Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of banana fusarium wilt using supervised classification algorithms with UAV-based multi-spectral imagery

The disease of banana Fusarium wilt currently threatens banana production areas all over the world. Rapid and large-area monitoring of Fusarium wilt disease is very important for the disease treatment and crop planting adjustments. The objective of this study was to evaluate the performance of supervised classification algorithms such as support vector machine (SVM), random forest (RF), and artificial neural network (ANN) algorithms to identify locations that were infested or not infested with Fusarium wilt. An unmanned aerial vehicle (UAV) equipped with a five-band multi-spectral sensor (blue, green, red, red-edge and near-infrared bands) was used to capture the multi-spectral imagery. A total of 139 ground sample-sites were surveyed to assess the occurrence of banana Fusarium wilt. The results showed that the SVM, RF, and ANN algorithms exhibited good performance for identifying and mapping banana Fusarium wilt disease in UAV-based multi-spectral imagery. The overall accuracies of the SVM, RF, and ANN were 91.4%, 90.0%, and 91.1%, respectively for the pixel-based approach. The RF algorithm required significantly less training time than the SVM and ANN algorithms. The maps generated by the SVM, RF, and ANN algorithms showed the areas of occurrence of Fusarium wilt disease were in the range of 5.21-5.75 hm2, accounting for 36.3%-40.1% of the total planting area of bananas in the study area. The results also showed that the inclusion of the red-edge band resulted in an increase in the overall accuracy of 2.9%-3.0%. A simulation of the resolutions of satellite-based imagery (i.e., 0.5, 1, 2, and 5 m resolutions) showed that imagery with a spatial resolution higher than 2 m resulted in good identification accuracy of Fusarium wilt. The results of this study demonstrate that the RF classifier is well suited for the identification and mapping of banana Fusarium wilt disease from UAV-based remote sensing imagery. The results provide guidance for disease treatment and crop planting adjustments. Keywords: banana fusarium wilt, UAV-based multi-spectral remote sensing, support vector machine, artificial neural network, random forest DOI: 10.25165/j.ijabe. 20201303.5524 Citation: Ye H C, Huang W J, Huang S Y, Cui B, Dong Y Y, Guo A T, et al. Identification of banana fusarium wilt using supervised classification algorithms with UAV-based multi-spectral imagery. Int J Agric & Biol Eng, 2020; 13(3): 136–142.
INVESTIGATING THE PERFORMANCE OF RANDOM FOREST AND SUPPORT VECTOR REGRESSION FOR ESTIMATION OF CLOUD-FREE NDVI USING SENTINEL-1 SAR DATA

Abstract. The current study focuses on the estimation of cloud-free Normalized Difference Vegetation Index (NDVI) using the Synthetic Aperture Radar (SAR) observations obtained from Sentinel-1 (A and B) sensor. South-West Summer Monsoon over the Indian sub-continent lasts for four months (mid-June to mid-October). During this time, optical remote sensing observations are affected by dense cloud cover. Therefore, there is a need for methodology to estimate state of vegetation during the cloud cover. The crops considered in this study are Paddy (Rice) from Punjab and Haryana, whereas Cotton, Turmeric, and Banana from Andhra Pradesh, India. We have considered, observations of Sentinel-1 and Sentinel-2 sensors with the same overpass day and non-cloudy pixels for each crop. We used Google Earth Engine to extract surface reflectance for the Sentinel-2 and Ground Range Detected (GRD) backscatter for Sentinel-1. The Red and NIR bands of Sentinel 2 were used to estimate NDVI. Sentinel-1 based VV, and VH backscatter was used for estimation of Normalized Ratio Procedure between Bands (NRPB). Regression analysis was performed by using NDVI as an independent variable, and VV, VH, NRPB, and radar incidence angle as dependant variables. We evaluated the performance of Linear regression with tuned Support Vector Regression (SVR) as well as tuned Random Forest Regression (RFR) using the independent data. Results showed that the RFR produced the lowest RMSE for all the crops in the study. The average RMSE using the RFR was 0.08, 0.09, 0.11, and 0.10 for Rice, Cotton, Banana, and Turmeric, respectively. Similarly, we have obtained R2 values of 0.79, 0.76, 0.69, and 0.71 for the same crops using the RFR. A model with 80 trees produced the best results for Rice and Cotton, whereas the model with 90 trees produced the best results for Banana and Turmeric. Analysis with NDVI threshold of 0.25 showed improved R2 and RMSE. We found that for grown crop canopy, SAR based NDVI estimates are reasonably matching with the optical NDVI. A good agreement was observed between the actual and estimated NDVI using the tuned RFR model.
Robustness Analysis of Urban Road Networks from Topological and Operational Perspectives

