Search results for: minimum data set

Authors: C. B. Abhilash, Kavi Mahesh

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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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Authors: Hafida Merzouk

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Urinary tract infections are among the most serious public health issues in all age groups. Thus, the empirical therapy should based on local levels of resistance, as indicated in several studies from different countries, to effectively avoid the emergence of multidrug-resistant bacterial strains and recurrent infections. Numerous effective antibiotic treatments are available, but wouldbe ineffective for treating recurrent cystitis caused by a urinary tract infection, as well as the emergence of drug resistance. That iswhy the aim of this study was to highlight the antibacterial and the antioxidant activity of 11 medicinal plants used traditionally in Algeria against E. coli, the most responsible urinary tract infections. First, the extraction of total polyphenols with aqueous acetone showed variable yields. The highest yield was obtained by Asplenium trichomanes with 27%, followed by Petroselinum crispum and Ciannamomum cassia with an equal yield of 21%. Artemisia herba-alba gave the lowest yield (9%). The extracts of different plants showed variable contents of phenolic compounds. Reducing power and DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging activity revealed that most of the extracts studied had significant activity. The anti-free radical activity was very high in the extract of A splenium adiantum-nigrum compared with the other extracts studied, but Petroselinum crispum and Parietaria officinalis had the lowest reducing activity; Antibacterial activity was determined on E. coli strainsusing the diffusion, MICs (Minimum Inhibitory Concentrations) and MBCs (Minimum Bactericidal concentrations) methods. The strains tested were sensitive to most extracts studied, except Asplenium adiantum-nigrum extract, for which both strains showed resistance.

Keywords: E. coli, medicinal plants, phenolic compounds, urinary infections

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Authors: M. A. Hernández-Ceballos, E. G. San Miguel, C. Galán, J. P. Bolívar

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The evolution of 7Be and 210Pb activity concentrations in surface air along the Guadalquivir valley (southern Iberian Peninsula) is presented in this study. Samples collected for 48 h, every fifteen days, from September 2012 to November 2013 at two sampling sites (Huelva city in the mouth and Cordoba city in the middle (located 250 km far away)), are used to 1) analysing the spatial variability and 2) understanding the influence of wind conditions on 7Be and 210Pb. Similar average concentrations were registered along the valley. The mean 7Be activity concentration was 4.46 ± 0.21 mBq/m3 at Huelva and 4.33 ± 0.20 mBq/m3 at Cordoba, although registering higher maximum and minimum values at Cordoba (9.44 mBq/m3 and 1.80 mBq/m3) than at Huelva (7.95 mBq/m3 and 1.04 mBq/m3). No significant differences were observed in the 210Pb mean activity concentrations between Cordoba (0.40 ± 0.04 mBq/m3) and Huelva (0.35 ± 0.04 mBq/m3), although the maximum (1.10 mBq/m3 and 0.87 mBq/m3) and minimum (0.02 mBq/m3 and 0.04 mBq/m3) values were recorded in Cordoba. Although similar average concentrations were obtained in both sites, the temporal evolution of both natural radionuclides presents differences between them. The meteorological analysis of two sampling periods, in which large differences on 7Be and 210Pb concentrations are observed, indicates the different impact of surface and upper wind dynamics. The analysis reveals the different impact of the two sea-land breeze patterns usually observed along the valley (pure and non-pure) and the corresponding air masses at higher layers associated with each one. The pure, with short development (around 30 km inland) and increasing accumulation process, favours high concentrations of both radionuclides in Huelva (coastal site), while the non-pure, with winds sweeping the valley until arrive to Cordoba (250 km far away), causes high activity values at this site. These results reveal the impact of mesoscale conditions on these two natural radionuclides, and the importance of these circulations on its spatial and temporal variability.

