Miracle-dz/UniFAR-FTUs huggingface dataset:
Innovative Privacy Practices

The panel is premised by a recurring theme in empirical privacy research: as privacy localism drive regulation and policy change, we are left with a landscape that is fragmented, across states and sectors; confusing, between places and stakeholders; and often insufficient, as laws address narrow sets of privacy harms or specific actors. This raises the question: How can organizations and individuals innovate to address privacy policy gaps and fragmentation? This panel aims to describe and discuss creative and experimental approaches to institutionalize privacy practices in different contexts and organizations, moving beyond relying on policy alone to promote social good. We address this from a variety of perspectives including licensing, contracting, privacy by design including via architecture, records laws, AI ethics, human rights, obfuscation, and activism.
Impacts of Information Source and Perceived Health on Information Behavior

This preliminary study revisits a fundamental information problem of information behavior, focusing on needs, overload, and information source use, in the context of the COVID‐19 pandemic. The associations between the impact of information source use on the extent of information needs, being exposed to information, and feeling of overload was examined. Furthermore, to understand the impact of context on information behavior, the differences in the degree of information resource use, needs, exposure, and overload between the two groups with different levels of health were investigated.
Building Areas Detection in SAR Images Based on Level Set

According to the characteristic of building areas in Synthetic Aperture Radar(SAR) images,a method based on the level set is used to detect building areas and building targets.It uses the boundary feature based on exponential wavelet and texture feature based on variogram to build the energy criterion model,and then the evolutive curve is implemented by minimizing the energy criterion via variational level set approach to detect the building areas.Compared with the traditional energy criterion model based on the gray information,experimental results show that the proposed method is effective and can detect building areas of the large SAR image accurately.
Relationship between Work Environment and Organizational Commitment among Private School Teachers in Klang Valley

The main purpose of this study is to determine the relationship between work environment and organizational commitment among private school teachers in Klang Valley. Survey questionnaires were distributed to five private schools. 110 private school teachers participated in the survey. Data regarding organizational commitment and work environment were analyzed by using IBM SPSS Software version 22.0. Descriptive statistic was employed to identify level of teachers' work environment and organizational commitment. Pearson correlation was used to analyze the relationship between work environment and organizational commitment among private school teachers. T-test is to identify the difference of private school teachers’ organizational commitment based on gender. The results demonstrated that there are moderate relationships between teachers' work environment and teacher's organizational commitment. The findings also revealed that there are no significant different between female and male private school teachers in organizational commitment.
Not in My Backyard: Personal Politics and Resident Attitudes toward Tourism

This research looks at the relationship between political libertarianism and personal self-interest, as informed by the concept of NIMBYism (not-in-my-backyard) that underlies much of the resident attitude toward tourism literature. Based on a comprehensive survey of more than 500 residents from Charleston, South Carolina, a city heavily dependent on tourism, the research determined, as the literature would predict, that general views toward tourism were highly dependent on where one lives. However, for specific tourism issues, one’s personal political views tended to trump geography. Application of theory and suggestions for tourism policy makers are provided.
An Adaptive Topic Tracking Model Based on 3-Dimension Document Vector

Topic Tracking(TT),which grows out of the Topic Detection and Tracking(TDT) tasks,is a technology of information intelligent acquisition for dynamic developments of events.Its aim is to automatically track the subsequent news stories of known events from the information stream of news media.By analyzing the lacks of traditional document vector space model and the characteristics of news reports,this paper presents a new document vector model of 3 dimensions,which stresses the theme and entities of news stories.Then we proposed a topic model consistent with the feature of news reports,which can adjust itself to the developments of events in the process of topic tracking by means of self-learning.Combining with the topic model,we also designed a complete adaptive KNN topic tricking model for Chinese topic tracking.The experimental results show that the proposed approach can accurately describe the news topic and effectively avoid theme drift and eventually achieve good performance in Chinese topic tracking.
Chapter 8: Deep Neural Network Sequence-Discriminative Training

The cross-entropy criterion discussed in the previous chapters treats each frame independently. However, speech recognition is a sequence classi fication problem. In this chapter, we introduce the sequence-discriminative training techniques that match better to the problem. We describe the popular maximum mutual information (MMI), boosted MMI (BMMI), minimum phone error (MPE), and minimum Bayes risk (MBR) training criteria, and discuss the practical techniques, including lattice generation, lattice compensation, frame dropping, frame smoothing, and learning rate adjustment, to make DNN sequence-discriminative training effective.
Optimization of Metro Passenger Organizing of Alighting and Boarding Processes: Simulated Evidence from the Metro Station in Nanjing, China