This study comprehensively analyses the robustness of urban road networks through topological indices based on the complex network theory and operational indices based on traffic assignment theory: User Equilibrium (UE), System Optimum (SO), and Price of Anarchy (POA). Analysing topological indices may pin down the most important nodes for URNs from the perspective of connectivity, while more sophisticated operational indices are helpful to examine the importance of nodes for URNs by taking into account link capacity, travel demand, and drivers’ behaviour. The previous way is calculated in a static way, which reduces the computation times and increases the efficiency for quick assessment of the robustness of URNs, while the latter is in a dynamic way, namely, calculating is based on removal of individual nodes, although this way is more likely to capture realistic meanings but consumes huge amount of time. The efforts made in this study try to find the relationship between topological and operational indices so as to assist the assessment of robustness of URNs to local disruptions. Seven realistic urban road networks such as Sioux Falls and Anaheim are used as network examples, and results show that different indices reflect robustness characteristics of urban road networks from different ways, and rank correlations between any two indices are poor although small network such as Sioux Falls have better correlations than others.
Brain Extraction Algorithm for T1 of Human Head Scans

- In this paper, we extend a brain segmentation algorithm developed Resonance Images (MRI). The proposed schem connected component analysis. Usually an and an intensity threshold is found for the diffused image. Using the diffused image and threshold T is obtained for extraction of brain. In the proposed use the undiffused image. We used T1-W and The whole Brain Atlas (WBA). Experimental resul and gave satisfactory results on T1-W images.
Relationships between the Osteocranium and Weberian Apparatus in Two Indian Catfishes of the Genus Clarias (Siluridae)

Stanford Univ. Publ. , Univ. Ser. Biol. Sci. 3(2):77-243. AND C. H. EIGENMANN. 1885. Notes on skeletons of Etheostomatinae. Proc. U. S. Natl. Mus. 8(484):68-72. AND B. W. EVERMANN. 1896. The fishes of North and Middle America. Bull. U. S. Natl. Mus. 47, part 1 1240 p. LACEPEDE, BERNHARD. 1802 (Vol. 3), 1803 (Vol. 4). Histoire naturelle des poissons. Plassan 558 p. (Vol. 3), 728 p. (Vol. 4). MORGAN, G. D. 1936. A study of the vestigial air bladder in the darter (Catonotis [sic] flabellaris Rafinesque). J. Sci. Labs. Denison Univ. 31(4-6):143-58. NIKOLSKY, G. V. AND N. A. EVTUKHOV. 1940. The fishes of the middle and lower courses of the Ili River. Bull. Mosk. Obsch. Isp. Prir. , Biol. 49(5-6):57-70. (In Russian.) OKEN, LORENZ. 1816. Lehrbuch der Naturgeschichte. Theil 3, Zool. , Abth. 2, Fleischthiere. Jena 1270 p. . 1817. Cuvier's und Oken's zoologien naben einander gestellt. Isis, Encyclo. Zeitung 8(148):1179-85. RAFINESQUE, C. S. 1820. Ichthyologia Ohiensis. Reprinted in Richard E. Call, 1899, Burrows Brothers Co., Cleveland p. 40-162. tanford Univ. Publ. , Univ. Ser. Biol. Sci REGAN, C. T. 1913. The classification of the percoid fishes. Ann. & Mag. Nat. Hist. ser. 8 12:111-45.
Treatment options in Clostridium difficile infection

