A conditional role-involved purpose-based access control model

This paper presents a role-involved conditional purpose-based access control (RCPBAC) model, where a purpose is defined as the intension of data accesses or usages. RCPBAC allows users using some data for certain purpose with conditions. The structure of RCPBAC model is defined and investigated. An algorithm is developed to achieve the compliance computation between access purposes (related to data access) and intended purposes (related to data objects) and is illustrated with role-based access control (RBAC) to support RCPBAC. According to this model, more information from data providers can be extracted while at the same time assuring privacy that maximizes the usability of consumers' data. It extends traditional access control models to a further coverage of privacy preserving in data mining environment as RBAC is one of the most popular approach towards access control to achieve database security and available in database management systems. The structure helps enterprises to circulate clear privacy promise, to collect and manage user preferences and consent

CancerLinker: Explorations of Cancer Study Network

Interactive visualization tools are highly desirable to biologist and cancer researchers to explore the complex structures, detect patterns and find out the relationships among bio-molecules responsible for a cancer type. A pathway contains various bio-molecules in different layers of the cell which is responsible for specific cancer type. Researchers are highly interested in understanding the relationships among the proteins of different pathways and furthermore want to know how those proteins are interacting in different pathways for various cancer types. Biologists find it useful to merge the data of different cancer studies in a single network and see the relationships among the different proteins which can help them detect the common proteins in cancer studies and hence reveal the pattern of interactions of those proteins. We introduce the CancerLinker, a visual analytic tool that helps researchers explore cancer study interaction network. Twenty-six cancer studies are merged to explore pathway data and bio-molecules relationships that can provide the answers to some significant questions which are helpful in cancer research. The CancerLinker also helps biologists explore the critical mutated proteins in multiple cancer studies. A bubble graph is constructed to visualize common protein based on its frequency and biological assemblies. Parallel coordinates highlight patterns of patient profiles (obtained from cBioportal by WebAPI services) on different attributes for a specified cancer studyComment: 7 pages, 9 figure

Dielectric, Ultrasonic and Viscoelastic Properties of Rubber Wood

Dielectric, ultrasonic and viscoelastic properties of rubber wood were studied with various physical parameters, such as moisture contents (MC), grain directions and temperatures. Three anisotropic directions, namely longitudinal, radial and tangential to the growth ring were considered for the measurement of these properties. Dielectric properties were measured at low frequencies from 10⁻² to 10⁻⁵ Hz and at microwave frequencies from 1 to 18 GHz. Ultrasonic properties were determined with a commercial ultrasonic tester at 45 kHz. Viscoelastic properties were carried out with the Dynamic Mechanical Thermal Analyzer at frequency ranging ,from 0.01 to 1 00 Hz. At low frequencies, five types of dielectric mechanism were observed for different MC such as 1) less than 5%, 2) 5-10%, 3) 11 - 17%, 4) 18-25% and 5) more than 25%. Dielectric constant increased with temperature for these frequencies while dielectric loss factor showed minimum value in oven-dry condition. Dielectric constant and dielectric loss factor varied in the order of longitudinal> radial 2:. tangential directions. Dielectric data at low frequency are in well agreement with those calculated from equivalent circuit using the concept of universal capacitor. Three equivalent circuits fitted well for data at very low MC or for oven-dried wood, MC below fiber saturation point and MC above fiber saturation point. Activation energies were 0.27eV, 0.34eV and 0.41eV for longitudinal, radial and tangential directions respectively. At microwave frequencies, dielectric constant and dielectric loss factor were found to increase with MC ranging from oven-dry up to saturation point. Dielectric constant also decreased with temperature and dielectric loss factor exhibited peaks at 10 GHz. Dielectric constants are predicted well by Winner, Lichteneker and generalized equations with lower value of the exponents. Above 3 G Hz, dielectric loss factor fitted well with the predicted values using Winner, Kraszewski, Looyenga or with generalized equations with lower values of the exponents. Below 3 GHz, dielectric loss factor are unpredictable by these mixture equations

Somatic Embryogenesis in Musa Spp.

