Search results for: species classification

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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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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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) as a result of interactions between visitors to the area and the animals that live there. We suppose that 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 as well as the chance of witnessing the species that live 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 areas 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, the existence of 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 demonstrated by numerical examples. Pontryagin's Maximum Principle was utilized to develop an optimal admission charge policy that maximized both social gain and ecosystem conservation.

Keywords: environmental preferences, singularities point, dynamical system, chaos

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Henry Kuppen

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In the last decade, tree managers have faced many threats of pests and diseases and the effects of climate change. Managers will recognize that they have to put more energy and more money into tree management. By recognizing the cause behind this, the opportunity will arise to build sustainable tree populations for the future. More and more, unwanted larvae are sprayed, ash dieback infected trees are pruned or felled, and emerald ash borer is knocking at the door of West Europe. A lot of specific knowledge is needed to produce management plans and best practices. If pest and disease have a large impact, society loses complete tree species and need to start all over again building urban forest. But looking at the cause behind it, landscape design, and tree species selection, the sustainable solution does not present itself in managing these threats. Every pest or disease needs two important basic ingredients to be successful: climate and food. The changing climate is helping several invasive pathogens to survive. Food is often designed by the landscapers and managers of the urban forest. Monocultures promote the success of pathogens. By looking more closely at the basics, tree managers will realise very soon that the solution will not be the management of pathogens. The long-term solution for sustainable tree populations is a different design of our urban landscape. The use of tree species diversity can help to reduce the impact of climate change and pathogens. Therefore landscapers need to be supported. They are the specialists in designing the landscape using design values like canopy volume, ecosystem services, and seasonal experience. It’s up to the species specialist to show what the opportunities are for different species that meet the desired interpretation of the landscape. Based on landscapers' criteria, selections can be made, including tree species related requirements. Through this collaboration and formation of integral teams, sustainable plant design will be possible.

Keywords: climate change, landscape design, resilient landscape, tree species selection

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Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park

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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence

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Authors: Samuel E. Okere, Anthony E. Ataga

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Introduction: The microbial ecology of Pleurotus osteratus and Pleurotus tuber–regium spent mushroom substrate (SMS) were characterized to determine other ways of its utilization. Materials and Methods: The microbiological properties of the spent mushroom substrate were determined using standard methods. This study was carried out at the Microbiology Laboratory University of Port Harcourt, Rivers State, Nigeria. Results: Quantitative microbiological analysis revealed that Pleurotus osteratus spent mushroom substrate (POSMS) contained 7.9x10⁵ and 1.2 x10³ cfu/g of total heterotrophic bacteria and total fungi count respectively while Pleurotus tuber-regium spent mushroom substrate (PTSMS) contained 1.38x10⁶ and 9.0 x10² cfu/g of total heterotrophic bacteria count and total fungi count respectively. The fungi species encountered from Pleurotus tuber-regium spent mushroom substrate (PTSMS) include Aspergillus and Cladosporum species, while Aspergillus and Penicillium species were encountered from Pleurotus osteratus spent mushroom substrate (POSMS). However, the bacteria species encountered from Pleurotus tuber-regium spent mushroom substrate include Bacillus, Acinetobacter, Alcaligenes, Actinobacter, and Pseudomonas species while Bacillus, Actinobacteria, Aeromonas, Lactobacillus and Aerococcus species were encountered from Pleurotus osteratus spent mushroom substrate (POSMS). Conclusion: Therefore based on the findings from this study, it can be concluded that spent mushroom substrate contain microorganisms that can be utilized both in bioremediation of oil-polluted soils as they contain important hydrocarbon utilizing microorganisms such as Penicillium, Aspergillus and Bacillus species and also as sources of plant growth-promoting rhizobacteria (PGPR) such as Pseudomonas and Bacillus species which can induce resistance on plants. However, further studies are recommended, especially to molecularly characterize these microorganisms.