There is an increased interest in exploring antibacterial, biotherapy and immunological treatment options for Clostridium dif®cile infection. The impetus has occurred from increased antibiotic use, the rising incidence of C. dif®cile infection in the elderly and high rates of recurrence associated with metronidazole and vancomycin therapy. However, progress has been hampered by the varied aetiology of diarrhoea, spontaneous and unpredictable symptomatic resolution in some patients and inconsistencies in diagnosis. C. dif®cile may be treated with vancomycin or metronidazole as the overall response and recurrence rates are not statistically signi®cantly different. However, metronidazole is the antibiotic of ®rst choice as it reduces the selective pressure for glycopeptide-resistant enterococci, promoted by the widespread use of vancomycin. Management of symptomatic recurrences is problematic; switching between vancomycin and metronidazole is not recommended as DNA ®ngerprinting studies demonstrate that relapses are often re-infections with different strains. Placebo-controlled, double-blind trials on Saccharomyces boulardii given prophylactically to patients receiving antibiotics reported a reduced incidence in antibiotic-associated diarrhoea. Further double-blind, placebo-controlled trials demonstrated that treatment with S. boulardii signi®cantly reduced recurrent C. dif®cile diarrhoea. Case reports suggested that Lactobacillus GG reduced recurrent C. dif®cile infection and there is only one partially reported, prospective, randomized, placebo-controlled trial of Lactobacillus GG in adults with C. dif®cile infection. Prophylactic bovine immunoglobulin prevented diarrhoea in C. dif®cile-exposed hamsters and two patients with severe colitis unresponsive to antibiotics improved following intravenous immunoglobulin therapy. SYNSORB Cd1, a novel compound, is reported to reduce C. dif®cile diarrhoeal recurrence rates and is undergoing phase III study. # 2001 Lippincott Williams & Wilkins
Efficacy of Fluid Administration Followed by Lung Sonography in Hemodynamic Assessment in Acute Circulatory Failure in Critically Ill Patients

Background: Early recognition and appropriate treatment of shock have been shown to decrease mortality. Incorporation of bedside ultrasound in patients with undiﬀerentiated shock allows for rapid evaluation of reversible causes of shock and improves accurate diagnosis in undiﬀerentiated hypotension. The aim of the present study was to evaluate efficacy of fluid administration followed by lung sonography in hemodynamic assessment in acute circulatory failure in critically ill patients. Materials and Methods: This prospective cohort controlled randomized study was carried out on 50 Critically ill Patients who had acute circulatory failure in intensive care unit Tanta university hospital Critically ill patients of either sex aged 21-60 years when mean blood pressure was below 65 mmHg were included. Patients have been uniformly distributed in 2 categories, The patients assigned either to the Control Group (group I) or to the FALLS (fluid administration limited by lung sonography) protocol group (group II). Results: Comparison between two groups revealed that, the heart rate showed that heart rate is lower in group II in comparison to group I . Comparison between two groups revealed that, the mean arterial blood pressure changes showed that it is higher in group II in comparison to group I . Comparison between two groups revealed that, the Central venous pressure showed that no significant difference in the base line . Intensive care unit stay in group I ranged between 5 – 11 days while in group II ranged between 3 – 8 days . Survival analysis (Kaplan Mier curve), Mortality at 28 days found in group I mean 21.28 days with SE 1.898 and in group II mean 24 days with SE 1.64 with no significant difference in time but there was significant difference in number of mortalities as discussed before. Conclusion: We conclude from this study that bedside Lung Ultrasound has a good accuracy and superiority in assessment over other traditionally used methods for detecting early signs of pulmonary congestion and thus guides the fluid administration in shock management to decrease complications, mortality and intensive care stay.
Vitamin D Deficiency in Implant Dentistry: Link to Early Implant Failure and Biomaterial-Related Complications

Dental implants are generally considered a safe and highly predictable surgical procedure performed by many dental surgeons with the aim of replacing missing teeth. Yet to this day, a number of implants are lost every year for yet explained reasons. Dental implants remain one of the only transmucosal implant utilized in medicine; meaning they integrate directly into bone (a phenomenon called osseointegration) yet span into the oral cavity through transmucosal tissues. In this area, a number of bacteria co-exist with host living cells (primarily epithelial and immune cells) creating peri-implant pockets. Here an array of cytokines and highly active complex compounds are secreted and may reduce host defense/antibacterial properties. This book chapter discusses the importance and relevance of tissue homeostasis as it relates to oxidative stress. Furthermore, one of the most prominent vitamin deficiencies known to mankind, that of vitamin D, is discussed as a primary cause linked with early dental implant failure. Recommended doses and guidelines are provided with ongoing future research
Stabilized Column Generation Via the Dynamic Separation of Aggregated Rows

