Search results for: forest fire monitor

Authors: Harry J. Witchel, James Ackah, Carlos P. Santos, Nachiappan Chockalingam, Carina E. I. Westling

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Introduction: Proxemics is the study of how people perceive and use space. It is commonly proposed that when people like or engage with a person/object, they will move slightly closer to it, often quite subtly and subconsciously. Music videos are known to add entertainment value to a pop song. Our hypothesis was that by adding appropriately matched video to a pop song, it would lead to a net approach of the head to the monitor screen compared to simply listening to an audio-only version of the song. Methods: We presented to 27 participants (ages 21.00 ± 2.89, 15 female) seated in front of 47.5 x 27 cm monitor two musical stimuli in a counterbalanced order; all stimuli were based on music videos by the band OK Go: Here It Goes Again (HIGA, boredom ratings (0-100) = 15.00 ± 4.76, mean ± SEM, standard-error-of-the-mean) and Do What You Want (DWYW, boredom ratings = 23.93 ± 5.98), which did not differ in boredom elicited (P = 0.21, rank-sum test). Each participant experienced each song only once, and one song (counterbalanced) as audio-only versus the other song as a music video. The movement was measured by video-tracking using Kinovea 0.8, based on recording from a lateral aspect; before beginning, each participant had a reflective motion tracking marker placed on the outer canthus of the left eye. Analysis of the Kinovea X-Y coordinate output in comma-separated-variables format was performed in Matlab, as were non-parametric statistical tests. Results: We found that the audio-only stimuli (combined for both HIGA and DWYW, mean ± SEM, 35.71 ± 5.36) were significantly more boring than the music video versions (19.46 ± 3.83, P = 0.0066 Wilcoxon Signed Rank Test (WSRT), Cohen's d = 0.658, N = 28). We also found that participants' heads moved around twice as much during the audio-only versions (speed = 0.590 ± 0.095 mm/sec) compared to the video versions (0.301 ± 0.063 mm/sec, P = 0.00077, WSRT). However, the participants' mean head-to-screen distances were not detectably smaller (i.e. head closer to the screen) during the music videos (74.4 ± 1.8 cm) compared to the audio-only stimuli (73.9 ± 1.8 cm, P = 0.37, WSRT). If anything, during the audio-only condition, they were slightly closer. Interestingly, the ranges of the head-to-screen distances were smaller during the music video (8.6 ± 1.4 cm) compared to the audio-only (12.9 ± 1.7 cm, P = 0.0057, WSRT), the standard deviations were also smaller (P = 0.0027, WSRT), and their heads were held 7 mm higher (video 116.1 ± 0.8 vs. audio-only 116.8 ± 0.8 cm above floor, P = 0.049, WSRT). Discussion: As predicted, sitting and listening to experimenter-selected pop music was more boring than when the music was accompanied by a matched, professionally-made video. However, we did not find that the proxemics of the situation led to approaching the screen. Instead, adding video led to efforts to control the head to a more central and upright viewing position and to suppress head fidgeting.

Keywords: boredom, engagement, music videos, posture, proxemics

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Authors: Marinella Majorano, Rachele Ferrari, Tamara Bastianello

