Search results for: conservation detection dogs

Authors: L. Sellami, D. Idoughi, P. F. Tiako

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Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Keywords: cloud computing, intrusion detection system, privacy, trust

Procedia PDF Downloads 282

Authors: Gasto Lyakurwa, Glory Bakari, Edwin Sabuhoro

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Wildlife Management Areas (WMAs) are established to promote and act as a remedy to the protection of wildlife resources outside the core protected area. WMAs aim to address issues of poverty, ensure sustainable use of wildlife resources, and share benefits from wildlife with the member villages. Successfully managed WMA in Tanzania improves local livelihood and conserves local biodiversity through tourism revenues and the protection of wildlife, respectively. Benefits accrued at household levels as a result of conservation activities in WMA can positively influence attitudes towards wildlife conservation. This research intends to assess the positive socio-economic impacts of WMA benefits on households in Burunge WMA in Tanzania. A questionnaire survey was conducted among four randomly selected villages in the ten villages forming the Burunge WMA to explore the household-level benefits of conservation activities. An example of a question item was whether household heads feel that they are benefiting from WMA and if they could remember some of the benefits. Interviews with leaders from WMA and member villages combined the survey to capture aspects of benefit distribution to households. A total of 80 households were used as samples of the recruited study sites. Moreover, the four WMA leaders and the eight village leaders of the respective study villages were interviewed. The study findings revealed that the shared benefit has mostly reached the community level and is less likely to reach the household level. Economic activities such as agriculture and livestock keeping were found to be more important for households than conservation-related economic activities. Conservation-related economic activities generate marginal direct benefits from WMA benefits to households, with ecotourism accounting for only 19.5%. The study also indicates that a direct share of financial benefits from WMA to households is lacking. Wildlife conservation benefits are less likely to reach household levels in WMAs, with the implication of reducing people's conservation attitudes and impeding community conservation success. WMA can utilize the finances from tourism fees and concessions to establish a Community Considerations Bank, which can lend money to some individuals at no or low interest rates. Considering the importance of education and health to households, WMA stands in a good position to provide health insurance premiums and student scholarships to motivate household participation in conservation activities. Community-based organizations and governments responsible for wildlife conservation should create mechanisms to channel conservation benefits to households in order to ensure the achievement of wildlife conservation objectives through WMA. These findings are expected to contribute to forming more WMAs with enhanced mechanisms for sharing conservation benefits to benefit the conservation of natural resources outside of the core protected areas. Motivated households are expected to respect wildlife and are less likely to engage in illegal activities such as poaching and harvesting conserved natural resources while coexisting with wildlife.

Keywords: social economic benefits, individuals, wildlife management areas, biodiversity, community

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Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

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In this paper approach to incoherent signal detection in multi-element antenna array are researched and modeled. Two types of useful signals with unknown wavefront were considered. First one is deterministic (Barker code), the second one is random (Gaussian distribution). The derivation of the sufficient statistics took into account the linearity of the antenna array. The performance characteristics and detecting curves are modeled and compared for different useful signals parameters and for different number of elements of the antenna array. Results of researches in case of some additional conditions can be applied to a digital communications systems.

Keywords: antenna array, detection curves, performance characteristics, quadrature processing, signal detection

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Authors: Andrey V. Timofeev

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A method is proposed for stable detection of seismoacoustic sources in C-OTDR systems that guarantee given upper bounds for probabilities of type I and type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this.

Keywords: guaranteed detection, C-OTDR systems, change point, interval estimation

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Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan

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Nowadays, advanced driver assistance systems (ADAS) have become popular, since they enable safe driving. Lane detection is a vital step for ADAS. The performance of the lane detection process is critical to obtain a high accuracy lane departure warning system (LDWS). Challenging factors such as road cracks, erosion of lane markings, weather conditions might affect the performance of a lane detection system. In this paper, 1-D weighted filter based on row filtering to detect lane marking is proposed. 2-D input image is filtered by 1-D weighted filter considering four-pixel values located symmetrically around the center of candidate pixel. Performance evaluation is carried out by two metrics which are true positive rate (TPR) and false positive rate (FPR). Experimental results demonstrate that the proposed approach provides better lane marking detection accuracy compared to the previous methods while providing real-time processing performance.

