Search results for: negative data

Authors: N. Thawornwisit, P. Pradoo, S. Nuypree, L. Jarukasetrporn, S. Jitpukdeebodintra

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Objective: The aim of this study was to evaluate the duration of the Enterococcus faecalis (E. faecalis) penetration into the gap between root canal wall and filling material at a 3 to 6 mm distance from the cementoenamel junction (CEJ) in the dislodged temporary filling, in vitro. Material and methods: Thirty-four single root canal mandibular premolars were divided into two experimental groups (N = 15) and one negative control (N = 4). Root canals were prepared and obturated with gutta-percha using lateral condensation technique, X-ray checked, and sterilized. Leakages were set up using the modified bacterial leakage model, and E. faecalis was used as a microbial marker. Leakages were evaluated at 3 and 7 days by culturing gutta-percha and dentine drilled from a 3-6 mm distance from CEJ. Broth turbidity was recorded and compared. Result: All four negative control and the 3-day experimental group showed no broth turbidity. For the 7-day experimental group, there was 33.3% leakage. Conclusion: Penetration of E. faecalis into the gap between root canal wall and filling material at a 3 to 6 mm distance from CEJ in the dislodged temporary filling were not found at three days. However, at seven days of exposure, bacteria could penetrate into the interface of the root canal and filling materials.

Keywords: coronal leakage, bacterial leakage model, enterococcus faecalis

Procedia PDF Downloads 89

Authors: Romeo Botes, Imelda Smit

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In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

Procedia PDF Downloads 238

Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

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In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

Procedia PDF Downloads 473

Authors: Shu-Hsi Ho

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The problems of aging and number of widowed peers gradually rise in Taiwan. It is worth to concern the related issues for elderly after the death of a spouse. Hence, this study is to examine the impact of spousal death on the surviving spouse’s self-perceived health and mental health for the elderly in Taiwan. A cross section data design and ordered logistic regression models are applied to investigate whether marriage is associated significantly to self-perceived health and mental health for the widowed older Taiwanese. The results indicate that widowed marriage shows significant negative effects on self-perceived health and mental health regardless of widows or widowers. Among them, widows might be more likely to show worse mental health than widowers. The belief confirms that marriage provides effective sources to promote self-perceived health and mental health, particularly for females. In addition, since the social welfare system is not perfect in Taiwan, the findings also suggest that family and social support reveal strongly association with the self-perceived health and mental health for the widows and widowers elderly.

Keywords: logistic regression models, self-perceived health, widow, widower

Procedia PDF Downloads 457

Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

Procedia PDF Downloads 298

Authors: V. Baweja, K. K. Gupta, V. Dubey, C. Keshavam

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Antimicrobial activity of six indigenous plants such as Tulsi Ocimum sanctum, Neem Azadirachta indica, Aloe vera, Turmeric Curcuma longa, Lantana Lantana camara, and Clove Syzygium aromaticum was assessed against the gut microbiota of the dengue fever mosquito Aedes aegypti, keeping in view that the presence of midgut bacteria may affect the ability of the vector to transmit pathogens. Eleven different types of bacterial clones were isolated from the midgut of lab-reared fourth instar larvae of Aedes aegypti and were grown on LB agar medium at an optimum temperature of 25 ºC. Identification of these bacteria was done on the basis of their colony characteristic such as colony size, shape, opacity, elevation, consistency, and growth. Light microscopic studies of the gut microbiota revealed dominance of Gram-negative cocci over gram positive cocci and bacilli and Gram-negative bacilli. Identification of species was done by chemical characterization of the colonies. Crude extracts of all test plants were screened for their antimicrobial activities against gut microbiota by disc diffusion assay. The zone of exclusion seen after 24 hr of incubation in different assays revealed the most potent antibacterial activities in neem followed by clove and turmeric. Lantana and Aloe vera were least effective.

