Sound Visualization for Deaf Assistance Using Mobile Computing

This thesis presents a new approach to the visualization of sound for deaf assistance that simultaneously illustrates important dynamic sound properties and the recognized sound icons in an easy readable view. .In order to visualize general sounds efficiently ,the MFCC sound features was utilized to represent robust discriminant properties of the sound. The problem of visualizing MFCC vector that has 39 dimensions was simplified by visualizing one-dimensional value, which is the result of comparing one reference MFCC vector with the input MFCC vector only. New similarity measure for MFCC feature vectors comparison was proposed that outperforms existing local similarity measures due to their problem of one to one attribute value calculation that leaded to incorrect similarity decisions. Classification of input sound was performed and attached to the visualizing system to make the system more usable for users. Each time frame of sound is put under K-NN classification algorithm to detect short sound events. In addition, every one second the input sound is buffered and forwarded to Dynamic Time Warping (DTW) classification algorithm which is designed for dynamic time series classification. Both classifiers works in the same time and deliver their classification results to the visualization model. The application of the system was implemented using Java programming language to work on smartphones that run Android OS, so many considerations related to the complexity of algorithms is taken into account. The system was implemented to utilize the capabilities of the smartphones GPU to guarantee the smoothness and fastness of the rendering. The system design was built based on interviews with five deaf persons taking into account their preferred visualizing system. In addition to that, the same deaf persons tested the system and the evaluation of the system is carried out based on their interaction with the system. Our approach yields more accessible illustrations of sound and more suitable for casual and little expert users

Comparative Analysis of the Performance of Popular Sorting Algorithms on Datasets of Different Sizes and Characteristics

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios

Exposure assessment of radon in the drinking water supplies: a descriptive study in Palestine

<p>Abstract</p> <p>Background</p> <p>Radon gas is considered as a main risk factor for lung cancer and found naturally in rock, soil, and water. The objective of this study was to determine the radon level in the drinking water sources in Nablus city in order to set up a sound policy on water management in Palestine.</p> <p>Methods</p> <p>This was a descriptive study carried out in two phases with a random sampling technique in the second phase. Primarily, samples were taken from 4 wells and 5 springs that supplied Nablus city residents. For each source, 3 samples were taken and each was analyzed in 4 cycles by RAD 7 device manufactured by Durridge Company. Secondly, from the seven regions of the Nablus city, three samples were taken from the residential tap water of each region. Regarding the old city, ten samples were taken. Finally, the mean radon concentration value for each source was calculated.</p> <p>Results</p> <p>The mean (range) concentration of radon in the main sources were 6.9 (1.5-23.4) Becquerel/liter (Bq/L). Separately, springs and wells' means were 4.6 Bq/L and 9.5 Bq/L; respectively. For the residential tap water in the 7 regions, the results of the mean (range) concentration values were found to be 1.0 (0.9-1.3) Bq/L. For the old city, the mean (range) concentration values were 2.3 (0.9-3.9) Bq/L.</p> <p>Conclusions</p> <p>Except for Al-Badan well, radon concentrations in the wells and springs were below the United State Environmental Protection Agency maximum contaminated level (U.S EPA MCL). The level was much lower for tap water. Although the concentration of radon in the tap water of old city were below the MCL, it was higher than other regions in the city. Preventive measures and population awareness on radon's exposure are recommended.</p

Molecular Characterization of Cryptosporidium Species and Giardia duodenalis from Symptomatic Cambodian Children

Background: In a prospective study, 498 single faecal samples from children aged under 16 years attending an outpatient clinic in the Angkor Hospital for Children, northwest Cambodia, were examined for Cryptosporidium oocysts and Giardia cysts using microscopy and molecular assays. Methodology/Principal Findings: Cryptosporidium oocysts were detected in 2.2% (11/498) of samples using microscopy and in 7.7% (38/498) with molecular tests. Giardia duodenalis cysts were detected in 18.9% (94/498) by microscopy and 27.7% (138/498) by molecular tests; 82% of the positive samples (by either method) were from children aged 1–10 years. Cryptosporidium hominis was the most common species of Cryptosporidium, detected in 13 (34.2%) samples, followed by Cryptosporidium meleagridis in 9 (23.7%), Cryptosporidium parvum in 8 (21.1%), Cryptosporidium canis in 5 (13.2%), and Cryptosporidium suis and Cryptosporidium ubiquitum in one sample each. Cryptosporidium hominis and C. parvum positive samples were subtyped by sequencing the GP60 gene: C. hominis IaA16R6 and C. parvum IIeA7G1 were the most abundant subtypes. Giardia duodenalis was typed using a multiplex real-time PCR targeting assemblages A and B. Assemblage B (106; 76.8% of all Giardia positive samples) was most common followed by A (12.3%) and mixed infections (5.1%). Risk factors associated with Cryptosporidium were malnutrition (AOR 9.63, 95% CI 1.67–55.46), chronic medical diagnoses (AOR 4.51, 95% CI 1.79–11.34) and the presence of birds in the household (AOR 2.99, 95% CI 1.16–7.73); specifically C. hominis (p = 0.03) and C. meleagridis (p<0.001) were associated with the presence of birds. The use of soap was protective against Giardia infection (OR 0.74, 95% CI 0.58–0.95). Conclusions/Significance: This is the first report to describe the different Cryptosporidium species and subtypes and Giardia duodenalis assemblages in Cambodian children. The variety of Cryptosporidium species detected indicates both anthroponotic and zoonotic transmission in this population. Interventions to improve sanitation, increase hand washing after defecation and before preparing food and promote drinking boiled water may reduce the burden of these two parasites

