Miracle-dz/UniFAR-FTUs huggingface dataset:
An Exploratory Statistical Method For Finding Interactions In A Large Dataset With An Application Toward Periodontal Diseases

FOR DISSERTATION An Exploratory Statistical Method For Finding Interactions In A Large Dataset With An Application Toward Periodontal Diseases It is estimated that Periodontal Diseases effects up to 90% of the adult population. Given the complexity of the host environment, many factors contribute to expression of the disease. Age, Gender, Socioeconomic Status, Smoking Status, and Race/Ethnicity are all known risk factors, as well as a handful of known comorbidities. Certain vitamins and minerals have been shown to be protective for the disease, while some toxins and chemicals have been associated with an increased prevalence. The role of toxins, chemicals, vitamins, and minerals in relation to disease is believed to be complex and potentially modified by known risk factors. A large comprehensive dataset from 1999-2003 from the National Health and Nutrition Examination Survey (NHANES) contains full and partial mouth examinations on subjects for measurement of periodontal diseases as well as patient demographic information and approximately 150 environmental variables. In this dissertation, a Feasible Solution Algorithm (FSA) will be used to investigate statistical interactions of these various chemical and environmental variables related to periodontal disease. This sequential algorithm can be used on traditional statistical modeling methods to explore two and three way interactions related to the outcome of interest. FSA can also be used to identify unique subgroups of patients where periodontitis is most (or least) prevalent. In this dissertation, FSA is used to explore the NHANES data and suggest interesting relationships between the toxins, chemicals, vitamins, minerals and known risk factors that have not been previously identified.
Unpacking old and new conflicts of sovereignty in the European polity

ABSTRACT In the post-Maastricht era, member states of the European Union (EU) have proved increasingly reluctant to transfer further competences to the supranational level and are willing to safeguard their sovereignty. Though the responses to the contemporary multiple crises – related to economic and monetary policy, borders and migrations, or democracy and the rule of law – have brought about conflicts over values and sovereignty losses surrounding the legal, economic and political legitimacy of the EU. Against this backdrop, we argue that beyond the traditional contentious (re)distribution of competences between nation-states (national sovereignty) and the EU (and its embryonic forms of supranational sovereignty), new conflicts of sovereignty involve two other key types of sovereignty belonging to the democratic tradition, namely parliamentary sovereignty and popular sovereignty. This introductory article proposes a common analytical framework in order to investigate conflicts in their multi-dimensionality.
New developments in super-resolution for GaoFen-4

In this paper, the application of super resolution (SR, restoring a high spatial resolution image from a series of low resolution images of the same scene) techniques to GaoFen(GF)-4, which is the most advanced geostationaryorbit earth observing satellite in China, remote sensing images is investigated and tested. SR has been a hot research area for decades, but one of the barriers of applying SR in remote sensing community is the time slot between those low resolution (LR) images acquisition. In general, the longer the time slot, the less reliable the reconstruction. GF-4 has the unique advantage of capturing a sequence of LR of the same region in minutes, i.e. working as a staring camera from the point view of SR. This is the first experiment of applying super resolution to a sequence of low resolution images captured by GF-4 within a short time period. In this paper, we use Maximum a Posteriori (MAP) to solve the ill-conditioned problem of SR. Both the wavelet transform and the curvelet transform are used to setup a sparse prior for remote sensing images. By combining several images of both the BeiJing and DunHuang regions captured by GF-4 our method can improve spatial resolution both visually and numerically. Experimental tests show that lots of detail cannot be observed in the captured LR images, but can be seen in the super resolved high resolution (HR) images. To help the evaluation, Google Earth image can also be referenced. Moreover, our experimental tests also show that the higher the temporal resolution, the better the HR images can be resolved. The study illustrates that the application for SR to geostationary-orbit based earth observation data is very feasible and worthwhile, and it holds the potential application for all other geostationary-orbit based earth observing systems.
Service Quality Scales and Tourists with Special Needs: A Systematic Review

This paper reviews the most commonly used scales for measuring service quality in sustainable tourism destinations to analyse if the requirements of tourists with special needs are considered. Results highlight that most of the recent research on service quality in tourism published in scientific journals is focused on a relative reduced number of validated scales. Variables related to tourists with special needs are often omitted or represent a reduced weight in the complete scale. Thus, this paper highlights the importance of including variables that collect the perceptions of service quality in this target group to better understand the individual perception of service quality and to move forward to sustainable tourism, considering the social dimension.
Learners in Advanced Nanotechnology MOOCs: Understanding their Intention and Motivation

