Search results for: toxicity data

Authors: Hitesh Tahbildar

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The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

Procedia PDF Downloads 391

Authors: Farrin Ghorbanalavi, Nihal Arıoğlu

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The concept of enhancing mechanical /thermal/physical properties of architectural materials is being practiced for over five decades. In comparison with other approaches, the current nanotechnology era equally attracted the structural scientists, engineers, and industries. It simply promises that using building blocks with dimensions in the nano size range makes it possible to design and develop new multi-functional materials. This research focuses on understanding the effects of nanotechnology on the building facade and new facade concepts based on the new possibilities of nanotechnology. Mentioned factors are very prosperous for the comfort as well as sustainability of the building itself. Furthermore, the study suggests that the potential for energy conservation and reduced waste, toxicity, non-renewable resource consumption, and carbon emissions through the architectural applications of nanotechnologies significant. More clearly, it provides us the information about what does the future hold for surface structures.

Keywords: sustainable, nano materials, façade, energy efficiency

Procedia PDF Downloads 549

Authors: V. Ivanov, J. Chu, V. Stabnikov

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Different biotechnological methods for the production of construction materials and for the performance of construction processes in situ are developing within a new scientific discipline of Construction Biotechnology. The aim of this research was to develop and test new biotechnologies and biotechnological grouts for the minimization of the hydraulic conductivity of the fractured rocks and porous soil. This problem is essential to minimize flow rate of groundwater into the construction sites, the tunneling space before and after excavation, inside levies, as well as to stop water seepage from the aquaculture ponds, agricultural channels, radioactive waste or toxic chemicals storage sites, from the landfills or from the soil-polluted sites. The conventional fine or ultrafine cement grouts or chemical grouts have such restrictions as high cost, viscosity, sometime toxicity but the biogrouts, which are based on microbial or enzymatic activities and some not expensive inorganic reagents, could be more suitable in many cases because of lower cost and low or zero toxicity. Due to these advantages, development of biotechnologies for biogrouting is going exponentially. However, most popular at present biogrout, which is based on activity of urease- producing bacteria initiating crystallization of calcium carbonate from calcium salt has such disadvantages as production of toxic ammonium/ammonia and development of high pH. Therefore, the aim of our studies was development and testing of new biogrouts that are environmentally friendly and have low cost suitable for large scale geotechnical, construction, and environmental applications. New microbial biotechnologies have been studied and tested in the sand columns, fissured rock samples, in 1 m3 tank with sand, and in the pack of stone sheets that were the models of the porous soil and fractured rocks. Several biotechnological methods showed positive results: 1) biogrouting using sequential desaturation of sand by injection of denitrifying bacteria and medium following with biocementation using urease-producing bacteria, urea and calcium salt decreased hydraulic conductivity of sand to 2×10-7 ms-1 after 17 days of treatment and consumed almost three times less reagents than conventional calcium-and urea-based biogrouting; 2) biogrouting using slime-producing bacteria decreased hydraulic conductivity of sand to 1x10-6 ms-1 after 15 days of treatment; 3) biogrouting of the rocks with the width of the fissures 65×10-6 m using calcium bicarbonate solution, that was produced from CaCO3 and CO2 under 30 bars pressure, decreased hydraulic conductivity of the fissured rocks to 2×10-7 ms-1 after 5 days of treatment. These bioclogging technologies could have a lot of advantages over conventional construction materials and processes and can be used in geotechnical engineering, agriculture and aquaculture, and for the environmental protection.