Since the long dwell time and chaotic crowds make metro trips inefficient and dissatisfying, the importance of optimizing alighting and boarding processes has become more prominent. This paper focuses on the adjustment of passenger organizing modes. Using field data from the metro station in Nanjing, China, a micro-simulation model of alighting and boarding processes based on an improved social force paradigm was built to simulate the movement of passengers under different passenger organizing modes. Unit flow rate, delay, and social force work (SFW) jointly reflect the efficiency and, especially, the physical energy consumption of passengers under each mode. It was found that when passengers alighted and boarded by different doors, efficiency reached its optimal level which was 76.92% higher than the status quo of Nanjing, and the physical energy consumption was reduced by 16.30%. Both the findings and the model can provide support for passenger organizing in metro stations, and the concept of SFW can be applied to other scenes simulated by the social force model, such as evacuations of large-scale activities, to evaluate the physical energy consumption of people.
Techniques for Noise Robustness in Automatic Speech Recognition

Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field
A Simulation Study on the Performance of the RAW in IEEE 802.11ah WLANs

Restricted Access Window (RAW) has been designed to improve power saving efficiency by reducing collisions of contending stations in the IEEE 802.11ah Wireless Local Area Networks (WLANs). We conduct simulations in order to observe the stations’ operations influencing the lengths of the Restricted Access Window (RAW). From the observation, we consider how to adjust the stations’ operations for proper RAW managements.
Safeness Discussions on TRBAC and GTRBAC Model and an Improved Temporal Role-Based Access Control Model

Bertino et al. propose a temporal Role-based Access Control (TRBAC) model, and Joshi et al. propose a Generalized TRBAC (GTRBAC) model based on TRBAC. Some periodic constraints and duration constraints are introduced to express the corresponding time-based access control policy semantics and enhance the expressiveness of the temporal RBAC model. We have analyzed the TRBAC and GTRBAC models and pointed out that the sufficient conditions for guaranteeing the safeness of the GTRBAC model was not comprehensive, so we have analyzed the reasons and designed a process rule to solve the safety problem. In this paper, an improved process rule is designed to solve the safety problem. In addition, a fault about translating a dependent trigger of TRBAC into an Oracle trigger is analyzed. In order to ensure the temporal RBAC model better, an Improved Generalized Temporal Role-based Access Control (IGTRBAC) based on the TRBAC and GTRBAC models is put forward. The two proposed restrictions in the IGTRBAC model are used to resolve the security problems caused by the dependent trigger and the cardinality constraint on role activation. At last, case study shows that the IGTRBAC model is safe.
Learning Fraction using the Context of Pipettes for Seventh-Grade Deaf-Mute Student

The deaf-mute students have limited communication and knowledge, which result in their limitations in learning mathematics. This study aims to determine the development of the deaf-mute student in learning mathematics, especially about a fraction. The method used is the Single Subject Research (SSR) by implementing the Indonesia Realistic Mathematics Education (IRME) Approach by using the context of pipettes. Data collection techniques used are video recordings, documentation, and written data. This research instrument uses videos to see the learning process and when students work on the given problems, photos to refer the results of student work, and written test in worksheets to get the data on student’s work. The data analysis technique used is analyzed in conditions and between conditions with A-B research design. The research results show that the implementation of IRME approach using the pipette context can improve the understanding of fraction concepts and the learning outcomes of the deaf-mute student. All intervention and student’s strategy in learning process would be described in this paper.
Self-collection of capillary blood and saliva to determine COVID-19 vaccine immunogenicity in patients with immune-mediated inflammatory diseases and health professionals

