questionnaires respectively. Reliability coefficients were tested; alpha coefficients were 0.967for Information Communication Technology (ICT) using management, 0.884 for SoC and 0.945 for LoU. The data were analyzed by frequency, percentage, mean, standard deviation, Pearson Product Moment Correlation and Multiple Regression. They were founded as follows: The high level overall score of Information Communication Technology (ICT) using management and issue were administration, hardware, software, and people. The overall score of the Stage of concern (SoC)ICTis at high level and the overall score of the Levels of Use (LoU) ICTis at moderate. The Information Communication Technology (ICT) using management had the positive relationship with the Stage of concern (SoC)ICTand the Levels of Use (LoU) ICT(p < .01). The results of Multiple Regression revealed that administration hardwear, software and people ware could predict SoC of ICT (18.5%) and LoU of ICT (20.8%).The factors that were significantly influenced by SoCs were people ware. The factors that were significantly influenced by LoU of ICT were administration hardware and people ware.

Keywords: information communication technology (ICT), management, the concerns-based adoption model (CBAM), stage of concern(SoC), the levels of use(LoU)

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25150 Willingness of Spanish Wineries to Implement Renewable Energies in Their Vineyards and Wineries, as Well as the Limitations They Perceive for Their Implementation

Authors: Javier Carroquino, Nieves García-Casarejos, Pilar Gargallo

Abstract:

Climate change, depletion of non-renewable resources in the current energies, pollution from them, the greater ecological awareness of the population, are factors that suggest the change of energy sources in business. The agri-food industry is a growth sector, concerned about product innovation, process and with a clear awareness of what climate change may mean for it. This sector is supposed to have a high receptivity to the implementation of clean energy, as this favors not only the environment but also the essence of its business. This work, through surveys, aims to know the willingness of Spanish wineries to implement renewable energies in their vineyards, as well as the limitations they perceive for their implementation. This questionnaire allows the characterization of the sector in terms of its geographical typologies, their activity levels, their perception of environmental issues, the degree of implementation of measures to mitigate climate change and improve energy efficiency, and its uses and energy consumption. The analysis of data proves that the penetration of renewable energies is still at low levels, being the most used energies, solar thermal, photovoltaic and biomass. The initial investment seems to be at the origin of the lack of implantation of this type of energy in the wineries, and not so much the costs of operations and maintenance. The environmental management of the wineries is still at an embryonic stage within the company's organization chart, because these services are either outsourced or, if technicians are available, they are not exclusively dedicated to these tasks. However, there is a strong environmental awareness, as evidenced by the number of climate change mitigation and energy efficiency measures already adopted. The gap between high awareness and low achievement is probably due to the lack of knowledge about how to do it or the perception of a high cost.

Keywords: survey, renewable energy, winery, Spanish case

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25149 Resonant Fluorescence in a Two-Level Atom and the Terahertz Gap

Authors: Nikolai N. Bogolubov, Andrey V. Soldatov

Abstract:

Terahertz radiation occupies a range of frequencies somewhere from 100 GHz to approximately 10 THz, just between microwaves and infrared waves. This range of frequencies holds promise for many useful applications in experimental applied physics and technology. At the same time, reliable, simple techniques for generation, amplification, and modulation of electromagnetic radiation in this range are far from been developed enough to meet the requirements of its practical usage, especially in comparison to the level of technological abilities already achieved for other domains of the electromagnetic spectrum. This situation of relative underdevelopment of this potentially very important range of electromagnetic spectrum is known under the name of the 'terahertz gap.' Among other things, technological progress in the terahertz area has been impeded by the lack of compact, low energy consumption, easily controlled and continuously radiating terahertz radiation sources. Therefore, development of new techniques serving this purpose as well as various devices based on them is of obvious necessity. No doubt, it would be highly advantageous to employ the simplest of suitable physical systems as major critical components in these techniques and devices. The purpose of the present research was to show by means of conventional methods of non-equilibrium statistical mechanics and the theory of open quantum systems, that a thoroughly studied two-level quantum system, also known as an one-electron two-level 'atom', being driven by external classical monochromatic high-frequency (e.g. laser) field, can radiate continuously at much lower (e.g. terahertz) frequency in the fluorescent regime if the transition dipole moment operator of this 'atom' possesses permanent non-equal diagonal matrix elements. This assumption contradicts conventional assumption routinely made in quantum optics that only the non-diagonal matrix elements persist. The conventional assumption is pertinent to natural atoms and molecules and stems from the property of spatial inversion symmetry of their eigenstates. At the same time, such an assumption is justified no more in regard to artificially manufactured quantum systems of reduced dimensionality, such as, for example, quantum dots, which are often nicknamed 'artificial atoms' due to striking similarity of their optical properties to those ones of the real atoms. Possible ways to experimental observation and practical implementation of the predicted effect are discussed too.