Keywords: biocementation, bioclogging, biogrouting, fractured rocks, porous soil, tunneling space

Procedia PDF Downloads 199

Authors: Hatice Kübra Koç

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For academia, collecting reliable and valid data is one of the most significant issues for researchers. However, it is not the same procedure for all different target groups; meanwhile, during data collection from teenagers, young adults, or adults, researchers can use common data collection tools such as questionnaires, interviews, and semi-structured interviews; yet, for young learners and very young ones, these reliable and valid data collection tools cannot be easily designed or applied by the researchers. In this study, firstly, common data collection tools are examined for ‘very young’ and ‘young learners’ participant groups since it is thought that the quality and efficiency of an academic study is mainly based on its valid and correct data collection and data analysis procedure. Secondly, two different data collection instruments for very young and young learners are stated as discussing the efficacy of them. Finally, a suggested data collection tool – a performance-based questionnaire- which is specifically developed for ‘very young’ and ‘young learners’ participant groups in the field of teaching English to young learners as a foreign language is presented in this current study. The designing procedure and suggested items/factors for the suggested data collection tool are accordingly revealed at the end of the study to help researchers have studied with young and very learners.

Keywords: data collection instruments, performance-based questionnaire, young learners, very young learners

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Authors: Yaxin Bi

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Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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Authors: Pirakorn Sukonthaman, Paphitchaya Temphattharachok, Warangkana Thammasanya, Kraichart Tantrakarnarpa, Tanongson Tientavorn

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Agriculture is the main occupation in Thailand. Excessive amount of pesticides are used to increase the products but are toxic to human body. In 2009, Bureau of Epidemiology received 1,691 cases reported with pesticides toxicity (2.66:100,000) which 10.61 % of them is caused by Organophosphate. The purposes are to find factors associated with pesticides used and plasma cholinesterase level and other emerging issues that previous studies did not explain among agricultural workers in Baan Na Yao, Chachoengsao, Thailand. This research was an exploratory mixed method study. Qualitative interviews and quantitative questionnaires were used together in order to gather information from the agricultural workers (mainly cassava and rice farming) directly exposed to pesticides within 2 months simultaneously. Qualitative participants were selected by purposive sampling and a total survey for quantitative ones. The quantitative data was statistically analyzed by using multiple logistic regression model. Qualitative data was transcribed verbatim and thematically analyzed. For qualitative study, 15 participants were interviewed and 300/323 participants (92.88%) were given questionnaires, of which were 175 male and 125 female and 113 among them were spraymen. The prevalence of abnormal plasma cholinesterase level was 92.28% (Safe 7.72% Risky 49.33% and Unsafe 42.95%). Participants with inappropriate behaviors during spraying had a significant association with plasma cholinesterase level (95%CI=1.399-14.858) but other factors such as age, gender, education, attitude and knowledge had no association. They also had encountered various symptoms from pesticides such as fatigue (61%), vertigo (59.67%) and headache (58.86%), etc. Although they had high knowledge and attitude they still had poor behaviors. Moreover, our qualitative component showed that though they had worn the personal protective equipment (PPE) regularly, their PPE was not standard. Not only substandard PPE, but also there were obstacles of wearing such as the hot climate and inconvenience. They misunderstood their symptoms from using pesticides as allergy. Therefore, they did not seek for proper medical check-ups and treatment. This research revealed almost all of the participants have abnormal levels of plasma cholinesterase related especially those with poor behaviors. They also wore PPE but inadequately and misunderstood the symptoms produced by organophosphate use as allergy. Therefore, they did not seek for medical treatment. Occupation health education, modification of PPE and periodic medical checking are ways to make agricultural workers concern and know if there is any progression in a long term.

Keywords: pesticides, plasma cholinesterase level, spraymen, agricultural workers

Procedia PDF Downloads 345

Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

Procedia PDF Downloads 469

Authors: N. F. Hamid, A. Kipar, J. Stewart, D. J. Antoine, B. K. Park, D. P. Williams