Keywords: 7Be, 210Pb, air masses, mesoscale process

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Authors: Sina Gharevali

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Staphylococcus aureus is one of the most important factors for nosocomial infections and infections acquired in a hospital setting role as is. Drug-resistant bacteria methicillin, which in 1961 was reported in many parts of the world, Made the role as the last drug, vancomycin, in the treatment of infections caused by the Staphylococcus aureus chain be taken into consideration. The aim of this study was to evaluate the antimicrobial effects of copper nanoparticles and compared it with antibiotics on Staphylococcus aureus resistant to vancomycin in vitro and animal model. In this study, this test was performed, and the most effective antibiotic for vancomycin-resistant Staphylococcus aureus was determined by disk diffusion method. After various concentrations of copper nanoparticles and antibiotics were prepared and vancomycin resistant Staphylococcus aureus bacteria with serial dilution method for determining antibiotic ciprofloxacin. Minimum Inhibitory Concentration and Minimum Bactericidal Concentrationcopper nanoparticles was performed. The agar dilution method for bacterial growth in different concentrations of copper nanoparticles and antibiotics ciprofloxacin was performed. The agar dilution method for bacterial growth in different concentrations of copper nanoparticles and antibiotics ciprofloxacin was performed. Then the broth dilution method for the antibiotic ciprofloxacin, nano-particles, and nano-particles of copper and copper-established antibiotic synergy MIC and MBC were obtained. MBC was obtained from the experimental animal model test method, and the results were compared. The results showed that copper nanoparticles compared with the antibiotic ciprofloxacin in vitro and animal model more effective in inhibiting the growth of Staphylococcus aureus resistant to vancomycin and ciprofloxacin and extent of the impact of the Synthetic effect of lower copper nanoparticles. Which can then be used to treat clinical research as a candidate.

Keywords: nanoparticles, copper, staphylococcus, aureus

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Authors: Magdalena Barbara Kaziuk, Waldemar Kosiba, Marek Jan Kuzniewski

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Introduction: Vitamin D3 has a proven pleiotropic effect, not only responsible for calcium and phosphate management, but also influencing normal functioning of the whole body. Aim: Evaluation of vitamin D3 resources and its effect on a nutritional status, obesity type and glomerular filtration in kidney transplant recipients. Methods: Group of 152 (81 women and 71 men, average age 47.8 ± 11.6 years) patients with a functioning renal transplant their body composition was assessed using the bioimpendance method (BIA) and anthropometric measurements more than 3 months after the transplant. The nutritional status and the obesity type were determined with the Waist to Height Ratio (WHtR) and the Waist to Hip Ratio (WHR). 25- Hydroxyvitamin D3 (25 (OH)D3) was determined, together with its correlation with the obesity type and the glomerular filtration rate (eGFR) calculated with the MDRD formula. Results: The mean 25 (OH)D3 level was 20.4 ng/ml. 30ng/ml was considered as a minimum correct level 22,7% of patients from the study group were classified to be a correct body weight, 56,7% of participants had an android type and 20,6% had a gynoid type. Significant correlation was observed between 25 (OH)D3 deficiency and abdominal obesity (p < 0.005) in patients. Furthermore, a statistically significant relationship was demonstrated between the 25 (OH)D3 levels and eGFR in patients after a kidney transplant. Patients with an android body type had lower eGFR versus those with the gynoid body type (p=0.004). Conclusions: Correct diet in patients after a kidney transplant determines minimum recommended serum levels of vitamin D3. Excessive fatty tissue, low levels of 25 (OH)D3), may be a predictor for android obesity and renal injury; therefore, correct diet and pharmacological management together with physical activities adapted to the physical fitness level of a patient are necessary.

Keywords: kidney transplantation, glomerular filtration rate, obesity, vitamin D3

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Authors: Dina Ahmad Alkhodary

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This study aimed to investigate the practices of Data Mining on the telecommunication companies in Jordan, from the viewpoint of the respondents. In order to achieve the goal of the study, and test the validity of hypotheses, the researcher has designed a questionnaire to collect data from managers and staff members from main department in the researched companies. The results shows improvements stages of the telecommunications companies towered Data Mining.