Keywords: characterization, microorganisms, mushroom, spent substrate

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Authors: Hacer Yeldan, Erhan Akamca, Sedat Gündogdu

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Length-Weight and Length-length relationship were estimated of 14 species Sparidae (Boops boops, Diplodus annularis, Diplodus cervinus, Dipladus puntazzo, Diplodus sargus, Diplodus vulgaris, Lithognathus mormyrus, Oblada melanura, Pagellus acarne, Pagellus erythrinus, Pagrus auriga, Pagrus caeruleostictus, Sarpa salpa, Sparus aurata) sampled from in the Northeastern Mediterranean Sea coast of Turkey, Iskenderun Bay. Samples were collected from July 2014 to June 2015, using bottom trawl and trammel net into three different depth; 0-10 m, 10-20 m, 20-50m. Length-length relationships were determined size measurements: standard length (SL) and fork length (FL) to total length (TL) for fish species. The relationships between TL, FL and TL, SL were all linear. The values of the exponent b of the length-weight relationships ranged between 2.685 and 3.473. The type of growth for fish species was algometric growth.

Keywords: Sparidae, Iskenderun bay, length-length, length-weight relationships

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Authors: Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Sakir Tasdemir, Sevda Altin

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In this study, an experimental study was executed related to the strength of wooden materials which have been commonly used both in the past and present against pressure and whether fire retardant materials used against fire have any effects or not. Totally, 81 samples which included three different wood species, three different sizes, two different fire retardants and two unprocessed samples were prepared. Compressive pressure tests were applied to the prepared samples, their variance analyses were executed in accordance with the obtained results and it was aimed to determine the most convenient wooden materials and fire-retardant coating material. It was also determined that the species of wood and the species of coating caused the decrease and/or increase in the resistance against pressure.

Keywords: resistance of wood against pressure, species of wood, variance analysis, wood coating, wood fire safety

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Authors: Garg Ramneesh, Uppal Sanjeev, Mittal Rajinder, Shah Sheerin, Jain Vikas, Singla Bhupinder

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Introduction: Despite advances in trauma care, a classification system for soft tissue injuries of the face still needs to be objectively defined. Aim: To develop a classification system for soft tissue injuries of the face; that is objective, easy to remember, reproducible, universally applicable, aids in surgical management and helps to develop a structured data that can be used for future use. Material and Methods: This classification system includes those patients that need surgical management of facial injuries. Associated underlying bony fractures have been intentionally excluded. Depending upon the severity of soft tissue injury, these can be graded from 0 to IV (O-Abrasions, I-lacerations, II-Avulsion injuries with no skin loss, III-Avulsion injuries with skin loss that would need graft or flap cover, and IV-complex injuries). Anatomically, the face has been divided into three zones (Zone 1/2/3), as per aesthetic subunits. Zone 1e stands for injury of eyebrows; Zones 2 a/b/c stand for nose, upper eyelid and lower eyelid respectively; Zones 3 a/b/c stand for upper lip, lower lip and cheek respectively. Suffices R and L stand for right or left involved side, B for presence of foreign body like glass or pellets, C for extensive contamination and D for depth which can be graded as D 1/2/3 if depth is still fat, muscle or bone respectively. I is for damage to facial nerve or parotid duct. Results and conclusions: This classification system is easy to remember, clinically applicable and would help in standardization of surgical management of soft tissue injuries of face. Certain inherent limitations of this classification system are inability to classify sutured wounds, hematomas and injuries along or against Langer’s lines.

