Miracle-dz/UniFAR-FTUs huggingface dataset:
A Tiered Analysis of Community Benefits and Conservation Engagement from the Makerere University Biological Field Station, Uganda

Conservation plans have evolved beyond biodiversity protection to include the welfare of the communities surrounding protected areas. Local community engagement initiatives include development of ecotourism, revenue-sharing arrangements, and resource access agreements. Although research stations are common in African national parks, their contributions to biodiversity protection and community benefits have seldom featured in the literature. In this article, we consider whether community benefits accruing from field research stations are effective and indicate how they could promote community–park relationships. We employ a mixed methods approach to understand the impacts on the local community of a field station located in Kibale National Park, Uganda. We find that the presence of a research station in Kibale National Park provides long-term direct employment for fifty-two people and indirect, cascading benefits for up to 720 people several kilometers away. Additionally, other important community benefits, primarily health care and education, are associated with the research field station. Although benefits of the research station do not eliminate community–park conflict, the long-term presence of researchers and the gains to local people associated with them are underappreciated and important means to better integrate the goals of biodiversity protection and local community investment. Key Words: community perception, conservation evaluation, economic benefits, inclusive conservation plans, park–people interaction, research station, Uganda.
Multiple Instance Learning for Computer Aided Diagnosis

Many computer aided diagnosis (CAD) problems can be best modelled as a multiple-instance learning (MIL) problem with unbalanced data: i.e. , the training data typically consists of a few positive bags, and a very large number of negative instances. Existing MIL algorithms are much too computationally expensive for these datasets. We describe CH, a framework for learning a Convex Hull representation of multiple instances that is significantly faster than existing MIL algorithms. Our CH framework applies to any standard hyperplane-based learning algorithm, and for some algorithms, is guaranteed to find the global optimal solution. Experimental studies on two different CAD applications further demonstrate that the proposed algorithmsignificantly improves diagnostic accuracywhen compared to both MIL and traditional classifiers. Although not designed for standard MIL problems (which have both positive and negative bags and relatively balanced datasets), comparisons against other MIL methods on benchmark problems also indicate that the proposed method is competitive with the state-of-the-art.
Effects of vegetation on the structure and diversity of soil bacterial communities in the Arctic tundra

The relatively simple vegetation of the Arctic tundra provides an ideal site in which to study the relationships between plants, bacterial communities and soil chemistry. Here, results of 16S rRNA gene sequencing of secondary Arctic brown soils collected from underneath colonies of Dryasoctopetala, Luzulaconfusa and Bistortavivipara in the Arctic tundra near Ny-Alesund, Svalbard, Norway, reveal significant differences in bacterial communities related to soil environmental properties. Redundancy analysis shows that all measured geochemical factors were significant in structuring microbiomes, with strong correlations related to soil pH and organic matter contents. Vegetation is likely to affect the physical and chemical properties of the soil, which in turn affects the bacterial community and composition of the soil. Citation:Ma Y, Wang N F, Wang S, et al. Effects of vegetation on the structure and diversity of soil bacterial communities in the Arctic tundra. Adv Polar Sci, 2019, 30(2): 139-148, doi: 10.13679/j.advps. 2018.0040
Task-aware Virtual Machine Scheduling for Multi-core Real-time Systems

Virtualization allows running multiple operating systems providing the performance isolation. Therefore, it can guarantee the required system utilization to realtime OS when both real-time OS and non real-time OS are serviced by virtual machine monitor (VMM). Virtualization is also an effective technique to manage multiple processors under recent multi-core systems. However, current VMMs cannot support a real-time scheduling in multi-core environment since the realtime task information is unavailable to VMM . This paper presents a task-aware virtual machine scheduling scheme which assigns the required utilization to each virtual CPU (VCPU) based on the information on the real-time task allocated to the VCPU. Experimental results showed that the proposed scheduling scheme supports real-time systems on multi-core processor.
Design and Implementation of Shooting Contest Ring Number Automatic Identification System Based on Image Processing

Automatic target-scoring system has great practical value in sports shooting competitions. From the needs of sports shooting competition point of view, this paper used image processing technology and studied a set of sport shooting competition ring number automatic identification system. In this system, the author firstly used the image registration algorithm based on SIFT and achieved accurate registration of two target images before and after shooting. And then OTSU thresholding algorithm was used to eliminate most continuous noise. Then the bullet hole image was intensified by image morphological operation. Finally, through differential operation of the edge features in two plots, the positions of bullet holes were obtained. Bullet holes in the final position by the geometric relationship with concentric circles and polar coordinates automatically identify the number of rings. Verified that the algorithm is faster time, adaptability, judgment precision can reach more than 80%, basically meet the actual needs of sports shooting competition.
STUDY OF THE FACTORS AND DEGREE OF ASSOCIATION BETWEEN VARYING POPULATION OF BIRD SPECIES AND THEIR MICROHABITAT