Keywords: data, mining, development, business

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Authors: Taisiia Gorshkova

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Since the 1980s, spatial correlation models have been used more often to model regional indicators. An increasingly popular method for studying regional indicators is modeling taking into account spatial relationships between objects that are part of the same economic zone. In 2000s the new class of model – spatial vector autoregressions was developed. The main difference between standard and spatial vector autoregressions is that in the spatial VAR (SpVAR), the values of indicators at time t may depend on the values of explanatory variables at the same time t in neighboring regions and on the values of explanatory variables at time t-k in neighboring regions. Thus, VAR is a special case of SpVAR in the absence of spatial lags, and the spatial panel data model is a special case of spatial VAR in the absence of time lags. Two specifications of SpVAR were applied to Russian regional data for 2000-2017. The values of GRP and regional CPI are used as endogenous variables. The lags of GRP, CPI and the unemployment rate were used as explanatory variables. For comparison purposes, the standard VAR without spatial correlation was used as “naïve” model. In the first specification of SpVAR the unemployment rate and the values of depending variables, GRP and CPI, in neighboring regions at the same moment of time t were included in equations for GRP and CPI respectively. To account for the values of indicators in neighboring regions, the adjacency weight matrix is used, in which regions with a common sea or land border are assigned a value of 1, and the rest - 0. In the second specification the values of depending variables in neighboring regions at the moment of time t were replaced by these values in the previous time moment t-1. According to the results obtained, when inflation and GRP of neighbors are added into the model both inflation and GRP are significantly affected by their previous values, and inflation is also positively affected by an increase in unemployment in the previous period and negatively affected by an increase in GRP in the previous period, which corresponds to economic theory. GRP is not affected by either the inflation lag or the unemployment lag. When the model takes into account lagged values of GRP and inflation in neighboring regions, the results of inflation modeling are practically unchanged: all indicators except the unemployment lag are significant at a 5% significance level. For GRP, in turn, GRP lags in neighboring regions also become significant at a 5% significance level. For both spatial and “naïve” VARs the RMSE were calculated. The minimum RMSE are obtained via SpVAR with lagged explanatory variables. Thus, according to the results of the study, it can be concluded that SpVARs can accurately model both the actual values of macro indicators (particularly CPI and GRP) and the general situation in the regions

Keywords: forecasting, regional data, spatial econometrics, vector autoregression

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Authors: Mona Hajirasouli

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Abstract: introduction: Antimicrobial compounds are important in the first line of the host defense system of many animal species. Material and methods: In the present study antibacterial activity of crude and proteins precipitate of hemolymph and crude hepatopancreas extracts from Portunus segnis and Grapsus albolineatus against a range of 6 different bacterial strains evaluated. Amoxicillin as a positive control were also used. Results: Maximum activity (15.9 mm) was recorded in male haemolymph of p.segnis against Entrobacter and minimum activity (7 mm) was recorded against Serratia marcescens, Enterobacter sp. and Proteus mirabilis from different extracts of Grapsus albolineatus. Data were analyzed using independent-t in SPSS version 16, and results indicate that there were not any significant differences between hemolymph and hepatopancreas extracts of 2 species. Discussion: Antimicrobial activity has been reported earlier in the hemolymph of some brachyuran crabs such as: blue crab Callinectes sapidus, mud crab Scylla serrata, Ocypode macrocera and Carcinus maenas. This study shows that hemolymph and hepatopancreas of Portunus segnis and Grapsus albolineatus may potential antibiotics.