Keywords: plant extract, aedes, dengue, antimicrobial activity

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Authors: Sibonakaliso Shadrack Nhlabathi

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In South Africa local governments which are charged with the provision of services and amenities, frequently, face challenges of public protests against what the public perceives to be poor services. Public protests are common, even though the Integrated Development Plan, a central public participation document, which informs local government planning and resources management, ought to be a reflection of the voices of the beneficiary communities. The Integrated Development Plan concept –which evolved from the international discourse on governance, planning, and urban management of the 1990s, and, which bears similarities to the UK’s approaches to urban management and planning– is a significant concept in the planning practice in South Africa. Against this backdrop of the spread of public protests and the supposedly public participation in IDP formulation, this study investigated the extent to which residents of the city of uMhlathuze municipality, South Africa, could use Geographical Information Systems (GIS) Story Maps to enhance public participation in the provision of services and amenities. To this effect, this study collected and analysed data obtained through interactive web maps or hard copy maps; this map data was accompanied by research participants’ attributes data. Research participants identified positive or negative service delivery areas. Positive places were the places which the residents represented as good infrastructural, and amenities areas and weak places were marked as poor amenities. Participants then located each of their identified strong or weak places as points on the GIS Story Maps or on hard copy maps of the city. The information which participants provided was subsequently analysed to produce maps of patterns of service provision. In this way, the study succeeded to identify places that needed attention regarding delivery of services and amenities. Thus, this study advanced service provision through GIS Story Maps.

Keywords: GIS, IPD, South Africa, story maps

Procedia PDF Downloads 123

Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

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Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

Procedia PDF Downloads 502

Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

Procedia PDF Downloads 422

Authors: B. Seetanah, H. Neeliah

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This paper investigates the relationship among energy, emissions and economic growth in Mauritius in the presence of trade activities, with capital and labour as other control variables. Using annual data from 1960 to 2011, it is found that the variables are non-stationary and cointegrated. The relationship among the various variables are thus examined in a dynamic VECM framework. Our empirical results comply with the growth hypothesis. Output elasticities of 0.17, 0.25 and 0.43 show that increases in energy consumption cause increases in economic growth, capital accumulation and trade in the long run. We also found that CO2 negatively affects output, but has no significant effect on trade. Findings for the long-run generally tend to tally with those in the short-run. Interestingly we found that energy consumption has a significant impact on CO2 emissions. Our results tend to suggest that implementing energy conservation strategies to mitigate the negative impact of CO2 emissions can dent economic growth, and that promoting cleaner energy production could be a better alternative for Mauritius.

Keywords: energy, emissions, economic growth, export, VECM

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Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

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In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

Procedia PDF Downloads 284

Authors: Anushtha Saxena

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This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

Procedia PDF Downloads 111

Authors: Mohamed M. Elsherbiny

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Social Avoidance is one of the most important problems that face a good number of disabled students. It results from the negative attitudes of non-disabled students, teachers and others. Some of the past research has shown that non-disabled individuals hold negative attitudes toward persons with disabilities. The present study aims to alleviate Social Avoidance by applying the Cognitive Behavioral Intervention. 24 Blind students aged 19–24 (university students) were randomly chosen we compared an experimental group (consisted of 12 students) who went through the intervention program, with a control group (12 students also) who did not go through such intervention. We used the Social Avoidance and Distress Scale (SADS) to assess social anxiety and distress behavior. The author used many techniques of cognitive behavioral intervention such as modeling, cognitive restructuring, extension, contingency contracts, self-monitoring, assertiveness training, role play, encouragement and others. Statistically, T-test was employed to test the research hypothesis. Result showed that there is a significance difference between the experimental group and the control group after the intervention and also at the follow up stages of the Social Avoidance and Distress Scale. Also for the experimental group, there is a significance difference before the intervention and the follow up stages for the scale. Results showed that, there is a decrease in social avoidance. Accordingly, cognitive behavioral intervention program was successful in decreasing social avoidance for blind students.

Keywords: social avoidance, cognitive behavioral intervention, blind disability, disability

Procedia PDF Downloads 405

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

Procedia PDF Downloads 194

Authors: Zhi Huang

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This study follows on from previous survey and focus group research exploring the effective teaching process in a translation classroom in Australian universities through case study method. The data analysis draws on social constructivist theory in translation teaching and focuses on teaching process aiming to discover how effective translation teachers conduct teaching in the classroom. The results suggest that effective teaching requires the teacher to have ability in four aspects: classroom management, classroom pedagogy, classroom communication, and teacher roles. Effective translation teachers are able to control the whole learning process, facilitate students in independent learning, guide students to be more critical about translation, giving both positive and negative feedback for students to reflect on their own, and being supportive, patient and encouraging to students for better classroom communication and learning outcomes. This study can be applied to other teachers in translation so that they can reflect on their own teaching in their education contexts and strive for being a more qualified translation teacher and achieving teaching effectiveness.