Keywords: terahertz gap, two-level atom, resonant fluorescence, quantum dot, resonant fluorescence, two-level atom

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25148 From Biowaste to Biobased Products: Life Cycle Assessment of VALUEWASTE Solution

Authors: Andrés Lara Guillén, José M. Soriano Disla, Gemma Castejón Martínez, David Fernández-Gutiérrez

Abstract:

The worldwide population is exponentially increasing, which causes a rising demand for food, energy and non-renewable resources. These demands must be attended to from a circular economy point of view. Under this approach, the obtention of strategic products from biowaste is crucial for the society to keep the current lifestyle reducing the environmental and social issues linked to the lineal economy. This is the main objective of the VALUEWASTE project. VALUEWASTE is about valorizing urban biowaste into proteins for food and feed and biofertilizers, closing the loop of this waste stream. In order to achieve this objective, the project validates three value chains, which begin with the anaerobic digestion of the biowaste. From the anaerobic digestion, three by-products are obtained: i) methane that is used by microorganisms, which will be transformed into microbial proteins; ii) digestate that is used by black soldier fly, producing insect proteins; and iii) a nutrient-rich effluent, which will be transformed into biofertilizers. VALUEWASTE is an innovative solution, which combines different technologies to valorize entirely the biowaste. However, it is also required to demonstrate that the solution is greener than other traditional technologies (baseline systems). On one hand, the proteins from microorganisms and insects will be compared with other reference protein production systems (gluten, whey and soybean). On the other hand, the biofertilizers will be compared to the production of mineral fertilizers (ammonium sulphate and synthetic struvite). Therefore, the aim of this study is to provide that biowaste valorization can reduce the environmental impacts linked to both traditional proteins manufacturing processes and mineral fertilizers, not only at a pilot-scale but also at an industrial one. In the present study, both baseline system and VALUEWASTE solution are evaluated through the Environmental Life Cycle Assessment (E-LCA). The E-LCA is based on the standards ISO 14040 and 14044. The Environmental Footprint methodology was the one used in this study to evaluate the environmental impacts. The results for the baseline cases show that the food proteins coming from whey have the highest environmental impact on ecosystems compared to the other proteins sources: 7.5 and 15.9 folds higher than soybean and gluten, respectively. Comparing feed soybean and gluten, soybean has an environmental impact on human health 195.1 folds higher. In the case of biofertilizers, synthetic struvite has higher impacts than ammonium sulfate: 15.3 (ecosystems) and 11.8 (human health) fold, respectively. The results shown in the present study will be used as a reference to demonstrate the better environmental performance of the bio-based products obtained through the VALUEWASTE solution. Other originalities that the E-LCA performed in the VALUEWASTE project provides are the diverse direct implications on investment and policies. On one hand, better environmental performance will serve to remove the barriers linked to these kinds of technologies, boosting the investment that is backed by the E-LCA. On the other hand, it will be a germ to design new policies fostering these types of solutions to achieve two of the key targets of the European Community: being self-sustainable and carbon neutral.

Keywords: anaerobic digestion, biofertilizers, circular economy, nutrients recovery

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25147 Intelligent Indoor Localization Using WLAN Fingerprinting

Authors: Gideon C. Joseph

Abstract:

The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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25146 Assimilating Multi-Mission Satellites Data into a Hydrological Model

Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

Abstract:

Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

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25145 RFID and Intelligence: A Smart Authentication Method for Blind People​

Authors: V. Vishu, R. Manimegalai

Abstract:

A combination of Intelligence and Radio frequency identification to bring an enhanced authentication method for the improvement of visually challenged people. The main goal is to provide an improved authentication by combining Advanced Encryption Standard algorithm and Intelligence. Here the encryption key will be generated as a combination of intelligent information from sensors and tag values. The main challenges are security, privacy and cost. Besides, the method was created to evaluate the amount of interaction between sensors and significant influence on the level of visually challenged people’s mental and physical states. The proposal is to apply various ideas on independent living or to assist them for a good life.