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The recent technological advance allows for applying innovative and multimedia screen-based assessment tools to test children's language and early literacy skills, monitor their growth over the preschool years, and test their readiness for primary school. Several are the advantages that a computer-based assessment tool offers with respect to paper-based tools. Firstly, computer-based tools which provide the use of games, videos, and audio may be more motivating and engaging for children, especially for those with language difficulties. Secondly, computer-based assessments are generally less time-consuming than traditional paper-based assessments: this makes them less demanding for children and provides clinicians and researchers, but also teachers, with the opportunity to test children multiple times over the same school year and, thus, to monitor their language growth more systematically. Finally, while paper-based tools require offline coding, computer-based tools sometimes allow obtaining automatically calculated scores, thus producing less subjective evaluations of the assessed skills and provide immediate feedback. Nonetheless, using computer-based assessment tools to test meta-phonological and language skills in children is not yet common practice in Italy. The present contribution aims to estimate the internal consistency of a computer-based assessment (i.e., the Simo-syl assessment). Sixty-three Italian pre-schoolers aged between 4;10 and 5;9 years were tested at the beginning of the last year of the preschool through paper-based standardised tools in their lexical (Peabody Picture Vocabulary Test), morpho-syntactical (Grammar Repetition Test for Children), meta-phonological (Meta-Phonological skills Evaluation test), and phono-articulatory skills (non-word repetition). The same children were tested through Simo-syl assessment on their phonological and meta-phonological skills (e.g., recognise syllables and vowels and read syllables and words). The internal consistency of the computer-based tool was acceptable (Cronbach's alpha = .799). Children's scores obtained in the paper-based assessment and scores obtained in each task of the computer-based assessment were correlated. Significant and positive correlations emerged between all the tasks of the computer-based assessment and the scores obtained in the CMF (r = .287 - .311, p < .05) and in the correct sentences in the RCGB (r = .360 - .481, p < .01); non-word repetition standardised test significantly correlates with the reading tasks only (r = .329 - .350, p < .05). Further tasks should be included in the current version of Simo-syl to have a comprehensive and multi-dimensional approach when assessing children. However, such a tool represents a good chance for the teachers to early identifying language-related problems even in the school environment.

Keywords: assessment, computer-based, early identification, language-related skills

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Authors: Muizz Sanni-Anibire

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The 21st century has witnessed growing concerns for the protection of built facilities against natural and man-made disasters. Studies in earthquake resistant buildings, fire, and explosion resistant buildings now dominate the arena. To protect people and facilities from the effects of the explosion, reinforced concrete walls have been designed to be blast resistant. Understanding the performance of these walls is a key step in ensuring the safety of built facilities. Blast walls are mostly designed using simple techniques such as single degree of freedom (SDOF) method, despite the increasing use of multi-degree of freedom techniques such as the finite element method. This study is the first stage of a continuous research into the safety and reliability of blast walls. It presents the SDOF approach applied to the analysis of a concrete wall panel under three representative bomb situations. These are motorcycle 50 kg, car 400kg and also van with the capacity of 1500 kg of TNT explosive.

Keywords: blast wall, safety, protection, explosion

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Authors: Abhishek Kumar, Mohamed Awadein, Georg Gramse, Luyang Song, He Sun, Wolfgang Schofberger, Stefan Müllegger

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Electron transfer is a crucial part of chemical reactions which drive everyday processes. With the help of an electro-chemical radio frequency scanning tunneling microscopy (EC-RF-STM) setup, we are observing single electron mediated oxidation-reduction processes in molecules like ferrocene and transition metal corroles. Combining the techniques of scanning microwave microscopy and cyclic voltammetry allows us to monitor such processes with attoampere sensitivity. A systematic study of such phenomena would be critical to understanding the nano-scale behavior of catalysts, molecular sensors, and batteries relevant to the development of novel material and energy applications.

Keywords: radiofrequency, STM, cyclic voltammetry, ferrocene

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Authors: Mark Lindquist

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This paper presents preliminary results of exploratory empirical research investigating the effect of viewing 3D landscape visualizations in virtual reality compared to a computer monitor, and how sound impacts perception. Five landscape types were paired with three sound conditions (no sound, generic sound, realistic sound). Perceived realism, preference, recreational value, and biodiversity were evaluated in a controlled laboratory environment. Results indicate that sound has a larger perceptual impact than display mode regardless of sound source across all perceptual measures. The results are considered to assess how sound can impact landscape preference and spatiotemporal understanding. The paper concludes with a discussion of the impact on designers, planners, and the public and targets future research endeavors in this area.

Keywords: landscape experience, perception, soundscape, virtual reality

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Authors: Seyed Mohammad Mahdi Zamani, Kamran Behdinan

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In this study, a multiscale framework is performed to model the strength of Nextel fibers in presence of an atomistic scale pre-crack at finite temperatures. The bridging cell method (BCM) is the multiscale technique applied in this study, which decomposes the system into the atomistic, bridging and continuum domains; solves the whole system in a finite element framework; and incorporates temperature dependent calculations. Since Nextel is known to be structurally stable and retain 70% of its initial strength up to 1100°C; simulations are conducted at both of the room temperatures, 25°C, and fire temperatures, 1200°C. Two cases are modeled for a pre-crack present in either phases of alumina or mullite of the Nextel structure. The materials’ response is studied with respect to deformation behavior and ultimate tensile strength. Results show different crack growth trends for the two cases, and as the temperature increases, the crack growth resistance and material’s strength decrease.