Keywords: soft tissue injuries, face, avulsion, classification

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Authors: Andrea Gion Saluz, Tal Hertig, Axel Heinrich, Stefan Stevanovic

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Higher temperatures, seasonal changes in precipitation, and extreme weather events are increasingly affecting trees. To counteract the increasing challenges of urban trees, strategies are increasingly being sought to preserve existing tree populations on the one hand and to prepare for the coming years on the other. One such strategy lies in strategic climate tree species selection. The search is on for species or varieties that can cope with the new climatic conditions. Many efforts in German-speaking countries deal with this in detail, such as the tree lists of the German Conference of Garden Authorities (GALK), the project Stadtgrün 2021, or the instruments of the Climate Species Matrix by Prof. Dr. Roloff. In this context, different methods for a correct species selection are offered. One possibility is to select certain physiological attributes that indicate the climate resilience of a species. To calculate the dissimilarity of the present climate of different geographic regions in relation to the future climate of any city, a weighted (standardized) Euclidean distance (SED) for seasonal climate values is calculated for each region of the Earth. The calculation was performed in the QGIS geographic information system, using global raster datasets on monthly climate values in the 1981-2010 standard period. Data from a European forest inventory were used to identify tree species growing in the calculated analogue climate regions. The inventory used is the compilation of georeferenced point data at a 1 km grid resolution on the occurrence of tree species in 21 European countries. In this project, the results of the methodological application are shown for the city of Zurich for the year 2060. In the first step, analog climate regions based on projected climate values for the measuring station Kirche Fluntern (ZH) were searched for. In a further step, the methods mentioned above were applied to generate tree species lists for the city of Zurich. These lists were then qualitatively evaluated with respect to the suitability of the different tree species for the Zurich area to generate a cleaned and thus usable list of possible future tree species.

Keywords: climate change, climate region, climate tree, urban tree

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Authors: Ahmad Almutairi

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Kuwait lies to the northwest of the Arabian Gulf. The levels of radionuclides are unknown in this area. Radionuclide like ²¹⁰Po, ²²⁶Ra, and ⁹⁰Sr accumulated in certain body tissues and bones, relate primarily to dietary uptake and inhalation. A large fraction of radiation exposure experienced by individuals comes from food chain transfer. In this study, some types of Kuwait fish were studied for radionuclide determination. These fish were taken from the Kuwaiti water territory during May. The study is to determine the radiation exposure for ²¹⁰Po in some fish species in Kuwait the ²¹⁰Po concentration was found to be between 0.089 and 2.544 Bq/kg the highs was in Zubaidy and the lowest was in Hamour.

Keywords: the radionuclide, radiation exposure, fish species, Zubaida, Hamour

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Authors: Kwounghee Choi

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Technological convergence between the various sectors is expected to have a very large impact on future industrial and economy. This study attempts to do empirical approach between specific technologies’ classification. For technological convergence classification, it is necessary to set the target technology to be analyzed. This study selected target technology from national research and development plan. At first we found a source technology for analysis. Depending on the weight of source technology, NT-based, BT-based, IT-based, ET-based, CS-based convergence types were classified. This study aims to empirically show the concept of convergence technology and convergence types. If we use the source technology to classify convergence type, it will be useful to make practical strategies of convergence technology.

Keywords: technology convergence, source technology, convergence type, R&D strategy, technology classification

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Authors: Malay K. Pramanik

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Climate change is continuously affecting the ecosystem, species distribution as well as global biodiversity. The assessment of the species potential distribution and the spatial changes under various climate change scenarios is a significant step towards the conservation and mitigation of habitat shifts, and species' loss and vulnerability. In this context, the present study aimed to predict the influence of current and future climate on an ecologically vulnerable medicinal species, Garcinia gummi-gutta, of the southern Western Ghats using Maximum Entropy (MaxEnt) modeling. The future projections were made for the period of 2050 and 2070 with RCP (Representative Concentration Pathways) scenario of 4.5 and 8.5 using 84 species occurrence data, and climatic variables from three different models of Intergovernmental Panel for Climate Change (IPCC) fifth assessment. Climatic variables contributions were assessed using jackknife test and AOC value 0.888 indicates the model perform with high accuracy. The major influencing variables will be annual precipitation, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest quarter. The model result shows that the current high potential distribution of the species is around 1.90% of the study area, 7.78% is good potential; about 90.32% is moderate to very low potential for species suitability. Finally, the results of all model represented that there will be a drastic decline in the suitable habitat distribution by 2050 and 2070 for all the RCP scenarios. The study signifies that MaxEnt model might be an efficient tool for ecosystem management, biodiversity protection, and species re-habitation planning under climate change.