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Acetaminophen (APAP) is a widely used analgesic that is safe at therapeutic doses. The mouse model of APAP has been extensively used for studies on pathogenesis and intervention of drug induced liver injury based on the CytP450 mediated formation of N-acetyl-p-benzo-quinoneimine and, more recently, as model for mechanism based biomarkers. Delay of the fasted CD1 mice to rebound to the basal level of hepatic GSH compare to fed mice is reported in this study. Histologically, 15 hours fasted mice prior to APAP treatment leading to overall more intense cell loss with no evidence of apoptosis as compared to non-fasted mice, where the apoptotic cells were clearly seen on cleaved caspase-3 immunostaining. After 15 hours post APAP administration, hepatocytes underwent stage of recovery with evidence of mitotic figures in fed mice and return to completely no histological difference to control at 24 hours. On the contrary, the evidence of ongoing cells damage and inflammatory cells infiltration are still present on fasted mice until the end of the study. To further measure the regenerative capacity of the hepatocytes, the inflammatory mediators of cytokines that involved in the progression or regression of the toxicity like TNF-α and IL-6 in liver and spleen using RT-qPCR were also included. Yet, quantification of proliferating cell nuclear antigen (PCNA) has demonstrated the time for hepatic regenerative in fasted is longer than that to fed mice. Together, these data would probably confirm that fasting prior to APAP treatment does not only modulate liver injury, but could have further effects to delay subsequent regeneration of the hepatocytes.

Keywords: acetaminophen, liver, proliferating cell nuclear antigen, regeneration, apoptosis

Procedia PDF Downloads 416

Authors: Hsien-Tsen Wang

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Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

Procedia PDF Downloads 82

Authors: John Q. Todd

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Given that modern equipment can provide comprehensive health, status, and error condition data via built-in sensors, maintenance organizations have a new and valuable source of insight to take advantage of. This presentation will expose what these data payloads might look like and how they can be filtered, visualized, calculated into metrics, used for machine learning, and generate alerts for further action.

Keywords: condition based maintenance, equipment data, metrics, alerts

Procedia PDF Downloads 169

Authors: Konstantza Tonova, Ivan Svinyarov, Milen G. Bogdanov

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Ionic liquids consisting of pairs of imidazolium or phosphonium cation and chloride or saccharinate anion were synthesized and compared with respect to their extraction efficiency towards the fermentative L-lactic acid. The acid partitioning in the equilibrated biphasic systems of ionic liquid and water was quantified through the extraction degree and the partition coefficient. The water transfer from the aqueous into the ionic liquid-rich phase was also always followed. The effect of pH, which determines the state of lactic acid in the aqueous source was studied. The effect of other salting-out substances that modify the ionic liquid/water equilibrium was also investigated in view to reveal the best liquid-liquid system with respect to low toxicity, high extraction and back extraction efficiencies and performance simplicity.

Keywords: ionic liquids, biphasic system, extraction, lactic acid

Procedia PDF Downloads 465

Authors: Dragana Calic

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The openness, availability and the sheer volume of big data have provided, what some regard as, an invaluable and rich dataset. Researchers, businesses, advertising agencies, medical institutions, to name only a few, collect, share, and analyze this data to enable their processes and decision making. However, there are important ethical considerations associated with the use of big data. The rapidly evolving nature of online technologies has overtaken the many legislative, privacy, and ethical frameworks and principles that exist. For example, should we obtain consent to use people’s online data, and under what circumstances can privacy considerations be overridden? Current guidance on how to appropriately and ethically handle big data is inconsistent. Consequently, this paper focuses on two quite distinct but related ethical considerations that are at the core of the use of big data for research purposes. They include empowering the producers of data and empowering researchers who want to study big data. The first consideration focuses on informed consent which is at the core of empowering producers of data. In this paper, we discuss some of the complexities associated with informed consent and consider studies of producers’ perceptions to inform research ethics guidelines and practice. The second consideration focuses on the researcher. Similarly, we explore studies that focus on researchers’ perceptions and experiences.

