Search results for: community detection

Authors: Samuel Richard Marcourt

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The economic impact of community sports facilities can be examined through various dimensions, such as job creation, tourism, local business development, and property values. The aim of the study is to evaluate the economic impacts of community sports facilities on residents who lived within 500m radii of 4 Astro Turf soccer facilities in Ghana. The results of the study were based on the responses from in-depth semi-structured interviews with 16 purposively selected participants aged between 25 and 55 years. Participants’ responses revealed that community sports facilities create direct and indirect benefits for residents. Further, the direct benefits include job creation and employment among residents in the locality. Again, the promotion of local entrepreneurship and small business development, as well promotion of tourism, were indirect benefits. Consequently, the study provides useful data for stakeholders, including The Ministry of Sports, Ghana Football Association (GFA), and Government and non-governmental organizations, to construct more community sports facilities to assist in reducing the level of unemployment in Ghanaian communities.

Keywords: economic impact, community sports facilities, Astro turf, residents

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Authors: Anja Jutraz, Tadeja Zupancic

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This article explores urban laboratory, which presents a combination of different physical and digital methods and tools for public participation in urban design. The city consists of built and unbuilt environments, which can be defined as a community of people, who live there. Communities should have the option to express opinions and decide about the future of their city, from the early stages of the design process onwards. In this paper, we presented the possibility of involving community into renewal of Banska Štiavnica in Slovakia (more exactly the old mining shaft and lake Michal Štolna) and the methods to promote the community building. As a case study we presented the eTHNo project, Education about Technical, Historical and Natural opportunities of Michal Štolna. Moreover, we discussed the possibility of using virtual digital tools for public participation in urban design, where we especially focused on Virtual Urban Laboratory, VuLab.

Keywords: community building, digital tools, public participation, urban design

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Authors: Alex Lundy

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As the suburban landscape has evolved over time, it has been slowly stripped down to the absolute bare essentials of housing. This has resulted in the loss of core elements of the built environment which previously supported community no longer being present in most neighborhoods. As a result, this work will explore how current and past designers have successfully introduced these concepts in similar settings, in an effort to re-implement them into the contemporary subdivision. Ultimately, this will result in a reimagining suburban design through elements like identity, adaptability, place, and social spaces to improve community interaction and cohesion. Overall, this thesis asserts that contemporary subdivisions don’t support the growing need for community in daily life and should be improved through the implementation of historical neighborhood design and select modern urban concepts to better suit living needs.

Keywords: suburbia, community, social connection, identity, adaptability, neighborhood, place, unity, leasure, social ties, third place, learning from history

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Authors: Udaykumar R., M. S. Ganachari

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In order to engage community pharmacies in Tuberculosis care, a survey has been conducted in Belgaum city, Karnataka state, India. After the survey divided into two groups one is control group and another one is intervention group. One is dispensing of anti-tuberculosis drugs, and another one is non-availability of anti-tuberculosis drugs. Those community pharmacists who are voluntarily interesting for becoming DOTS (Directly observed treatment short course) provider and RNTCP (Revised national tuberculosis control programme) objectives. Structured training is conducted for community pharmacist who are dispensing anti-tuberculosis drugs. The training module includes record maintaining, reporting to the RNTCP, Medication adherence etc. In case of non-availability of anti-tuberculosis drugs, the district RNTCP has been given training for community pharmacist by providing free of drugs to the community pharmacies. So, community pharmacies can dispense anti-tuberculosis drugs to the patients. The target of this study is Private community pharmacies. A simple random sampling method is used and 550 private community pharmacy shops has been involved in Belgaum city of Karnataka state, India. Significance of the Study: This study mainly focused on training of DOTS (Directly observed treatment short course) to the private community pharmacist. Indian Govt. Considers Private Providers as Assets for TB Control and Care to Achieve National Strategic Plan for TB Elimination 2017-2025. The Govt. has not fully tapped the Potential of Private Pharmacies to Fight TB. Providing DOTS as per patient’s convenience through community DOT Providers with periodic monitoring may reduce the treatment Default. We explore RNTCP objectives interventions that can have directly managed by private community pharmacy shop. Objectives: Survey of anti-tuberculosis drugs in Community pharmacy shop in Belgaum city. Interested community pharmacist who are willing to become DOTS (Directly observed treatment short course) Provider. Major Findings:Most of the community pharmacist are dispensing anti-tuberculosis drugs without having knowledge of DOTS therapy and RNTCP objectives. No community pharmacist is aware of RNTCP and Tuberculosis burden in India. Most of the Pharmacist agreed to come for RNTCP Training module for the community pharmacist. Some of the community pharmacist not dispensing anti-tuberculosis drugs and they agreed to become official DOTS provider. Concluding Statement: Awareness of role of community pharmacist on tuberculosis control and care has been neglected. More than 50% of tuberculosis patients seeking treatments from privatesector. In this study finds the major gap between government and private sector on tuberculosis treatment.