Embryogenesis competent material (scalp) was initiated from shoot tip of Musa spp. cultivar Mas (AA), Berangan (AAA), Intan (AAA), Raja (AAB) and Tanduk (AAB). Somatic embryogenesis were investigated from four explant sources viz., scalps, male flower primordia, in vitro corm slices and immature ovules of Musa acuminata cv. Mas. Scalp formation was optimal on Murashige and Skoog (MS) medium with modified vitamins supplemented with 100 /lM BAP and 1.0 /lM IAA. Among the cultivars investigated, cv. Mas was the most responsive for scalp formation whereby 40% of the shoot tips formed scalps by the 7th month of culture. Cultivar Mas was also the most responsive for meristematic globule formation from scalps attaining 100% meristematic globule formation by week 7 of culture of scalps in Z medium. Cells with embryogenic potential were released from the meristematic globules of cv . Mas after 10 to 12 months of culture of the meristematic globules in Z medium . The embryogenic cell suspension was transferred to liquid S medium and formed globular embryos after 3 to 4 months in culture. Matured globular embryos upon transfer to liquid S regeneration medium supplemented with 0, 1.0, 5.0, 10, 20, 40 and 80 /lM BAP germinated to form roots but without shoots

Effect of hydrated lime on the laboratory performance of superpave mixtures

Permanent deformation and moisture damage are the most common distresses found in asphalt pavements today. Extensive experimental studies have revealed that the use of hydrated lime in Hot-Mix Asphalt (HMA) mixtures can reduce permanent deformation, long-term aging, and moisture susceptibility of mixtures. In addition, it increases the stiffness and fatigue resistance of mixtures. The objectives of this study were to evaluate (1) the fundamental engineering properties of HMA mixtures containing hydrated lime compared to conventional mixtures designed to meet the current Louisiana Superpave specifications and (2) the influence of the method of addition of hydrated lime on the mechanical properties of HMA mixtures. Nine 19.0 mm Level 2 HMA mixtures were designed and examined. Siliceous limestone aggregates that are commonly used in Louisiana were included in this study. The nine mixtures were divided into three sets where the first set of three mixtures named as conventional or control mixtures did not include hydrated lime, and contained two SB polymer modified asphalt cement meeting Louisiana specifications for PG 76-22M, PG 70-22M, and a neat PG 64-22 asphalt. Mixtures in the second set included hydrated lime that was incorporated into the aggregate/asphalt cement mixture as slurry, whereas hydrated lime was blended dry with the asphalt cement for the third set of mixtures. For the latter two sets, the asphalt cements used were identical to the ones used in the first set, namely PG 76-22M, PG 70-22M, and PG 64-22. Mechanistic tests namely, Indirect Tensile Strength test, Semi-Circular Bend test, Dissipated Creep Strain Energy test, Dynamic Modulus test, Flow Number test, Flow Time test, and Loaded Wheel Tracking test were conducted to define the permanent deformation and endurance life of HMA mixtures with and without hydrated lime. In addition, physical and rheological tests on asphalt binders were performed. The overall results indicated that the addition of hydrated lime improved the permanent deformation characteristics of the HMA mixtures. This improvement was substantial particularly at higher testing temperatures for mixtures containing polymer modified asphalt binders

Joint modeling of binary longitudinal measurement and time-to-event: An application to depression and time-to-dementia