Very little is known about the specific types of learners and their various needs and intentions with regards to STEM-related MOOCs. As MOOCs become increasingly popular and completion rates stay in the single digits, it is important to understand who is enrolling in MOOCs, what is motivating them to do so, and what they want from the courses. Results from a survey of 1,624 learners enrolled in three highly-technical STEM MOOCs revealed that while learners are coming from a variety of backgrounds, 64% of respondents indicated engineering or architecture as their primary field of study. In addition, 47% indicated desire to apply information obtained to an engineering project, and 29% desired to obtain a deep level of knowledge. These findings suggest that MOOCs can be marketed as professional development of working engineers and dissemination of highly technical information.
An Efficient Method of Web Page Noise Cleaning for Effective Web Mining

In the huge network of World Wide Web, web pages contained large amount of information. Web researches are always requiring main content (e.g., an article text) from the web pages to be gathered, processed and stored quickly and efficiently. Mining the data on the Web has become a major task for locating useful information from the Web. The Web information„s that are considered as useful information usually has huge amounts of noise data„s such as navigation bars, links, advertisements, copyright notices etc. Performance of Web mining can be improved by identifying and removing noises from Web pages. In this paper new method is proposed for removing noise content tag and extracts the information of main content tag from web pages. General Terms Web Mining, Global Noises, Local Noises, DOM, Web Pages and WWW.
Detection Windows for Drugs in Oral Fluid: Cannabinoids, Stimulants, and Opioids

In impaired driving enforcement, blood has traditionally been the preferred biological specimen in determining the presence of drugs in drivers. However, collecting blood specimens from drivers can be challenging, often resulting in delays impacting test results and noncompliance. The use of oral fluid as a matrix for the analysis of drugs is gaining popularity and an increasing number of research studies substantiate the correlation between drug concentrations in oral fluid and blood (Bosker & Huestis, 2009; Busardo et al., 2018). Drugs may be deposited in oral fluid via ingestion (e.g., smoked or oral) and passive diffusion from blood into saliva (Lee & Huestis, 2014). As a detection matrix, oral fluid has several advantages over blood and urine: collection is easy, noninvasive, and can be observed, limiting opportunities for adulteration. Oral fluid also can be collected at the roadside, close to the time of a suspected impaired driving offense. However, there is still much to be learned about the use of oral fluid especially as a detection matrix at the roadside. The objective of this research brief is to assess the literature on oral fluid detection times to address how long after a person uses a drug it can be detected in oral fluid, and what factors may influence detection times. As drug prevalence does not imply impairment, efforts to understand the proximity of drivers’ drug use in time may assist in better understanding and properly enforcing drug-impaired driving laws.
Spatial-Temporal Topology and Performance Analysis of Airport Taxi Network

1 This paper proposes a spatial-temporal topology from a macroscopic view to analyze the 2 performance of airport taxi network operations. Through a macroscopic modelling of arrival and 3 departure aircraft taxi processes in the airport taxi network, we establish a system of taxi network 4 performance indicators (TNPIs) consisting 5 categories and 26 indicators, which includes the 5 surface instantaneous flow indicators (SIFIs), surface cumulative flow indicators (SCFIs), aircraft 6 queue length indicators (AQLIs), slot resource demand indicators (SRDIs) and aircraft taxi time 7 indicators (ATTIs). Then, we analyze the correlation among different TNPIs. By identifying the 8 key factors affecting aircraft taxi time such as takeoff and landing queue length, we provide 9 models for predicting aircraft taxi time based on multiple regression analysis. The real-world case 10 study in Shanghai Pudong airport demonstrates significant correlations among some of the 11 proposed TNPIs, and the results also show the significantly improved accuracy of the proposed 12 prediction models over some conventional models, which brings significant benefits to analyze the 13 performance of airport taxi network and support decision making in airport operations. 14 15 16
Translation Alignment and Extraction Within a Lexica-Centered Iterative Workflow