Introduction Being able to independently determine vaccine induced antibody responses by minimal-invasive methods is of great interest to enable a flexible and effective vaccination strategy. This study aimed to evaluate (1) the accuracy, feasibility, usability and acceptability of capillary blood and saliva self-sampling to determine SARS-CoV-2 antibody responses in patients with immune-mediated inflammatory diseases (IMIDs) and health professionals (HP). Methods IMID patients and HP having received two doses of SARS-CoV-2 vaccines, self-collected capillary blood (Tasso+) and saliva samples. Capillary samples were considered interchangeable with venous blood if three criteria were met: Spearman's correlation coefficient (r) > 0.8, non-significant Wilcoxon signed-rank test (i.e., p > 0.05), and a small bias or 95% of tests within 10% difference through Bland-Altman. Participants completed a survey to investigate self-sampling usability (system usability scale; SUS) and acceptability (net promoter score; NPS). Study personnel monitored correct self-sampling completion and recorded protocol deviations. Results 60 participants (30 IMID patients and 30 HP) were analyzed. We observed interchangeability for capillary samples with an accuracy of 98.3/100% for Anti-SARS-CoV-2 IgG/IgA antibodies, respectively. Fifty-eight capillary blood samples and all 60 saliva samples were successfully collected within the first attempt. Usability of both self-sampling procedures was rated as excellent, with significantly higher saliva ratings (p < 0.001). Capillary self-sampling was perceived as significantly (p < 0.001) less painful compared to traditional venous blood collection. Participants reported a NPS for capillary and saliva self-sampling of +68% and +63%, respectively. The majority of both groups (73%) preferred capillary self-sampling over professional venous blood collection. Conclusion Our results indicate that capillary self-sampling is accurate, feasible and preferred over conventional venous blood collection. Implementation could enable easy access, flexible vaccination monitoring, potentially leading to a better protection of vulnerable patient groups. Self-collection of saliva is feasible and safe however more work is needed to determine its application in clinical practice.
Exploring two measures of spatial accessibility to organizational resources in a small city

ABSTRACT Research has documented neighborhood-level disparities in organizational resources. Organizational resources may meet residents’ needs because, as social organization theory suggests, they generate social ties, establish and enforce local norms, and promote social control. However, few studies have examined access to organizational resources in micropolitan cities, which are important for research on place and inequality because of their growing population and poverty. This study presents findings from an assessment conducted in a Midwestern micropolitan city implementing a new community development initiative. We collected data on program delivery locations and assessed spatial accessibility using two measures of organizational resources in neighborhoods: (1) the count of programs and (2) the average distance to all programs from a neighborhood centroid. Findings reveal distinct characteristics of micropolitan geography. Access to resources was not equitably distributed. However, neighborhood socioeconomic disadvantage was not associated with organizational resource access. Implications for assessment and community development efforts are discussed.
Long-term agrichemical use leads to alterations in bacterial community diversity.

Bacterial communities are key drivers of soil fertility and agriculture productivity. Understanding how soil bacterial communities change in response to different conditions is an important aspect in the development of sustainable agriculture. There is a desire to reduce the current reliance on high inputs of chemicals and fertilisers in agriculture, but limited data are available on how this might impact soil bacterial communities. This study investigated the bacterial communities in a spring barley monoculture site subjected to two different input regimes for over 12 years: a conventional chemical/fertiliser regime, and a reduced input regime. A culture independent approach was performed to compare the bacterial communities through 16S rRNA gene PCR-DGGE. PCO analysis revealed that the rhizosphere has a strong structuring effect on the bacterial community. Moreover, high inputs of agrichemicals lead to an increase of phosphorus level in the soil and a concomitant reduction of the bacterial diversity. These results may help to evaluate the environmental risks associated with agrichemical usage.
Intranet Exploitation of Social Network Knowledge Intelligence

Intranets are almost as old as the concept of a web site. More than twenty-five years ago the text Business Data Communications closed with a discussion of intranets (Stallings, 1990). Underlying technology improvements in intranets have been incremental; intranets were never seen as killer developments. Yet the popularity of Online Social Networks (OSNs) has led to increased interest in the part OSNs play – or could play – in using intranets to foster knowledge management. This chapter reviews research into how social graphs for an enterprise, team or other collaboration group interacts with the ways intranets have been used to display, collect, curate and disseminate information over the knowledge life cycle. Future roles that OSN-aware intranets could play in emerging technologies, such as process mining, elicitation methods, domain-specific intelligent agents, big data, and just-in-time learning are examined.
Self-Concept and Social Adjustment of First-Year Students