Keywords: AES, encryption, intelligence, smart key

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25144 Influence of Maternal Factors on Growth Patterns of Schoolchildren in a Rural Health and Demographic Surveillance Site in South Africa: A Mixed Method Study

Authors: Perpetua Modjadji, Sphiwe Madiba

Abstract:

Background: The growth patterns of children are good nutritional indicators of their nutritional status, health, and socioeconomic level. However, the maternal factors and the belief system of the society affect the growth of children promoting undernutrition. This study determined the influence of maternal factors on growth patterns of schoolchildren in a rural site. Methods: A convergent mixed method study was conducted among 508 schoolchildren and their mothers in Dikgale Health and Demographic Surveillance System Site, South Africa. Multistage sampling was used to select schools (purposive) and learners (random), who were paired with their mothers. Anthropometry was measured and socio-demographic, obstetrical, household information, maternal influence on children’s nutrition, and growth were assessed using an interviewer administered questionnaire (quantitative). The influence of the cultural beliefs and practices of mothers on the nutrition and growth of their children was explored using focus group discussions (qualitative). Narratives of mothers were used to best understand growth patterns of schoolchildren (mixed method). Data were analyzed using STATA 14 (quantitative) and Nvivo 11 (qualitative). Quantitative and qualitative data were merged for integrated mixed method analysis using a joint display analysis. Results: Mean age of children was 10 ± 2 years, ranging from 6 to 15 years. Substantial percentages of thinness (25%), underweight (24%), and stunting (22%) were observed among the children. Mothers had a mean age of 37 ± 7 years, and 75% were overweight or obese. A depressed socio-economic status indicated by a higher rate of unemployment with no income (82.3%), and dependency on social grants (86.8%) was observed. Determinants of poor growth patterns were child’s age and gender, maternal age, height and BMI, access to water supply, and refrigerator use. The narratives of mothers suggested that the children in most of their households were exposed to poverty and the inadequate intake of quality food. Conclusion: Poor growth patterns were observed among schoolchildren while their mothers were overweight or obese. Child’s gender, school grade, maternal body mass index, and access to water were the main determinants. Congruence was observed between most qualitative themes and quantitative constructs. A need for a multi sectoral approach considering an evidence based and feasible nutrition programs for schoolchildren, especially those in rural settings and educating mothers, cannot be over-emphasized.

Keywords: growth patterns, maternal factors, rural context, schoolchildren, South Africa

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25143 Chain Networks on Internationalization of SMEs: Co-Opetition Strategies in Agrifood Sector

Authors: Emilio Galdeano-Gómez, Juan C. Pérez-Mesa, Laura Piedra-Muñoz, María C. García-Barranco, Jesús Hernández-Rubio

Abstract:

The situation in which firms engage in simultaneous cooperation and competition with each other is a phenomenon known as co-opetition. This scenario has received increasing attention in business economics and management analyses. In the domain of supply chain networks and for small and medium-sized enterprises, SMEs, these strategies are of greater relevance given the complex environment of globalization and competition in open markets. These firms face greater challenges regarding technology and access to specific resources due to their limited capabilities and limited market presence. Consequently, alliances and collaborations with both buyers and suppliers prove to be key elements in overcoming these constraints. However, rivalry and competition are also regarded as major factors in successful internationalization processes, as they are drivers for firms to attain a greater degree of specialization and to improve efficiency, for example enabling them to allocate scarce resources optimally and providing incentives for innovation and entrepreneurship. The present work aims to contribute to the literature on SMEs’ internationalization strategies. The sample is constituted by a panel data of marketing firms from the Andalusian food sector and a multivariate regression analysis is developed, measuring variables of co-opetition and international activity. The hierarchical regression equations method has been followed, thus resulting in three estimated models: the first one excluding the variables indicative of channel type, while the latter two include the international retailer chain and wholesaler variable. The findings show that the combination of several factors leads to a complex scenario of inter-organizational relationships of cooperation and competition. In supply chain management analyses, these relationships tend to be classified as either buyer-supplier (vertical level) or supplier-supplier relationships (horizontal level). Several buyers and suppliers tend to participate in supply chain networks, and in which the form of governance (hierarchical and non-hierarchical) influences cooperation and competition strategies. For instance, due to their market power and/or their closeness to the end consumer, some buyers (e.g. large retailers in food markets) can exert an influence on the selection and interaction of several of their intermediate suppliers, thus endowing certain networks in the supply chain with greater stability. This hierarchical influence may in turn allow these suppliers to develop their capabilities (e.g. specialization) to a greater extent. On the other hand, for those suppliers that are outside these networks, this environment of hierarchy, characterized by a “hub firm” or “channel master”, may provide an incentive for developing their co-opetition relationships. These results prove that the analyzed firms have experienced considerable growth in sales to new foreign markets, mainly in Europe, dealing with large retail chains and wholesalers as main buyers. This supply industry is predominantly made up of numerous SMEs, which has implied a certain disadvantage when dealing with the buyers, as negotiations have traditionally been held on an individual basis and in the face of high competition among suppliers. Over recent years, however, cooperation among these marketing firms has become more common, for example regarding R&D, promotion, scheduling of production and sales.