Keywords: Nextel fibers, multiscale modeling, pre-crack, ultimate tensile strength

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Authors: Hao-Jun Hong, Jung-Tang Huang

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The world is gradually becoming an aging society, and with the lack of laboring forces, this phenomenon is affecting the nation’s economy growth. Although nursing centers are booming in recent years, the lack of medical resources are yet to be resolved, thus creating an innovative wearable medical device could be a vital solution. This research is focused on the design and development of a wearable device which obtains a more precise heart failure measurement than products on the market. The method used by the device is based on the sensor fusion and big data algorithm. From the test result, the modified structure of wearable device can significantly decrease the MA (Motion Artifact) and provide users a more cozy and accurate physical monitor experience.

Keywords: big data, heart failure, motion artifact, sensor fusion, wearable medical device

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Authors: Emily A. Gilbert, Jephte Sompud, Andy R. Mojiol, Cynthia B. Sompud, Alim Biun

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Gaya Island of Sabah is known for its wildlife and marine biodiversity. It has marks itself as one of the hot destinations of tourists from all around the world. Gaya Island tourism activities have contributed to Sabah’s economy revenue with the high number of tourists visiting the island. However, it has led to the increased anthropogenic noise derived from tourism activities. This may greatly interfere with the animals such as understory birds that rely on acoustic signals as a tool for communication. Many studies in other parts of the regions reveal that anthropogenic noise does decrease species richness of avian community. However, in Malaysia, published research regarding the impact of anthropogenic noise on the understory birds is still very lacking. This study was conducted in order to fill up this gap. This study aims to investigate the anthropogenic noise’s impact towards understory bird population. There were three sites within the Primary forest of Gaya Island that were chosen to sample the level of anthropogenic noise in relation to the understory bird population. Noise mapping method was used to measure the anthropogenic noise level and identify the zone with high anthropogenic noise level (> 60dB) and zone with low anthropogenic noise level (< 60dB) based on the standard threshold of noise level. The methods that were used for this study was solely mist netting and ring banding. This method was chosen as it can determine the diversity of the understory bird population in Gaya Island. The preliminary study was conducted from 15th to 26th April and 5th to 10th May 2015 whereby there were 2 mist nets that were set up at each of the zones within the selected site. The data was analyzed by using the descriptive analysis, presence and absence analysis, diversity indices and diversity t-test. Meanwhile, PAST software was used to analyze the obtain data. The results from this study present a total of 60 individuals that consisted of 12 species from 7 families of understory birds were recorded in three of the sites in Gaya Island. The Shannon-Wiener index shows that diversity of species in high anthropogenic noise zone and low anthropogenic noise zone were 1.573 and 2.009, respectively. However, the statistical analysis shows that there was no significant difference between these zones. Nevertheless, based on the presence and absence analysis, it shows that the species at the low anthropogenic noise zone was higher as compared to the high anthropogenic noise zone. Thus, this result indicates that there is an impact of anthropogenic noise on the population diversity of understory birds. There is still an urgent need to conduct an in-depth study by increasing the sample size in the selected sites in order to fully understand the impact of anthropogenic noise towards the understory birds population so that it can then be in cooperated into the wildlife management for a sustainable environment in Gaya Island.

Keywords: anthropogenic noise, biodiversity, Gaya Island, understory bird

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Authors: Dengpan Wu, Dan Liu

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In view of the present cloud security problem has increasingly become one of the major obstacles hindering the development of the cloud computing, put forward a kind of memory based on Xen cloud environment security isolation technology implementation. And based on Xen virtual machine monitor system, analysis of the model of memory virtualization is implemented, using Xen memory virtualization system mechanism of super calls and grant table, based on the virtual machine manager internal implementation of access control module (ACM) to design the security isolation system memory. Experiments show that, the system can effectively isolate different customer domain OS between illegal access to memory data.

