Search results for: species classification

Authors: Min Woo Park, Jin Do Chung, Kyu Yeol Kim, Byoung Uk Im, Jang Woo Kim, Hae Yeul Ryu

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Nine representative species of trees among all the street trees were selected to estimate the absorption amount of carbon dioxide emitted from street trees in Seoul calculating the biomass, amount of carbon saved, and annual absorption amount of carbon dioxide in each of the species. Planting distance of street trees in Seoul was 1,851,180 m, the number of planting lines was 1,287, the number of planted trees was 284,498 and 46 species of trees were planted as of 2013. According to the result of plugging the quantity of species of street trees in Seoul on the absorption amount of each of the species, 120,097 ton of biomass, 60,049.8 ton of amount of carbon saved, and 11,294 t CO2/year of annual absorption amount of carbon dioxide were calculated. Street ratio mentioned on the road statistics in Seoul in 2022 is 23.13%. If the street trees are assumed to be increased in the same rate, the number of street trees in Seoul was calculated to be 294,823. The planting distance was estimated to be 1,918,360 m, and the annual absorption amount of carbon dioxide was measured to be 11,704 t CO2/year. Plans for improving the annual absorption amount of carbon dioxide from street trees were established based on the expected amount of absorption. First of all, it is to improve the annual absorption amount of carbon dioxide by increasing the number of planted street trees after adjusting the planting distance of street trees. If adjusting the current planting distance to 6 m, it was turned out that 12,692.7 t CO2/year was absorbed on an annual basis. Secondly, it is to change the species of trees to tulip trees that represent high absorption rate. If increasing the proportion of tulip trees to 30% up to 2022, the annual absorption rate of carbon dioxide was calculated to be 17804.4 t CO2/year.

Keywords: absorption of carbon dioxide, source of absorbing carbon dioxide, trees in city, improving species

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Authors: Marref Cherine, Bezzala Adel, Houhamdimoussa

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Wetlands represent ecosystems of great importance through their ecological and socio-economic functions and biological diversity, even if they are most threatened by anthropization. This study aimed to contribute to the creation of an inventory of bird species in the Gadaïne eco-complex (Batna, Algeria) from 2019 to 2021. Counts were carried out from 8:00 to 19:00 using a telescope (20 × 60) and a pair of binoculars (10 × 50) and by employing absolute and relative methods. Birds were categorized by phenology, habitat, biogeography, and diet. A total of 80 species in 58 genera and 19 families were observed. Migratory birds were dominant (38%) phenologically, and the birds of Palearctic origin dominated (26.25%) biogeographically. Invertivorous and carnivorous species were the most common (35%). Ecologically, the majority of species were waterbirds (73.75%), which are protected in Algeria. This study highlights the need for the preservation of ecosystem components and the enhancement of biological resources of protected, rare, and key species. We observed 43797 individuals of Marmaronetta angustirostris during our study and reported the nesting of Podiceps nigricollis, Porphyrio porphyrio, and Tadorna ferruginea. For this reason, it is recommended to propose the area as a Ramsar site.

Keywords: biodiversity, avifauna, ecological status, wetlands

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Authors: Olatunde Sunday Eludoyin, Charles Obiechina Olisa