Keywords: case study, classroom observation, classroom teaching, effective translation teaching, teacher effectiveness

Procedia PDF Downloads 418

Authors: Kenneth Harper

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Blockchain technology presents solutions for managing healthcare data, addressing critical challenges in privacy, integrity, and access. This paper explores how privacy-preserving technologies, such as zero-knowledge proofs (ZKPs) and homomorphic encryption (HE), enhance decentralized healthcare platforms by enabling secure computations and patient data protection. An examination of the mathematical foundations of these methods, their practical applications, and how they meet the evolving demands of healthcare data security is unveiled. Using real-world examples, this research highlights industry-leading implementations and offers a roadmap for future applications in secure, decentralized healthcare ecosystems.

Keywords: blockchain, cryptography, data privacy, decentralized data management, differential privacy, healthcare, healthcare data security, homomorphic encryption, privacy-preserving technologies, secure computations, zero-knowledge proofs

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Authors: Leila Mohammadi

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This paper presents the impact of persuasive communication implemented by fertility clinics websites, and how this information influences women at their decision-making for undertaking this procedure. The influential factors for women decisions to do social egg freezing (SEF) are analyzed from a framing theory perspective, with a specific focus on the impact of persuasive information on women’s decision making. This study follows a quantitative approach. A two-phase survey has been conducted to examine the interest rate to undertake SEF. In the first phase, a questionnaire was available during a month (May 2015) to women to answer whether or not they knew enough information of this process, with a total of 230 answers. The second phase took place in the two last weeks of July 2015. All the respondents were invited to a seminars called ‘All about egg freezing’ and afretwards they were requested to answer the second questionnaire. After the seminar, in which they were given an extensive amount of information about egg freezing, a total of 115 women replied the questionnaire. The collected data during this process were analyzed using descriptive statistics. Most of the respondents changed their opinion in the second questionaire which was after receiving information. Although in the first questionnaire their self-evaluation of having knowledge about this process and the implemented technologies was very high, they realized that they still need to access more information from different sources in order to be able to make a decision. The study reached the conclusion that persuasive and framed information by clinics would affect the decisions of these women. Despite the reasons women have to do egg freezing and their motivations behind it, providing people necessary information and unprejudiced data about this process (such as its positive and negative aspects, requirements, suppositions, possibilities and consequences) would help them to make a more precise and reasonable decision about what they are buying.

Keywords: decision making, fertility clinics, framing theory, persuasive information, social egg freezing

Procedia PDF Downloads 246

Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

Procedia PDF Downloads 450

Authors: Farrukh Javed, Krzysztof Podgórski

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We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

Procedia PDF Downloads 380

Authors: Piyanee Klainin-Yobas, Debbie Ramirez, Zenaida Fernandez, Jenneth Sarmiento, Wareerat Thanoi, Jeanette Ignacio, Ying Lau

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In many countries, university students experience various stressors that may negatively affect their psychological well-being (PWB). Hence, they are at risk for physical and mental problems. This research aimed to examine the predicting effects of mindfulness, self-efficacy, and social support on psychological well-being among undergraduate students. A non-experimental research was conducted at a university in the Philippines. All students enrolled in undergraduate programs were eligible for this study unless they had chronic medical or mental health problems. Power analysis was used to calculate an adequate sample size and a convenience sampling of 630 was recruited. Data were collected through online self-reported questionnaires from year 2013 to 2015. All self-reported scales used in this study had sound psychometric properties. Descriptive statistics, correlational analyses, and structural equation modeling were performed to analyze the research data. Results showed that the participants were mostly Filipino, female, Christian, and in Schools of Nursing. Mindfulness, self-efficacy, support from family, support from friends, and support from significant others were significant predictors of psychological well-being. Mindfulness was the strongest predictor of positive psychological well-being whereas self-efficacy was the strongest predictor of negative psychological well-being. In conclusion, findings from this study add knowledge to the existing literature regarding the predictors of psychological well-being. Psychosocial interventions, with the focus on strengthening mindfulness and self-efficacy, could be delivered to undergraduate students to help them enhance psychological well-being. More studies can be undertaken to test the interventions and multi-centered research can be conducted to enhance generalizability of research findings.