Keywords: cloud security, memory isolation, xen, virtual machine

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Authors: Muslim Khan, Kenneth B. Jensen, Kevin A. Francesconi

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Trace amounts (ca 1 µg/L, 13 nM) of arsenic are present in sea water mostly as the oxyanion arsenate. In contrast, arsenic is present in marine biota (animals and algae) at very high levels (up to100,000 µg/kg) a significant portion of which is present as lipid-soluble compounds collectively termed arsenolipids. The complex nature of sea water presents an analytical challenge to detect trace compounds and monitor their environmental path. We developed a simple method using liquid-liquid extraction combined with HPLC-High Resolution Mass Spectrometer capable of detecting trace of arsenolipids (99 % of the sample matrix while recovering > 80 % of the six target arsenolipids with limit of detection of 0.003 µg/L.)

Keywords: arsenolipids, sea water, HPLC-high resolution mass spectrometry

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Authors: Gameel Abdelmageed

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Arabs have a rhetorical heritage which has greatly contributed to the monitoring and analyzing of the rhetoric of the Holy Quran, Hadith, and Arabic texts on poetry and oratory. But Arab scholars - as far as the researcher knows – have not contributed to monitoring and analyzing the rhetoric of digital Arabic discourse although it has prominence, particularly in social media and has strong effectiveness in the political and social life of Arab society. This discourse has made its impact by using very new rhetorical techniques in language, voice, image, painting and video clips which are known as “Multimedia” and belong to “Digital Rhetoric”. This study suggests that it is time to draw the attention of Arab scholars and invite them to monitor and analyze the rhetoric of digital Arabic discourse.

Keywords: digital discourse, digital rhetoric, Facebook, social media

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Authors: Lenka Bodnárová, Rudolf Hela, Michala Hubertová, Iveta Nováková

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This paper is concerning the issues of behaviour of lightweight expanded clay aggregates concrete exposed to high temperature. Lightweight aggregates from expanded clay are produced by firing of row material up to temperature 1050°C. Lightweight aggregates have suitable properties in terms of volume stability, when exposed to temperatures up to 1050°C, which could indicate their suitability for construction applications with higher risk of fire. The test samples were exposed to heat by using the standard temperature-time curve ISO 834. Negative changes in resulting mechanical properties, such as compressive strength, tensile strength, and flexural strength were evaluated. Also visual evaluation of the specimen was performed. On specimen exposed to excessive heat, an explosive spalling could be observed, due to evaporation of considerable amount of unbounded water from the inner structure of the concrete.

Keywords: expanded clay aggregate, explosive spalling, high temperature, lightweight concrete, temperature-time curve ISO 834

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Authors: Ankita Jadon, Sidi Souvi, Nathalie Girault, Denis Petitprez

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Safety requirements for Generation IV nuclear reactor designs, especially the new generation sodium-cooled fast reactors (SFR) require a risk-informed approach to model severe accidents (SA) and their consequences in case of outside release. In SFRs, aerosols are produced during a core disruptive accident when primary system sodium is ejected into the containment and burn in contact with the air; producing sodium aerosols. One of the key aspects of safety evaluation is the in-containment sodium aerosol behavior and their interaction with fission products. The study of the effects of sodium fires is essential for safety evaluation as the fire can both thermally damage the containment vessel and cause an overpressurization risk. Besides, during the fire, airborne fission product first dissolved in the primary sodium can be aerosolized or, as it can be the case for fission products, released under the gaseous form. The objective of this work is to study the interactions between sodium aerosols and fission products (Iodine, toxic and volatile, being the primary concern). Sodium fires resulting from an SA would produce aerosols consisting of sodium peroxides, hydroxides, carbonates, and bicarbonates. In addition to being toxic (in oxide form), this aerosol will then become radioactive. If such aerosols are leaked into the environment, they can pose a danger to the ecosystem. Depending on the chemical affinity of these chemical forms with fission products, the radiological consequences of an SA leading to containment leak tightness loss will also be affected. This work is split into two phases. Firstly, a method to theoretically understand the kinetics and thermodynamics of the heterogeneous reaction between sodium aerosols and fission products: I2 and HI are proposed. Ab-initio, density functional theory (DFT) calculations using Vienna ab-initio simulation package are carried out to develop an understanding of the surfaces of sodium carbonate (Na2CO3) aerosols and hence provide insight on its affinity towards iodine species. A comprehensive study of I2 and HI adsorption, as well as bicarbonate formation on the calculated lowest energy surface of Na2CO3, was performed which provided adsorption energies and description of the optimized configuration of adsorbate on the stable surface. Secondly, the heterogeneous reaction between (I2)g and Na2CO3 aerosols were investigated experimentally. To study this, (I2)g was generated by heating a permeation tube containing solid I2, and, passing it through a reaction chamber containing Na2CO3 aerosol deposit. The concentration of iodine was then measured at the exit of the reaction chamber. Preliminary observations indicate that there is an effective uptake of (I2)g on Na2CO3 surface, as suggested by our theoretical chemistry calculations. This work is the first step in addressing the gaps in knowledge of in-containment and atmospheric source term which are essential aspects of safety evaluation of SFR SA. In particular, this study is aimed to determine and characterize the radiological and chemical source term. These results will then provide useful insights for the developments of new models to be implemented in integrated computer simulation tool to analyze and evaluate SFR safety designs.