Keywords: lane marking filter, lane detection, ADAS, LDWS

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Authors: Valbona Sota, Efigjeni Kongjika

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Wild almond is a woody species, which is difficult to propagate either generatively by seed or by vegetative methods (grafting or cuttings) and also considered as Endangered (EN) in Albania based on IUCN criteria. As a wild relative of cultivated fruit trees, this species represents a source of genetic variability and can be very important in breeding programs and cultivation. For this reason, it would be of interest to use an effective method of in vitro mid-term conservation, which involves strategies to slow plant growth through physicochemical alterations of in vitro growth conditions. Multiplication of wild almond was carried out using zygotic embryos, as primary explants, with the purpose to develop a successful propagation protocol. Results showed that zygotic embryos can proliferate through direct or indirect organogenesis. During subculture, stage was obtained a great number of new plantlets identical to mother plants derived from the zygotic embryos. All in vitro plantlets obtained from subcultures underwent in vitro conservation by minimal growth in low temperature (4ºC) and darkness. The efficiency of this technique was evaluated for 3, 6, and 10 months of conservation period. Maintenance in these conditions reduced micro cuttings growth. Survival and regeneration rates for each period were evaluated and resulted that the maximal time of conservation without subculture on 4ºC was 10 months, but survival and regeneration rates were significantly reduced, specifically 15.6% and 7.6%. An optimal period of conservation in these conditions can be considered the 5-6 months storage, which can lead to 60-50% of survival and regeneration rates. This protocol may be beneficial for mass propagation, mid-term conservation, and for genetic manipulation of wild almond.

Keywords: micropropagation, minimal growth, storage, wild almond

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Authors: Benjamin Bonsu Bruce, Marian Dorcas Quain David Appiah-Kubi, Gertrude Osei-Diko, Harrison Kwame Dapaah

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Taro [Colocasia esculenta (L.) Schott] is a major staple food and remains a significant crop to many cultural and agricultural customs worldwide. In Ghana, taro is mostly propagated using vegetative material, which is conserved in field collection and recycled from their farms to establish new fields. However, this practice promotes the accumulation of systemic pathogens. Prior exposure to pests and subsequent expression of disease symptoms can also be a huge constraint to sustainable conservation and utilization of taro genetic resources. In vitro, slow growth is one of the most promising techniques to be utilized for conservation. The objective of this study was to find a medium-term in vitro conservation protocol for local and exotic taro genotypes. The medium-term conservation study was conducted using actively growing shoots obtained from in vitro cultures. Explants were cultured to full strength in complete Murashige and Skoog medium supplemented with Mannitol at different concentrations (0g/l, 20g/l, 25g/l, and 30g/l). Another medium that was tested as an additional treatment is the White’s medium. The highest number of shoots (6.33) and leaves (22.67) occurred on medium containing 20 and 25g/l mannitol in genotype SAO 006 as compared to other genotypes, whereas 30g/l mannitol was the best to restrict growth for the entire 6 months period in terms of shoot height (22.50cm). The study reveals that mannitol supplemented culture media could reduce the growth of Colocasia plantlets, especially in stem height. Culture growth following 6 months of conservation, showed that healthy shoot cultures of Taro were obtained after 6 months of storage in a medium containing 20gl⁻¹ and 25gl⁻¹ mannitol.