Keywords: mindfulness, self-efficacy, social support, psychological wellbeing

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Authors: Anya Glikman, Anastasia Gorodzeisky

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Since the late 1990th labor immigration and its consequences on the society have become one of the most frequently discussed and debated issues in Russia. Social scientists point that the negative attitudes towards immigrants among Russian majority population is widespread, and their level, at least, twice as high as their level in most other European countries. Moreover, recent study by Gorodzeisky, Glikman and Maskyleison (2014) demonstrates that the two sets of individual level predictors of anti-foreigner sentiment – socio-economic status and conservative views and ideologies – that have been repeatedly proved in research in Western countries are not effective in predicting of anti-foreigner sentiment in Post-Socialist Russia. Apparently, the social mechanisms underlying anti-foreigner sentiment in Western countries, which are characterized by stable regimes and relatively long immigration histories, do not play a significant role in the explanation of anti-foreigner sentiment in Post-Socialist Russia. The present study aims to examine alternative possible sources of anti-foreigner sentiment in Russia while controlling for socio-economic position of individuals and conservative views. More specifically, following the research literature on the topic worldwide, we aim to examine whether and to what extent human values (such as tradition, universalism, safety and power), ethnic residential segregation, fear of crime and exposure to mass media affect anti-foreigner sentiments in Russia. To do so, we estimate a series of multivariate regression equations using the data obtained from 2012 European Social Survey. The national representative sample consists of 2337 Russian born respondents. Descriptive results reveal that about 60% percent of Russians view the impact of immigrants on the country in negative terms. Further preliminary analysis show that anti-foreigner sentiments are associated with exposer to mass media as well as with fear of crime. Specifically, respondents who devoted more time watching news on TV channels and respondents who express higher levels of fear of crime tend to report higher levels of anti-immigrants sentiments. The findings would be discussed in light of sociological perspective and the context of Russian society.

Keywords: anti-immigrant sentiments, fear of crime, human values, mass media, Russia

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

Procedia PDF Downloads 271

Authors: Ruixia Liu

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Qinghai-Tibet Plateau has an important influence on the precipitation of its lower reaches. Data from remote sensing has itself advantage and numerical prediction model which assimilates RS data will be better than other. We got the assimilation data of MHS and terrestrial and sounding from GSI, and introduced the result into WRF, then got the result of RH and precipitation forecast. We found that assimilating MHS and terrestrial and sounding made the forecast on precipitation, area and the center of the precipitation more accurate by comparing the result of 1h,6h,12h, and 24h. Analyzing the difference of the initial field, we knew that the data assimilating about Qinghai-Tibet Plateau influence its lower reaches forecast by affecting on initial temperature and RH.

