Miracle-dz/UniFAR-FTUs huggingface dataset:
云计算中面向隐私保护的查询处理技术研究 = Privacy-preserving query processing in cloud computing

A vital concern in cloud computing is how to protect both data privacy and query privacy while providing query services for users. This paper surveys several critical techniques of privacy-preserving query processing in cloud computing, which include cloud database indexing, query optimization, encryption-based privacy-preserving techniques, privacy-preserving techniques based on secure multi-party computation and authorization auditing techniques. Finally, the paper analyzes the challenges of privacy-preserving query processing in cloud computing and figures out the trend of this area.
Education and Knowledge of Noise Exposure, Hearing Loss, and Hearing Conservation in College Students

ABSTRACT: Purpose: College students were surveyed to identify their knowledge of, and sources of education for, the effects of noise to hearing health and to determine their efforts at hearing conservation. Method: A questionnaire was developed to assess college students’ noise exposure and hearing conservation practices, the educational sources from which they receive information, and their overall knowledge concerning the effects of noise to hearing. Results: The questionnaire was completed by 329 undergraduateand graduate-level students of various educational concentrations. Respondents were >18 years (Mage = 21 years); approximately one fourth (27%) were majors of communication sciences and disorders (CSD). Most respondents (>85%) reported exposure to potentially damaging levels of noise, with approximately half (51%) reporting temporary tinnitus immediately after exposure to loud noise. However, the large majority (80%), including CSD majors, reported almost never using hearing protection. There was no significant difference (p = >0.05) in the use of hearing protection, spending time at noisy locations, or participating in noisy recreational activities between the categories of gender, academic level (graduate or undergraduate), and major (CSD or other). A
Proceeding toward the development of poly(ɛ-caprolactone)/cellulose microfibrils electrospun biocomposites using a novel ternary solvent system

Abstract In the current study, a mixture of formic acid (FA), acetic acid (AA), and acetone was used, for the first time, as a ternary solvent system to dissolve poly(ɛ-caprolactone) (PCL). In addition, as a biomaterial reinforcement, various amounts of cellulose microfibrils (CMF) (1.5, 3, and 5 wt.%), extracted from rice husk, were added to PCL solution, and subsequently the prepared suspensions were individually electrospun. Adding acetone to FA/AA solvent system led to fabrication of uniform electrospun nanofibers with the average diameter of 178 ± 38 nm. Upon CMF incorporation, the mean electrospun fiber diameter was increased to 320 ± 132 nm at 5 wt. % CMF mostly due to the solution viscosity rise. In addition, scanning electron microscopy (SEM) confirmed wider diameter distribution in the presence of CMF. The electrospun fibers were also analyzed via wide angle X-ray scattering (WAXS) and differential scanning calorimetry (DSC) to study the supermolecular structure and thermal behavior of fibrous bionanocomposites, respectively. Both the characterizations positively affect the PCL crystallinity as a result of CMF incorporation. The DSC measurements showed the highest crystallinity (70.11%) at 1.5 wt. % CMF incorporation. The effect of CMF addition on the hydrophilicity of PCL was also investigated by contact angle measurement, where a decreasing trend in contact angle was observed upon CMF loading. Moreover, in vitro degradability of the bionanocomposite nonwoven mats was studied in PBS solution. The rate of degradation was enhanced in the presence of CMF. Moreover, tensile mechanical analysis was carried out and CMF inclusion had a reinforcing impact on electrospun PCL. The highest modulus (19.17 ± 0.8 MPa) and ultimate tensile strength (UTS) (4.45 ± 0.32 MPa) were achieved at 1.5 wt. % CMF addition to PCL.
A Population Model for Academia: Case Study of the Computer Science Community Using DBLP Bibliography 1960-2016

The academic community has seen a tremendous growth in number of authors and publications in recent times. Most previous studies of the academic community, whether on individual activity, productivity and influence, or collaboration patterns and their implications, have been based on a flat and static view of the system. However, the academic community resembles a dynamic growing population, with entry and exit of authors. In this paper, we study this systemic inflation by proposing a population model for academia. We use a generalized branching process as an overarching framework, which enables us to describe the research community from an evolutionary and structural perspective. Further, the observed patterns allow us to shed light on researchers’ life-cycle encompassing their arrival, academic life expectancy, activity, productivity and offspring distribution in the community. In our study, we used data from DBLP for a case study in the computer science community, although our methodology can be adopted in a systematic manner to any other research domain with sufficient publication records. We believe that the results can help academics and policy makers alike to better understand and evaluate the development and evolution of their respective academic communities.
1D+1D modeling of reversible Solid Oxide Cell (rSOC) reactors for steady state and dynamic process analyses of electricity storage systems