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The study examined the spatial interactions between earthworm abundance (EA) and tree growth characteristics in ecological belts of Western Niger Delta, Nigeria. Eight 20m x 20m quadrat were delimited in the natural vegetation in each of the rainforest (RF), mangrove (M), fresh water swamp (FWS), and guinea savanna (GS) ecological belts to gather data about the tree species (TS) characteristics which included individual number of tree species (IN), diversity (Di), density (De) and richness (Ri). Three quadrats of 1m x 1m were delineated in each of the 20m x 20m quadrats to collect earthworm species the topsoil (0-15cm), and subsoil (15-30cm) and were taken to laboratory for further analysis. Descriptive statistics and inferential statistics were used for data analysis. Findings showed that a total of 19 earthworm species was found, with 58.5% individual species recorded in the topsoil and 41.5% recorded in the subsoil. The total population ofEudriliuseugeniae was predominantly highest in both topsoil (38.4%) and subsoil (27.1%). The total population of individual species of earthworm was least in GS in the topsoil (11.9%) and subsoil (8.4%). A total of 40 different species of TS was recorded, of which 55.5% were recorded in FWS, while RF was significantly highest in the species diversity(0.5971). Regression analysis revealed that Ri, IN, DBH, Di, and De of trees explained 65.9% of the variability of EA in the topsoil, while 46.9 % of the variability of earthworm abundance was explained by the floristic parameters in the subsoil.Similarly, correlation statistics revealed that in the topsoil, EA is positively and significantly correlated with Ri (r=0.35; p<0.05), IN (r=0.523; p<0.05) and De (r=0.469; p<0.05) while DBH was negatively and significantly correlated with earthworm abundance (r=-0.437; p<0.05). In the subsoil, only Ri and DBH correlated significantly with EA. The study concluded that EA in the study locations was highly influenced by tree growth species especially Ri, IN, DBH, Di, and De. The study recommended that the TSabundance should be improved in the study locations to ensure the survival of earthworms for ecosystem functions.

Keywords: interactions, earthworm abundance, tree growth, ecological zones, western niger delta

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Paolo Russu

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This paper investigates the economic and ecological dynamics that emerge in Protected Areas (PAs) due to interactions between visitors and the animals that live there. The PAs contain two species whose interactions are determined by the Lotka-Volterra equations system. Visitors' decisions to visit PAs are influenced by the entrance cost required to enter the park and the chance of witnessing the species living there. Visitors have contradictory effects on the species and thus on the sustainability of the protected areas: on the one hand, an increase in the number of tourists damages the natural habitat of the regions and thus the species living there; on the other hand, it increases the total amount of entrance fees that the managing body of the PAs can use to perform defensive expenditures that protect the species from extinction. For a given set of parameter values, saddle-node bifurcation, Hopf bifurcation, homoclinic orbits, and a Bogdanov–Takens bifurcation of codimension two has been investigated. The system displays periodic doubling and chaotic solutions, as numerical examples demonstrate. Pontryagin's Maximum Principle was utilised to develop an optimal admission charge policy that maximised social gain and ecosystem conservation.

Keywords: chaos, bifurcation points, dynamical model, optimal control

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Authors: Khaled Khleifat

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This study detects the bacterial species that responsible for UTI in both diabetic patients and non-diabetic patients, Jordan. 116 urine samples were investigated in order to determine UTI-causing bacteria. These samples distributed unequally between diabetic male (12) and diabetic female (25) and also non-diabetic male (13) and non-diabetic female (66). The results represent that E.coli is responsible for UTI in both diabetic and non-diabetic patients (15.5% and 29.3% respectively) with large proportion (44.8%). This study showed that not all bacterial species that isolated from the non-diabetic sample could be isolated from diabetic samples. E. coli (15.5%), P. aeruginosa (4.3%), K. pneumonia (1.7%), P. mirabilis (2.6%), S. marcescens (0.9%), S. aureus (1.7%), S. pyogenes (1.7%), E. faecalis (0.9%), S. epidermidis (1.7%) and S. saprophyticus (0.9%). But E. aerogenes, E. cloacae, C. freundii, A. baumannii and B. subtilis are five bacterial species that can’t isolate from all diabetic samples. This study shows that for the treatment of UTI in both diabetic and non-diabetic patients, Chloramphenicol (30 μg), Ciprofloxacin (5 μg) and Vancomycin (30 μg) are more favorable than other antibiotics. In the same time, Cephalothin (30μg) is not recommended.