Keywords: brachyuran, Portunus segnis, Grapsus albolineatus, hemolymph, hepatopancreas, antibacterial

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Authors: Amal M. Alrayes

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Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance.Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: data quality, performance, system quality, Kingdom of Bahrain

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research and transfers of big data are not confined to a particular jurisdiction, but there is a lack of clarity regarding the legal requirements for importing and exporting such data. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Tejinder Singh

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Information system is the flow of data from different levels to different directions for decision making and data operations in information system (IS). Data can be violated by different manner like manual or technical errors, data tampering or loss of integrity. Security system called firewall of IS is effected by such type of violations. The flow of data among various levels of Information System is done by networking system. The flow of data on network is in form of packets or frames. To protect these packets from unauthorized access, virus attacks, and to maintain the integrity level, network security is an important factor. To protect the data to get pirated, various security techniques are used. This paper represents the various security techniques and signifies different harmful attacks with the help of detailed data analysis. This paper will be beneficial for the organizations to make the system more secure, effective, and beneficial for future decisions making.

Keywords: information systems, data integrity, TCP/IP network, vulnerability, decision, data

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Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

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The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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Authors: Yonosuke Murayama

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We have developed and studied a metastable beta Ti alloy, which shows super-elasticity and low Young’s modulus according to the phase stability of its beta phase. The super-elasticity and low Young’s modulus are required in a wide range of applications in various industrial fields. For example, the metallic implant with low Young’s modulus and non-toxicity is desirable because the large difference of Young’s modulus between the human bone and the implant material may cause a stress-shielding phenomenon. We have investigated the role of Sn and Al in metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys. The metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys form during quenching from the beta field at high temperature. While Cr and V act as beta stabilizers, Sn and Al are considered as elements to suppress the athermal omega phase produced during quenching. The athermal omega phase degrades the properties of super-elasticity and Young’s modulus. Although Al and Sn as single elements are considered as an alpha stabilizer and neutral, respectively, Sn and Al acted also as beta stabilizers when added simultaneously with beta stabilized element of Cr or V in this experiment. The quenched microstructure of Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys shifts from martensitic structure to beta single-phase structure with increasing Cr or V. The Young’s modulus of Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys decreased and then increased with increasing Cr or V, each showing its own minimum value of Young's modulus respectively. The composition of the alloy with the minimum Young’s modulus is a near border composition where the quenched microstructure shifts from martensite to beta. The border composition of Ti-Cr-Sn and Ti-V-Sn alloys required only less amount of each beta stabilizer, Cr or V, than Ti-Cr-Al and Ti-V-Al alloys. This indicates that the effect of Sn as a beta stabilizer is stronger than Al. Sn and Al influenced the competitive relation between stress-induced martensitic transformation and slip deformation. Thus, super-elastic properties of metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys varied depending on the alloyed element, Sn or Al.

Keywords: metastable beta Ti alloy, super-elasticity, low Young’s modulus, stress-induced martensitic transformation, beta stabilized element

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Authors: Ekaterina S. Marchenko, Gulsharat A. Baigonakova, Kirill M. Dubovikov, Igor A. Khlusov