Keywords: co-petition networks, international supply chain, maketing agrifood firms, SMEs strategies

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25142 Survey of Indoor Radon/Thoron Concentrations in High Lung Cancer Incidence Area in India

Authors: Zoliana Bawitlung, P. C. Rohmingliana, L. Z. Chhangte, Remlal Siama, Hming Chungnunga, Vanram Lawma, L. Hnamte, B. K. Sahoo, B. K. Sapra, J. Malsawma

Abstract:

Mizoram state has the highest lung cancer incidence rate in India due to its high-level consumption of tobacco and its products which is supplemented by the food habits. While smoking is mainly responsible for this incidence, the effect of inhalation of indoor radon gas cannot be discarded as the hazardous nature of this radioactive gas and its progenies on human population have been well-established worldwide where the radiation damage to bronchial cells eventually can be the second leading cause of lung cancer next to smoking. It is also known that the effect of radiation, however, small may be the concentration, cannot be neglected as they can bring about the risk of cancer incidence. Hence, estimation of indoor radon concentration is important to give a useful reference against radiation effects as well as establishing its safety measures and to create a baseline for further case-control studies. The indoor radon/thoron concentrations in Mizoram had been measured in 41 dwellings selected on the basis of spot gamma background radiation and construction type of the houses during 2015-2016. The dwellings were monitored for one year, in 4 months cycles to indicate seasonal variations, for the indoor concentration of radon gas and its progenies, outdoor gamma dose, and indoor gamma dose respectively. A time-integrated method using Solid State Nuclear Track Detector (SSNTD) based single entry pin-hole dosimeters were used for measurement of indoor Radon/Thoron concentration. Gamma dose measurements for indoor as well as outdoor were carried out using Geiger Muller survey meters. Seasonal variation of indoor radon/ thoron concentration was monitored. The results show that the annual average radon concentrations varied from 54.07 – 144.72 Bq/m³ with an average of 90.20 Bq/m³ and the annual average thoron concentration varied from 17.39 – 54.19 Bq/m³ with an average of 35.91 Bq/m³ which are below the permissible limit. The spot survey of gamma background radiation level varies between 9 to 24 µR/h inside and outside the dwellings throughout Mizoram which are all within acceptable limits. From the above results, there is no direct indication that radon/thoron is responsible for the high lung cancer incidence in the area. In order to find epidemiological evidence of natural radiations to high cancer incidence in the area, one may need to conduct a case-control study which is beyond this scope. However, the derived data of measurement will provide baseline data for further studies.

Keywords: background gamma radiation, indoor radon/thoron, lung cancer, seasonal variation

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25141 Physicochemical Properties of Pea Protein Isolate (PPI)-Starch and Soy Protein Isolate (SPI)-Starch Nanocomplexes Treated by Ultrasound at Different pH Values

Authors: Gulcin Yildiz, Hao Feng

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Soybean proteins are the most widely used and researched proteins in the food industry. Due to soy allergies among consumers, however, alternative legume proteins having similar functional properties have been studied in recent years. These alternative proteins are also expected to have a price advantage over soy proteins. One such protein that has shown good potential for food applications is pea protein. Besides the favorable functional properties of pea protein, it also contains fewer anti-nutritional substances than soy protein. However, a comparison of the physicochemical properties of pea protein isolate (PPI)-starch nanocomplexes and soy protein isolate (SPI)-starch nanocomplexes treated by ultrasound has not been well documented. This study was undertaken to investigate the effects of ultrasound treatment on the physicochemical properties of PPI-starch and SPI-starch nanocomplexes. Pea protein isolate (85% pea protein) provided by Roquette (Geneva, IL, USA) and soy protein isolate (SPI, Pro-Fam® 955) obtained from the Archer Daniels Midland Company were adjusted to different pH levels (2-12) and treated with 5 minutes of ultrasonication (100% amplitude) to form complexes with starch. The soluble protein content was determined by the Bradford method using BSA as the standard. The turbidity of the samples was measured using a spectrophotometer (Lambda 1050 UV/VIS/NIR Spectrometer, PerkinElmer, Waltham, MA, USA). The volume-weighted mean diameters (D4, 3) of the soluble proteins were determined by dynamic light scattering (DLS). The emulsifying properties of the proteins were evaluated by the emulsion stability index (ESI) and emulsion activity index (EAI). Both the soy and pea protein isolates showed a U-shaped solubility curve as a function of pH, with a high solubility above the isoelectric point and a low one below it. Increasing the pH from 2 to 12 resulted in increased solubility for both the SPI and PPI-starch complexes. The pea nanocomplexes showed greater solubility than the soy ones. The SPI-starch nanocomplexes showed better emulsifying properties determined by the emulsion stability index (ESI) and emulsion activity index (EAI) due to SPI’s high solubility and high protein content. The PPI had similar or better emulsifying properties at certain pH values than the SPI. The ultrasound treatment significantly decreased the particle sizes of both kinds of nanocomplex. For all pH levels with both proteins, the droplet sizes were found to be lower than 300 nm. The present study clearly demonstrated that applying ultrasonication under different pH conditions significantly improved the solubility and emulsify¬ing properties of the SPI and PPI. The PPI exhibited better solubility and emulsifying properties than the SPI at certain pH levels