Keywords: Qinghai-Tibet Plateau, precipitation, data assimilation, GSI

Procedia PDF Downloads 228

Authors: Ryotaro Ishikawa

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INTRODUCTION: Post-traumatic stress disorder (PTSD) is a psychiatric label for a collection of psychological symptoms following a traumatic event. PTSD is as a result of a traumatic experience such as rape or sexual assault. A victim may have PTSD if she/he has experienced the following symptoms for at least a month: a) Stressor, b) Intrusion symptoms, c) Avoidance, d) Negative alterations in cognitions and mood, e) Alterations in arousal and reactivity. Studies on the cognitive theory of PTSD emphasized the roles of (a) negative appraisals of trauma memories in maintaining the symptomatology of PTSD, and (b) disorganized trauma memories in the development of PTSD. Mental contamination is primarily caused by experiences involving humans (e.g. violators or perpetrators) as opposed to substances (e.g. dirt or bodily fluids). Feelings of mental contamination may evoke following experiences of ill-treatment, sexual assault, domination, degradation, manipulation, betrayal, or humiliation. Some studies have demonstrated that traumatic thoughts related to sexual assault are particularly strong predictors of mental contamination. Treatment protocols based on cognitive-behavioral therapy appear to be beneficial in reducing the severity of PTSD and mental contamination. Studies on the cognitive theory of PTSD emphasized the roles of (A) negative appraisals of trauma memories in maintaining the symptomatology of PTSD, and (B) disorganized trauma memories in the development of PTSD. We will demonstrate a feasibility study of individual CBT for PTSD and mental contamination in Japanese clinical settings. METHOD: The single-arm trial is a group setting CBT intervention. The primary outcome is the self-rated Posttraumatic Stress Diagnostic Scale, with secondary measurements of depressive severity and mental pollution questionnaire. Assessments are conducted at baseline, after a waiting period before CBT, during CBT, and after CBT. RESULTS: Participants are eligible for the study and complete the outcome measures at all assessment points. In our hypothesis, receiving CBT would lead to improvements in primary and secondary PTSD severity. CONCLUSION: We will demonstrate a feasibility study of individual CBT for PTSD and mental contamination in Japanese clinical settings. Our treatment would achieve favorable treatment outcomes for PTSD with mental contamination in Japanese clinical settings.

Keywords: CBT, cognitive theory, PTSD, mental pollution

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Authors: Wayde Veldman, Ozlem T. Bishop, Igor Polikarpov

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In bacteria, mono and disaccharides are phosphorylated during uptake into the cell via the widely used phosphoenolpyruvate (PEP)-dependent phosphotransferase transport system. As an initial step in the phosphorylated disaccharide metabolism pathway, certain glycoside hydrolase family 1 (GH1) enzymes play a crucial role in releasing phosphorylated and non-phosphorylated monosaccharides. However, structural determinants for the specificity of these enzymes still need to be clarified. GH1 enzymes are known to have a wide array of functions. According to the CAZy database, there are twenty-one different enzymatic activities in the GH1 family. Here, the structure and substrate specificity of a GH1 enzyme from Bacillus licheniformis, hereafter known as BlBglH, was investigated. The sequence of the enzyme BlBglH was compared to the sequences of other characterized GH1 enzymes using sequence alignment, sequence identity calculations, phylogenetic analysis, and motif discovery. Through these various analyses, BlBglH was found to have sequence features characteristic of the 6-phospho-β-glucosidase activity enzymes. Additionally, motif and structure comparisons of the three most commonly studied GH1 enzyme-activities revealed a shared loop amongst the different structures that consist of different sequence motifs – this loop is thought to guide specific substrates (depending on activity) towards the active-site. To further affirm BlBglH enzyme activity, molecular docking and molecular dynamics simulations were performed. Docking was carried out using 6-phospho-β-glucosidase enzyme-activity positive (p-Nitrophenyl-beta-D-glucoside-6-phosphate) and negative (p-Nitrophenyl-beta-D-galactoside-6-phosphate) control ligands, followed by 400 ns molecular dynamics simulations. The positive-control ligand maintained favourable interactions within the active site until the end of the simulation. The negative-control ligand was observed exiting the enzyme at 287 ns. Binding free energy calculations showed that the positive-control complex had a substantially more favourable binding energy compared to the negative-control complex. Jointly, the findings of this study suggest that the BlBglH enzyme possesses 6-phospho-β-glucosidase enzymatic activity.

Keywords: 6-P-β-glucosidase, glycoside hydrolase 1, molecular dynamics, sequence analysis, substrate specificity

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Authors: Byung Ho Jung, Ji Eun Shin, Dong Hoon Lim

Abstract:

Rhipe that integrates R and Hadoop environment made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data. Experimental results for comparing the performance of our Rhipe with stats and biglm packages available on bigmemory, showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases. We also compared the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster. The results showed that fully-distributed mode was faster than pseudo-distributed mode, and computing speeds of fully-distributed mode were faster as the number of data nodes increases.