Plants and trees support the survival of many species. The aim of this study is to get an elementary idea of the role of habitat, mainly the niche, in the growth and survival of the population of the bird species. Two sampling stations were chosen, one at the Chintamani Kar Bird Sanctuary, Kolkata and the other at the East Kolkata Wetlands. Species of birds common to both these regions were chosen and their number was recorded. The population varied to a great extent at these two habitats. Thus, this study aims to focus on the importance of the relationship between the habitat requirements and niche specification of the bird species. It also gives the idea, that conspicuous species like birds are helpful in the study of ecosystem and effects of the rise of pollution in the ecosystem, can be studied, through monitoring the changes, in the interaction of the species with the environmental factors. The present study was concluded with the fact, that their food habits, nesting spaces, local landscape, vegetation and breeding practices affect their growth and population, even in the regions with similar altitude-longitude-latitude scale, temperature and climatic zone (macrohabitat remaining the same, changes occurring in the microhabitat). Micro factors like-nesting space, breeding habits, feeding practices as well as their body features, play an important role in the interactions. Mathematical analysis has been performed upon sample data to figure out the correlation between the two attributes. Thus, consolidated evidence has been created to support the aim of this study. This study has been conducted at a very elementary level and factors in the variation of population like-interspecific and intraspecific interactions and any kind associations could not be included within the scope of this study. But, future findings including the physico-chemical factors as well as, better metrics would give us a better view of our ecological parameters and environmental health. As birds are conspicuous species, their population or change in population from one microhabitat to another, is one of the easiest ways to spot the changing dynamics of our ecosystem. Their niche, habitat requirement and growth and survival is very specific and thus any change in the parameters would in turn change their numbers, in a definite geographical zone. The study focuses on the habitat specifications and how a particular species of bird, interacts with it. Finally, at the end of the study we have tried to establish a correlation between the habitat specifications of the individual bird species with the niche that is how the species, under study interacts with their habitats on a micro-scale i.e., the microhabitat (a very definitive component in our ecosystem that we often overlook at the superficial level).
Opportunities and challenges for GeoBIM in Europe: developing a building permits use-case to raise awareness and examine technical interoperability challenges

ABSTRACT The integration of geoinformation with BIM (GeoBIM) is critical to underpin solutions to many city-related challenges. However, to achieve an effective integration it is necessary to consider not only data and technical options but also current practice and users’ needs. This paper describes work carried out within the EuroSDR-GeoBIM project to address this challenge. After investigating potential uses for GeoBIM and existing challenges, we address a planning permits for buildings use case, to help bridging the gap between theory and practice. The resultshighlights a high-level harmonised workflow envisaging the use of GeoBIM information for automating the planning permits process.
Optimal finger combinations in multi-finger biometric systems

Single-finger fingerprint biometric systems require less time to verify a user's identity when compared to a ten-print fingerprint system since there are more fingers to verify. There is a need to examine understand how fingerprint recognition systems can balance the speed of a single-print system with the robustness of a ten-print system by using a combination of fingers. The goal of this research was to find the optimal number of fingers to use in a biometric system that provides the best trade-off between verification speed and fewest matching errors. In this study, images of all ten fingers were used from seventy individuals. The combinations of images were judged on matching performance using both the False Accept Rate (FAR) and False Reject Rate (FRR). It was found that the thumb, index, and middle fingers of both hands had the highest quality scores. All fingers had an FRR of 0.0% except for the right ring finger which had an FRR of 0.5556%. The FAR was 0.0% in all cases except for the left index (0.524%) and the right ring (0.0087%). Ten different combination levels were used (1 finger, 2 fingers, up to 10). For each level the optimal combinations were identified. The least desirable combinations had FRRs between 0.005% and 0.010%. The ideal number of fingers to use in a biometric system falls inclusively between four and six fingers.
Cost Reduction with Environmentally Correct Destination of Liquid Waste in Machining Processes

Machining processes use synthetic oils, either cutting or soluble, for the heavy processing stage, generating a liquid residue, composed largely of heavy metals, which are highly polluting and can not be disposed of without adequate treatment. This paper presents an already successful and successful case study of a renowned company located in the PIM Manaus industrial pole, pointing out an economically viable alternative, with support in the available technologies and meeting the requirements of the applicable laws, as well as describing the whole learning process in the co urse of activities. Keywords— Synthetic oils, Destination, Liquid waste, Applicable law requirements.
Analysis of Dry/Wet Variations in the Poyang Lake Basin Using Standardized Precipitation Evapotranspiration Index Based on Two Potential Evapotranspiration Algorithms