Keywords: emulsifying properties, pea protein isolate, soy protein isolate, ultrasonication

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25140 Assessment the Implications of Regional Transport and Local Emission Sources for Mitigating Particulate Matter in Thailand

Authors: Ruchirek Ratchaburi, W. Kevin. Hicks, Christopher S. Malley, Lisa D. Emberson

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Air pollution problems in Thailand have improved over the last few decades, but in some areas, concentrations of coarse particulate matter (PM₁₀) are above health and regulatory guidelines. It is, therefore, useful to investigate how PM₁₀ varies across Thailand, what conditions cause this variation, and how could PM₁₀ concentrations be reduced. This research uses data collected by the Thailand Pollution Control Department (PCD) from 17 monitoring sites, located across 12 provinces, and obtained between 2011 and 2015 to assess PM₁₀ concentrations and the conditions that lead to different levels of pollution. This is achieved through exploration of air mass pathways using trajectory analysis, used in conjunction with the monitoring data, to understand the contribution of different months, an hour of the day and source regions to annual PM₁₀ concentrations in Thailand. A focus is placed on locations that exceed the national standard for the protection of human health. The analysis shows how this approach can be used to explore the influence of biomass burning on annual average PM₁₀ concentration and the difference in air pollution conditions between Northern and Southern Thailand. The results demonstrate the substantial contribution that open biomass burning from agriculture and forest fires in Thailand and neighboring countries make annual average PM₁₀ concentrations. The analysis of PM₁₀ measurements at monitoring sites in Northern Thailand show that in general, high concentrations tend to occur in March and that these particularly high monthly concentrations make a substantial contribution to the overall annual average concentration. In 2011, a > 75% reduction in the extent of biomass burning in Northern Thailand and in neighboring countries resulted in a substantial reduction not only in the magnitude and frequency of peak PM₁₀ concentrations but also in annual average PM₁₀ concentrations at sites across Northern Thailand. In Southern Thailand, the annual average PM₁₀ concentrations for individual years between 2011 and 2015 did not exceed the human health standard at any site. The highest peak concentrations in Southern Thailand were much lower than for Northern Thailand for all sites. The peak concentrations at sites in Southern Thailand generally occurred between June and October and were associated with air mass back trajectories that spent a substantial proportion of time over the sea, Indonesia, Malaysia, and Thailand prior to arrival at the monitoring sites. The results show that emissions reductions from biomass burning and forest fires require action on national and international scales, in both Thailand and neighboring countries, such action could contribute to ensuring compliance with Thailand air quality standards.

Keywords: annual average concentration, long-range transport, open biomass burning, particulate matter

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25139 Application of New Sprouted Wheat Brine for Delicatessen Products From Horse Meat, Beef and Pork

Authors: Gulmira Kenenbay, Urishbay Chomanov, Aruzhan Shoman, Rabiga Kassimbek

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The main task of the meat-processing industry is the production of meat products as the main source of animal protein, ensuring the vital activity of the human body, in the required volumes, high quality, diverse assortment. Providing the population with high-quality food products what are biologically full, balanced in composition of basic nutrients and enriched by targeted physiologically active components, is one of the highest priority scientific and technical problems to be solved. In this regard, the formulation of a new brine from sprouted wheat for meat delicacies from horse meat, beef and pork has been developed. The new brine contains flavored aromatic ingredients, juice of the germinated wheat and vegetable juice. The viscosity of meat of horse meat, beef and pork were studied during massaging. Thermodynamic indices, water activity and binding energy of horse meat, beef and pork with application of new brine are investigated. A recipe for meat products with vegetable additives has been developed. Organoleptic evaluation of meat products was carried out. Physicochemical parameters of meat products with vegetable additives are carried out. Analysis of the obtained data shows that the values of the index aw (water activity) and the binding energy of moisture in the experimental samples of meat products are higher than in the control samples. It has been established by investigations that with increasing water activity and the binding energy of moisture, the tenderness of ready meat delicacies increases with the use of a new brine.

