The Assessment of Fingerprint Quality for a More Effective Match Score in Minutiae-Based Matching Performers

One of the most common types of evidence recovered from a crime scene are latent fingerprints, however these impressions are often of low quality. The quality of a latent fingerprint is described as the degree to which the ridge details can be observed. If the quality of the latent fingerprint is very clear, a minutiae-based matching algorithm with automatic extraction may detect and utilize the minutiae that are truly present in the fingerprint. However, if the impression is of poor quality, the minutiae-based matching algorithm\u27s automatic extraction may detect fewer features and could completely miss features resulting in the return of an unrelated candidate. The aim of this research was to determine a method to improve the match score of latent fingerprints by removing the bad quality regions, where both a subjective and objective methods were utilized. The subjective method utilized the predetermined quality categories of good, bad or ugly to assign a latent fingerprint. After classification, each impression was processed by AdobeRTM PhotoshopRTM and four quality areas were serially removed. In the objective method, each latent fingerprint was assessed with NFIQ algorithm and then MINDTCT algorithm. The MINDTCT algorithm provided a quality map that was used to remove successive portions of each latent fingerprint. The resulting new images from both methods were compared to a database using the two different minutiae-based matching algorithms: AFIX TrackerRTM and BOZORTH3.;The results were examined utilizing the statistical methods of receiver operator characteristic (ROC) curves, area under the ROC curve (AUC), cumulative match characteristic (CMC) curve, Wilcoxon signed-rank test, Spearman\u27s rank correlation and the comparison of the removal methods. ROC curves and the resulting AUC were able to determine that the AFIX TrackerRTM program is a reliable performer with high AUC values, while the BOZORTH3 minutiae-based algorithm did not perform well with low AUC scores of around 0.5. The results produced from the CMC curves showed that the subjective method produced higher rank 1 and top 10 rank identification than the objective method, contrary to what was hypothesized. The correlation scores showed the manual and automatic extraction were weakly correlated to one another. However, a very weak to no correlation between the algorithms of the BOZORTH3 and AFIX Tracker R was observed. The comparison between the subjective and objective methods of removal showed the examiner allowed for a more conservative removal of the fingerprint than the objective method. With this result in connection with the CMC curve results shows that being more conservative produces higher rank 1 and top ten rank identification scores

Barriers and solutions to addressing tobacco dependence in addiction treatment programs.

Despite the high prevalence of tobacco use among people with substance use disorders, tobacco dependence is often overlooked in addiction treatment programs. Several studies and a meta-analytic review have concluded that patients who receive tobacco dependence treatment during addiction treatment have better overall substance abuse treatment outcomes compared with those who do not. Barriers that contribute to the lack of attention given to this important problem include staff attitudes about and use of tobacco, lack of adequate staff training to address tobacco use, unfounded fears among treatment staff and administration regarding tobacco policies, and limited tobacco dependence treatment resources. Specific clinical-, program-, and system-level changes are recommended to fully address the problem of tobacco use among alcohol and other drug abuse patients

Russian Verbs of Sound’s Web-Scraping Results from the A.A. Zalizniak Grammatical Dictionary and the Russian National Corpus. Multi-Dimensional Scaling Techniques and Visualization Strategies

This project aims to enhance web extraction techniques pertaining to a specific lexical-semantic group of Russian verbs of sounds, which undergo semantic modifications at the word-formation level (affixation). Additionally, it seeks to organize search results in a manner conducive to linguistic research using Multi-Dimensional Scaling (MDS) techniques and novel visualization strategies. The primary objective in this phase of the research was to gather, consolidate, analyze, and present a comprehensive index of all forms of verbs of sound sourced from the A.A. Zalizniak Grammatical Dictionary of the Russian language, hyperlink each verbal form in this index with the Russian National Corpus (RNC) - a closed digital repository of more than two billion entries with over five-million-word forms. The output not only encompasses all documented modifications of verbs of sound but also identifies gaps, duplicates, and suggests new potential units. The research methodology has value for developing diverse applications aimed at searching, collecting, and visualizing linguistic data of various volumes and complexities. Leveraging combinatorial optimization techniques in processing open and closed linguistic databases can be particularly crucial when extracting information from diverse digital lexicographic sources across single or multiple languages, national linguistic corpora, and digital text collections. Our cross-disciplinary research highlights the transformative role of digital tools in advancing linguistic inquiry and illustrates the ways for future explorations at the intersection of natural language, technology, and culture