Keywords: urinary tract infections, diabetes mellitus, bacterial species, infections

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Authors: Ali F. Al-Baz, Mohsen M. Al-Husaini, James M. Bishop

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Intertidal fixed stake net trap (hadrah) is one of the oldest fishing gears used throughout the Arabian Gulf countries since 1800s and also one of most efficient methods of capturing fish from the intertidal area. This study described the hadrah fishery in Kuwait. From October 2001 to December 2002, more than 37,372 specimens representing 95 species (89 fish, 2 mollusks, 4 crustaceans) were measured from hadrah located in three different areas along Kuwait's coast. In Kuwait Bay, catch rates averaged 62 kg/sir day (range 14 kg/sir-day in February to 160 kg/sir-day in October 2002). Commercial species accounted for 41% of the catches. Catches from Failakah Island averaged 96 kg/sir-day from June through September, with 61% of the catch being commercial species. In the southern area, catches averaged only 32 kg/sir-day, and only 34% were commercially important. Forty percent of the hadrah catches were juveniles which shows that the shallow intertidal waters are prime nursery habitat, particularly in Kuwait Bay. To maintain ecosystem biodiversity and recruitment success of the fishes, we recommended that all hadrah should be removed from Kuwait Bay. In the future, removal of hadrah in other locations should be considered.

Keywords: catch and effort, hadrah, intertidal fixed stake net, Kuwait, species composition

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Authors: Ila Shrestha

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Bridim Village Development Committee (VDC) is one of the medicinal plants hot spots of Nepal. It is located on a ridge above the lower Langtang Khola, steep and narrow spot in between 1944 m to 4833 m altitude. The study area is homogeneously inhabited by Tamang communities. An investigation on folk herbal medicine on the basis of traditional uses of medicinal plants was done in 2014. The local traditional healers, elder men and women, traders and teachers, were consulted as key informants for documentation of indigenous knowledge on the medicinal plants. It was found that altogether seventy-one medicinal plant species belonging to sixty genera and thirty-three families were used by local people for twenty-seven diseases. Roots of thirty-four species were the most frequently used plant parts and bigger numbers of species were found to be used in fever of ten species. Most medicines were prepared in the form of juice of forty species. The attempt of the study was to document ethno medicinal practices to treat different diseases in the study area for conservation of indigenous knowledge.

Keywords: Bridim village, ethnomedicine, national park, plants

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Authors: Petr Konvalina, Jan Moudry

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As organic farmers are searching foregoing crops for horticultural crops, there is possible to choice neglected wheat species and also have a new market and sale opportunities. Concerning wheat, there are landraces so called hulled wheat species (einkorn, emmer wheat, spelt) comprising parts of collections of the world gene banks. The advantage of this wheat species are small demands on growing conditions and also droughtiness in conditions of changing climate. Our paper aims at presenting the results of the study and the assessment of spring wheat forms, four einkorn cultivars, eight emmer wheat cultivars, seven spelt wheat cultivars in particular, as compared to modern bread wheat variety. Small-plot trials were established at two different localities within the Czech Republic and Austria in 2009 and 2012. The results of the trials show that some varieties were inclined to lodging. On the other hand, they were resistant to common wheat diseases (mildew, brown rust). Hulls served as barriers and obstacles against the DON grain contamination. The yield rate was lower. The grains were characterized by a high proportion of protein in grain (up to 18.1 %). However, they may be difficult to use for common baking. Moreover, new food products demonstrating a different technological quality of the hulled wheat species have to be launched on the market. They will be suitable for regional marketing.

Keywords: organic farming, hulled wheat species, einkorn, emmer, spelt

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Authors: Mohamed R. Mhereeg

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The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spread-sheet developers competency over a network. It is designed to automatically and autonomously monitor spread-sheet users and gather their development activities based on the utilization of the software Multi-Agent Technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spread-sheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: classification, design, MACS, MAS, prometheus

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Authors: Ning Li, Yaner Yan, Yajun Qiao, Shu-qing An

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Although seed dispersal is considered to be a key process determining the spatial structure and spread of invasive plant populations, few studies have explicitly addressed the link between dispersal vector behaviour, and seedling recruitment to gain insight into the process of exotic species invasion within a urban landscape. The present study tests the effects of native bird species on the dispersal and recruitment of invasive Phytolacca Americana in an urban garden. We found the invasive population of American pokeweed attracted both generalist species and specialist species to forage and disperse its seeds, with generalists Pycnonotus sinensis and Urocissa erythrorhyncha being by far the most important dispersers. Seedling numbers of P. Americana was strongly affected by perching behavior of bird dispersers. Moreover, two main disperser species, P. sinensis and U. erythrorhyncha govern a high quality dispersal service for P. Americana. Our results highlight the ability of invasive P. americana to recruit seed dispersal agents in urban habitats. However, if the newly recruited species could use the seedling safe site for perching shelter, the invasive plants will get a high regenerate rate in the invasive new habitats thus enhancing their invasive ability.