Column generation (CG) algorithms are well known to suffer from convergence issues due, mainly, to the degenerate structure of their master problem and the instability associated with the dual variables involved in the process. In the literature, several strategies have been proposed to overcome this issue. These techniques rely either on the modification of the standard CG algorithm or on some prior information about the set of dual optimal solutions. In this paper, we propose a new stabilization framework, which relies on the dynamic generation of aggregated rows from the CG master problem. To evaluate the performance of our method and its flexibility, we consider instances of three different problems, namely, vehicle routing with time windows (VRPTW), bin packing with conflicts (BPPC), and multiperson pose estimation (MPPEP). When solving the VRPTW, the proposed stabilized CG method yields significant improvements in terms of CPU time and number of iterations with respect to a standard CG algorithm. Huge reductions in CPU time are also achieved when solving the BPPC and the MPPEP. For the latter, our method has shown to be competitive when compared with a tailored method. Summary of Contribution: Column generation (CG) algorithms are among the most important and studied solution methods in operations research. CG algorithms are suitable to cope with large-scale problems arising from several real-life applications. The present paper proposes a generic stabilization framework to address two of the main issues found in a CG method: degeneracy in the master problem and massive instability of the dual variables. The newly devised method, called dynamic separation of aggregated rows (dyn-SAR), relies on an extended master problem that contains redundant constraints obtained by aggregating constraints from the original master problem formulation. This new formulation is solved in a column/row generation fashion. The efficacy of the proposed method is tested through an extensive experimental campaign, where we solve three different problems that differ considerably in terms of their constraints and objective function. Despite being a generic framework, dyn-SAR requires the embedded CG algorithm to be tailored to the application at hand.
ACCURACY ASSESSMENT OF DIGITAL SURFACE MODELS FROM UNMANNED AERIAL VEHICLES’ IMAGERY ON ARCHAEOLOGICAL SITES

With the developing technologies, the use of unmanned aerial vehicles’s (UAV) is increasing in all areas. Compared with the conventional photogrammetry and remote sensing sensors, UAVs are more convenient to collect data for small areas. In this study, the accuracy of UAV products was investigated in the archeological area of Eskisehir Şarhoyuk. In order to produce reference data for the orthophoto and DTM accuracy analysis, a digital map from the test area was produced using in-situ measurements. Also, for the comparison of the point cloud, a small test area was determined and reference point cloud data was collected with terrestrial laser scanner. The comparison of the results showed significant difference between the UAV images and images collected by conventional methods. Thus, while there was 1 m difference between the data without the use of control points, and the use of control points significantly improved the results.
Viability Analysis and Design of an Electronic System for Monitoring Population Dynamics in the City of Cúcuta

This document shows the results of a feasibility analysis and the design of an electronic system for monitoring population dynamics inthe city of Cúcuta. The feasibility analysis was carried out by investigating the position of the citizenry regarding the behavior of the population dynamics, its impact on the region and the preference for the use of technology as a solution to social problems. Likewise, the design of the electronic signal processing system was made by selecting the hardware and software tools by means of a prioritization matrix, comparing eleven factors of interest, which allowed to elaborate the algorithms of people detection based on the techniques of oriented gradient histogram and background subtraction with blobs extraction, later tested with the authors’ own images.
Comparison of membrane fouling and cleaning in one-pass reverse osmosis and two-pass nanofiltration approaches to seawater desalination