Life Cycle Management of Infrastructures

By definition, life cycle management (LCM) is a framework “of concepts, techniques, and procedures to address environmental, economic, technological, and social aspects of products and organizations in order to achieve continuous ‘sustainable’ improvement from a life cycle perspective” (Hunkeler et al.\ua02001). Thus, LCM theoretically integrates all sustainability dimensions, and strives to provide a holistic perspective. It also assists in the efficient and effective use of constrained natural and financial resources to reduce negative impacts on society (Sonnemann and Leeuw\ua02006; Adibi et al.\ua02015). The LCM of infrastructures is the adaptation of product life cycle management (PLM) as techniques to the design, construction, and management of infrastructures. Infrastructure life cycle management requires accurate and extensive information that might be generated through different kinds of intelligent and connected information workflows, such as building information modeling (BIM)

Anthroponotic transmission of Cryptosporidium parvum predominates in countries with poorer sanitation - a systematic review and meta-analysis

Background: Globally cryptosporidiosis is one of the commonest causes of mortality in children under 24 months old and may be associated with important longterm health effects. Whilst most strains of Cryptosporidium parvum are zoonotic, C. parvum IIc is almost certainly anthroponotic. The global distribution of this potentially important emerging infection is not clear. Methods: We conducted a systematic review of papers identifying the subtype distribution of C. parvum infections globally. We searched PubMed and Scopus using the following key terms Cryptospor* AND parvum AND (genotyp* OR subtyp* OR gp60). Studies were eligible for inclusion if they had found C. parvum within their human study population and had subtyped some or all of these samples using standard gp60 subtyping. Pooled analyses of the proportion of strains being of the IIc subtype were determined using StatsDirect. Meta-regression analyses were run to determine any association between the relative prevalence of IIc and Gross Domestic Product, proportion of the population with access to improved drinking water and improved sanitation. Results: From an initial 843 studies, 85 were included in further analysis. Cryptosporidium parvum IIc was found in 43 of these 85 studies. Across all studies the pooled estimate of relative prevalence of IIc was 19.0% (95% CI: 12.9–25.9%), but there was substantial heterogeneity. In a meta-regression analysis, the relative proportion of all C. parvum infections being IIc decreased as the percentage of the population with access to improved sanitation increased and was some 3.4 times higher in those studies focussing on HIV-positive indivduals. Conclusions: The anthroponotic C. parvum IIc predominates primarily in lower-income countries with poor sanitation and in HIV-positive individuals. Given the apparent enhanced post-infectious virulence of the other main anthroponotic species of Cryptosporidium (C. hominis), it is important to learn about the impact of this subtype on human health

Anthroponotic transmission of Cryptosporidium parvum predominates in countries with poorer sanitation - a systematic review and meta-analysis

Background: Globally cryptosporidiosis is one of the commonest causes of mortality in children under 24 months old and may be associated with important longterm health effects. Whilst most strains of Cryptosporidium parvum are zoonotic, C. parvum IIc is almost certainly anthroponotic. The global distribution of this potentially important emerging infection is not clear. Methods: We conducted a systematic review of papers identifying the subtype distribution of C. parvum infections globally. We searched PubMed and Scopus using the following key terms Cryptospor* AND parvum AND (genotyp* OR subtyp* OR gp60). Studies were eligible for inclusion if they had found C. parvum within their human study population and had subtyped some or all of these samples using standard gp60 subtyping. Pooled analyses of the proportion of strains being of the IIc subtype were determined using StatsDirect. Meta-regression analyses were run to determine any association between the relative prevalence of IIc and Gross Domestic Product, proportion of the population with access to improved drinking water and improved sanitation. Results: From an initial 843 studies, 85 were included in further analysis. Cryptosporidium parvum IIc was found in 43 of these 85 studies. Across all studies the pooled estimate of relative prevalence of IIc was 19.0% (95% CI: 12.9–25.9%), but there was substantial heterogeneity. In a meta-regression analysis, the relative proportion of all C. parvum infections being IIc decreased as the percentage of the population with access to improved sanitation increased and was some 3.4 times higher in those studies focussing on HIV-positive indivduals. Conclusions: The anthroponotic C. parvum IIc predominates primarily in lower-income countries with poor sanitation and in HIV-positive individuals. Given the apparent enhanced post-infectious virulence of the other main anthroponotic species of Cryptosporidium (C. hominis), it is important to learn about the impact of this subtype on human health

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised