Search results for: plant detection

Authors: Prasenjit Singha, Ajay Kumar Shukla

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To produce high-quality steel in larger volumes, dynamic control of composition and temperature throughout the process is essential. In this paper, we developed a mass transfer model based on thermodynamics to simulate the ladle metallurgy steel-making process using FactSage and its macro facility. The overall heat and mass transfer processes consist of one equilibrium chamber, two non-equilibrium chambers, and one adiabatic reactor. The flow of material, as well as heat transfer, occurs across four interconnected unit chambers and a reactor. We used the macro programming facility of FactSage™ software to understand the thermochemical model of the secondary steel making process. In our model, we varied the oxygen content during the process and studied their effect on the composition of the final hot metal and slag. The model has been validated with respect to the plant data for the steel composition, which is similar to the ladle metallurgy steel-making process in the industry. The resulting composition profile serves as a guiding tool to optimize the process of ladle metallurgy in steel-making industries.

Keywords: desulphurization, degassing, factsage, reactor

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Emily Arangote

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This paper defined the association between the indigenous knowledge, cultural practices and the ecosystem its implication to the environmental education to the farmers. Farmers recognize the need for sustainability of the ecosystem they inhabit. The cultural practices of farmers on use of indigenous pest control, use of insect-repellant plants, soil management practices that suppress diseases and harmful pests and conserve soil moisture are deemed to be ecologically-friendly. Indigenous plant materials that were more drought- and pest-resistant were grown. Crop rotation was implemented with various crop seeds to increase their disease resistance. Multi-cropping, planting of perennial crops, categorization of soil and planting of appropriate crops, planting of appropriate and leguminous crops, alloting land as watershed, and preserving traditional palay seed varieties were found to be beneficial in preserving the environment. The study also found that indigenous knowledge about crops are still relevant and useful to the current generation. This ensured the sustainability of our environment and incumbent on policy makers and educators to support and preserve for generations yet to come.

Keywords: cultural practices, ecosystem, environmental education, indigenous knowledge

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Authors: F. Villaret, I. Jacot, Y. Shen, Z. Kong, T. XU, Y. Wang, D. Lu

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Wire Arc Additive Manufacturing (WAAM) allows the rapid production of large, homogeneous parts with complex geometry. However, in the nuclear field, parts can reach dimensions of ten to a hundred tons. In this case, the usual WAAM TIG or CMT processes do not have sufficient deposition rates to consider the manufacture of parts of such dimensions within a reasonable time. The submerged arc welding process (SAW, Submerged Arc Welding) allows much higher deposition rates. Although there are very few references to this process for additive manufacturing in the literature, it has been used for a long time for the welding and coating of nuclear power plant vessels, so this process is well-known and mastered as a welding process. This study proposes to evaluate the SAW process as an additive manufacturing technique by taking as an example a low-alloy steel of type 16MND5. In the first step, a parametric study allowed the evaluation of the effect of the different parameters and the deposition rate on the geometry of the beads and their microstructure. Larger parts were also fabricated and characterized by metallography and mechanical tests (tensile, impact, toughness). The effect of different heat treatments on the microstructure is also studied.

Keywords: WAAM, low alloy steel, submerged arc, caracterization

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Authors: E. Kam, G. Karahan, H. Aslıyuksek, A. Bozkurt

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This study aims to determine the natural radioactivity levels in some foodstuffs produced in Turkey. For this purpose, 48 different foods samples were collected from different land parcels throughout the country. All samples were analyzed to designate both gross alpha and gross beta radioactivities and the radionuclides’ concentrations. The gross alpha radioactivities were measured as below 1 Bq kg^-1 in most of the samples, some of them being due to the detection limit of the counting system. The gross beta radioactivity levels ranged from 1.8 Bq kg^-1 to 453 Bq kg^-1, larger levels being observed in leguminous seeds while the highest level being in haricot bean. The concentrations of natural radionuclides in the foodstuffs were investigated by the method of gamma spectroscopy. High levels of ⁴⁰K were measured in all the samples, the highest activities being again in leguminous seeds. Low concentrations of ²³⁸U and ²²⁶Ra were found in some of the samples, which are comparable to the reported results in the literature. Based on the activity concentrations obtained in this study, average annual effective dose equivalents for the radionuclides ²²⁶Ra, ²³⁸U, and ⁴⁰K were calculated as 77.416 µSv y^-1, 0.978 µSv y^-1, and 140.55 µSv y^-1, respectively.