Keywords: frugivorous birds, phytolacca americana, seed dispersal, urban landscape

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Authors: Suganiya Rama Rao, Yoon-Yen Yow, Thor-Seng Liew, Shyamala Ratnayeke

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Invasive snails in the genus Pomacea have spread across Southeast Asia including Peninsular Malaysia. Apart from significant economic costs to wetland crops, very little is known about the snails’ effects on native species, and wetland function through their alteration of macrophyte communities. This study was conducted to establish diagnostic characteristics of Pomacea species in the Malaysian environment using genetic and morphological criteria. Snails were collected from eight localities in northern and central regions of Peninsular Malaysia. The mitochondrial COI gene of 52 adult snails was amplified and sequenced. Maximum likelihood analysis was used to analyse species identity and assess phylogenetic relationships among snails from different geographic locations. Shells of the two species were compared using geometric morphometric analysis and covariance analyses. Shell height accounted for most of the observed variation between P. canaliculata and P. maculata, with the latter possessing a smaller mean ratio of shell height: aperture height (p < 0.0001) and shell height to shell width (give p < 0.0001). Genomic and phylogenetic analysis demonstrated the presence of two monophyletic taxa, P. canaliculata and P. maculata, in Peninsular Malaysia samples. P. maculata co-occurred with P. canaliculata in 5 localities, but samples from 3 localities contained only P. canaliculata. This study is the first to confirm the presence of two of the most invasive species of Pomacea in Peninsular Malaysia using a genomic approach. P. canaliculata appears to be the more widespread species. Despite statistical differences, both quantitative and qualitative morphological characteristics demonstrate much interspecific overlap and intraspecific variability; thus morphology alone cannot reliably verify species identity. Molecular techniques for distinguishing between these two highly invasive Pomacea species are needed to understand their specific ecological niches and develop effective protocols for their management.

Keywords: Pomacea canaliculata, Pomacea maculata, invasive species, phylog enetic analysis, geometric morphometric analysis

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

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Authors: Lobna Mnif Fakhfakh, Mohamed Chaieb

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Most ecological studies in North Africa reveal a process of continuous degradation of pastoral ecosystems as a result of overgrazing. This degradation appears across the depletion of perennial grass species. Indeed, the majority of steppic ecosystems are characterized by a low density of perennial grasses. This phenomenon reveals a drop in food value of rangelands, which is now estimated at less than 100 UF.ha -1. -1 Year in all North African steppes. However, for ecological restoration initiatives, some species such the genus of Stipagrostis and Stipa can be considered a good candidates species for effective pastoral improvement under arid bioclimate. The present work concerns Stipagrostis ciliata (Desf.) De Winter, perennial grasses, abundant in ecosystems characterized by the high content of gypsum (CaSO4)2H2O in the southern Tunisia. This tufted species with C4 biochemical photosynthesis type is able to grow and develop under high temperature and low annual rainfall, where the minimum water potential (ψmd), can reach -4 MPa during the summer season with a phenological growth maintained throughout the season unfavorable. At this point in the early autumn rains, S. ciliata begins its growth, especially with a heading which occurs 2-3 weeks after the first autumn rains. From the foregoing, it can be concluded that Stipagrostis ciliata is an excellent promising pastoral species for the ecological restoration, and enhancement of ecosystems biological productivity in arid bioclimate of North Africa.

Keywords: Stipagrostis ciliata, pastoral species, ecological restoration, arid bioclimate

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Authors: P. Byrnes, F. A. DiazDelaO

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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.

Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines

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Authors: Vadivel Ayyasamy

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The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation

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Authors: Vincent Mokoka, Kai Behn, Edwin Mudongo, Jan Ruppert, Kingsley Ayisi, Anja Linstädter

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Severe drought may trigger a transition of vegetation composition in dryland grasslands, with productive perennial grasses often being replaced by annual grasses. Grazing pressure is thought to exacerbate drought effects, but little is known on the joint effects of grazing and drought on the functional and taxonomic composition of the herbaceous vegetation in African savannas. This study thus aimed to elucidate which herbaceous species and plant functional types (PFTs) are most resistant to prolonged drought and grazing and whether resting plays a role in this context. Thus, we performed a six-year field experiment in South Africa’s Limpopo province, combining drought and grazing treatments. Aboveground herbaceous biomass was harvested annually and separated into species. We grouped species into five PFTs, i.e. very broad-leaved perennial grasses, broad-leaved perennial grasses, narrow-leaved perennial grasses, annual grasses, and forbs. For all species, we also recorded three-leaf traits (leaf area - LA, specific leaf area – SLA, and leaf dry matter content – LDM) to describe their resource acquisition strategies. We used generalized linear models to test for treatment effects and their interaction. Association indices were used to detect the relationship between species and treatments. We found that there were no absolute winner species or PFTs, as the six-year severe drought had a pronounced negative impact on the biomass production of all species and PFTs. However, we detected relative winners with increases in relative abundances, mainly forbs and less palatable narrow-leafed grasses with comparatively low LA and high LDMC, such as Aristida stipidata Hack. These species and PFTs also tended to be favored by grazing. Although few species profited from resting, for most species, the combination of drought and resting proved to be particularly unfavorable. Winners and losers can indicate ecological transition and may be used to guide management decisions.

Keywords: aboveground net primary production, drought, functional diversity, winner and loser species

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Authors: Guler D. Uzel, Andrew G. Parker, Robert L. Mach, Adly Abd-Alla

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Several tsetse fly species (Diptera: Glossinidae) in natural or colonized populations can be infected with the salivary gland hypertrophy virus (SGHV), a circular dsDNA virus (Hytrosaviridae). The virus infection is mainly asymptomatic but, in some species under certain conditions, the infection can produce salivary gland hypertrophy (SGH) symptoms. In the laboratory colonized tsetse, flies with SGH have reduced fertility, which negatively affects colony performance. Therefore, a high prevalence of SGH in insect mass rearing represents a major challenge for tsetse control using the sterile insect technique. The main objective of this study is to analyze the impact of Glossina pallidipes SGHV infection in various tsetse species on mortality and productivity and its impact on the symbiotic bacteria. Hypertropied salivary glands (SG) were collected from G. pallidipes into phosphate buffered saline (PBS) to prepare suspension; 2 µl aliquots were injected into adults of several tsetse species (G. pallidipes (Gp), G. p. gambiensis (Gpg), G. brevipalpis (Gb), G. morsitans morsitans (Gmm), G. morsitans centralis (Gmc) and G. fuscipes (Gf)) and the change in virus and symbiont titers were analyzed using qPCR. The development of SGH in the F1 was detected by dissection 10 days after emergence and virus infection was confirmed by PCR. The impact of virus infection on fly mortality and productivity was recorded. 2 µl aliquots were also injected into 3rd instar larvae of the different species and the adult SGs assayed by PCR for virus. Virus positive SGs from each species were homogenized in PBS and pooled within species for injection into larvae of the same species. Flies injected with PBS were used as control. Injecting teneral flies with SGHV caused increasing virus titer over time in all species but no SGH was detected. Dissection of the F1 also showed no development of SGH except in Gp (the homologous host). Injection of SGHV did not have any impact on the prevalence of the tsetse symbionts, but an increase in Sodalis titer was observed correlated with fly age regardless of virus infection. The virus infection had a negative impact on productivity and mortality. SGHV injection into larvae of the different species produced SGHV infected glands in the adults determined by PCR with a rate of 60%, 27%, 16%, 7% and 7% for Gp, Gf, Gpg, Gmm and Gmc, respectively. Virus positive SGs observed in the heterologous species were smaller than SGH found in Gp. No virus positive SG was detected by PCR in Gb and no SGH was observed in any adults except in Gp. Injecting virus suspension from the virus positive SGs into conspecific larvae did not produce any adults with infected SGs (except in Gp). SGHV can infect all tested tsetse species. Although the virus can infect and increase in titer in other tsetse species and affect fly mortality and productivity, no vertical virus transmission was observed in other tsetse species with might indicate a transmission barrier in these species, and virus collected from flies injected as larvae was not infective by injection.