Keywords: big data, ethics, producers’ perceptions, researchers’ perceptions

Procedia PDF Downloads 276

Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

Procedia PDF Downloads 455

Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

Procedia PDF Downloads 458

Authors: Islam Zeb

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Water of poor quality has a potential of probable contamination and a way to spread pollutant in the field and surrounding environment. A number of comprehensive reviews articles have been published which highlight irrigation water as a source of pathogenic microorganisms and heavy metals toxicity that leads to chronic diseases in human. Here a study was plan to determine the microbial status of irrigation water collected from various location of district Swat in various months. The analyses were carried out at Environmental Horticulture Laboratory, Department of Horticulture, The University of Agriculture Peshawar, during the year 2018 – 19. The experiment was laid out in Randomized Complete Block Design (RCBD) with two factors and three replicates. Factor A consist of different locations, and factor B represent various months. The results of microbial status for various locations in irrigation water showed the highest value for Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella, and Listeria (9.05, 8.54, 6.01, 5.84, and 5.03 log cfu L-1 respectively) for samples collected from mingora location, whereas the lowest values for Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella and Listeria (6.70, 6.38, 4.47, 4.42 and 3.77 log cfu L-1 respectively) were observed for matta location. Data for various months showed maximum Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella, and Listeria (12.01, 11.70, 8.46, 8.41, and 6.88 log cfu L-1, respectively) were noted for the irrigation water samples collected in May/June whereas the lowest range for Total Bacterial Count, Enterobacteriacea, E. coli, Salmonella and Listeria (4.41, 4.08, 2.61, 2.55 and 3.39 log cfu L-1 respectively) were observed in Jan/Feb. A significant interaction was found for all the studied parameters it was concluded that maximum bacterial groups were recorded in the months of May/June from Mingora location, it might be due to favorable weather condition.

Keywords: contamination, irrigation water, microbes, SWAT, various months

Procedia PDF Downloads 58

Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

Procedia PDF Downloads 358

Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

Procedia PDF Downloads 73

Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

Procedia PDF Downloads 278

Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

Procedia PDF Downloads 86

Authors: Houneïda Benbouzid, Houria Berrebbah, Mohammed-Réda Djebar

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The toxicological impacts of the increasing number of synthetic compounds present in the aquatic environment are assessed predominantly in laboratory studies where test organisms are exposed to a range of concentrations of single compounds. The bio-indicator Paramecium sp., characterized by a short life cycle, rapid multiplication and normal behavior that may be affected by the presence of pollutants. We therefore investigated the inhibitory effect of a newly synthesized acaricide: the chlorfenapyr tested at concentrations of 250, 300, and 350 µM on a pure culture of Paramecium sp. during 6 day. Paramecia treated with different concentrations of Chlorfenapyr illustrate strong inhibition of cell growth from the second day of treatment. Low levels of glutathione, increased glutathione S-transferase and the decrease in respiratory metabolism, recorded in the presence of different concentrations of Chlorfenapyr, involve the activation of detoxification system.

Keywords: Paramecium sp., chlorfenapyr, oxidative enzymes, detoxification

Procedia PDF Downloads 356

Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: M. Djekoun, H. Berrebah, M. R. Djebar

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Fusarium wilt is destructive disease of cereal crops with small grains. It affects yields but also the quality of the crop and economic losses arising are often very heavy. Chemical control is currently one of the most effective ways to fight against these diseases. In this study, the efficacy of three fungicides (tebuconazole, thiram, and fludioxonil-difenoconazole mixture) was tested. In vitro, on the phytopathogenic Fusarium spp. isolated from seeds of wheat. The active ingredients were tested at different concentrations: 0.06, 1.39, 2.79, 5.58, and 11.16 mg/l for tebuconazole, 0.035, 0.052, 0.105, 0.21, and 0.42 mg/l for thiram and finally, for the mixture fludioxonil-difenoconazole 4 concentrations were tested: 0.05, 0.1, 0.5 and 1 mg/l. Toxicity responses were expressed as effective concentration, which inhibits mycelial growth by 50%, (EC50). Of the three selected fungicides, thirame proved to be the most effective with EC50 value of the order of 0,15 mg/l followed by the mixture of fludioxonil-difenoconazole with 0,27mg/l and finally tebuconazole with a value of 3.79 mg/l.