Keywords: Garcinia gummi gutta, maximum entropy modeling, medicinal plants, climate change, western ghats, MaxEnt

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Authors: Haftay Abraha Tadesse, Dawit Gebreegziabiher Hagos, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli (E. 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. Method: A cross-sectional study was conducted from January to December 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 overall bacterial contamination. About 100% of the tested isolates were sensitive to ciprofloxacin, gentamicin, Co trimoxazole , sulphamethoxazole, ceftriaxone, and trimethoprim and ciprofloxacin, gentamicin, and norfloxacine of E. coli and Salmonella species, respectively, 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 handwashing practice and not using glove during meat handling showed a 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, raw meat, salmonella species

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Yosiya Chanta, Jantrararuk Tovaranont

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Species distribution model (SDMs) is one of the powerful tools used to create a suitability map used to predict and address ecology and conservation approaches. MaxEnt is a tool used among SDMs that is highly popular because it only uses presence data. Zanthoxylum rhetsa has more than 200 species distributed in the tropics. Most commonly found in cooler forest environments, there are 8-9 species found in Thailand. In northern Thailand, 3 varieties are commonly grown: Zanthoxylum myriacanthum, Zanthoxylum rhetsa and Zanthoxylum armatum. In the northern regions, these varieties are mainly used as a spice and as a cooking ingredient. MaxEnt has been used in this study to predict potential habitats for these Zanthoxylums in current and future times (2041and 2060). Suitable habitats are predicted using data from the EC-Earth3-Veg general circulation model with 19 climatic variables. The results indicate that the suitability of future habitats of Zanthoxylum rhetsa may expand into the lower northern part of Thailand. The habitat suitability map obtained from the MaxEnt tool shows that the Precipitation of Wettest Quarter (Bio16) is the most important climatic variable influencing the current and future spread of Zanthoxylum rhetsa.

Keywords: MaxEnt, Zanthoxylum rhets, species distribution modelling, climate change

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Hanan Alshaher, Jinsheng Xu

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Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Sintayehu W. Dejene, Ignas M. A. Heitkönig, Herbert H. T. Prins, Zewdu K. Tessema, Willem F. de Boer

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Current theories on diversity-disease relationships describe host species diversity and species identity as important factors influencing disease risk, either diluting or amplifying disease prevalence in a community. Whereas the simple term ‘diversity’ embodies a set of animal community characteristics, it is not clear how different measures of species diversity are correlated with disease risk. We, therefore, tested the effects of species richness, Pielou’s evenness and Shannon’s diversity on bTB risk in cattle in the Afar Region and Awash National Park between November 2013 and April 2015. We also analysed the identity effect of a particular species and the effect of host habitat use overlap on bTB risk. We used the comparative intradermal tuberculin test to assess the number of bTB infected cattle. Our results suggested a dilution effect through species evenness. We found that the identity effect of greater kudu - a maintenance host – confounded the dilution effect of species diversity on bTB risk. bTB infection was positively correlated with habitat use overlap between greater kudu and cattle. Different diversity indices have to be considered together for assessing diversity-disease relationships, for understanding the underlying causal mechanisms. We posit that unpacking diversity metrics is also relevant for formulating control strategies to manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interactions.