Keywords: big data, Hadoop, Parallel regression analysis, R, Rhipe

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Authors: Shu-Jen Chen, Yi-Chien Wan, Ruey-Chi Wang

Abstract:

Hydroxyapatite (Ca10(PO4)6(OH)2, HAp) can be applied to the fabrication of bone replacement materials, the composite of dental filling, and the adsorption of biomolecules and dyes. The integration of HAp and magnetic materials would offer several advantages for bio-separation process because the magnetic adsorbents is capable of recovered by applied magnetic field. C-phycocyanin (C-PC) and Allophycocyanin (APC), isolated from Spirulina platensis, can be used in fluorescent labeling probes, health care foods and clinical diagnostic reagents. Although the purification of C-PC and APC are reported by HAp adsorption, the adsorption of C-PC and APC by magnetic HAp composites was not reported yet. Therefore, the fabrication of HAp with magnetic silica nanoparticles for proteins adsorption was investigated in this work. First, the magnetic silica particles were prepared by covering silica layer on Fe3O4 nanoparticles with a reverse micelle method. Then, the Fe3O4@SiO2 nanoparticles were mixed with calcium carbonate to obtain magnetic silica/calcium carbonate composites (Fe3O4@SiO2/CaCO3). The Fe3O4@SiO2/CaCO3 was further reacted with K2HPO4 for preparing the magnetic silica/hydroxyapatite composites (Fe3O4@SiO2/HAp). The adsorption experiments indicated that the adsorption capacity of Fe3O4@SiO2/HAp toward C-PC and APC were highest at pH 6. The adsorption of C-PC and APC by Fe3O4@SiO2/HAp could be correlated by the pseudo-second-order model, indicating chemical adsorption dominating the adsorption process. Furthermore, the adsorption data showed that the adsorption of Fe3O4@SiO2/HAp toward C-PC and APC followed the Langmuir isotherm. The isoelectric points of C-PC and APC were around 5.0. Additionally, the zeta potential data showed the Fe3O4@SiO2/HAp composite was negative charged at pH 6. Accordingly, the adsorption mechanism of Fe3O4@SiO2/HAp toward C-PC and APC should be governed by hydrogen bonding rather than electrostatic interaction. On the other hand, as compared to C-PC, the Fe3O4@SiO2/HAp shows higher adsorption affinity toward APC. Although the Fe3O4@SiO2/HAp cannot recover C-PC and APC from Spirulina platensis homogenate, the Fe3O4@SiO2/HAp can be applied to separate C-PC and APC.

Keywords: hydroxyapatite, magnetic, C-phycocyanin, allophycocyanin

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Authors: A. Bere, H. G. Sithuba, K. Kyei, C. Sigauke

Abstract:

We employ a discrete logit survival model to investigate the risk factors for early alcohol intake among students at two tertiary institutions in Thohoyandou, South Africa. Data were collected from a sample of 744 students using a self-administered questionnaire. Significant covariates were arrived at through a regularization algorithm implemented using the glmmLasso package. The tuning parameter was determined using a five-fold cross-validation algorithm. The baseline hazard was modelled as a smooth function of time through the use of spline functions. The results show that the hazard of initial alcohol intake peaks at the age of about 16 years and that at any given time, being of a male gender, prior use of other drugs, having drinking peers, having experienced negative life events and physical abuse are associated with a higher risk of alcohol intake debut.

Keywords: cross-validation, discrete hazard model, LASSO, smooth baseline hazard

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Authors: Fatma Ezzahra Kateb, Neila Boulila Taktak, Mohamed Kabir Hassan

Abstract:

We examine the impact of Islamic accounting and auditing standards issued by the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) on the income smoothing perspective of Islamic financial institutions located in the Middle East and North Africa region between 2013 and 2018. Based on General Least square regression for panel data, we find a significant and positive relationship between intentional income smoothing and earning persistence and cash flow predictability in all models. However, we discovered that AAOIFI accounting standards (FAS) had a negative and significant effect on intentional income smoothing and earning persistence. As a result, the income smoothing efficiency is lower for IFIs that use FASs than IFIs that use IFRSs. Our findings emphasize the need for specific standards to enhance the relevance of financial reports disclosed by Islamic financial institutions.

Keywords: AAOIFI, financial reporting quality, income smoothing perspective, MENA countries

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

Abstract:

Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

Procedia PDF Downloads 139