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NiTi alloys combine biomechanical and biochemical properties. This makes them a perfect candidate for medical applications. However, there is a serious problem with these alloys, such as the release of Ni from the matrix. Ni ions are known to be toxic to living tissues and leach from the matrix into the surrounding implant tissues due to corrosion after prolonged use. To prevent the release of Ni ions, corrosive strong coatings are usually used. Titanium nitride-based coatings are perfect corrosion inhibitors and also have good bioactive properties. However, there is an opportunity to improve the biochemical compatibility of the surface by depositing another layer. This layer can consist of elements such as calcium and phosphorus. The Ca and P ions form different calcium phosphate phases, which are present in the mineral part of human bones. We therefore believe that these elements must promote osteogenesis and osteointegration. In view of the above, the aim of this study is to investigate the effect of crystallinity on the biocompatibility of a two-layer coating deposited on NiTi substrate by sputtering. The first step of the research, apart from the NiTi polishing, is the layer-by-layer deposition of Ti-Ni-Ti by magnetron sputtering and the subsequent synthesis of this composite in an N atmosphere at 900 °C. The total thickness of the corrosion resistant layer is 150 nm. Plasma assisted RF sputtering was then used to deposit a bioactive film on the titanium nitride layer. A Ca-P powder target was used to obtain such a film. We deposited three types of Ca-P layers with different crystallinity and compared them in terms of cytotoxicity. One group of samples had no Ca-P coating and was used as a control. We obtained different crystallinity by varying the sputtering parameters such as bias voltage, plasma source current and pressure. XRD analysis showed that all coatings are calcium phosphate, but the sample obtained at maximum bias and plasma source current and minimum pressure has the most intense peaks from the coating phase. SEM and EDS showed that all three coatings have a homogeneous and dense structure without cracks and consist of calcium, phosphorus and oxygen. Cytotoxic tests carried out on three types of samples with Ca-P coatings and a control group showed that the control sample and the sample with Ca-P coating obtained at maximum bias voltage and plasma source current and minimum pressure had the lowest number of dead cells on the surface, around 11 ± 4%. Two other types of samples with Ca-P coating have 40 ± 9% and 21 ± 7% dead cells on the surface. It can therefore be concluded that these two sputtering modes have a negative effect on the corrosion resistance of the whole samples. The third sputtering mode does not affect the corrosion resistance and has the same level of cytotoxicity as the control. It can be concluded that the most suitable sputtering mode is the third with maximum bias voltage and plasma source current and minimum pressure.

Keywords: calcium phosphate coating, cytotoxicity, NiTi alloy, two-layer coating

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Authors: Haley Gershon

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The transition from using fossil fuel-based building material to formulating eco-friendly and biobased building materials plays a key role in sustainable building. The growing demand on a global level for biobased materials in the building and construction industries heightens the importance of carbon-14 testing, an analytical method used to determine the percentage of biobased content that comprises a material’s ingredients. This presentation will focus on the use of carbon-14 analysis within the building materials sector. Carbon-14, also known as radiocarbon, is a weakly radioactive isotope present in all living organisms. Any fossil material older than 50,000 years will not contain any carbon-14 content. The radiocarbon method is thus used to determine the amount of carbon-14 content present in a given sample. Carbon-14 testing is performed according to ASTM D6866, a standard test method developed specifically for biobased content determination of material in solid, liquid, or gaseous form, which requires radiocarbon dating. Samples are combusted and converted into a solid graphite form and then pressed onto a metal disc and mounted onto a wheel of an accelerator mass spectrometer (AMS) machine for the analysis. The AMS instrument is used in order to count the amount of carbon-14 present. By submitting samples for carbon-14 analysis, manufacturers of building materials can confirm the biobased content of ingredients used. Biobased testing through carbon-14 analysis reports results as percent biobased content, indicating the percentage of ingredients coming from biomass sourced carbon versus fossil carbon. The analysis is performed according to standardized methods such as ASTM D6866, ISO 16620, and EN 16640. Products 100% sourced from plants, animals, or microbiological material are therefore 100% biobased, while products sourced only from fossil fuel material are 0% biobased. Any result in between 0% and 100% biobased indicates that there is a mixture of both biomass-derived and fossil fuel-derived sources. Furthermore, biobased testing for building materials allows manufacturers to submit eligible material for certification and eco-label programs such as the United States Department of Agriculture (USDA) BioPreferred Program. This program includes a voluntary labeling initiative for biobased products, in which companies may apply to receive and display the USDA Certified Biobased Product label, stating third-party verification and displaying a product’s percentage of biobased content. The USDA program includes a specific category for Building Materials. In order to qualify for the biobased certification under this product category, examples of product criteria that must be met include minimum 62% biobased content for wall coverings, minimum 25% biobased content for lumber, and a minimum 91% biobased content for floor coverings (non-carpet). As a result, consumers can easily identify plant-based products in the marketplace.