Global warming has resulted in unevenly distributed changes in precipitation and evapotranspiration, which has some influence on dry/wet conditions, thus exerting a tremendous impact on national life and the social economy, especially agricultural production. In order to characterize the dry/wet variations in the Poyang Lake basin during 1958–2013, based on the potential evapotranspiration (PET) estimated by the Thornthwaite (TH) and Penman–Monteith (PM) formulas, two types of Standardized Precipitation Evapotranspiration Index (SPEI), namely SPEI_th and SPEI_pm, were calculated in this study. The characteristic of dry/wet variations in the Poyang Lake basin was analyzed and a comparative analysis of two SPEIs was conducted. The results indicate that both SPEI series showed a wet trend in the Poyang Lake basin on an annual scale as well as seasonal scales during 1958–2013, except for spring and autumn. A drying trend was observed in spring, while in autumn, the dry and wet conditions in two SPEIs had opposite trends. However, all trends from two SPEIs were not significant, except for summer SPEI_pm. Meanwhile, significant positive correlations were detected between precipitation and two SPEIs, with the correlation coefficients above 0.95, whereas negative correlations were detected between PET and two SPEIs, with the correlation coefficients ranging from −0.17 to −0.85. This indicates that precipitation was the main climatic factor to determine change in dry/wet conditions in the Poyang Lake basin. Although there were obvious differences between the accumulated values of the Penman–Monteith-based PET (ET_pm) and Thornthwaite-based PET (ET_th), trends in the SPEI_pm series were generally consistent with those in the SPEI_th series, revealing that the method for PET calculation was not critical to the change in dry/wet conditions. Moreover, the results of the conditional probability of SPEI_pm and SPEI_th show that both SPEI_pm and SPEI_th could detect wet or dry events that were identified by SPEI_pm or SPEI_th.
A Survey of Corner Detection Algorithms

Corner is a significant local feature of images,because the shape of the objective is decided by it,so it is very useful in object description,motion estimation and object tracking.In this paper,the corner detection algorithms are divided into four classes:boundary-based corner detection,gray level-based corner detection,binary image-based corner detection and mathematical morphology-based corner detection.This paper details the four corner detection methods,and compared with each other.At last,it points out the future direction of research and development of corner detection.
Research on Cloud Safe Storage Evaluation Model from Perspective of Internet Finance

Cloud storage plays a role of file management and store backups with characteristics of scalability and flexibility. With increment of the formation the clients store in the cloud, cloud safe storage from perspective of internet finance becomes the hot spot in the current researches. This paper proposes the cloud safe storage evaluation model, builds the fuzzy math comprehensive evaluation system from perspective of Internet finance, and establishes evaluation matrix in order to calculate discrete assessment values based on expert evaluation mechanism. The product of the weight vector and the evaluation vector is considered the comprehensive evaluation results of cloud storage model finally by the evaluation model. Secondly, taking a comparable analysis on HDFS safety storage model, DES encryption cloud safety storage model and AES encryption cloud safety storage model that are based on encrypting, will then provide a theoretical direction for customers to select suitable storage service.
Reliably flattened radar backscatter for wet snow mapping from wide-swath sensors

: Retrieval of wet snow extent with high temporal resolution over large areas that include topography requires use of wide swath SAR and radiometric terrain correction to enable backscatter comparisons across different orbital tracks. We report on springtime wet snow mapping using a time series of Envisat ASAR wide swath (WS) images covering the Swiss Alps. The ASAR observations were used to constrain a runoff model for a local catchment; performance was assessed with and without integration of the radar data. Our EOPI project began an unprecedentedly dense series of ASAR WS acquisitions over Switzerland in March 2012. Wet snow maps at the national scale were generated and integrated for the first time on an operational basis within the Swiss Institute for Snow and Avalanche Research SLF. Lessons learned from this initial operational integration test are discussed, with a view toward the monitoring possibilities coming soon with the Sentinel-1 radar satellites. ABSTRACT Retrieval of wet snow extent with high temporal resolution over large areas that include topography requires use of wide swath SAR and radiometric terrain correction to enable backscatter comparisons across different orbital tracks. We report on springtime wet snow mapping using a time series of Envisat ASAR wide swath (WS) images covering the Swiss Alps. The ASAR observations were used to constrain a runoff model for a local catchment; performance was assessed with and without integration of the radar data. Our EOPI project began an unprecedentedly dense series of ASAR WS acquisitions over Switzerland in March 2012. Wet snow maps at the national scale were generated and integrated for the first time on an operational basis within the Swiss Institute for Snow and Avalanche Research SLF. Lessons learned from this initial operational integration test are discussed, with a view toward the monitoring possibilities coming soon with the Sentinel-1 radar satellites.
Diets and Trophic Structure of Fish Assemblages in a Large and Unexplored Subtropical River: The Uruguay River