This thesis addresses two closely related problems. The first, translation alignment, consists of identifying bilingual document pairs that are translations of each other within multilingual document collections (document alignment); identifying sentences, titles, etc, that are translations of each other within bilingual document pairs (sentence alignment); and identifying corresponding word and phrase translations within bilingual sentence pairs (phrase alignment). The second is extraction of bilingual pairs of equivalent word and multi-word expressions, which we call translation equivalents (TEs), from sentenceand phrase-aligned parallel corpora. While these same problems have been investigated by other authors, their focus has been on fully unsupervised methods based mostly or exclusively on parallel corpora. Bilingual lexica, which are basically lists of TEs, have not been considered or given enough importance as resources in the treatment of these problems. Human validation of TEs, which consists of manually classifying TEs as correct or incorrect translations, has also not been considered in the context of alignment and extraction. Validation strengthens the importance of infrequent TEs (most of the entries of a validated lexicon) that otherwise would be statistically unimportant. The main goal of this thesis is to revisit the alignment and extraction problems in the context of a lexica-centered iterative workflow that includes human validation. Therefore, the methods proposed in this thesis were designed to take advantage of knowledge accumulated in human-validated bilingual lexica and translation tables obtained by unsupervised methods. Phrase-level alignment is a stepping stone for several applications, including the extraction of new TEs, the creation of statistical machine translation systems, and the creation of bilingual concordances. Therefore, for phrase-level alignment, the higher accuracy of human-validated bilingual lexica is crucial for achieving higher quality results in these downstream applications. There are two main conceptual contributions. The first is the coverage maximization approach to alignment, which makes direct use of the information contained in a lexicon, or in translation tables when this is small or does not exist. The second is the introduction of translation patterns which combine novel and old ideas and enables precise and productive extraction of TEs. As material contributions, the alignment and extraction methods proposed in this thesis have produced source materials for three lines of research, in the context of three PhD theses (two of them already defended), all sharing with me the supervision of my advisor. The topics of these lines of research are statistical machine translation, algorithms and data structures for indexing and querying phrase-aligned parallel corpora, and bilingual lexica classification and generation. Four publications have resulted directly from the work presented in this thesis and twelve from the collaborative lines of research.
DETERMINING A FLEXIBLE LOW-RANK GRAPH USING SUBSPACE CLUSTERING

By utilizing a meager representation or low-rank representation of information, chart based subspace bunching has as of late pulled in impressive consideration in PC vision, given its ability and productivity in grouping information. Be that as it may, the chart weights worked by utilizing representation coefficients are not the correct ones as the conventional definition. The two stages of portrayal what's more, bunching are led in an autonomous way; in this manner a general ideal outcome can't be ensured. Moreover, it is vague how the bunching execution will be influenced by utilizing this chart. For instance, the diagram parameters, i.e., the weights on edges, must be falsely pre-indicated while it is extremely hard to pick the ideal. To this end, in this paper, a novel subspace bunching by means of taking in a versatile low-rank diagram proclivity lattice is proposed, where the partiality framework and the representation coefficients are found out in a bound together system. All things considered, the pre-figured chart regularize is successfully blocked and better execution can be accomplished. Test comes about on a few well known databases illustrate that the proposed technique performs better against the state-of the- workmanship approaches, in grouping.
Antimicrobial Activity of the Crude Extracts and Fractions of ThreeBaccharis Species

The antimicrobial activities of crude extracts and fractions from three Baccharis L. species were tested against Staphylococcus aureus (ATCC 6538), Escherichia coli (ATCC 8738), Pseudomonas aeruginosa (ATCC 9027), and Candida albicans (ATCC 10231) using the microdilution plate method. The results showed that the crude extract from female B. burchellii Baker had moderate activity against S. aureus (minimum inhibitory concentration [MIC], 0.9 mg.mL-1). Among the fractions obtained from this extract, the dichloromethane fraction showed the highest activity against S. aureus (MIC, 0.4 mg.mL-1). The ethyl acetate fractions from female B. burchellii (MIC, 0.6 mg.mL-1 and 1.2 mg.mL-1, respectively) and B. aracatubaensis Malag (MIC, 1.1 mg.mL-1 for both) were moderately effective against S. aureus and P. aeruginosa. The extracts from B. organensis Baker showed no significant activity against any organism tested. None of the extracts from Baccharis species showed any activity against C. albicans. In addition, the chemical investigation of the dichloromethane and ethyl acetate fractions from female B. burchellii was carried out, resulting in the identification of trans-ferulic acid, ethyl caffeoate, naringenin, and 7-hydroxy-benzaldehyde compounds. These phenolic compounds were found in other species of Baccharis and have been shown to possess antimicrobial activity. The results obtained in this work with respect to B. burchellii indicate that this species is a promising source of compounds with antimicrobial activities.
Product opinion analysis using text mining and analysis

The enormous growth and usage of e-commerce offer positive ways to any business by sharing the emotions, feelings and experiences. Web users are benefited with valuable online reviews. There are many instances, where these reviews are not considered for evaluation of a product in the market, thus affecting the sales of the products. We intend to solve the problem of sentiment polarity computation, which is one of the most basic problems of sentiment analysis. A general process for sentiment polarity computation, department wise classification and feature extraction is proposed with detailed procedure. Data on online product reviews from Amazon.com was used in this study. ProSent is a real-time web service, which provides insights of the product by applying sentiment analysis on the reviews. It eases the way to manage bulk customer reviews and also simplifies handling of customer reviews with customisable workflow processes and meaningful graphs and charts.
Study on Temporal Variations of Surface Temperature and Rainfall at Conakry Airport, Guinea: 1960–2016