Keywords: Fusarium spp., thiram, tebuconazole, fludioxonil, difenoconazole, percentage of inhibition, EC50

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Authors: Inkyu Kim, SangMan Moon

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This IEEE 802.11b protocol provides up to 11Mbps data rate, whereas aerospace industry wants to seek higher data rate COTS data link system in the UAV. The Total Maximum Throughput (TMT) and delay time are studied on many researchers in the past years This paper provides theoretical data throughput performance of UAV formation flight data link using the existing 802.11b performance theory. We operate the UAV formation flight with more than 30 quad copters with 802.11b protocol. We may be predicting that UAV formation flight numbers have to bound data link protocol performance limitations.

Keywords: UAV datalink, UAV formation flight datalink, UAV WLAN datalink application, UAV IEEE 802.11b datalink application

Procedia PDF Downloads 376

Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

Procedia PDF Downloads 790

Authors: Bing Yan

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Nanomaterials are widely used in various industrial sectors, biomedicine, and more than 1300 consumer products. Although there is still no standard safety regulation, their potential toxicity is a major concern worldwide. We discovered that nanoparticles target and enter human cells1, perturb cellular signaling pathways2, affect various cell functions3, and cause malfunctions in animals4,5. Because the majority of atoms in nanoparticles are on the surface, chemistry modification on their surface may change their biological properties significantly. We modified nanoparticle surface using nano-combinatorial chemistry library approach6. Novel nanoparticles were discovered to exhibit significantly reduced toxicity6,7, enhance cancer targeting ability8, or re-program cellular signaling machineries7. Using computational chemistry, quantitative nanostructure-activity relationship (QNAR) is established and predictive models have been built to predict biocompatible nanoparticles.

Keywords: nanoparticle, nanotoxicity, nano-bio, nano-combinatorial chemistry, nanoparticle library

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

Procedia PDF Downloads 252

Authors: Rajesh A. Rane, Shital S. Naphade, Rajshekhar Karpoormath

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Thiozolidin-4-one, a mimic of thiazolobenzimidazole (TBZ) has drawn many attentions due to its potent and selective inhibition against the HIV-1 and low toxicity by binding to the allosteric site of the reverse transcriptase (RT) as a non-nucleoside RT inhibitor (NNRTI). Similarly, marine bromopyrrole alkaloids are well known for their diverse array of anti-infective properties. Hence, we have reported synthesis and in vitro HIV-1 RT inhibitory activity of a series of 4-thiazolidinone-bromopyrrole alkaloid hybrids tethered with amide linker. The results of in vitro HIV-1 RT kit assay showed that some of the compounds, such as 4c, 4d, and 4i could effectively inhibit RT activity. Among them, compounds 4c having 4-chlorophenyl substituted 4-thiazolidione ring was the best one with the IC50 value of 0.26 µM. The sturdy emerges with key structure-activity relationship that pyrrole-NH-free core benefited inhibition against HIV-1 RT inhibition. This study identified conjugate 4c with potent activity and selectivity as promising compound for further drug development to HIV.

Keywords: antiviral drugs, bromopyrrole alkaloids, HIV-1 RT inhibition, 4-thiazolidinone

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Authors: Malinee Pongsavee

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Sodium formate is the chemical substance used for food additive. Catalase is the important antioxidative enzyme in protecting the cell from oxidative damage by reactive oxygen species (ROS). The resultant level of oxidative stress in sodium formatetreated lymphocytes was investigated. The sodium formate concentrations of 0.05, 0.1, 0.2, 0.4 and 0.6 mg/mL were treated in human lymphocytes for 12 hours. After 12 treated hours, catalase activity change was measured in sodium formate-treated lymphocytes. The results showed that the sodium formate concentrations of 0.4 and 0.6 mg/mL significantly decreased catalase activities in lymphocytes (P < 0.05). The change of catalase activity in sodium formate-treated lymphocytes may be the oxidative damage marker for detect sodium formate exposure in human.

Keywords: sodium formate, catalase activity, oxidative damage marker, toxicity

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Authors: Zeba Mahmood

Abstract:

The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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