Keywords: complete murashige, skoog medium, culture conditions, mannitol, slow growth conservation

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Authors: Anima Ashraf

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Over the past few decades biodiversity has become the issue of global concern for its rapid reduction worldwide. Bangladesh is no exception. The country is exceptionally endowed with a vast variety of flora and fauna, but due to tremendous population pressure, rural poverty and unemployment it has been decreased alarmingly. Since, both biodiversity and sustainable development are the part of human life in modern era and both work together to make our life safer and comfortable therefore balance should be kept in development and biodiversity conservation and priority should be given to alternative and sustainable development paths. This paper is based on study of two projects undertaken by Arannayk Foundation jointly with its local NGO partners. The aim was to understand previous, current and future scenarios for the hilly biodiversity of Khagrachari in the Chittagong Hill Tracts (CHT) of Bangladesh. It is also observed how alternative income generating activities (AIGA) improve livelihood of the tribal inhabitants of the area, decrease their dependency on forest resources and also aid conservation activities. Intensive field visits were made and interviews were conducted with key informants to see the progress and achievements of local NGOs working with the tribal community for the past seven years to restore the denuded hills of Khagrachari. The paper also covers the impacts and interventions of the projects and the methods used to aid conservation activities. Raising awareness among the villagers has reduced extraction of forests resources by 47% and granting funds and access to microcredit to adopt AIGAs have increased their average annual income by 25%. Finally, the paper concludes that effective community-based conservation practices are fundamental to ensure biodiversity conservation in the Chittagong Hill Tracts. In order to conserve biodiversity and restore the forests of CHT, livelihood development of the villagers has to be considered as the main component of the projects undertaken by all NGOs and the Government.

Keywords: biodiversity, conservation, forests, livelihood

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Zhengyu Yan, Yan Yu, Jianqiu Chen

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A novel sensing system has been designed for naphthalene detection based on the quenched fluorescence signal of CdS quantum dots. The fluorescence intensity of the system reduced significantly after adding CdS quantum dots to the water pollution model because of the fluorescent static quenching f mechanism. Herein, we have demonstrated the facile methodology can offer a convenient and low analysis cost with the recovery rate as 97.43%-103.2%, which has potential application prospect.

Keywords: CdS quantum dots, modification, detection, naphthalene

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Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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Authors: Rishabh Agrawal, S. C. Kaushik, T. S. Bhatti

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In order to reduce energy consumption for sustainable development, continuous energy consumption tracking of building energy systems are essential. In this paper an assessment study has been done to identify the energy consumption & energy conservation potential for commercial buildings sector in Karnataka state, India. There are a total of 326 commercial buildings in the state of Karnataka who has qualified as designated consumers (i.e., having a Contract Demand ≥ 600 KVA), was consider for the study. It has estimated that the annual electricity sale to commercial sector is 3.62 Billion Units (BU) in alone Karnataka State, India, which is an account for 9.57 % of the total electricity sold. The commercial sector constitutes Government & private establishments, hospitals, hotels, restaurants, educational institutions, malls etc. Total 326 commercial buildings in the state accounting for annual energy consumption of 1295.72 Million Units (MU) which works out to about 35% of the sectoral consumption. The annual energy savings potential for 326 commercial buildings is assessed to be 0.25 BU.

Keywords: commercial buildings, connected load, energy conservation studies, energy savings, energy efficiency, energy conservation strategy, energy efficiency, thermal energy, HVAC system

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Authors: Hossam Hassan Elborombaly, Nader Y. Azab

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The Middle East region is rich with its architecture and urban settings. This makes it viable for exploring and applying different strategies that deal with conservation. Current context characterized by pollution, socioeconomic issues, behavioral problems, etc. affects architectural and urban heritage –literally- in all Middle Eastern countries. Although there have been numerous strategies in place to preserve and/ or rehabilitate heritage, all has been designed and implemented following political more than technical or methodical processes. This only resulted in more deterioration of the targeted areas. This paper explores different approaches in some selected Arab countries and relies on comparative analysis with some successful European experiences. The aim is to establish some solid basis for dealing with heritage areas; an approach that respects heritage and traditions without compromising sustainability or socioeconomic opportunities.