The Neotropics represent a hotspot for freshwater biodiversity with vast number of fish species of scarce ecological knowledge. This hold true for the Uruguay River, where fish assemblages and their diets remain unexplored. Fish assemblages were surveyed in 14 sites along its main course, from headwaters to mouth (approximately 1800 km), with the aim to identify the trophic roles of fish and to describe trophic structure of these assemblages. Following standardized samplings, diet was determined to perform a trophic classification of species. One hundred species (2309 gut contents) were analysed and classified into four trophic groups subdivided into eight lower-level groups: Piscivore, piscivore-invertivore, detritivore, omnivore-detritivore, omnivore-invertivore, omnivore-planktivore and omnivore-herbivore. The trophic structure of the assemblages varied along the river, with the relative species richness of fish consuming terrestrial invertebrates increasing towards the middle river section, probably driven by the large floodplains in that areas, supporting global theories such as flood pulse concept. This study describes the feeding habits of fish along the Uruguay River, being the first dietary description for 29 species. This knowledge is essential for management and conservation, serving as baseline in the context of future environmental changes and generates novel evidence about the functioning of ecosystems in this scarcely studied climatic region.
Maximizing Economic Performance in the Mining Industry by Applying Bioleaching Technology for Extraction of Polymetallic Mineral Deposits

There are many sources to increase value in an integrated mining–metallurgy context. The optimal strategy for concentration of minerals from the ore is one of these sources. The elements of mining-metallurgy operations from resources, infrastructure, mining site, processing, and metallurgy are mutually dependent, and reinforce and interact positively with each other to generate a combined value greater than the sum of their individual contributions. Bioleaching technology is an alternative processing technology for treatment of low-grade sulphide ore, and its application contributes to the achievement of better economic results than the conventional pyrometallurgical technology. This work presents the application of bioleaching technology in laboratory conditions for metal extraction from the polymetallic deposit Tenka in East Serbia, belonging to the company Serbia Zijin Bor Copper Doo (formerly the Mining Smelter Basin Bor Group). Bioleaching of sulphide polymetallic raw material is performed by chemolithoautotrophic microorganisms. Applying the bioleaching technology, the achieved recoveries of metals from the polymetallic ore are as follows: Cu 90%, Au 90%, Ag 80%, Zn 72% and Pb 90%. The calculated values for Net Present Value (NPV) and Internal Rate of Return (IRR) are $ 21.927 million and 12.55%, respectively.
Spatial Data Mining Analytical Environment for Large Scale Geospatial Data

This Dissertation is protected by copyright and/or related rights. It has been brought to you by ScholarWorks@UNO with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself.
一种基于合作博弈的社区检测算法 A Community Detection Algorithm Based on Cooperative Game

随着互联网技术的迅速发展，虚拟大规模社会网络普遍存在。 社区结构是社会网络的重要特征，挖掘大规模社会网络中的社区结构能帮助人们了解网络中的内部结构和关系，从而更好的应用这些网络。 因此，社区检测具有重要的现实意义。 本文基于合作博弈检测社区的模型及高效计算Shapley值(SH值)的迭代公式，提出了一种以个体理性为核心的合作博弈社区检测算法(CDCG算法)。 CDCG算法包括初检测和社区调整两个步骤，初检测中每个节点在不断变化的策略环境下依据自身获得最大SH值作出决策，经过多轮决策后，网络中所有节点的SH值达到平衡状态，初检测结束；社区调整是利用社区内部连接紧密、社区之间连接相对稀疏的特征对初检测产生的不合理、无意义的小簇进行调整，使得检测得出的簇具有明显的社区特征。 为了提高算法时间效率，本文提出了无贡献节点剪枝策略和已归属节点剪枝策略。 最后通过大量实验验证了CDCG算法能够自动确定最终社区划分个数且具有较好的社区检测效果及时间效率。 With the rapid development of Internet technology, the virtual large-scale social networks are wide- spread. Community structure is an important characteristic of social network, mining the communi-ty structure in large-scale social networks can help us to understand the internal structure and relationships of the network, so as to better apply these networks. Therefore, community detection has important practical significance. A kind of individual rationality as the core of cooperative game community detection algorithm was proposed in this paper, which based on cooperative game com- munity detection model and efficient iterative formula for computing the Shapley value (SH). CDCG algorithm includes initial detection and community adjustment. In the initial detection of changing the strategy environment, every node based on its own maximum SH value to make a decision, after several rounds of decisions, when all of the nodes’ SH value become balance in the network, then the initial detection ended. The characteristics of the internal tight connection of community and rela-tively sparse in communities, by which can detect the unreasonable and meaningless small clusters in step of community adjusting, then the detected cluster has obvious community features. In order to improve efficiency of the algorithm, no contribution nodes pruning and ownership nodes pruning strategies were proposed. Finally, extensive experiments show that CDCG algorithm can automati-cally determine the final number of divided communities, which is effective and efficiency.