Keywords: community pharmacist, directly observed treatment short course(DOTS), revised national tuberculosis control programme (RNTCP), private pharmacies, anti-tuberculosis drugs

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Authors: Laxmi Prasad Bhattarai

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Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is a growing global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods, and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: community forestry, climate change, global warming, adaptation, Nepal

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Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

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Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

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Authors: Bikram Jung Kunwar, Pralhad Kunwor

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The Community-Based Forest Management (CBFM) approach is often glorified as the best forest management alternatives in the developing countries. However, how the approach has been understood by the local user households, who implement it is remained unanswered for many planners, policy makers, and sometimes researcher as well. The study attempts to assess the understanding of ecology and economics of CBFM in Nepal, where community forest program has been implemented since the 1970s. In order to understand the impacts of the program, eight criteria and sixteen indicators for ecological conservation and similarly same number of criteria and indicators for socio-economic impacts of the program were designed and compared between before and after the program implementation. The community forestry program has positive effects in forest ecology conservation and at the same time rural livelihood improvement of local people. The study revealed that collective understanding of forest ecology and economics leads the CBFM approach towards the sustainability of the program in a win-win situation. The recommendations of the study are expected to be useful to natural resource managers, planners, and policy makers.

Keywords: community, forest management, ecology, economics, Nepal

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Authors: Ravi Kumar Pandit

Abstract:

Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is growing a global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore the local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: climate change, community forestry, global warming, adaptation in Nepal

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Authors: Akila Murali, Prithika Manivel

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Disasters are defined as a serious disruption of the functioning of a community or a society, which involves widespread human, material, economic or environmental impacts. The number of people suffering food crisis as a result of natural disasters has tripled in the last thirty years. The economic losses due to natural disasters have shown an increase with a factor of eight over the past four decades, caused by the increased vulnerability of the global society, and also due to an increase in the number of weather-related disasters. Efficient disaster detection and alerting systems could reduce the loss of life and properties. In the event of a disaster, another important issue is a good search and rescue system with high levels of precision, timeliness and safety for both the victims and the rescuers. Wireless Sensor Networks technology has the capability of quick capturing, processing, and transmission of critical data in real-time with high resolution. This paper studies the capacity of sensors and a Wireless Sensor Network to collect, collate and analyze valuable and worthwhile data, in an ordered manner to help with disaster management.

Keywords: alerting systems, disaster detection, Ad Hoc network, WSN technology

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Authors: Ahmadu Maidorawa, Idrissa Djibo, Muhammad Tella

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This paper presents a method for detecting flow chart and figure plagiarism based on shape of image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets. Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offense that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide these checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts result in look holes that people can take advantage. That means people can plagiarize figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts.