Keywords: iodine adsorption, sodium aerosols, sodium cooled reactor, DFT calculations, sodium carbonate

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

Procedia PDF Downloads 80

Authors: George Hanna Abdelmelek Henien

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Quality and safety issues are common in Ethiopia's food processing industry, which can negatively impact consumers' health and livelihoods. The country is known for its various agricultural products that are important to the economy. However, food quality and safety policies and management practices in the food processing industry have led to many health problems, foodborne illnesses and economic losses. This article aims to show the causes and consequences of food safety and quality problems in the food processing industry in Ethiopia and discuss possible solutions to solve them. One of the main reasons for food quality and safety in Ethiopia's food processing industry is the lack of adequate regulation and enforcement mechanisms. Inadequate food safety and quality policies have led to inefficiencies in food production. Additionally, the failure to monitor and enforce existing regulations has created a good opportunity for unscrupulous companies to engage in harmful practices that endanger the lives of citizens. The impact on food quality and safety is significant due to loss of life, high medical costs, and loss of consumer confidence in the food processing industry. Foodborne diseases such as diarrhoea, typhoid and cholera are common in Ethiopia, and food quality and safety play an important role in . Additionally, food recalls due to contamination or contamination often cause significant economic losses in the food processing industry. To solve these problems, the Ethiopian government began taking measures to improve food quality and safety in the food processing industry. One of the most prominent initiatives is the Ethiopian Food and Drug Administration (EFDA), which was established in 2010 to monitor and control the quality and safety of food and beverage products in the country. EFDA has implemented many measures to improve food safety, such as carrying out routine inspections, monitoring the import of food products and implementing labeling requirements. Another solution that can improve food quality and safety in the food processing industry in Ethiopia is the implementation of food safety management system (FSMS). FSMS is a set of procedures and policies designed to identify, assess and control food safety risks during food processing. Implementing a FSMS can help companies in the food processing industry identify and address potential risks before they harm consumers. Additionally, implementing an FSMS can help companies comply with current safety and security regulations. Consequently, improving food safety policy and management system in Ethiopia's food processing industry is important to protect people's health and improve the country's economy. . Addressing the root causes of food quality and safety and implementing practical solutions that can help improve the overall food safety and quality in the country, such as establishing regulatory bodies and implementing food management systems.

Keywords: food quality, food safety, policy, management system, food processing industry food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

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Authors: Kristina Amaleviciute, Ieva Jokubauskaite, Alvyra Slepetiene, Jonas Volungevicius, Inga Liaudanskiene