I Abstract The intermittent nature of renewable energy sources demands energy storage systems to stabilize the grid. The Reversible solid oxide cell (rSOC) system is a promising solution for energy storage. To facilitate its development, system modeling and simulation is a useful tool. In this work, a 1D+1D transient model of a co/counter-flow planar rSOC stack suitable for system modeling is developed. As a basis, an experimentally validated 1D model of an rSOC single repeat unit (SRU) model is first refined in following aspects: 1. Higher resolution of structures of fuel and air channel is achieved; 2. Better heat convection model between gas flow and solid elements is employed; 3. Dusty gas model (DGM) for multicomponent gas diffusion in porous electrode is implemented; 4. Butler-Volmer equation is adopted instead of its inverse hyperbolic approximation; 5. Electrochemical parameters for calculation of exchange current densities are determined through detailed experimental analysis. Heat transfer between stack and surroundings in the test bench is modeled for validation purposes. The developed stack model is validated against the experimental results.
Ethnicity, Perceptions of Stress, and Depressive Symptoms Among Female Undergraduate Students

Ethnicity, Perceptions of Stress, and Depressive Symptoms Among Female Undergraduate Students by Claudia Priscilla Cobos MS, Mount St. Mary’s University, 2000 BA, Mount St. Mary’s University, 1997 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Psychology
Tables and graphs for monitoring temporal crime trends

This article is a practical review on how to construct tables and graphs to monitor temporal crime trends. Such advice is mostly applicable to crime analysts to improve the readability of their products, but is also useful to general consumers of crime statistics in trying to identify crime trends in reported data. First, the use of percent change to identify significant changes in crime trends is critiqued, and an alternative metric based on the Poisson distribution is provided. Second, visualization principles for constructing tables are provided, and a practical example of remaking a poor table using these guidelines is shown. Finally, the utility of using time series charts to easily identify short- and long-term increases, as well as outliers in seasonal data using examples with actual crime data is illustrated.
Micromechanics-based multiscale modelling for nonlinear analysis of fibre-reinforced composites using DIGIMAT

The research work presents numerical investigations on nonlinear mechanics, damage and failure behavior for a class of composite materials and structures through micromechanicsbased multiscale analysis. A computational framework based on DIGIMAT and MSC NASTRAN is utilized to model the problem in hand [1]. At the microscale, various constituents of the microstructure (fiber, inclusions, cavities, etc.) are modeled as a representative volume element (RVE). Two approaches are utilized to address the virtual material characterization and scale transition, namely, the direct finite element analysis (FEA) and mean field homogenization technique (MFH). The former method provides a detailed and accurate description of the micro field, but may lead to very high computational overheads from a macroscopic structural perspective. The latter is based on a semi-analytical method (Self-consistent, Mori-Tanaka and Double Inclusion) accompanied by great computational efficiency with lower details on local distributions due to volume averaging. Nonlinearity within the microstructure constituents is modeled through a class of nonlinear models such as the elasto-plastic damage model (Lemaitre-Chaboche model [2]). The study shall address how the aforementioned approaches prove efficient and accurate in the prediction of composite materials and structures response across different scales, from micro (investigating the effect of defects, local distributions, singularities) to macro (with the structural analysis of a composite panel). Numerical predictions are validated against existing numerical and experimental results from literature.
Modelling and Mining of Data mining Workflows in Data Science Scripts

Knowledge discovery and data mining (KDD) is the process that extracts new knowledge from data. Data scientists program their solutions of their KDD challenges in data mining programming scripts. Data mining programming scripts contain multiple or all steps of the KDD process. In other words, these scripts start with data and end with knowledge. Learning from the knowledge and experience documented in the scripts would be beneficial, but till know a formalized sharing of this information between Data Scientist is missing. This is partly because there is now formalized model to share it and partly due to Intellectual property of companies on the solution of their employed Data Scientist. In this thesis, we describe an open source repository of data mining scripts in order to find out how data mining solutions are constructed. Gaining knowledge on these solutions and making it possible to share this knowledge. The scripts are described by an adapted KDD process model. This model extends the existing models, while these existing models were too conceptual and abstract to describe and classify data mining scripts. The extension of the current models consists of an additional layer of Methods that connects the abstract models and the data mining scripts. This additional layer has been constructed by combining various KDD ontologies. After the modelling, the script lines are labelled with the methods from the adapted KDD process model. Which is achieved by going through the different steps of a KDD process. During the transformation from text to numbers, required for training an automatic classifier, word embedding techniques are applied. Hereby, the implemented Word2Vec algorithm learns what the semantically similar words are within the code. Script lines with semantically similar words get a similar vector. This makes it possible to train a supervised classifier that assigns labels to script lines. This results in a list of labels per script describing the KDD process of the script. These lists of labels have been analysed in various ways. First, it can be demonstrated that data scientists usually use two or more script lines to perform a Step or Task. Furthermore, we analyse which Methods are often used together. This makes it possible to recommend appropriate Methods during a future process. Lastly, we studied the transitions in the scripts from Step to Step, Task to Task and Method to Method, of the adapted KDD model. Here we see that the conceptual process model is indeed reflected in the scripts. In addition, we see that the scripts, like the process, are cyclic and iterative, often returning to an earlier step. Lastly commonly used transitions in the script are visualized and describes. The description of scripts gives insight into the choices Data Scientist make to solve their KDD challenges. This is useful information if you want to contribute towards solving newly encountered KDD challenges. Furthermore, the extended model and the developed workflow offer starting points for future work that supports the knowledge discovery and data mining process.
Developing and Validating a Health-Related Quality of Life Measure for People with Aphasia