Keywords: compounding, functional products, delicatessen products, brine, vegetable additives

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25138 An Investigation of the Science Process Skills of 48-66 Months Old Children

Authors: Nilüfer Kuru, Berrin Akman

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In this study, science process skills of children with ages varying between 48-months and 66-months are analyzed. Science process skills of children are investigated in terms of factors including gender of children, attendance of children to the previous educational institution and duration of their attendance, educational background of their parents, ages of children and teachers, professional experience of teachers, educational background, and department of graduation of teachers, type of pre-school education institution of teachers and children. Sample of research consists of 250 children aged between 48-months and 66-months who attend state and private kindergartens under the Ministry of National Education, nursery classes of elementary schools and kindergartens of establishments in central districts of Ankara and 50 teachers who serve in these children’s classes. Science Observation Form, reached from the website of Alaska Department of Education & Early, are analyzed in terms of language, content, construct validity, and reliability by the researchers. Additionally, Personal Information Form is also developed by the researchers. Data obtained in the study are analyzed with SPSS 16.0 package program to obtain percentage and frequency, Kruskal Wallis H-test, and Mann- Whitney U test, which are one of the non-parametric tests, are used. Within the context of this study it has been seen that independent variables of age, type of school attending and status of attendance to pre-school education, educational background of children’s father are meaningful expositive in gaining science process skills for children. It has been seen that period of service of teachers, duration of attendance to pre-school education for children, gender of children and educational background of children’s mother are not meaningful expositive in gaining science process skills for children.

Keywords: preschool, science process skills, early childhood education, science

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25137 Modeling and Simulation of the Structural, Electronic and Magnetic Properties of Fe-Ni Based Nanoalloys

Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

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25136 Hidden Hot Spots: Identifying and Understanding the Spatial Distribution of Crime

Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

Procedia PDF Downloads 235
25135 Advancing Urban Sustainability through Data-Driven Machine Learning Solutions

Authors: Nasim Eslamirad, Mahdi Rasoulinezhad, Francesco De Luca, Sadok Ben Yahia, Kimmo Sakari Lylykangas, Francesco Pilla

Abstract:

With the ongoing urbanization, cities face increasing environmental challenges impacting human well-being. To tackle these issues, data-driven approaches in urban analysis have gained prominence, leveraging urban data to promote sustainability. Integrating Machine Learning techniques enables researchers to analyze and predict complex environmental phenomena like Urban Heat Island occurrences in urban areas. This paper demonstrates the implementation of data-driven approach and interpretable Machine Learning algorithms with interpretability techniques to conduct comprehensive data analyses for sustainable urban design. The developed framework and algorithms are demonstrated for Tallinn, Estonia to develop sustainable urban strategies to mitigate urban heat waves. Geospatial data, preprocessed and labeled with UHI levels, are used to train various ML models, with Logistic Regression emerging as the best-performing model based on evaluation metrics to derive a mathematical equation representing the area with UHI or without UHI effects, providing insights into UHI occurrences based on buildings and urban features. The derived formula highlights the importance of building volume, height, area, and shape length to create an urban environment with UHI impact. The data-driven approach and derived equation inform mitigation strategies and sustainable urban development in Tallinn and offer valuable guidance for other locations with varying climates.

Keywords: data-driven approach, machine learning transparent models, interpretable machine learning models, urban heat island effect

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25134 Cross-Comparison between Land Surface Temperature from Polar and Geostationary Satellite over Heterogenous Landscape: A Case Study in Hong Kong

Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

Abstract:

Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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25133 Microarray Data Visualization and Preprocessing Using R and Bioconductor

Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

Abstract:

Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

Procedia PDF Downloads 472
25132 Spatial Pattern of Environmental Noise Levels and Auditory Ailments in Abeokuta Metropolis, Southwestern Nigeria

Authors: Olusegun Oguntoke, Aramide Y. Tijani, Olayide R. Adetunji

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Environmental noise has become a major threat to the quality of human life, and it is generally more severe in cities. This study assessed the level of environmental noise, mapped the spatial pattern at different times of the day and examined the association with morbidity of auditory ailments in Abeokuta metropolis. The entire metropolis was divided into 80 cells (areas) of 1000 m by 1000 m; out of which 33 were randomly selected for noise levels assessment. Portable noise meter (AR824) was used to measure noise level, and Global Positioning System (Garmin GPS-72H) was employed to take the coordinates of the sample sites for mapping. Risk map of the noise levels was produced using Kriging interpolation techniques based on the spatial spread of measured noise values across the study area. Data on cases of hearing impairments were collected from four major hospitals in the city. Data collected from field measurements and medical records were subjected to descriptive (frequency and percentage) and inferential (mean, ANOVA and correlation) statistics using SPSS (version 20.0). ArcMap 10.1 was employed for spatial analysis and mapping. Results showed mean noise levels range at morning (42.4 ± 4.14 – 88.2 ± 15.1 dBA), afternoon (45.0 ± 6.72– 86.4 ± 12.5 dBA) and evening (51.0 ± 6.55–84.4 ± 5.19 dBA) across the study area. The interpolated maps identified Kuto, Okelowo, Isale-Igbein, and Sapon as high noise risk areas. These are the central business district and nucleus of Abeokuta metropolis where commercial activities, high traffic volume, and clustered buildings exist. The monitored noise levels varied significantly among the sampled areas in the morning, afternoon and evening (p < 0.05). A significant correlation was found between diagnosed cases of auditory ailments and noise levels measured in the morning (r=0.39 at p < 0.05). Common auditory ailments found across the metropolis included impaired hearing (25.8%), tinnitus (16.4%) and otitis (15.0%). The most affected age groups were between 11-30 years while the male gender had more cases of hearing impairments (51.2%) than the females. The study revealed that environmental noise levels exceeded the recommended standards in the morning, afternoon and evening in 60.6%, 61% and 72.7% of the sampled areas respectively. Summarily, environmental noise in the study area is high and contributes to the morbidity of auditory ailments. Areas identified as hot spots of noise pollution should be avoided in the location of noise sensitive activities while environmental noise monitoring should be included as part of the mandate of the regulatory agencies in Nigeria.