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The main task of this research was to investigate the chemical composition of the differently used soil in profiles. To identify the differences in the soil were investigated organic carbon (SOC) and its fractional composition: dissolved organic carbon (DOC), mobile humic acids (MHA) and C to N ratio of natural and anthropogenically affected Luvisols. Research object: natural and anthropogenically affected Luvisol, Akademija, Kedainiai, distr. Lithuania. Chemical analyses were carried out at the Chemical Research Laboratory of Institute of Agriculture, LAMMC. Soil samples for chemical analyses were taken from the genetics soil horizons. SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. For mobile humic acids (MHA) determination the extraction procedure was carried out using 0.1 M NaOH solution. Dissolved organic carbon (DOC) was analyzed using an ion chromatograph SKALAR. pH was measured in 1M H2O. N total was determined by Kjeldahl method. Results: Based on the obtained results, it can be stated that transformation of chemical composition is going through the genetic soil horizons. Morphology of the upper layers of soil profile which is formed under natural conditions was changed by anthropomorphic (agrogenic, urbogenic, technogenic and others) structure. Anthropogenic activities, mechanical and biochemical disturbances destroy the natural characteristics of soil formation and complicates the interpretation of soil development. Due to the intensive cultivation, the pH values of the curve equals (disappears acidification characteristic for E horizon) with natural Luvisol. Luvisols affected by agricultural activities was characterized by a decrease in the absolute amount of humic substances in separate horizons. But there was observed more sustainable, higher carbon sequestration and thicker storage of humic horizon compared with forest Luvisol. However, the average content of humic substances in the soil profile was lower. Soil organic carbon content in anthropogenic Luvisols was lower compared with the natural forest soil, but there was more evenly spread over in the wider thickness of accumulative horizon. These data suggest that the organization of geo-ecological declines and agroecological increases in Luvisols. Acknowledgement: This work was supported by the National Science Program ‘The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems’ [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agrogenization, dissolved organic carbon, luvisol, mobile humic acids, soil organic carbon

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Authors: Andrey V. Timofeev, Viktor M. Denisov

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A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture

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Authors: P. K. Guha Thakurta, Shouvik Roy, Bhawana Raj

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A congestion control scheme in mobile networks is proposed in this paper through a verification based model. The model proposed in this work is represented through performance metric like buffer Occupancy, latency and packet loss rate. Based on pre-defined values, each of the metric is introduced in terms of three different states. A Markov chain based model for the proposed work is introduced to monitor the occurrence of the corresponding state transitions. Thus, the estimation of the network status is obtained in terms of performance metric. In addition, the improved performance of our proposed model over existing works is shown with experimental results.

Keywords: congestion, mobile networks, buffer, delay, call drop, markov chain

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Authors: Sapan Bhatnagar, Danish Akhtar, Salman Ahmed, Asif Ekbal, Gufran Beig

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Particulates are the solid and liquid droplets present in the atmosphere, they have serious negative effects on human health and environment. PM10 and PM2.5 are so small that they can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Air Quality Index is an index tells us how clean or polluted our air is, and what associated health effects might be a concern for us. The AQI focuses on health affects you may experience within a few hours or days after breathing polluted air. The quality rating for each pollutant was calculated. The geometric mean of these quality ratings gives the Air Quality Index. The existing concentrations of pollutants were compared with ambient air quality standards.

Keywords: air quality index, particulate, respirable dust sampler, dust sampler

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Authors: J. S. Bedi, J. P. S. Gill, R. S. Aulakh, Prabhjit Kaur

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The present study was undertaken to monitor organochlorine, organophosphate and synthetic pyrethroid pesticide residues in butter and ghee samples collected from six different districts of Punjab. The estimation of pesticide residues was done by multiple residue analytical technique using gas chromatography equipped with GC-ECD and GC-FTD. The confirmation of residues was done on gas chromatography mass spectrometry in both SIM and Scan mode. Results indicated the presence of HCH and pp DDE as predominant contaminant in both butter and ghee even after their ban/restriction on usage in India. Residues of HCH were detected in 25.5 and 23.2 % samples of butter and ghee, respectively, while residues of pp DDE were recorded in 29.3 and 25.0 % butter and ghee samples, respectively. More importantly, the presence of endosulfan, cypermethrin, fenvalerate, deltamethrin and chlorpyrifos was observed in few butter and ghee samples indicating the serious concerns. The spatial variation of pesticide residues occurrence indicated the cotton belt of Punjab as most affected.