Aphasia is a neurological disorder resulting from damage to the brain. Individuals with aphasia experience deficits in language-based abilities, such as reading, writing, speech comprehension and/or speech production. These limitations reflect in the population's social and personal lives, with individuals often reporting fewer social contacts, fewer social activities and increased feelings of isolation, social exclusion, anxiety and depression. Considering this, efforts must be made to increase the support and accessibility for this population. Integral to gauging the efficacy of these initiatives is the assessment of health-related quality of life (HRQoL). There are currently several measures used to evaluate HRQoL in people with aphasia. Each measure provides an evaluation of HRQoL from a broad perspective. However, several shortcomings cause these measures to lack sensitivity to the specific problems faced by this population, particularly with regard to communication. Stemming from this, the primary objective of this study was to design and validate an accessible HRQoL measure for people with aphasia while the secondary objective was to determine how individuals with aphasia score on this measure and the well-established SAQOL-39 compared with a matched control group. While this new measure demonstrates favorable properties, findings from the analyses of reliability, construct validity and concurrent validity have informed some essential changes. Once these changes have been made, these properties will be re-evaluated in a larger population. Consistent with the hypothesis, the findings from a Mann-Whitney U test indicate that participants with aphasia scored lower on both measures of HRQoL compared with a matched control group. Overall, this study served as an essential step in the development of this measure. The findings provide us with a more comprehensive understanding of how communication loss can impact an individual's life and help us pinpoint how to better aid this population.
Chapter 1 The Early Frankfurt School Critique of Capitalism: Critical Theory between Pollock's “State Capitalism” and the Critique of Instrumental Reason

Despite profound differences, both the German Historical School and the Critical Theory of the Frankfurt School share a common theoretical and cultural heritage in Central European traditions of social thought and philosophy. Although both schools often are perceived as quintessentially German traditions of economic and social research, their methodological presuppositions and critical intent diverge strongly. Since the objective of the Frankfurt School was to carry the theoretical critique initiated by Marx into the twentieth century, and since its members did so on a highly abstract level of theoretical criticism, the suggestion may be surprising that in terms of their respective research agendas, there was a common denominator between the German Historical School and Frankfurt School Critical Theory. To be sure, as will become apparent, the common ground was rather tenuous and indirect. We must ask, then: in what respects did their theoretical and analytical foundations and orientations overlap? How did the German Historical School, as a nineteenth-century tradition of economic thinking, influence the development of the Frankfurt School?
Development and Validation of the Eustress Questionnaire

Stress experiences are unavoidably in our everyday-life. Within research and press, stress is considered negative and its negative effects are exceedingly emphasized. The positive response to stress, called eustress, is much less researched. Eustress is a healthy, positive and constructive response to stressful events and can improve performance, health and well-being. Empirical research and a suitable scale to assess eustress are missing. The objective of this research was to develop and validate the Eustress Questionnaire (EQ) that can be used for empirical research. Therefore the psychometric properties factorial structure, internal consistency and convergent and discriminant validity were examined.
International Deal Experience and Cross-Border Acquisitions

By tracing nearly thirty thousand directors as they move across firms during a twenty-eight year period, I show that that a firm's decision to undertake its first cross-border acquisition is positively influenced by experience with these transactions gained by its current board members during their prior service on other companies' boards. Board experience most affects acquisitions of targets headquartered in culturally or institutionally dissimilar countries, with these deals being more likely to be completed successfully and to be received favorably by financial markets. These findings imply that the geography of international fixed capital investments is influenced by the experiential human capital of a firm's board of directors. Publication Status:
Active Balancing and Online Electrochemical Impedance Spectroscopy for Electric Vehicle Battery Management