Keywords: rehabilitation, socioeconomic, urban conservation, urban strategy

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Authors: Preston Nabors, Nasseh Tabrizi

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Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

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Authors: Milagros S. Salibad, Levita B. Grana

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The presence and role of Indigenous Peoples residing in key biodiversity, protected, and watershed areas within the ancestral domain in the Caraga Region hold immense significance. This study aimed to determine the level of biodiversity conservation practices among the Mamanwas, Manobos, and Higaonons, and identify facilitating or hindering factors. Employing a mixed-method research design, 421 respondents participated through a researcher-made questionnaire. Focus group discussions, key informant interviews, researcher field notes, community immersions, and secondary sources were done. The three groups have demonstrated a high level of biodiversity conservation practices manifesting their commitment to conserving their natural resources and ecosystems. Evidently, selecting and cutting only mature trees for shelter and tribal usage, and preservation of large trees that harbor ancestors’ spirits and worship through rituals (Mambabaja). Each group exhibited unique environmental practices shaped by their distinct cultures, traditions, customary knowledge, and access to information. The Mamanwa practiced traditional hunting and gathering by using traps while Manobo practiced shifting cultivation to maintain soil fertility and biodiversity, and Higaonon managed forest resources through traditional forest management (establishment of sacred forests and conservation areas). Various facilitating and hindering factors influenced their conservation efforts. Their traditional knowledge and practices, partnership and collaboration, legal recognition and support, access to information, and biodiversity monitoring system facilitate practices. Insufficient government assistance, political and social issues, scarce financial support, inadequate policy enforcement, lack of livelihood opportunities, and land use conflicts hinder them. Monitoring the sustainability of IPs' local biodiversity conservation practices is essential as they contribute to conservation endeavors.

Keywords: biodiversity, conservation, indigenous peoples, traditional knowledge

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Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

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Authors: Sang-Hoon Park, Yeji Ho, Gwang-Moon Eom

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Fast and accurate detection of Freezing of Gait (FOG) is desirable for appropriate application of cueing which has been shown to ameliorate FOG. Utilization of frequency spectrum of leg acceleration to derive the freeze index requires much calculation and it would lead to delayed cueing. We hypothesized that FOG can be reasonably detected from the time domain amplitude of foot acceleration. A time instant was recognized as FOG if the mean amplitude of the acceleration in the time window surrounding the time instant was in the specific FOG range. Parameters required in the FOG detection was optimized by simulated annealing. The suggested time domain methods showed performances comparable to those of frequency domain methods.

Keywords: freezing of gait, detection, Parkinson's disease, time-domain method

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Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

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Authors: Moustapha H. Ibrahim, Dahir Abdourahman

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This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: M. Khouil, N. Saber, M. Mestari

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In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: collision identification, fixed time, convex polyhedra, neural network, AMAXNET

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Authors: Sriraman Kothuri, Komal Teja Mattupalli

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In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Zdenek Silar, Martin Dobrovolny

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This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.

Keywords: background estimation, direction of optical flow, K-means clustering, objects detection, railway crossing monitoring, velocity vectors

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

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This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

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Authors: Samra Naz, Aneeqa Ahmed, Qurat-ul-ain Mubarak, Irum Nausheen

Abstract:

Driver safety systems protect driver from accidents by sensing signs of drowsiness. The paper proposes a technique which can detect the signs of drowsiness and make corresponding decisions to make the driver alert. This paper presents a technique in which the driver will be continuously monitored by a camera and his eyes, head and mouth movements will be observed. If the drowsiness signs are detected on the basis of these three movements under the predefined criteria, driver will be declared as sleepy and he will get alert with the help of alarms. Three robust techniques of drowsiness detection are combined together to make a robust system that can prevent form accident.

Keywords: drowsiness, eye closure, fatigue detection, yawn detection

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