In recent years, the methodological development of joint models of longitudinal and time-to-event data has become one of the most popular areas of studies in clinical research and its application has increased substantially over the past decades. Joint model in this area combines both the longitudinal and survival data into a single statistical model to obtain robust estimates and draw valid inference. While most of studies concentrate on continuous longitudinal measurements, little attention has been paid to joint modeling for binary longitudinal outcome and event time data. In clinical research, patients often have binary longitudinal measurement that affects the main event of interest during the follow-up time. For example, depression, a dichotomous longitudinal measurement, might have relationship with dementia. However, no study has examined this association using a joint model. This study focuses on the joint modeling technique for binary repeated measurement and time-to-event data. This approach mainly models the longitudinal and survival processes for each individual through a shared random effect jointly, where the longitudinal part is supposed to be modeled by a generalized linear mixed model and time-to-event component is characterized by employing a parametric survival model. We applied the joint modeling technique to the Korean Health Panel Study. A generalized linear mixed model was used to model the binary repeated measurements of depression and a piecewise constant hazard model was employed for time-to-dementia. A total of 3,611 individuals aged 65 years or older were eligible for this study between 2008 and 2015. Depression and dementia were identified by the diagnosis code in medical data. In this study, 215 (6%) were diagnosed with dementia during the 8-year follow-up period. The mean age at entry was 72.2 (±5.7) years. The overall median follow-up time was 5.8 years; 3.6 years for people living with dementia compared to 5.9 years for people without dementia. Baseline depression and sex were not significantly associated with time-to-dementia. However, time-varying depression and baseline covariates including age, economic activity, education, walking frequency/week, living with other family members and diabetes were significant in multivariable joint modeling. The risk of dementia was 2.4 times (95% CI: 1.30-4.50, p-value = 0.005) higher among depressed people compared to non-depressed people. This study also found that walking not at all or less than three days a week, being older (>70 years old), having diabetes, being less educated and living in a household with multiple generations increased the risk of dementia

Social media analytics with applications in disaster management and COVID-19 events

Social media such as Twitter offers a tremendous amount of data throughout an event or a disastrous situation. Leveraging social media data during a disaster is beneficial for effective and efficient disaster management. Information extraction, trend identification, and determining public reactions might help in the future disaster or even avert such an event. However, during a disaster situation, a robust system is required that can be deployed faster and process relevant information with satisfactory performance in real-time. This work outlines the research contributions toward developing such an effective system for disaster management, where it is paramount to develop automated machine-enabled methods that can provide appropriate tags or labels for further analysis for timely situation-awareness. In that direction, this work proposes machine learning models to identify the people who are seeking assistance using social media during a disaster and further demonstrates a prototype application that can collect and process Twitter data in real-time, identify the stranded people, and create rescue scheduling. In addition, to understand the people’s reactions to different trending topics, this work proposes a unique auxiliary feature-based deep learning model with adversarial sample generation for emotion detection using tweets related to COVID-19. This work also presents a custom Q&A-based RoBERTa model for extracting related phrases for emotions. Finally, with the aim of polarization detection, this research work proposes a deep learning pipeline for political ideology detection leveraging the tweet texts and the expressed emotions in the text. This work also studies and conducts the historical emotion and polarization analysis of the COVID-19 pandemic in the USA and several individual states using tweeter data --Abstract, page iv

Sustainable business practices and reporting:case study of a garment manufacturing company in Bangladesh

Given the widespread prevalence of industrial accidents and human rights violations in the Ready-Made Garments (RMG) sector, the concept of ‘Sustainable Business Practices and Reporting’ (SBPR) has become a key issue in International Retailers’ (IR) sourcing decisions. This study makes important contributions to the social and environmental accounting and reporting (SEAR) literature from the perspective of developing countries. This study deploys institutional theory as the fundamental theoretical framework in order to explain why and how the case company (CC), which is subjected to multiple conflicting pressures, has adopted and implemented SBPR practice at CC. This study has employed a case-study approach and collected evidence from multiple methods, such as in-depth interviews, focus group discussions and documentary analysis, in order to understand the case company’s adoption and implementation of the SBPR process. The findings of this thesis indicate that organizations do not blindly conform to the expectations of the institutional environment; rather they prefer to engage in a customized response by taking into consideration various technical-competitive, institutional, and relational factors. This study also argues that institutional pressures can operate in concert with other pressures, such as technical-competitive pressures, so as to influence the practice adoption process. It further explores whether careful mixing of both substantive and symbolic practices in response to different conflicting pressures can help organizations to achieve ceremonial conformity with the support of a decoupling strategy and the logic of confidence. This study also provides necessary clarification of the practice adoption and implementation process by clearly articulating the connections between the concepts of ceremonial conformity, decoupling and logic of confidence. The findings of the study are useful, given the limited number of empirical investigations of organizational responses in pre-institutionalized environments, and reveal that organizations are aware of their latitude for manoeuvre and can engage in calculative responses, whilst taking into consideration of their technical-competitive issues/pressures