An Intelligent Analysis of Crime through Newspaper Articles - Clustering and Classification

Crime analysis is one of the most important activities of the majority of the intelligent and law enforcement organizations all over the world. Thus, it seems necessary to study reasons, factors and relations between occurrence of different crimes and finding the most appropriate ways to control and avoid more crimes. A major challenge faced by most of the law enforcement and intelligence organizations is efficiently and accurately analyzing the growing volumes of crime related data. The vast geographical diversity and the complexity of crime patterns have made the analyzing and recording of crime data more difficult. This paper presents an intelligent crime analysis system which is designed to overcome the above mentioned problems. Data mining is used extensively in terms of analysis, investigation and discovery of patterns for occurrence of different crimes. The proposed system is a web-based system which performs crime analysis through news articles. In this paper we use a clustering/ classification based model to automatically group the retrieved documents into a list of meaningful categories. The data mining techniques are used to analyze the web data

Ethnic Variations in Perception of Human Papillomavirus and its Vaccination among Young Women in Nepal

Background: The Human Papillomavirus (HPV) is strongly associated with cervical and other cancers. In women, cervical cancer is the third most common cancer. HPV infection can be largely prevented through vaccination of (adolescent) girls. At the same time, Nepal is a low-income country experiencing a cultural change in attitudes towards sex and sexual behaviour. However, in the adolescent population knowledge about HPV, factors associated with an increased risk of HPV and the existence of the vaccination is often low. Materials and Methods: This was a cross-sectional study with female students enrolled in health and non-health science courses in Pokhara, Nepal. The questionnaire included demographic details, knowledge and attitude questions related to HPV, associated risk behaviour and its vaccination. Descriptive statistics, including Chi-Square test, were used to identify statistically significant relationships. Ethical approval was granted by the relevant authority in Nepal. Results: Hindu religion (75.0 %; 95% CI: 70.9, 78.6) and Newari caste (75.5%; CI: 61.1, 86.7) were more aware about HPV, HPV vaccination. Hindus religion (55.6%; 95% CI: 51.2, 60.0) and Dalit caste (61.6%, 95% CI: 53.3, 69.4) more willing to be vaccinated than other religions and other castes, respectively. Not unsurprisingly, students on health-related courses had a greater awareness of HPV, HPV vaccination and were more willing to be vaccinated than students on other courses. Similar patterns of association arose for knowledge related to those sexually active at an early age; HPV risk and multiple sex partners; and fact that condoms cannot fully prevent the transmission of HPV. Conclusion: Knowledge about the link between HPV and (a) early sexual initiation, (b) having multiple sexual partners, and (c) the limited protection of condoms and other birth control measures was poor in our study compared to similar research conducted in other parts of the world. One key implication is the need for education campaigns in Nepal to educate young women and their parents about HPV, its risk factors and the benefits of vaccination

Fast Local Binary Patterns for Efficient Face Recognition

LBP, Local Binary Patterns, is an accepted technique for efficient face recognition. The local features improve the recognition process. However, high memory and computational resources are needed for LBP required approaches to improve the performance. Many people used LBP for extracting features and Support Vector Machine (SVM), histogram matching, neural networks as recognition tools. These approaches consume considerable computational resources. We have proposed a fast LBP which uses Two-level Correlation for the classification & recognition. The exhaustive experiments on FERET database 8750 images substantiate the performance compared to others. [Keywords— Face Recognition, LBP, Histogram Matching, Two-level Correlation, FERET data set

SOLUTION OF ELD PROBLEM WITH VALVE POINT EFFECTS AND MULTI FUELS USING IPSO ALGORITHM

ABSTRACT: This project presents a novel and improved method for solving the Non Convex Economic Dispatch (ELD) problems with valve-point effects and Multiple Fuels, by integrating the particle swarm optimization (PSO) with the chaotic sequences and Cross over Operations. The results of the IPSO were compared with previous methods and the conventional Genetic Algorithm (GA), revealing that the results clearly show that the proposed IPSO outperforms other state-of-the-art algorithms in solving ELD problems with the valve-point effect

A Comprehensive Survey of Convolutional Neural Networks for Skin Cancer Classification and Prediction

Skin cancer, a prevalent and potentially fatal condition, requires early detection and precise classification to ensure effective treatment. In recent years, there has been a significant rise in the popularity of Convolutional Neural Networks (CNNs) prominence as a robust solution for image processing and analysis, significantly surpassing conventional techniques in skin cancer prediction and classification. This survey paper offers a thorough examination of CNNs and their diverse applications in diagnosing skin cancer, emphasizing their benefits, existing obstacles, and potential avenues for future research

Genomic strategies for soybean oil improvement and biodiesel production

Track II: Transportation and BiofuelsIncludes audio file (21 min.)Soybean oil, a promising renewable energy resource, comprises 73% of biodiesel in addition to other industrial applications. Missouri is the fifth largest state in the US for soybean plantation. With the target to produce 225 million gallons of biodiesel by 2015 from the current 75 million gallons produced in 2005, efforts should not only focus on expanding the number of oil crops to meet the demand but also to increase the amount of oil per hectare for each crop. Considering the ever increasing need for biodiesel and the potential for Missouri to play a major role in national and international demand, We, at the National Center for Soybean Biotechnology focus on discovering the genetic factors that are responsible for oil content in soybean using genetic and genomic strategies. The long term goal is to apply discoveries in breeding programs and biotechnology for the development of improved soybean cultivars with increased oil content that will make this crop more competitive in end-uses. Our multidisciplinary approaches include traditional Quantitative Trait Loci (QTL) mapping, association mapping, bioinformatics and transgenics by developing new resources and utilizing already available resources such as mapping populations, diverse germplasm collections, genome sequence information and transgenes. In addition to total oil content, we are focusing on improving quality traits such as oleic acid which has direct human health benefits and application in biodiesel production. With the use of advanced genomic technologies, genetic materials, and synergistic efforts involving intra- and inter institutional collaborations, we believe that our current and future research will contribute substantially to biodiesel production. Increased production using high oil soybean cultivars will not only increase the economic gains to farmers/growers but also facilitate the US to emerge as the global leader in biodiesel production