Keywords: carbon-14 testing, biobased, biobased content, radiocarbon dating, accelerator mass spectrometry, AMS, materials

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Authors: Nazia Zaffar, Alam Khan, Abdul Haq, Malik Badshah

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Pakistan is an agricultural country. The increasing population leads to an increase in demand for food. A large number of crops are infected by different microbes, and nutrient deficiency of soil adversely affects the yield of crops. Furthermore, the use of chemical fertilizers like Nitrogen, Phosphorus, Potassium (NPK) Urea, and Diammonium phosphate (DAP) and pesticides have environmental consequences. Therefore, there is an urgent need to explore alternative renewable and sustainable biofertilizers. Maize is one of the top growing crops in Pakistan, but it has low yield compared to other countries due to deficiency of organic matter, widespread nutrients deficiency (phosphorus and nitrogen), unbalanced use of fertilizers and various fungal diseases. In order to get rid of all these disadvantages, Digestate emerged as a win-win opportunity for the control of a few plant diseases and a replacement for the chemical fertilizers. The present study was designed to investigate the effect of Anerobic digestate on Antifungal Activity and in different parameters of Maize. The antifungal activity, minimum inhibitory concentration (MIC), and minimum fungicidal concentration (MFC) against selected phytopathogens (Colletotrichum coccodis, Pythium ultimum, Phytophthora capsci, Rhizoctonia solani, Bipolaris oryzae and Fusarium Fujikuroi) were determined by microtiter plate method. The effect of various fertilizers in different growth parameters height, diameter, chlorophyll, leaf area, biomass, and yield were studied in field experiments. The extracts from anaerobic digestate have shown antifungal activity against selected phytopathogens, the highest activity was noted against P. ultimum, the MIC activity was high in case of P. ultimum and B. oryzae. The present study concludes that anaerobic digestate have a positive effect on maize growth and yield as well as an antifungal activity which can be potentially a good biofertilizer.

Keywords: anaerobic digestate, antifungal activity, MIC, phytopathogens

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Authors: Melis Inalpulat, Levent Genc

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Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), and Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased % 29 between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32 °C in 1984 and 27-33 °C in 2014. Minimum temperature of agricultural lands was increased 3 °C and reached to 23 °C. In contrast, maximum temperature of A class decreased to 41 °C from 44 °C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2 °C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: census data, landsat, land surface temperature (LST), land use land cover (LULC)

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Authors: Ernest Nweke

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The work of Professional Accountants and Corporate governance are synonymous and cannot be divorced from each other. Organizations, profit and non-profit alike cannot implement sound corporate practices without inputs from Professional Accountants. In today’s dynamic corporate world, good corporate governance practice is a sine qua non. More so, following the corporate failures of the past decades like Enron and WorldCom, governments around the world, including Mongolia are becoming more proactive in ensuring sound corporate governance mechanisms. In the past fifteen years, the Mongolian government has taken several measures to establish and strengthen internal corporate governance structures in firms. This paper highlights the role of professional accountants and auditors play in ensuring that good corporate governance mechanisms are entrenched in listed companies in Mongolia. Both primary and secondary data are utilized in this research. In collection of primary data, Delphi method was used, securing responses from only knowledgeable senior employees, top managers, and some CEOs. Using this method, a total of 107 top-level company employees and executives randomly selected from 22 companies were surveyed; maximum of 5 and minimum of 4 from each company. These companies cut across several sectors. It was concluded that Professional Accountants play key roles in setting and maintaining firm governance. They do this by ensuring full compliance with all the requirements of good and sound corporate governance, establishing reporting, monitoring and evaluating standards, assisting in the setting up of proper controls, efficient and effective audit systems, sound fraud risk management and putting in place an overall vision for the enterprise. Companies with effective corporate governance mechanisms are usually strong and fraud-resilient. It was also discovered that companies with big 4 audit firms tend to have better governance structures in Mongolia.

Keywords: accountants, corporate disclosure, corporate failure, corporate governance

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Authors: Luvisa Kusuma, Panji Yudha Prakasa

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Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

Procedia PDF Downloads 357

Authors: Prabhsharan Singh, Rahul Sindhu, Piyush Sikka

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The steering system is an integral part and medium through which the driver communicates with the vehicle and terrain, hence the most suitable steering geometry as per requirements must be chosen. The function of the chosen steering geometry of an All-Terrain Vehicle (ATV) is to provide the desired understeer gradient, minimum tire slippage, expected weight transfer during turning as these are requirements for a good steering geometry of a BAJA ATV. This research paper focuses on choosing the best suitable steering geometry for BAJA ATV tracks by reasoning the working principle and using fundamental trigonometric functions for obtaining these geometries on the same vehicle itself, namely Ackermann, Anti- Ackermann, Parallel Ackermann. Full vehicle analysis was carried out on Adams Car Analysis software, and graphical results were obtained for various parameters. Steering geometries were achieved by using a single versatile knuckle for frontward and rearward tie-rod placement and were practically tested with the help of data acquisition systems set up on the ATV. Each was having certain characteristics, setup, and parameters were observed for the BAJA ATV, and correlations were created between analytical and practical values.

Keywords: all-terrain vehicle, Ackermann, Adams car, Baja Sae, steering geometry, steering system, tire slip, traction, understeer gradient

Procedia PDF Downloads 154

Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

Procedia PDF Downloads 158

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 226

Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

Procedia PDF Downloads 307

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 362

Authors: Muhammad Asim Nazir

Abstract:

The investigations reported in this manuscript were carried on the screening of one hundred and seventy-eight chickpea germplasm lines/cultivars against wilt disease, caused by Fusarium oxysporum f. sp. ciceris. The screening was conducted in vivo (field) conditions. The field screening was accompanied with the study of some epidemiological factors affecting the occurrence and severity of the disease. Among the epidemiological factors maximum temperature range (28-40°C), minimum temperature range (12-24°C), relative humidity (19-44%), soil temperature (26-41°C) and soil moisture range (19-34°C) was studied for affecting the disease incidence/severity. The results revealed that air temperature was positively correlated with diseases. Soil temperature data revealed that in all cultivars disease incidence was maximum as 39°C. Most of the plants show 40-50% disease incidence. Disease incidence decreased at 33.5°C. The result of correlation of relative humidity of air and wilt incidence revealed that all cultivars/lines were negatively correlated with relative humidity. With increasing relative humidity wilt incidence decreased and vice versa.

Keywords: chickpea, epidemiological, screening, disease

Procedia PDF Downloads 641

Authors: Muhd. Barzani Gasim, Mohd. Ekhwan Toriman, Mohd. Khairul Amri Kamarudin, Azman Azid, Siti Humaira Haron, Muhammad Hafiz Md. Saad

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Malaysia is a country in Southeast Asia that constantly exposed to flooding and landslide. The disaster has caused some troubles such loss of property, loss of life and discomfort of people involved. This problem occurs as a result of climate change leading to increased stream flow rate as a result of disruption to regional hydrological cycles. The aim of the study is to determine hydrologic processes in the east coasts of Peninsular Malaysia, especially in Kelantan Basin. Parameterized to account for the spatial and temporal variability of basin characteristics and their responses to climate variability. For hydrological modeling of the basin, the Soil and Water Assessment Tool (SWAT) model such as relief, soil type, and its use, and historical daily time series of climate and river flow rates are studied. The interpretation of Landsat map/land uses will be applied in this study. The combined of SWAT and climate models, the system will be predicted an increase in future scenario climate precipitation, increase in surface runoff, increase in recharge and increase in the total water yield. As a result, this model has successfully developed the basin analysis by demonstrating analyzing hydrographs visually, good estimates of minimum and maximum flows and severe floods observed during calibration and validation periods.

Keywords: east coasts of Peninsular Malaysia, Kelantan river basin, minimum and maximum flows, severe floods, SWAT model

Procedia PDF Downloads 262