Keywords: foods, radioactivity, gross alpha, gross beta, annual equivalent dose, Turkey

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Authors: Walid Mousa, Mohamed Nayel, Ahmed Zaghawa, Akram Salama, Ahmed El-Sify, Hesham Rashad, Dina El-Shafey

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Mycoplasmosis in small ruminants constitutes a serious contagious problem in smallholders causing severe economic losses worldwide. This study was conducted to determine the clinical, Minimum Inhibitory Concentration (MIC) and molecular characterization of Mycoplasma species associated in sheep breeding herds in Menoufiya governorate, Egypt. Out of the examination of 400 sheep, 104 (26%) showed respiratory manifestations, nasal discharges, cough and conjunctivitis with systemic body reaction. Meanwhile, out of these examined sheep, only 56 (14%) were positive for mycoplasma isolation onto PPLO(Pleuropneumonia-like organisms) specific medium. The MIC for evaluating the efficacy of sensitivity of Mycoplasma isolates against different antibiotics groups revealed that both the Linospectin and Tylosin with 2ug, 0.25ug/ml concentration were the most effective antibiotics for Mycoplasma isolates. The application of PCR was the rapid, specific and sensitive molecular approach for detection of M. ovipneumoniae, and M. arginine at 390 and 326 bp, respectively, in all tested isolates. In conclusion, the diagnosis of Mycoplsamosis in sheep is important to achieve effective control measures and minimizing the disease dissemination among sheep herds.

Keywords: MIC, mycoplasmosis, PCR, sheep

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Wei Ji

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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.

Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis

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Authors: Li Minghui, Min Shaorong, Zhang Jun

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This paper aims for studying the operational efficiency of surface warship’s motorized evasion to acoustic homing torpedo. It orderly developed trajectory model, self-guide detection model, vessel evasion model, as well as anti-torpedo error model in three-dimensional space to make up for the deficiency of precious researches analyzing two-dimensionally confrontational models. Then, making use of the Monte Carlo method, it carried out the simulation for the confrontation process of evasion in the environment of MATLAB. At last, it quantitatively analyzed the main factors which determine vessel’s survival probability. The results show that evasion relative bearing and speed will affect vessel’s survival probability significantly. Thus, choosing appropriate evasion relative bearing and speed according to alarming range and alarming relative bearing for torpedo, improving alarming range and positioning accuracy and reducing the response time against torpedo will improve the vessel’s survival probability significantly.

Keywords: acoustic homing torpedo, vessel evasion, monte carlo method, torpedo defense, vessel's survival probability

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Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

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Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

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Authors: R. Marandi, H. Shahrir, T. Nejad Ghaffar Borhani, M. Kamaruddin

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In the present study, a steady state population balance model was developed to predict the polymer particle size distribution (PSD) in ethylene gas phase fluidized bed olefin polymerization reactors. The multilayer polymeric flow model (MPFM) was used to calculate the growth rate of a single polymer particle under intra-heat and mass transfer resistance. The industrial plant data were used to calculate the growth rate of polymer particle and the polymer PSD. Numerical simulations carried out to describe the influence of effective monomer diffusion coefficient, polymerization rate and initial catalyst size on the catalyst particle growth and final polymer PSD. The results present that the intra-heat and mass limitation is important for the ethylene polymerization, the growth rate of particle and the polymer PSD in the fluidized bed reactor. The effect of the agglomeration on the PSD is also considered. The result presents that the polymer particle size distribution becomes broader as the agglomeration exits.