Keywords: butter, ghee, pesticides residues, Punjab

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Authors: Adhimoolam Saravana Kumar, K. N. Govindarajan, B. Devanand, R. Rajakumar

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The quality of Computed Tomography (CT) procedures has improved in recent years due to technological developments and increased diagnostic ability of CT scanners. Due to the fact that CT doses are the peak among diagnostic radiology practices, it is of great significance to be aware of patient’s CT radiation dose whenever a CT examination is preferred. CT radiation dose delivered to patients in the form of volume CT dose index (CTDIvol) values, is displayed on scanner monitors at the end of each examination and it is an important fact to assure that this information is accurate. The objective of this study was to estimate the CTDIvol values for great number of patients during the most frequent CT examinations, to study the comparison between CT dose monitor values and measured ones, as well as to highlight the fluctuation of CTDIvol values for the same CT examination at different centres and scanner models. The output CT dose indices measurements were carried out on single and multislice scanners for available kV, 5 mm slice thickness, 100 mA and FOV combination used. The 100 CT scanners were involved in this study. Data with regard to 15,000 examinations in patients, who underwent routine head, chest and abdomen CT were collected using a questionnaire sent to a large number of hospitals. Out of the 15,000 examinations, 5000 were head CT examinations, 5000 were chest CT examinations and 5000 were abdominal CT examinations. Comprehensive quality assurance (QA) was performed for all the machines involved in this work. Followed by QA, CT phantom dose measurements were carried out in South India using actual scanning parameters used clinically by the hospitals. From this study, we have measured the mean divergence between the measured and displayed CTDIvol values were 5.2, 8.4, and -5.7 for selected head, chest and abdomen procedures for protocols as mentioned above, respectively. Thus, this investigation revealed an observable change in CT practices, with a much wider range of studies being performed currently in South India. This reflects the improved capacity of CT scanners to scan longer scan lengths and at finer resolutions as permitted by helical and multislice technology. Also, some of the CT scanners have used smaller slice thickness for routine CT procedures to achieve better resolution and image quality. It leads to an increase in the patient radiation dose as well as the measured CTDIv, so it is suggested that such CT scanners should select appropriate slice thickness and scanning parameters in order to reduce the patient dose. If these routine scan parameters for head, chest and abdomen procedures are optimized than the dose indices would be optimal and lead to the lowering of the CT doses. In South Indian region all the CT machines were routinely tested for QA once in a year as per AERB requirements.

Keywords: CT dose index, weighted CTDI, volumetric CTDI, radiation dose

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Authors: Mona Loraine M. Barabad, Duckshin Park, Michael E. Versoza

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This study gives a comparison of the commuters’ exposure to particulate matter while taking different transportation mode (jeepney, motorcycle and taxi) in Cebu City, Philippines. A personal aerosol monitor (Sidepak AM510) was used for data collection; in addition, both temperature and humidity were also documented. Analysis was done and showed that Jeepney, which is the most commonly used mode in the country, has the highest PM collected having an average of 358.0μg/m^3, followed by the motorcycle with an average of 244.6 μg/m^3. The taxi recorded to have an average of 50.0 μg/m^3 and the lowest between the microenvironments sampled. The outcome was greatly significant to the traffic volume together with several factors that could possibly affect the result. However, due to the lack of time and resources, the data collected was limited. Further and thorough investigation should be implemented to provide more essential information regarding the subject.

Keywords: air quality, particulate matter, Philippines, transportation

Procedia PDF Downloads 355

Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Ponshano Kaselekela, Simooya O. Oscar, Lunshano Boyd