Keywords: evenness, diversity, greater kudu, identity effect, maintenance hosts, multi-host disease ecology, habitat use overlap

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Authors: Fuad M. Alkoot

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Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Helen Yetunde Omoboye, Adebukola Adenike Adedeji, Israel Funso Adeniyi

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This study of the biodiversity, community structure, and production capacity of the zooplankton community is an aspect of bio-monitoring of the aquatic ecosystem. Samples were selected horizontally and vertically from Esa-Odo Reservoir using improvised Meyer’s water sampler. Planktonic samples were collected at two months intervals for two years. Net and total plankton were sampled by filtration and sedimentation methods. Planktonic samples were preserved as 5% formalin and 1% Lugol’s solution. Measurement, enumeration, and scaled pictures of the recorded zooplankton were taken using a photomicrograph. The taxonomic composition of zooplankton biota was determined using identification keys. Eighty three (83) species of zooplankton recorded in this study belong to 4 groups: Rotifera, Cladocera, Copepoda, and Insecta. Rotifera was the most represented group (61.21%). Horizontally, 24 species with the highest mean abundance characterized the lacustrine; while 12 species and 10 species were unique to the transition and riverine zones, respectively. Vertically, most species had their mean abundance decreased from the surface to the bottom of the reservoir. A total of nine (9), two (2), and one (1) species were peculiar to the surface, bottom and mid-depth, respectively. Zooplankton was most abundant during the dry season. In conclusion, Esa-Odo Reservoir comprised highly diversified zooplankton fauna with great potential to support a rich aquatic community and fishery production. The reservoir can be classified as fairly clean based on the abundance of the rotifer group. However, the lake should be subjected to regular proper monitoring because of the presence of some pollution tolerant copepod species identified among the zooplankton fauna.

Keywords: zooplankton, spatial, temporal, abundance, biodiversity, reservoir

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Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

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Authors: Francisco Domingos Francisco

Abstract:

Tropical forests are key providers of many Ecosystem Services (ES), contributing to human wellbeing on a global and local scale. Communities around and within Moribane Forest Reserve (MFR), Manica Province - Mozambique, benefit from ES through the exploitation of non-wood and wood forest products. The objective was to assess the provisioning capacity of the MFR in woody forest products in species and profiles of interest to local communities in the main sources of extraction. Social data relating to the basic needs of local communities for these products were captured through an exploratory study before this one. From that study, it became known about the most collected wood species, the sources of collection, and their availability in the profiles of greatest interest to them. A field survey through 39 rectangular 50mx20m plots was conducted with 13 plots established in each of the three land-use types (LUT), namely Restricted Forest, Unrestricted Forest, and Disturbed areas. The results show that 89 species were identified, of which 28 (31.4%) are assumed to be the most used by the communities. The number of species of local interest does not vary across the LUT (p>0.05). The most used species (MUS) is distributed in 82% in Restricted Forest, 75% in Unrestricted, and also 75% in Disturbed. Most individuals of both general and MUS found in Unrestricted Forest, and Degraded areas have lower end profiles (5-7 cm), representing 0.77 and 0.26%, respectively. The profile of individuals of species of local interest varies by LUT (p<0.05), and their greatest proportion (0.51%) outside the lower end is found in Restricted Forest. There were no similarities between the LUT for the species in general (JCI <0.5) but between the MUS (JCI >0.5). Conclusion, the areas authorized for the exploitation of wood forest products in the MFR tend to reduce their ability to provide local communities with forest products in species and profiles of their interest. This reduction item is a serious threat to the biodiversity of the Restricted Forest. The study can help the academic community in future studies by replicating the methodology used for monitoring purposes or conducting studies in other similar areas, and the results may support decision-makers in designing better strategies for sustainability.