Keywords: DNA viruses, glossina, hytrosaviridae, symbiotic bacteria, tsetse

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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Authors: Tülin Koldaş, Özlem Çetin Erdoğan, Ahmet Beyarslan

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Brachistinae Föerster, 1862 is a subfamily of the family Braconidae (order Hymenoptera) with about 410 species distributed all around the world. Brachistinae includes the genera, Eubazus Nees von Esenbeck 1814, Foersteria Szépligeti 1896, Chelostes van Achterberg 1990, Triaspis Haliday 1835 and Schizoprymnus Förster 1862. Members of the subfamily live as parasitoids on the families Curculionidae and Apionidae (Coleoptera), which also include very important agricultural pests.  In generally, members of the genus Triaspis are poorly known biologically. The genus is represented by 37 species in the West Palearctic region and 118 species worldwide. Adult specimens of Triaspis were collected from as wide a range of habitats as possible at different altitudes in different parts of Turkey between 1982 and 2010. Samples collected from short plants using standard insect sweeping nets were transferred into tubes containing 70% ethanol and labelled following their preparations according to museum techniques. Seven Triaspis species have been reported from Turkey in this study. Five of these species are new to the fauna of Turkey.

Keywords: Triaspis, Braconidae, Hymenoptera, Turkey, fauna

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Authors: Mahpara Pirzada, Mansoor Ali Shah, Saima Pthan, Kamal Khan, Faiza

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Present study based on biodiversity of aphid in different crops of Hyderabad district and its, surrounding area to observe the biodiversity of aphids, host plant range of the aphids in Hyderabad and their population also infestation and yield loss aphid on different crops. We have surveyed different fields of Hyderabad, Jamshoro, and collected the aphids from various parts of plants, grasses, and herb with the help of camel brush. They have been brought to the laboratory into plastic jars and preserved in Glycerin (Glycerol). As a result, 383 individuals belonging to 3 species were identified. These identified species were Aphis fabae, Myzus persicae, and Brevicoryne brassicae. Out of the 3 habitats the maximum richness, evenness, and diversity were recorded in agriculture crops followed by flowering vegetables and minimum in fodder crops. The most abundant specie is Myzus persicae.

Keywords: aphid species, biodiversity, Homoptera:Aphididae, Pakistan

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Authors: S. S. Patil, Sachidanand Kini

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Classification of land use patterns is compelling in complexity and variability of remote sensing imageries data. An imperative research in remote sensing application exploited to mine some of the significant spatially variable factors as land cover and land use from satellite images for remote arid areas in Karnataka State, India. The diverse classification techniques, unsupervised and supervised consisting of maximum likelihood, Mahalanobis distance, and minimum distance are applied in Bellary District in Karnataka State, India for the classification of the raw satellite images. The accuracy evaluations of results are compared visually with the standard maps with ground-truths. We initiated with the maximum likelihood technique that gave the finest results and both minimum distance and Mahalanobis distance methods over valued agriculture land areas. In meanness of mislaid few irrelevant features due to the low resolution of the satellite images, high-quality accord between parameters extracted automatically from the developed maps and field observations was found.