The monthly averaged data time series of temperatures and rainfall without interruption of Conakry Airport (9.34° N 13.37° W, Guinea) from 1960 to 2016 were used. Inter-annual and annual changes in temperature and rainfall were investigated. Then, different models: Mann-Kendall Test, Multi-Linear-Regression analysis, Theil-Sen’s slope estimates and wavelet analysis where used for trend analysis and the dependency with these climate forcings. Results showed an increase in temperature with semi-annual and annual cycles. A sharp and abrupt rise in the temperature in 1998 was found. The results of study have shown increasing trends for temperature (about 0.21°/year). A decrease in rainfall (about −8.14 mm/year) is found since the end of 1960s and annual cycle with a maximum value of about 1118.3 mm recorded in August in average. The coherence between the two parameters and climate indices: El Niño 3.4, Atlantic Meridional Mode, Tropical Northern Atlantic and Atlantic Niño, were investigated. Thus, there is a clear need for increased and integrated research efforts in climate parameters variations to improve knowledge in climate change.
PLC Virtualization and Software Defined Architectures in Industrial Control Systems

Tampereen ammattikorkeakoulu Tampere University of Applied Sciences Degree Programme in Mechanical and Production Engineering Machine Automation PELTONEN, MIKAEL PLC Virtualization and Software Defined Architectures in Industrial Control Systems Bachelor's thesis 53 pages, appendices 3 pages August 2017 Today’s automation systems are going through a transition called Industry 4.0, referring to the Fourth Industrial Revolution. New concepts, such as cyber-physical systems, microservices and Smart Factory are introduced. This brings up the question of how some of these new technologies can be utilized in Industrial Control Systems. Machines and production lines are nowadays controlled by hardware PLCs and this is considered as a state-of-the-art solution. However, the market demands are continuously increasing and pushing the industry e.g. to lower the operational costs and to develop more agile solutions. Industry 4.0 provides promising approaches to take a step forward and consider PLC virtualization. The purpose of this thesis was to evaluate PLC virtualization possibilities using different Software Defined Architectures. Requirements and benefits of different solutions were evaluated. The major objective of the case study was to compare containerand hypervisor-based virtualization solutions using Docker and KVM. The case study provides a modular and scalable IIoT solution in which a virtual PLC takes over the control instead of a hardware PLC. Node-RED was used as a runtime environment and an I/O-module was needed to set up a control loop test. Response time of the control loop was measured by capturing Modbus traffic with tcpdump. Multiple iterations were performed to show minimum, maximum, average, median and 90 pctl. latencies. The results indicate that the container-based solution has a smaller overhead than the hypervisor-based solution and it has a very little overhead in general. Peak latencies are a concern and even the average latencies show that this solution would not be suitable for any hard real-time or safety-related applications. Further investigation on the topic would be needed to estimate the actual potential of PLC virtualization on hard real-time applications. First of all, a more powerful hardware PC would be needed to perform such tests. Secondly, a faster industrial protocol than Modbus TCP/IP would be required. Perhaps another kind of approach would be needed to overcome the issues that were experienced in this case study. It would be interesting to test a direct communication between virtual PLC and I/O and use Node-RED nodes for example to trigger inputs. Anyhow, it seems that container-based solution is holding much promise as a virtualization approach.
Return migration and identity change: A Hungarian case study

This study analyses the identity changes experienced by migrants returning to Hungary before, during, and after their stay abroad. Sussman’s (2011) cultural identity change model is used as a theoretical framework to which two factors, ‘skills’ and ‘family status’ are added. Although identity change plays an important role in the success or failure of return, reintegration, and reemployment of returnees, to date this has not been studied in Hungary in detail. According to the research results, Hungarian returnees can be categorised into the same four groups as distin-guished by Sussman (2011). Returnees in the affirmative identity group are found to be mostly low skilled migrants unable to integrate into the host society; as such, reintegration after their return is relatively easy. The members of the subtractive and additive identity groups can better integrate into the host country as they feel less attached to their native country than the affirmative group, but this causes various reintegration issues. The group of global identity shifters has the most natural reintegration process. Based on the research results, it is recommended that Hungarian return migration policies and initiatives should give greater consideration to these reintegration differences.
Family Comes First: Reproductive Health and the Gender Gap in Entrepreneurship

Better access to reproductive healthcare increases women’s propensity to become entrepreneurs. Access correlates positively with female entrepreneurial activity and negatively with female entrepreneurial age. Examining firm size and personal income suggests it also improves success of female-led businesses. None of these results hold when tested on men, women above 40, or other placebo professions. To establish causality, I exploit Roe v. Wade, state laws restricting abortion providers, and an index tracking state-level regulation of reproductive care. All three analyses suggest that policies securing better reproductive care enable more women to become entrepreneurs. I conclude by discussing various possible channels and mechanisms.