Keywords: flowchart, multimedia retrieval, figures similarity, image comparison, figure retrieval

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Authors: Adebayo J. Julius, Oluremi N. Iluyomade

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Livelihood in Nigeria is a paradox of poverty amidst plenty. The Country is endowed with a good climate for agriculture, naturally growing fruit trees and vegetables, and undomesticated water resources. In spite of all its endowment, Nigeria continues to live in poverty year in year out. Rural communities adopted for this study are Ido, Omi-Adio, Onigambari, Okija and Lambata, 500 questionnaires were administered to solicit information from the respondents. This study focused on comparative analysis of the utilization of community informatics for sustainable livelihoods through agriculture. The idea projected in this study is that small strategic changes in the modus operandi of social informatics can have a significant impact on the sustainability of livelihoods. This paper carefully explored the theories of community informatics and its efficacies in dealing with sustainability issues. This study identified, described and evaluates the roles of community informatics in some sectors of the economy, different analytical tools to benchmark the influence of social informatics in agriculture against what is obtainable in agricultural sectors of the economy were used. It further employed comparative analysis to build a case model for sustainable livelihood in agriculture through community informatics.

Keywords: informatics, model, rural community, livelihood, Nigeria

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: Alvin Manuel Vazhayil, Chaozhong Tan, Karl M. Wantzen

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As local community participation in river restoration projects is increasingly recognized to be crucial for sustainable outcomes, researchers are exploring factors that motivate community participation globally. In India, while there is consensus in literature on the importance of community engagement in river restoration projects, research on what drives local communities to participate is limited, especially given the societal and economic challenges common in the Global South. This study addresses this gap by exploring the drivers of community participation in the local river restoration initiatives of the "Now Let Me Flow" campaign in Kerala, India. The project aimed to restore 87,000 kilometers of streams through the middle-ground governance approach that integrated bottom-up community efforts with top-down governmental support. The fieldwork involved interviews with 26 key agents, including local leaders, policy practitioners, politicians, and environmental activists associated with the project, and the collection of secondary data from 12 documents including project reports and news articles. The data was analyzed in NVivo (NVivo 11 Plus for Windows, version 11.3.0.773) using thematic analysis which included two cycles of systematic coding. The findings reveal two main drivers influencing community participation: top-down actions from local governments, and bottom-up drivers within the community. The study highlights the importance of local stakeholder collaboration, support of local governments, and local community engagement in successful river restoration projects. These findings are consistent with other empirical studies on participatory environmental problem-solving globally. The results offer crucial insights for policymakers and governments to better design and implement effective and sustainable participatory river restoration projects.

Keywords: community initiatives, drivers of participation, environmental governance, river restoration

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Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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Authors: Pennapa Palapin

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This research sought to study the traditional local wisdom and study the promotion and dissemination of traditional local wisdom in order to find the forms of promotion and dissemination of traditional local wisdom to create occupations among the elderly at Nonmueng Community, Muang Sub-District, Baan Dung District, UdonThani Province. The criterion used to select the research sample group was, being a person having a role involved in the promotion and dissemination of traditional local wisdom to create occupations among the elderly at Nonmueng Community, Muang Sub-District, Baan Dung District, UdonThani Province; being an experienced person whom the residents of Nonmueng Community find trustworthy; and having lived in Nonmueng Community for a long time so as to be able to see the development and change that occurs. A total of 16 people were selected. Data was gathered as a qualitative study, through semi-structured in-depth interviews. The collected data was then summarised and discussed according to the research objectives. Finally, the data was presented in a narrative format. Results found that the identifying traditional local wisdom of the community (which grew from the residents’ experience and beneficial usage in daily life, passed down from generation to generation) was the weaving of cloth and basketry. As for the manner of promotion and dissemination of traditional local wisdom, the skills were passed down through teaching by example to family members, relatives and others in the community. This was done by the elders or elderly members of the community. For the promotion and dissemination of traditional local wisdom to create occupations among the elderly, the traditional local wisdom should be supported in every way through participation of the community members. For example, establish a museum of traditional local wisdom for the collection of traditional local wisdom in various fields, both in the past and at present. This would be a source of pride for the community, in order to make traditional local wisdom widely known and to create income for the community’s elderly. Additional ways include exhibitions of products made by traditional local wisdom, finding both domestic and international markets, as well as building both domestic and international networks aiming to find opportunities to market products made by traditional local wisdom.