Objective - Students who study in higher education institutions should have a good socialization process since it later influences their happiness and sadness during their first year of university life. They may face some difficulties and problems that may inhibit their academic success if they cannot adjust well. One of the successful social adjustment criteria is self-concept, in which is derived from interactions with others, for example, the environment. For that reason, it is important to investigate the self-concept and social adjustment of Psychology students, at UIN Maulana Malik Ibrahim Malang, during the first semester. This paper therefore aims to a) determine the degree of student social adjustment, b) determine the quality of self-concept, and c) identify the relationship between self-concept and social adjustment among first year students of Psychology, UIN Maulana Malik Ibrahim Malang. Methodology/Technique – The subjects of this study include 134 first year students at the Faculty of Psychology, UIN Maulana Malik Ibrahim Malang, East Java. The data was collected in accordance with the scale of self-concept and social adjustment. Finding & Novelty - The results show that 1) the degree of first students’ self-concept is in average scale, 69.4%, 2) the social adjustment of first year students belongs to a moderate category, 71,6%, and 3) self-concept has positive correlation to social adjustment (r = 0,703, p = 0,000). These findings confirm that the higher the self-concept the students poses, the better the social adjustment they perform. This study suggests the need for intervention to escalate self-concept and social adjustment of students by collaborating with some stakeholders, particularly students’ parents, universities, government, societies, and religious figures. Type of Paper: Empirical.
A Survey of Blind Source Separation and Blind Deconvolution

Blind signal processing is attractive in the community of signal processing.Blind source separation and Blind deconvolution are main components in blind signal processing and advances have been developed in recent years.We introduce the basic model of blind source separation and blind deconvolution,the mathematical principle of them,and the latest progresses in research.We then analyze the characteristic of typical algorithms and point out the future development.
Toolkit for Automatic Collection and Predictive Modelling of Software Metrics

For empirical software researchers, the management of experimental data and results is time-intensive and a significant source of error. As a result, research in this area is often difficult to reproduce, falsify and generalize. Software projects deemed feasible for study are typically of a limiting size and belong to particular domains for which measurement tools are available. We propose a toolkit for data gathering and exploratory modelling in empirical software research. Requirements are derived from issues commonly affecting studies of defect prediction and software evolution. We develop the toolkit by using a prototype-driven approach. The prototype toolkit is used to carry out a case study illustrating its effectiveness and potential for future extension.
Virtual coaching for child welfare workers – a tool to promote learning

ABSTRACT This pilot study considers the effects of a virtual coaching intervention on learning outcomes of an online training for child welfare workers. A two-group pretest–posttest design was used to assess differences in outcomes for participants taking part in virtual coaching (n = 27) compared with similar participants who received online training only (n = 300). The virtual coaching group completed significantly more training modules and perceived greater improvements in knowledge and practice than the no-coaching group. Findings suggest the importance of coaching to support transfer of learning and the efficacy of virtual coaching.
The Role of Cooperative Extension in Chronic Disease Prevention and Management: Perspectives from Professionals in the Field

Chronic diseases are strongly associated with premature death and increased health care costs. Nearly half of American adults report they have one or more chronic health conditions. Cooperative Extension is calling for refocus to refine and align with broader efforts to promote public health by supporting the prevention and management of chronic disease. The success of this refocus is dependent on a shared vision between funding agencies, stakeholders, and Extension. As part of developing this shared vision, the Chronic Disease Health Implementation Team surveyed 152 Extension administrators, faculty, and Extension Agents/Educators to determine their perception of the role of Extension in chronic disease prevention and management in the next century. Respondents answered the open-ended question, “What role should Cooperative Extension have in working to reduce chronic diseases in America for the next 10, 25, and 100 years? " Analysis with grounded theory identified three themes. The respondents perceived the role of Extension professionals as educators and collaborators in chronic disease prevention and management who focus on influencing individuals and environments. As educators, Extension should deliver evidence-based programs to communicate, inform, facilitate, and teach. As collaborators, Extension should facilitate and nurture partnerships to effect changes in chronic disease prevention and management.
Review of Statistical Shape Prior-based Level Set Image Segmentation

Image segmentation problem often demands the incorporation of as much prior information as possible to help the segmentation algorithms extract the tissue of interest.The model of image segmentation based on statistical shape prior level set was reviewed.The feature of mode is the energy function of the model composed by two terms.The first one is data term based on the image gradient or region gray intensity,the second one is the shape prior term which provides robustness against missing shape information due to cluttering,occlusion and gaps.How to construct the implicit shape model which aims to extract a compact representation for the structure of interest from a set of training examples,how to construct the evolve model to constrain an implicit surface to follow global shape consistence while preserving its ability to capture local deformation were discussed intensively.The key problems such as shape registration and the correspondence problem were introduced.Finally the open issues and possible future research directions were pointed.