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The Copperbelt University Health Services (CBUHS) was designated by the Zambia Medicines Regulatory Authority (ZAMRA), formally the Pharmaceutical Regulatory Authority (PRA) as a regional pharmacovigilance centre to carryout activities of drug safety monitoring in four provinces in Zambia. CBUHS’s mandate included stimulating the reporting of adverse drug reactions (ADRs), as well as collecting and collating ADR reports from health institutions in the four provinces. This report covers the researchers’ experiences from May 2008 to September, 2016. The main objectives are 1) to monitor ADRs in the Zambian population, 2) to disseminate information to all health professionals in the region advising that the CBU health was a centre for reporting ADRs in the region, 3) to monitor polypharmacy as well as the benefit-risk profile of medicines, 4) to generate independent, evidence based recommendations on the safety of medicines, 5) to support ZAMRA in formulating safety related regulatory decisions for medicines, and 6) to communicate findings with all key stakeholders. The methodology involved monthly visits, beginning in early May 2008 to September, 2016, by the CBUHS to health institutions in the programme areas. Activities included holding discussions with health workers, distribution of ADR forms and collection of ADRs reports. These reports, once collected, were documented and assessed at the CBUHS. A report was then prepared for ZAMRA on quarterly basis. At ZAMRA, serious ADRs were noted and recommendations made to the Ministry of Health of the Republic of Zambia. The results show that 2,600 ADRs reports were received at the pharmacovigilance regional centre. Most of the ADRs reports that received were due to antiretroviral drugs, as well as a few from anti-malarial drugs like Artemether/Lumefantrine – Coartem®. Three hundred and twelve ADRs were entered in the Uppsala Monitoring Centre WHO Vigiflow for further analysis. It was concluded that in general, 2008-16 were exciting years for the pharmacovigilance group at CBUHS. From a very tentative beginning, a lot of strides were made and contacts established with healthcare facilities in the region. The researchers were encouraged by the support received from the Copperbelt University management, the motivation provided by ZAMRA and most importantly the enthusiasm of health workers in all the health care facilities visited. As a centre for drug safety in Zambia, the results show it achieves its objectives for monitoring ADRs, Pharmacovigilance (drug safety monitoring), and activities of monitoring ADRs as well as preventing them. However, the centre faces critical challenges caused by erratic funding that prevents the smooth running of the programme.

Keywords: adverse drug reactions, drug safety, monitoring, pharmacovigilance

Procedia PDF Downloads 191

Authors: M. M. Mekkakia, M. P Luong, A. Arab

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These controlling the water content of compaction are a major concern of fundamental civil engineers. Also, the knowledge of the fundamentals of the behaviour of compacted clay soils is essential to predict and quantify the effects of a change in water content. The study of unsaturated soils is a very complex area which several studies are directed to in recent years. Our job work is to perform tests of Proctor, Oedometer and shear, on samples of unsaturated clay in order to see the influence of water content on the compressibility and the shear strength. The samples were prepared at different amounts of water from water content to optimum water contents close to saturation. This study thus allowed us to measure and monitor the parameters of compressibility and shear strength as a function of water content.

Keywords: laboratory tests, clay, unsaturated soil, atterberg limits, compaction, compressibility, shear

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

Procedia PDF Downloads 421

Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

Procedia PDF Downloads 389

Authors: Waraporn Wimuktalop

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This research will select regions which are vulnerable to flooding in different level. Mathematical principles will be systematically and rationally utilized as a tool to solve problems of selection the regions. Therefore the method called Multiple Criteria Decision Making (MCDM) has been chosen by having two analysis standards, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and AHP (Analytic Hierarchy Process). There are three criterions that have been considered in this research. The first criterion is climate which is the rainfall. The second criterion is geography which is the height above mean sea level. The last criterion is the land utilization which both forest and agriculture use. The study found that the South has the highest risk of flooding, then the East, the Centre, the North-East, the West and the North, respectively.

Keywords: multiple criteria decision making, TOPSIS, analytic hierarchy process, flooding

Procedia PDF Downloads 217

Authors: Wilaiwan Sornpoon, Sébastien Bonnet, Savitri Garivait

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Continuous measurements of greenhouse gases (GHGs) emitted from soils are required to understand diurnal and seasonal variations in soil emissions and related mechanism. This understanding plays an important role in appropriate quantification and assessment of the overall change in soil carbon flow and budget. This study proposes to monitor GHGs emissions from soil under sugarcane cultivation in Thailand. The measurements were conducted over 379 days. The results showed that the total net amount of GHGs emitted from sugarcane plantation soil amounts to 36 Mg CO2eq ha-1. Carbon dioxide (CO2) and nitrous oxide (N2O) were found to be the main contributors to the emissions. For methane (CH4), the net emission was found to be almost zero. The measurement results also confirmed that soil moisture content and GHGs emissions are positively correlated.

Keywords: soil, GHG emission, sugarcane, agriculture, Thailand

Procedia PDF Downloads 415