Keywords: Mahalanobis distance, minimum distance, supervised, unsupervised, user classification accuracy, producer's classification accuracy, maximum likelihood, kappa coefficient

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Authors: Sahar Elkaee Behjati

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Air pollution, particularly with dust, is one of the biggest issues Tehran is dealing with, and the city's green space which consists of trees has a critical role in absorption of it. The question this study aimed to investigate was which tree species the highest uptake capacity of the dust and carbon have suspended in the air. On this basis, 30 samples of trees from two different districts in Tehran were collected, and after washing and centrifuging, the samples were oven dried. The results of the study revealed that Ulmus minor had the highest amount of deposited dust in both districts. In addition, it was found that in Chamran district Ailanthus altissima and in Gandi district Ulmus minor has had the highest absorption of deposited carbon. Therefore, it could be argued that decision making on the selection of species for urban green spaces should take the above-mentioned parameters into account.

Keywords: dust, leaves, uptake total carbon, Tehran, tree species

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Majid Abdolrazzagh-Nezhad, Salwani Abdullah

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The job-shop scheduling problem (JSSP) is an important decision facing those involved in the fields of industry, economics and management. This problem is a class of combinational optimization problem known as the NP-hard problem. JSSPs deal with a set of machines and a set of jobs with various predetermined routes through the machines, where the objective is to assemble a schedule of jobs that minimizes certain criteria such as makespan, maximum lateness, and total weighted tardiness. Over the past several decades, interest in meta-heuristic approaches to address JSSPs has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides the classification, constraints and objective functions imposed on JSSPs that are available in the literature.

Keywords: job-shop scheduling, classification, constraints, objective functions

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Authors: Haftay Abraha Tadesse, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from January to September 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli, Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI: (4.69 27.10) were associated with an overall bacterial contamination.About 95.5% of the tested isolates were sensitive to chloramphenicol and norfloxacin while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor hand washing practice and not using glove during meat handling showed significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, e. coli, salmonella species

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Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

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Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Geetika Barman, B. S. Daya Sagar

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In this article, we proposed a pixel-wise classification of hyperspectral images using a mathematical morphology operator-based distance metric called “dilation distance” and “erosion distance”. This method involves measuring the spatial distance between the spectral features of a hyperspectral image across the bands. The key concept of the proposed approach is that the “dilation distance” is the maximum distance a pixel can be moved without changing its classification, whereas the “erosion distance” is the maximum distance that a pixel can be moved before changing its classification. The spectral signature of the hyperspectral image carries unique class information and shape for each class. This article demonstrates how easily the dilation and erosion distance can measure spatial distance compared to other approaches. This property is used to calculate the spatial distance between hyperspectral image feature vectors across the bands. The dissimilarity matrix is then constructed using both measures extracted from the feature spaces. The measured distance metric is used to distinguish between the spectral features of various classes and precisely distinguish between each class. This is illustrated using both toy data and real datasets. Furthermore, we investigated the role of flat vs. non-flat structuring elements in capturing the spatial features of each class in the hyperspectral image. In order to validate, we compared the proposed approach to other existing methods and demonstrated empirically that mathematical operator-based distance metric classification provided competitive results and outperformed some of them.

Keywords: dilation distance, erosion distance, hyperspectral image classification, mathematical morphology

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Authors: Zakiya Shireen, Sujin B. Babu

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Irreversible diffusion-limited cluster aggregation (DLCA) of binary sticky spheres was simulated by modifying the Brownian Cluster Dynamics (BCD). We randomly distribute N spheres in a 3D box of size L, the volume fraction is given by Φtot = (π/6)N/L³. We identify NA and NB number of spheres as species A and B in our system both having identical size. In these systems, both A and B particles undergo Brownian motion. Irreversible bond formation happens only between intra-species particles and inter-species interact only through hard-core repulsions. As we perform simulation using BCD we start to observe binary gels. In our study, we have observed that species B always percolate (cluster size equal to L) as expected for the monomeric case and species A does not percolate below a critical ratio which is different for different volume fractions. We will also show that the accessible volume of the system increases when compared to the monomeric case, which means that species A is aggregating inside the cage created by B. We have also observed that for moderate Φtot the system undergoes a transition from flocculation region to percolation region indicated by the change in fractal dimension from 1.8 to 2.5. For smaller ratio of A, it stays in the flocculation regime even though B have already crossed over to the percolation regime. Thus, we observe two fractal dimension in the same system.

Keywords: BCD, fractals, percolation, sticky spheres

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