Effect of Subsurface Microseismicity on the Motion of Surrounding Dispersed Droplets: Supporting Information

The human-induced seismicity has called substantial attention in recent years. The effect of seismicity on the subsurface structure has been extensively studied. However, the effect of seismicity, especially those microseismicity, on surrounding immiscible fluids is rarely investigated. In porous media with two or more immiscible fluids, different amplitudes of vibration induced by seismicity have distinct effects on the dynamic behavior of fluids. Three types of pore-scale models are prevalent in the analysis of the motion of immiscible droplets. The underlying assumptions and accuracy of these models are compared in this study in both frequency domain and time domain. The frequency domain analysis shows that the resonance can be addressed in all of three models, but the frequency response curves present significant differences. These differences are attributed to the missing physics considered in some models. The time domain analysis in both small-amplitude oscillation and large-amplitude oscillation is performed. The nonlinear feature in large-amplitude oscillation is attributed to the constricted geometry of capillary tube. The momentum balance model is identified as so-far the most accurate oscillatory model by the comparison with computational fluid dynamics simulations. In addition, the potential approach to incorporate this pore-scale model in seismic wave attenuation analysis is found possible. The frequency correction function and structural factor are calculated to embed the momentum balance model into Biot \u27s poroelastic model. The resonance of dispersed phase can also be addressed theoretically in porous media of random packed spheres

Staffing Levels in Rural Nursing Homes.

This mixed methods study used multiple regression analyses to examine the impact of organizational and market characteristics on staffing hours and staffing mix, and qualitative interview to explore the challenges and facilitators of recruiting and retaining qualified staff. Rural nursing homes (NHs) certified by Medicare or Medicaid (N = 161) were sampled from the Online Survey Certification and Reporting system. A subsample (n = 23) was selected purposively for the qualitative analysis. Smaller NHs or government-affiliated homes had more total nursing hours per resident day and more hours of care by certified nursing assistants and RNs than larger and nongovernment-affiliated homes; however, almost 87% of NHs in this study were below the national recommendation for RN hours. Informants voiced challenges related to enough staff, qualified staff, and training staff. Development of nursing resources is critical, especially in rural locales where aging resources may not be well developed

Experimental Investigation of the Dynamics of Trapped Non-Wetting Droplets Subjected to the Seismic Stimulation in Constricted Tubes: Supporting Information

Aspect Ratio of 4.5 Aspect Ratio of 9.0 Video Demo

Plant Identification in a Combined-Imbalanced Leaf Dataset

Plant identification has applications in ethnopharmacology and agriculture. Since leaves are one of a distinguishable feature of a plant, they are routinely used for identification. Recent developments in deep learning have made it possible to accurately identify the majority of samples in five publicly available leaf datasets. However, each dataset captures the images in a highly controlled environment. This paper evaluates the performance of EfficientNet and several other convolutional neural network (CNN) architectures when applied to a combination of the LeafSnap, Middle European Woody Plants 2014, Flavia, Swedish, and Folio datasets. To normalize the impact of imbalance resulting from combining the original datasets, we used oversampling, undersampling, and transfer learning techniques to construct an end-to-end CNN classifier. We placed greater emphasis on metrics appropriate for a diverse-imbalanced dataset rather than stressing high performance on any one of the original datasets. A model from EfficientNet’s family of CNN models achieved a highly accurate F-score of 0.9861 on the combined dataset

Experimental multi-dimensional scaling of web-scraping results from the A.A Zalizniak Grammatical Dictionary and the Russian National Corpus. Creating a corpus fragment of all possible word-forms of modified Russian sound verbs using web-scraping methodology. Compilation of a summary table for the present tense, future tense, imperative, imperfective and perfective gerund forms.