Keywords: traditional local wisdom, occupation, elderly, community

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Authors: Temesgen Geremew

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The excessive emission of heavy metal ions from industrial processes poses a serious threat to both the environment and human health. This study presents a distinct approach utilizing (PTh-MnS/CoS NPs) for the highly selective and sensitive detection of Hg²⁺ ions in water. Such detection is crucial for safeguarding human health, protecting the environment, and accurately assessing toxicity. The fabrication method employs a simple and efficient chemical precipitation technique, harmoniously combining polythiophene, MnS, and CoS NPs to create highly active substrates for SERS. The MnS@Hg²⁺ exhibits a distinct Raman shift at 1666 cm⁻¹, enabling specific identification and demonstrating the highest responsiveness among the studied semiconductor substrates with a detection limit of only 1 nM. This investigation demonstrates reliable and practical SERS detection for Hg²⁺ ions. Relative standard deviation (RSD) ranged from 0.49% to 9.8%, and recovery rates varied from 96% to 102%, indicating selective adsorption of Hg²⁺ ions on the synthesized substrate. Furthermore, this research led to the development of a remarkable set of substrates, including (MnS, CoS, MnS/CoS, and PTh-MnS/CoS) nanoparticles were created right there on SiO₂/Si substrate, all exhibiting sensitive, robust, and selective SERS for Hg²⁺ ion detection. These platforms effectively monitor Hg²⁺ concentrations in real environmental samples.

Keywords: surface-enhanced raman spectroscopy (SERS), sensor, mercury ions, nanoparticles, and polythiophene.

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Authors: In-Geun Lim, Sung-Woong Ra

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As high resolution satellite images can be used, lots of studies are carried out for exploiting these images in various fields. This paper proposes the method based on mathematical morphology for extracting the ‘horse's hoof shaped object’. This proposed method can make an automatic object detection system to track the meaningful object in a large satellite image rapidly. Mathematical morphology process can apply in binary image, so this method is very simple. Therefore this method can easily extract the ‘horse's hoof shaped object’ from any images which have indistinct edges of the tracking object and have different image qualities depending on filming location, filming time, and filming environment. Using the proposed method by which ‘horse's hoof shaped object’ can be rapidly extracted, the performance of the automatic object detection system can be improved dramatically.

Keywords: facility detection, satellite image, object, mathematical morphology

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Authors: Ramzi Rihane, Yassine Benayed

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Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Yea-Mei Leou, Shiu-Hsung Huang, T. C. Shen, Chin-Ya Fang

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The purposes of this study were to explore how to establish a professional learning community for English teachers at a junior high school, and to explore how teachers and students think about the guided reading program. The participants were three experienced English teachers and their ESL seventh-grade students from three classes in a junior high school. Leveled picture books and worksheets were used in the program. Questionnaires and interviews were used for gathering information. The findings were as follows: First, most students enjoyed this guided reading program. Second, the teachers thought the guided reading program was helpful to students’ learning and the discussions in the professional learning community refreshed their ideas, but the preparation for the teaching was time-consuming. Suggestions based on the findings were provided.

Keywords: ESL students, guided reading, leveled books, professional learning community

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Authors: H. Bakhshi, E. Khayyamian

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Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

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Authors: M. Y. Achouri, O. A. Alleg, M. C. L. Moulai, M. A. Selka

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This study aims to assess the perception and attitudes of community pharmacists in Sidi-Bel-Abbes (Algeria) towards generic drugs. This is a descriptive cross-sectional prospective survey and quantitative, conducted over a period of two months from April to May 2014. The target population consisted of 118 pharmacists practicing in pharmacies in Sidi-Bel-Abbes. Data collection was conducted through a questionnaire consisting of thirteen (13) items. Fifty six (67%) of community pharmacists in the town of Sidi-Bel-Abbes in the survey believe that generics have a lower quality compared to brand name medicines Only 42% of respondents viewed locally manufactured generic medicines as equal in quality compared to the imported generic medicines, and 63% believe that the generics substitution has led to change the relationship between a pharmacist and patient. In order to promote the practice of generic medicines in Algeria, an educational program should be implemented.