Keywords: ecosystem services, land-use types, local communities, species profile, wellbeing, wood forest product

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Authors: A. Loayza

Abstract:

Wood acetilationhapens when woody cell wall is saturated with acetic anhydride, the free hydroxyl groups present on cellulosic structures are replaced. Thus, the capillary spaces are filled with acetyl groups, and this replacement avoids further reactions with water. But, there is no information about wood acetilation in peruvianamzonic Wood species (SchizolobiumExcelsumVoge and CalycophyllumSpruceanum). So, in this research, we test acetylation of this two peruvian species in order to assess its ability as a protection estrategy, like the artificially cultivated species common for this type of treatment. A know experimental methodology was applied, using a laboratory reactor, evaluating the time as a principal variable. In this research, we were able to evaluate weight gains. The acetylation was carriet out considering one immersion time of 3 and 6 hours on acetic anhydride, were could it be observed weight gains ranged between 14 and 20% and the improvement of mention properties such as: a) Dimensional stability and water absorption capacity improved as well as its compressive strength.

Keywords: acetylation, calycophyllum spruceanum benth. Hook. F., cedrelinga cateniformis, copaifera langsdorffii, dimensional stability, schizolobium parahybum

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Authors: Fadila Tazerouti, Affaf Boukadoum, Kamilia Gharbi, Karima Benmeslem

Abstract:

Parasites are recognized as an important component of biodiversity because of their crucial role in providing valuable information on host populations and in the functioning and balance of natural ecosystems. Although the knowledge about these pathogen organisms' diversity has increased these last years, many species still need to be identified and more investigations should be performed. Batoid fishes represent a significant biological resource, especially among populations of the Mediterranean basin. However, the data on their parasitic fauna, particularly in Algeria, remains unknown and still incomplete. Therefore, the aim of this study is to survey and provide data on the biodiversity of Platyhelminthes parasites of Elasmobranches fishes from Algerian coasts. 3217 specimens of Batoids belonging to 4 families, Topedinidae, Rajdae, Dasyatidae and Myliobatidae, caught in several sites on the Algerian coasts, were examined for their parasites. 47 taxa, including 7 new for science and belonging to 2 classes Monogenea and Cestoda, have been identified. Monogeneans presented the highest richness with 24 taxa and 5 new species for science: 4 Amphibdelloides species and one Calicotyle species. Cestodes are represented by 23 taxa and 3 new species: 2 Acanthobothrium and 1 species Echinobothrium. This study allowed us to establish for the first time in Algeria an inventory of Platyhelminthes parasites of this group of Chondrichthyes fish, as well as an invaluable contribution to the knowledge about the parasitic fauna of Algerian and Mediterranean Elasmobranch fishes.

Keywords: parasitic platyhelminthes, biodiversity, elasmobranches, algerian coasts, inventory

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Authors: Ahdieh Alijani, Mina Zarrabi, Abdollah Jamshidi, Jamshid Razmyar

Abstract:

Avian intestinal spirochetosis (AIS) is caused by spiral-shaped Gram-negative Brachyspira spp. in poultry and is known as a cause of diarrhea, low egg production and increased the occurrence of dirty eggs in layer hens. In this study the presence of some Brachyspira spp. was investigated in laying hens. A total of 100 cloacal swab samples were individually collected from 20 laying hen flocks showing fecal egg staining in northeastern Iran. By culture and morphologic examination, 41 samples (41%) from 20 flocks were positive but by using genus–specific PCR only 37 (37%) samples were confirmed as Brachyspira spp. Using species-specific primers, single colonization was identified in 18 samples associated with B. pilosicoli (48.6%) while single colonization with B. intermedia was found in only two samples (5.4%). Simultaneous colonization by B. intermedia and B. murdochii was detected in 3 samples (8.1%). B. pilosicoli was the most prevalent species in concurrent colonization in 11 cases (29.7%). Finally, co-colonization by B. intermedia and B. innocens was identified in 3 samples (8.1%). The results of this study show the colonization of different species of Brachyspira with the dominance of B. pilosicoli in layer hens. In simultaneous colonization with pathogenic and non-pathogenic species the symptoms of intestinal spirochetosis were reduced, suggesting a competitive role in preventing and reducing the colonization of pathogenic species.

Keywords: intestinal spirochetosis, Brachyspira, laying hen, PCR

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