The emergence and development of electronic versions of dictionaries and corpus databases allows the researcher to finally do what was technically impossible on paper: to collect, compile and analyze the entire index of all possible verbal forms of different ranges and scales. This project attempts to improve the method of web extraction in relation to the source material (lexical-semantic group of Russian sound verbs, semantically modified at the word-forming level) and summarize the search results as an interactive summary table. A novel, four-position system of numbering the verbal forms have been introduced and a subsequent experimental multi-dimensional scaling of results successfully carried out. The output takes into account not only all documented (submitted) modifications of sound verbs from the A.A Zaliznijak Grammatical Dictionary and the Russian National Corpus, but also reveals lacunae, dublets, and indicates new (potential) units. The results of the study may be useful for the development of various web applications for the search, collection, and visualization of linguistic material. Possibilities of combinatorial optimization in the processing of open and closed linguistic databases can be particularly important when extracting information from various digital lexicographic sources (across a single or multiple languages), from national linguistic corpora, as well as from digital text collections. Появление и развитие электронных версий словарей русского языка и корпусных баз данных позволяют исследователю сделать то, что прежде было технически неосуществимо при работе с бумажными словарями: собрать, скомпилировать (соединить результаты) и проанализировать обобщающий индекс всех возможных глагольных форм в различных диапазонах и масштабах. В данном проекте предпринята попытка не только усовершенствовать методику веб-извлечения применительно к исходному материалу (лексико-семантической группе русских звуковых глаголов, модифицированных на словообразовательном уровне), но и обобщить результаты поиска. Разработана и введена новая четырехпозиционная система нумерации исходных форм глагола и их словоформ. Успешно проведено системное извлечение и фиксирование результатов поиска в виде многомерной сводной интерактивной таблицы. Выходные данные документируют не только все словоформы звуковых глаголов, представленные в Грамматическом словаре А.А. Зализняка и Национальном корпусе русского языка, но и выявляют существующие дублеты, внутриязыковые лакуны, указывают на новые (потенциальные) единицы. Результаты исследования могут быть полезны в разработке различных веб-приложений для поиска, сбора и визуализации лингвистического материала. Возможности комбинаторной оптимизации открытых и закрытых баз данных могут быть особенно значимы при извлечении информации из цифровых лексикографических источников (на одном или нескольких языках), из национальных языковых корпусов, а также из электронных текстовых коллекций

Adult Cognitive and Non-cognitive Skills: An Overview of Existing PIAAC Data

As of summer 2019, more than 60 PIAAC datasets from participating countries worldwide were available for research purposes. These datasets can be differentiated, for example, in terms of their accessibility, the extent of the information provided, the population group in focus, and the design of the underlying study. PIAAC Public Use Files, for instance, are freely available and are therefore highly anonymised, whereas PIAAC Scientific Use Files are available only for scientific research purposes and provide access to more detailed variables. The majority of the PIAAC data are available as public use files, but some participating countries (e.g. Germany and the United States) have also made several scientific use files or other extended file versions available to the research community. Some of the available PIAAC datasets focus on specific population groups - for example, the incarcerated adult population in the United States. Regarding the design of the underlying studies, most available datasets are cross-sectional, but some longitudinal data already exist (e.g. PIAAC-L in Germany). The present chapter provides an overview of the structure, accessibility, and use of the PIAAC datasets available worldwide

Correlates of Smoke-Free Policies in Homes and Cars Among Hawaii Residents

The detrimental health effects of environmental tobacco smoke (ETS) have been well established. Cars and homes are two of the primary places that nonsmokers, particularly children, are exposed to ETS. This study examined the prevalence of smoke-free policies in homes and cars among 4,557 residents of Hawaii using cross-sectional data collected from a random-digit dial telephone survey. Smokers were much less likely than nonsmokers and former smokers to have smoke-free policies. Multivariate analysis of current smokers revealed that significant predictors of banning smoking in the home were: disagreeing that it is okay to smoke indoors, smoking fewer cigarettes per day, and higher confidence in ability to quit smoking. Significant predictors of banning smoking in the car were: disagreeing that it is okay to smoke indoors, smoking fewer cigarettes per day, and having children in the household. This study indicates that changing smokers’ attitudes about ETS may be an important component of a comprehensive program to increase smoke-free homes and cars