A survey of Post-Traumatic Stress Disorder, Anxiety and Depression among Flood Affected Populations in Kerala, India

Background: Globally, post traumatic stress disorder (PTSD) is one of the most common psychiatric illnesses following a disaster. We aimed to evaluate the relationship between the socio-economic and flood exposure factors with PTSD, depression and anxiety among the flood-affected populations in Kerala, India. Methods: A cross-sectional household survey was conducted from November 2019 to January 2020 in Kozhikode district of Kerala, India. Adults (≥ 18 years), who were permanent residents and had been directly exposed to the flood, were invited to take part in the study. Individuals with a history of mental health issues and those who had other stressful situations in the past were excluded. The survey questionnaire was based on three screening tools: (1) PTSD Checklist for DSM-5 (PCL-5); (2) patient health questionnaire (PHQ-9); and (3) generalized anxiety disorder (GAD-7). Data included sociodemographic factors and flood exposure variables. The primary outcome variable was psychiatric morbidity (PTSD, anxiety and depression). Results: A total of 276 respondents (150 males/126 females) participated in the study. A significant correlation was observed between total score on PCL-5 and GAD-7 (r=0.339, p=0.001) and PHQ-9 (r=0.262, p=0.001). Females had significantly higher total PTSD symptom severity scores (8.24±5.88 vs. 6.07±5.22; p=0.001), severity of symptoms of intrusion (4.66±3.60 vs. 3.69±3.20; p=0.04), increased level of anxiety (2.54±1.94 vs. 1.79±1.53; p=0.001) and depression (3.02±2.26 vs. 2.04±1.67; p=0.001) compared to males. However, the gender difference for PTSD symptoms disappeared when controlling for age. Conclusion: The findings of this survey revealed that the vast majority of respondents (92 percent females and 87 percent males) still had subclinical psychiatric symptoms one year after the flood. Therefore, tailored psychological interventions are warranted to counter the long-lasting impact of flooding on the mental health of individuals

A survey of Post-Traumatic Stress Disorder, Anxiety and Depression among Flood Affected Populations in Kerala, India

Background: Globally, post traumatic stress disorder (PTSD) is one of the most common psychiatric illnesses following a disaster. We aimed to evaluate the relationship between the socio-economic and flood exposure factors with PTSD, depression and anxiety among the flood-affected populations in Kerala, India. Methods: A cross-sectional household survey was conducted from November 2019 to January 2020 in Kozhikode district of Kerala, India. Adults (≥ 18 years), who were permanent residents and had been directly exposed to the flood, were invited to take part in the study. Individuals with a history of mental health issues and those who had other stressful situations in the past were excluded. The survey questionnaire was based on three screening tools: (1) PTSD Checklist for DSM-5 (PCL-5); (2) patient health questionnaire (PHQ-9); and (3) generalized anxiety disorder (GAD-7). Data included sociodemographic factors and flood exposure variables. The primary outcome variable was psychiatric morbidity (PTSD, anxiety and depression). Results: A total of 276 respondents (150 males/126 females) participated in the study. A significant correlation was observed between total score on PCL-5 and GAD-7 (r=0.339, p=0.001) and PHQ-9 (r=0.262, p=0.001). Females had significantly higher total PTSD symptom severity scores (8.24±5.88 vs. 6.07±5.22; p=0.001), severity of symptoms of intrusion (4.66±3.60 vs. 3.69±3.20; p=0.04), increased level of anxiety (2.54±1.94 vs. 1.79±1.53; p=0.001) and depression (3.02±2.26 vs. 2.04±1.67; p=0.001) compared to males. However, the gender difference for PTSD symptoms disappeared when controlling for age. Conclusion: The findings of this survey revealed that the vast majority of respondents (92 percent females and 87 percent males) still had subclinical psychiatric symptoms one year after the flood. Therefore, tailored psychological interventions are warranted to counter the long-lasting impact of flooding on the mental health of individuals

Rangelands, conflicts, and society in the Upper Mustang Region, Nepal

Rangelands are considered critical ecosystems in the Nepal Himalayas and provide multiple ecosystem services that support local livelihoods. However, these rangelands are under threat from various anthropogenic stresses. This study analyzes an example of conflict over the use of rangeland, involving two villages in the Mustang district of Nepal. This prolonged conflict over the use of rangeland rests on how use rights are defined by the parties, that is, whether they are based on traditional use or property ownership. Traditionally, such conflicts in remote areas were managed under the Mukhiya (village chief) system, but this became dysfunctional after the political change of 1990. The continuing conflict suggests that excessive demand for limited rangelands motivates local villagers to gain absolute control of the resources. In such contexts, external support should focus on enhancing the management and production of forage resources locally, which requires the establishment of local common property institutions to facilitate sustainable rangeland management.<br /