Keywords: noise pollution, associative analysis, auditory impairment, urban, human exposure

Procedia PDF Downloads 135
25131 Adaptive Multiple Transforms Hardware Architecture for Versatile Video Coding

Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

Abstract:

The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: adaptive multiple transforms, AMT, DCT II, hardware, transform, versatile video coding, VVC

Procedia PDF Downloads 139
25130 Serological Screening of Barrier Maintained Rodent Colony

Authors: R. Posia, J. Mistry, K. Kamani

Abstract:

The health screening of laboratory rodents is essential for ensuring animal health and the validity of biomedical research data. Routine health monitoring is necessary to verify the effectiveness of biosecurity and the specific pathogen free (SPF) status of the colony. The present screening was performed in barrier maintained rat (Rattus norvegicus) colony. Rats were maintained under a controlled environment and strict biosecurity in the facility. The screening was performed on quarterly bases from randomly selected animals from breeding and or maintenance colonies. Selected animals were subject to blood collection under isoflurane anaesthesia. Serum was separated from the collected blood and stored samples at -60 ± 10 °C until further use. A total of 88 samples were collected quarterly bases from animals in a year. In the serological test, enzyme-linked immunosorbent assay (ELISA) was used for screening of serum samples against sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV). ELISA kits were procured from XpressBio, USA. Test serum samples were run along with positive control, negative control serum in 96 well ELISA plates as per the procedure recommended by the vendor. Test ELISA plate reading was taken in the microplate reader. This screening observed that none of the samples was observed positive for the sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV), indicating that effectiveness of biosecurity practices followed in the rodent colony. The result of serological screening helps us to declare that our rodent colony is specifically pathogen free for these pathogens.

Keywords: biosecurity, ELISA, specific pathogen free, serological screening, serum

Procedia PDF Downloads 74
25129 Damage Identification in Reinforced Concrete Beams Using Modal Parameters and Their Formulation

Authors: Ali Al-Ghalib, Fouad Mohammad

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The identification of damage in reinforced concrete structures subjected to incremental cracking performance exploiting vibration data is recognized as a challenging topic in the published and heavily cited literature. Therefore, this paper attempts to shine light on the extent of dynamic methods when applied to reinforced concrete beams simulated with various scenarios of defects. For this purpose, three different reinforced concrete beams are tested through the course of the study. The three beams are loaded statically to failure in incremental successive load cycles and later rehabilitated. After each static load stage, the beams are tested under free-free support condition using experimental modal analysis. The beams were all of the same length and cross-sectional area (2.0x0.14x0.09)m, but they were different in concrete compressive strength and the type of damage presented. The experimental modal parameters as damage identification parameters were showed computationally expensive, time consuming and require substantial inputs and considerable expertise. Nonetheless, they were proved plausible for the condition monitoring of the current case study as well as structural changes in the course of progressive loads. It was accentuated that a satisfactory localization and quantification for structural changes (Level 2 and Level 3 of damage identification problem) can only be achieved reasonably through considering frequencies and mode shapes of a system in a proper analytical model. A convenient post analysis process for various datasets of vibration measurements for the three beams is conducted in order to extract, check and correlate the basic modal parameters; namely, natural frequency, modal damping and mode shapes. The results of the extracted modal parameters and their combination are utilized and discussed in this research as quantification parameters.

Keywords: experimental modal analysis, damage identification, structural health monitoring, reinforced concrete beam

Procedia PDF Downloads 259
25128 Bayesian Analysis of Topp-Leone Generalized Exponential Distribution

Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

Procedia PDF Downloads 521
25127 Machine Learning Application in Shovel Maintenance

Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

Procedia PDF Downloads 206
25126 Standard Languages for Creating a Database to Display Financial Statements on a Web Application

Authors: Vladimir Simovic, Matija Varga, Predrag Oreski

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XHTML and XBRL are the standard languages for creating a database for the purpose of displaying financial statements on web applications. Today, XBRL is one of the most popular languages for business reporting. A large number of countries in the world recognize the role of XBRL language for financial reporting and the benefits that the reporting format provides in the collection, analysis, preparation, publication and the exchange of data (information) which is the positive side of this language. Here we present all advantages and opportunities that a company may have by using the XBRL format for business reporting. Also, this paper presents XBRL and other languages that are used for creating the database, such XML, XHTML, etc. The role of the AJAX complex model and technology will be explained in detail, and during the exchange of financial data between the web client and web server. Here will be mentioned basic layers of the network for data exchange via the web.

Keywords: XHTML, XBRL, XML, JavaScript, AJAX technology, data exchange

Procedia PDF Downloads 391
25125 Review of Cable Fault Locating Methods and Usage of VLF for Real Cases of High Resistance Fault Locating

Authors: Saadat Ali, Rashid Abdulla Ahmed Alshehhi

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Cable faults are always probable and common during or after commissioning, causing significant delays and disrupting power distribution or transmission network, which is intolerable for the utilities&service providers being their reliability and business continuity measures. Therefore, the adoption of rapid localization & rectification methodology is the main concern for them. This paper explores the present techniques available for high voltage cable localization & rectification and which is preferable with regards to easier, faster, and also less harmful to cables. It also provides insight experience of high resistance fault locating by utilization of the Very Low Frequency (VLF) method.

Keywords: faults, VLF, real cases, cables

Procedia PDF Downloads 97
25124 Analyze and Visualize Eye-Tracking Data

Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

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Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

Procedia PDF Downloads 127
25123 Peach as a Potential Functional Food: Biological Activity and Important Phenolic Compound Source

Authors: Luís R. Silva, Catarina Bento, Ana C. Gonçalves, Fábio Jesus, Branca M. Silva

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Nowadays, the general population is more and more concerned about nutrition and the health implications of an unbalanced diet. Current knowledge regarding the health benefits and antioxidant properties of certain foods such as fruits and vegetables has gained the interest of both the general public and scientific community. Peach (Prunus persica (L.) Batsch) is one of the most consumed fruits worldwide, with low sugar contents and a broad range of nutrients essential to the normal functioning of the body. Six different peach cultivars from the Fundão region in Portugal were evaluated regarding their phenolic composition by LC-DAD and biological activity. The prepared extracts’ capacity to scavenge free-radicals was tested through the stable free radical DPPH• and nitric oxide (•NO). Additionally, antidiabetic potential and protective effects against peroxyl radical (ROO•) induced damage to erythrocytes were also tested. LC-DAD analysis allowed the identification of 17 phenolic compounds, among which 5-O-caffeoylquinic acids and 3-O-caffeoylquinic acids are pointed out as the most abundant. Regarding the antioxidant activity, all cultivars displayed concentration-dependent free-radical scavenging activity against both nitrogen species and DPPH•. In respect to α-glucosidase inhibitory activity, Royal Magister and Royal Glory presented the highest inhibitory activity (IC50 = 11.7 ± 1.4 and 17.1 ± 1.7 μg/mL, respectively), nevertheless all six cultivars presented higher activity than the control acarbose. As for the protective effect of Royal Lu extract on the oxidative damage induced in erythrocytes by ROO•, the results were quite promising showing inhibition IC50 values of 110.0 ± 4.5 μg/mL and 83.8 ± 6.5 μg/mL for hemolysis and hemoglobin oxidation, respectively. The demonstrated activity is of course associated to the peaches’ phenolic profile, rich in phenolic acids and flavonoids with high hydrogen donating capacity. These compounds have great industrial interest for the manufacturing of natural products. The following step would naturally be the extraction and isolation from the plant tissues and large-scale production through biotechnology techniques.

Keywords: antioxidants, functional food, phenolic compounds, peach

Procedia PDF Downloads 282
25122 Design of a 3-dB Directional Coupler Using Symmetric Coupled-Lines

Authors: Cem Çindaş, Serkan Şimşek

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In this paper, the study and design of a 3-dB 90° directional coupler operating in the S-band is proposed. The coupler employs symmetrical multi-section coupled lines designed in a stripline technique. Design is realized in AWR Design Environment and CST Microwave Studio. Using these two programs played a key role in attaining outcomes swiftly and precisely. The simulation results show that the coupler maintains amplitude consistency within ± 0.3 dB, isolation and reflection losses better than 16 dB, and phase difference between two output ports of 88º±0.6˚ in the 1.7 – 4.35 GHz range. This simulation results indicate an improvement is achieved in fractional bandwidth (FBW) performance around the center frequency of f0 = 3 GHz.

Keywords: coupled stripline, directional coupler, multi-section coupler, symmetrical coupler

Procedia PDF Downloads 73