Keywords: generic drugs, perception, attitudes, community pharmacists

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Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

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Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

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Authors: Bo Liu, Chi-Man Pun

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A novel technique for digital forgery detection by signal noise inconsistency is proposed in this paper. The forged area spliced from the other picture contains some features which may be inconsistent with the rest part of the image. Noise pattern and the level is a possible factor to reveal such inconsistency. To detect such noise discrepancies, the test picture is initially segmented into small pieces. The noise pattern and level of each segment are then estimated by using various filters. The noise features constructed in this step are utilized in energy-based graph cut to expose forged area in the final step. Experimental results show that our method provides a good illustration of regions with noise inconsistency in various scenarios.

Keywords: forgery detection, splicing forgery, noise estimation, noise

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Authors: Sehreen Moorat, Hiba, Maham Mahnoor, Faryal Soomro

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Leakage of gases in a system makes infrastructures and users vulnerable; it can occur due to its environmental conditions or old groundwork. In hospitals and industries, it is very important to detect any small level of gas leakage because of their sensitivity. In this research, a portable detection system for the small leakage of gases has been developed, gas sensor (MQ-2) is used to find leakage when it’s at its initial phase. The sensor and transmitting module senses the change in level of gas by using a sensing circuit. When a concentration of gas reach at a specified threshold level, it will activate an alarm and send the alarming situation notification to receiver through GSM module. The proposed system works well in hospitals, home, and industries.

Keywords: gases, detection, Arduino, MQ-2, alarm

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Authors: Deepanjali Gurav, Kun Qian

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In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

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Authors: Naser Safdarian, Nader Jafarnia Dabanloo

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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

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Authors: Hyun-Woo Cho

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Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: Kanyarat Bussaban, Siriporn Poolsuwan

Abstract:

This study is conducted with the objective to prove how the distorted distribution of welfare affects the quality of school-age children lives differently in the case of an urban community in Bangkok. 334 samples are households from Suan Oi and Ratchapatubtim communities. The study of sample communities found the difference between two community areas that are close. The people of Suan Oi community are economically better off people than the people of the Ratchapatubtim community. They share the benefits of using most services except the welfare of a child’s education. The resulting analysis of the variability in quality of life of the school age children indicate that heads of the households are women looking for quality of life benefits when the compulsory school age is less. A study of the two communities suggests that the inequality in income distribution currently affects the quality of life of school-age children.

Keywords: inequality, income distribution, quality of school-age children lives, welfare state

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Authors: Anisha Mandal, Swambabu Varanasi

Abstract:

Lead is one of the most prevalent toxic heavy metal ions, and its pollution poses a significant threat to the environment and human health. On the other hand, Ethylenediaminetetraacetic acid is a widely used metal chelating agent that, due to its poor biodegradability, is an incessant pollutant to the environment. For the first time, a green, simple, and cost-effective approach is used to hydrothermally synthesise photoluminescent carbon dots using Moringa Oleifera Gum in a single step. Then, using Moringa Oleifera Gum-derived carbon dots, a photoluminescent "ON-OFF-ON" mechanism for dual mode detection of trace Pb2+ and EDTA was proposed. MOG-CDs detect Pb2+ selectively and sensitively using a photoluminescence quenching mechanism, with a detection limit (LOD) of 0.000472 ppm. (1.24 nM). The quenched photoluminescence can be restored by adding EDTA to the MOG-CD+Pb2+ system; this strategy is used to quantify EDTA at a level of detection of 0.0026 ppm. (8.9 nM). The quantification of Pb2+ and EDTA in actual samples encapsulated the applicability and dependability of the proposed photoluminescent probe.

Keywords: carbon dots, photoluminescence, sensor, moringa oleifera gum

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