A recent innovation in seawater desalination is the use of multi-stage and multi-pass combinations of nanofiltration (NF) and reverse osmosis (RO) membranes. One example of this approach is the “Long Beach method,” in which seawater passes through two different types of NF membranes to produce potable water. After several years of pilot studies comparing the performance of two-pass NF and single-pass RO systems, a number of membrane elements were sacrificed for autopsy analyses. The selected membranes represent different stages of operation including (1) new, (2) fouled, and (3) cleaned membranes. Used NF and RO spiral wound elements were removed from the first and last positions of the demonstration plant. Although operating data suggested no outward signs of membrane fouling – inorganic, organic, and bacterial accumulation were identified on all membranes. First pass RO and NF membranes contained similar amounts of deposited solids, while significantly fewer solids were found on second pass NF membranes. Viable, culturable marine bacteria were observed on all fouled and cleaned membranes, indicating that bacterial colonization of seawater NF/RO membranes was not (a) detected by plant performance monitoring devices, (b) prevented by microfiltration and chlorination, or (c) removed by chemical cleaning. Chemical cleaning recovered the measurable performance of both first pass RO and second pass NF membranes, but was relatively ineffective at removing deposited solids from first-pass NF membranes. Therefore, chemical-cleaning methods may need to be tailored and optimized more specifically for NF membranes used in seawater desalination.
Performance Evaluation of Biometric Cryptosystem Using Fuzzy Vault

: Biometric Cryptosystem is a security model which cannot be easily cracked as compared to traditional methods like password, ID card etc to get information. Information regarding a particular person in the database makes it vulnerable to template database attack. Fuzzy vault is a popular biometric cryptosystem technique which basically secure biometric template. In this technique the biometric features are used to lock and unlock the secret key, where coefficient of a polynomial equation is encoded. Existing method for chaff point generation is insufficient for real time implementation of biometric cryptosystem as would be required in today’s information security system. Performance of system can be enhanced by adding more number of chaff points to the vault. These paper propose and aim to improvise the performance and security of fingerprint fuzzy vault scheme by using fast chaff point generation algorithm.
Annual Rainfall Model by Using Machine Learning Techniques for Agricultural Adjustment

The change of weather conditions is considered as the major problem which is delicate for populations particularly the developing countries such as Thailand, e.g., the area in the southern region of Thailand, a case study of Andaman seaside which is the area most affected by the change of weather conditions compared with others. This research purposes to develop the model for rainfall forecasting for agricultural adjustment in the areas located at Andaman seaside using Machine Learning Technique to monitor the impact of the change of weather conditions such as the volume of rainfall in each year affecting to agricultural sector by studying the 30-year regressive data in order to estimate the coefficient of the model. The analysis results indicated that the rainfall volume of the areas located at the Andaman seaside of southern region tended to decrease which was resulted from the change of weather conditions where the model was able to provide the awareness of the impact caused by the change of weather to the agriculturists to prepare the proper supporting
Natural products and their derived compounds inhibitors of the enzyme acetylcholinesterase

Received Date: May 01, 2020 / Accepted Date: May 11, 2020 / Published Date: May 13, 2020 Abstract Alzheimer’s disease (AD) is a progressive, neurodegenerative pathology that primarily affects the elderly population, and is estimated to account for 50-60% of dementia cases in persons over 65 years of age. The main characteristics connected with AD implicate the dysfunction of cognitive role, mainly loss of memory. While, the main features linked with AD at later stages include deficits of language, depression and problems associated with behavior. One of the most important approaches for medication of this disease is to improve level of the acetylcholine in the brain tissues using inhibitors of acetylcholinesterase (AChE). The present work reviews the literature on natural products from plants and plant-derived compounds inhibitors of enzyme acetylcholinesterase.
FACTORS AFFECTING PROFITS RELATING TO PURCHASE AND SALES: A STUDY ON TITAS GAS TRANSMISSION & DISTRIBUTION COMPANY LIMITED

JEL Classification: L-95 ABSTRACT The present study is an attempt to find out the factors affecting profits relating to purchase and sales of Titas Gas Transmission & Distribution Company Limited. The objectives of the study are to overview the affecting factors on profits, to determine the important factors that affect on profit relating to purchase and sales and to provide some suggestions and recommendations to enhance the profits. Correlation and regression have been applied to analyze the data. It is estimated that commercial, fertilizer and CNG are the most important factors to drive the profit both for the cases of purchase and sales. These three factors collectively explained the total variance of gross profit by 96.6 percent and 96.8 percent for the situation of purchase and sales respectively. The suggestions and recommendations are given to emphasize the purchase and sales on the identified factors to enhance the benefits of the company.