Active Balancing and Online Electrochemical Impedance Spectroscopy for Electric Vehicle Battery Management Zhe Gong Master of Applied Science The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 2018 The Electric Vehicle (EV) battery system performance-to-cost ratio has been identified as a roadblock in the mass commercial adoption of EVs. This ratio can be increased by improving the models and management algorithms used in the Battery Management System (BMS). In this work, the potential for impedance-based battery models to enable such BMS improvements is explored. A power management architecture featuring active balancing and high-current online Electrochemical Impedance Spectroscopy (EIS) for real-time model identification of high-capacity, low-impedance automotive cells is proposed and experimentally demonstrated. The active balancing system eliminates the vehicle’s auxiliary power supply and incurs less cost than existing designs. The highcurrent EIS is enabled by a hybrid linear and switched-mode power architecture. The final vision of this work is the implementation of an EV BMS with real-time model identification and advanced model-based balancing, and the analysis and results here represent a starting point toward achieving that vision.
Sporting dissent: Colin Kaepernick, NFL activism, and media framing contests

In August 2016, Colin Kaepernick, a quarterback on the San Francisco 49ers of the National Football League, sat in protest during the national anthem. He made it clear that his stance was a political statement against racialized oppression and police brutality carried out against people of color in the USA, and in doing so he became a polarizing cultural figure. This article uses content analysis to examine newspaper coverage of the emergence and evolution of Kaepernick’s political activism over a critical two-year period, from August 2016 through August 2018. First, we identify the dominant frames that media adopted when covering his protests and their aftermath. Then we examine who got to speak in the articles: which sources tended to predominate and how did this inflect the principal frames? Finally, we explore whether Kaepernick’s activism deepened discussions over police brutality against African Americans or racial inequality in the USA. We conclude that the print media’s coverage was largely favorable to Kaepernick even as much of the coverage reduced the protest from being about racial injustice in the USA to being framed, reductively, as an “anthem protest. ”
Three Components of Readiness to Change: Communication of Change and Change-Efficacy as Antecendents

In order to fulfill the planned change, an organization should seriously take the role of individual perception into consideration, in which the individual plays a pivotal role in the change implementation stage through their act. This study aims to investigate the attitude of readiness to change based on the multidimensional concept, with communication of change and change-efficacy as antecedents. This study involved shariah rural bank, located in East Java, as a research object. Furthermore, a quantitative approach was employed in this study, in which survey as a procedure for collecting data through questionnaires. In addition, PLS-SEM was employed as an analysis of research method. The results exhibit that communication of change contribute to develop of almost all forms attitude of readiness to change and change-efficacy can predict all forms of readiness to change. Finally, this study offers several implications, both theoretically and practically.
Relationship between ambidexterity and entrepreneurial intensity

Abstract Within organisational analysis, a concept that has been gaining importance has been organisational ambidexterity, where two factors play an important role: entrepreneurial intensity and innovations. The objective of this article is to analyse the relationship between entrepreneurial intensity and ambidexterity. The conceptualisation of ambidexterity distinguishes between ambidextrous activities and ambidextrous outcomes. To carry out this objective, we have tested several theoretical relationships. We have used partial least squares methodology to develop an empirical study in 25 European countries. Results confirm that collaboration networks have a positive effect on entrepreneurship intensity. This effect is greater than the one obtained by ambidextrous activities or new technologies. We also show that entrepreneurship intensity has a mediating role between ambidextrous activities and ambidextrous outcomes.
The Effects of the CEO’s perceptual bias in economic decision-making and judgment on the capabilities of the financial reporting quality

The current research sets out to identify and scrutinize the impact of the CEO’s perceptual biases in judgment and economic decision-making on the reporting quality of the firms listed on the Tehran Stock Exchange. Adopting a mixed method, the present study first seeks to detect the components and indices of CEO’s perceptual biases via critical appraisal and with the special participation of 10 accounting experts. Afterwards, the rec-ognized indices are set to undergo a Delphi analysis given the mean and the coefficient of agreement. The verified indices are then adapted to the ac-counting models and analyzed in the form of research hypotheses. The re-sults of qualitative analysis using Delphi method verify the reliability of 16 indices out of 22 ones. Regarding the quantitative analysis, the association between the indices of the CEO’s perceptual biases in judgment and econom-ic decision-making, and the primary proxies of financial reporting, namely reliability and competitiveness is tested. The findings reveal that the indices of the CEO’s perceptual biases in judgment and economic decision-making exert a significantly negative effect on financial reporting reliability and competitiveness.