Keywords: population balance, olefin polymerization, fluidized bed reactor, particle size distribution, agglomeration

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Rahul Agarwal, Ashutosh Singh

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Colorectal cancer (CRC) also refers as bowel cancer or colon cancer. It involves the development of abnormal growth of cells in colon or rectum part of the body. This work leads to the development of a miRNA database in colorectal cancer. We named this database- miCoRe. This database comprises of all validated colon-rectal cancer miRNAs information from various published literature with an effectual knowledge based information retrieval system. miRNAs have been collected from various published literature reports. MySQL is used for main-framework of miCoRe while the front-end was developed in PHP script. The aim of developing miCoRe is to create a comprehensive central repository of colorectal carcinoma miRNAs with all germane information of miRNAs and their target genes. The current version of miCoRe consists of 238 miRNAs which are known to be implicated in malignancy of CRC. Alongside with miRNA information, miCoRe also contains the information related to the target genes of these miRNA. miCoRe furnishes the information about the mechanism of incidence and progression of the disease, which would further help the researchers to look for colorectal specific miRNAs therapies and CRC specific targeted drug designing. Moreover, it will also help in development of biomarkers for the better and early detection of CRC and will help in better clinical management of the disease.

Keywords: colorectal cancer, database, miCoRe, miRNAs

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Authors: Giti Sabri, Sohrab Imani, Ali Ahadiyat, Aref Maroof, Yahya Ostadi

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Recently, there has been a growing interest in research concerning the possible use of plant extracts as alternatives to synthetic insecticides. In this research, the insecticidal effects of Carum copticum essential oils against rice weevil adults were investigated in laboratory condition. Essential oils was extracted through distillation with water using Clevenger apparatus. Tests of randomized complete block included six concentrations and three replications for essential oils (fumigant toxicity) along with control treatment in condition of 27±1ºC degrees Celsius temperature, relative humidity of 65 ± 5 percent and darkness. LC50 values were calculated by SPSS.21.0 software which presented the value of LC50 of Carum copticum essential oils after 48 hurs, 187.35± 0.40 µl/l air on rice weevil adults. Results showed that increasing the concentration of essential oils increased the mortality rate cases. The results also showed that essential oils of Carum copticum are effective biological sources which can effectively protect stored grain from infestation by the rice weevil; although for application of these combinations further research may be needed.

Keywords: insecticidial effects, essential oil, Carum copticum, Sitophilus oryzae

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Authors: Wadzani Dauda Palnam, Alao S. Emmanuel Laykay, Afiniki Bawa Zarafi, Olufunmilola Alabi, Dora N. Iortsuun

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Onion production is affected by several diseases including fusariosis. Study was conducted to investigate the histopathological features of different onion tissues infected with Fusarium equiseti by inoculation with soil drench, root dip and mycelia paste methods. This was carried out by fixation, dehydration, clearing, wax embedding, sectioning, staining and mounting of leaf and root sections for microscopical examination at 400x. Once infection occurred in the roots, the pathogen moved through the vascular system to colonize the whole plant. At first, it grew in the intercellular spaces of the root cortex but soon invaded the cells, followed by colonization of the cells by its hyphae and microconidia. At later stages of infection, the cortex tissue became completely disorganized and decomposed as the pathogen advance to the shoot system via the vessel elements; this may be responsible for the early wilting symptom of infected plants arising from the severe water stress due to blockage of the xylem tissues.

Keywords: onion, histopathology, infection, fusaria, inoculation

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Muthukumarasamy Govindarajan

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Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

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Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

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Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

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Authors: A. Ghadbane, M. N. Bouaziz, S. Hanini, B. Baggoura, M. Abbaci

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The spacer grids are used to fix the rods bundle in a nuclear reactor core also act as turbulence-enhancing devices to improve the heat transfer from the hot surfaces of the rods to the surrounding coolant stream. Therefore, the investigation of thermal-hydraulic characteristics inside the rod bundles is important for optima design and safety operation of a nuclear reactor power plant. This contribution presents a feasibility study to use the ribbed spacer grids as mixing devices. The present study evaluates the effects of different ribbed spacer grids configurations on flow pattern and heat transfer in the downstream of the mixing devices in a 2 x 2 rod bundle array. This is done by obtaining velocity and pressure fields, turbulent intensity and the heat transfer coefficient using a three-dimensional CFD analysis. Numerical calculations are performed by employing K-ε turbulent model. The computational results obtained are promising and the comparison with standard spacer grids shows a clear difference which required the experimental approach to validate.

Keywords: PWR fuel assembly, spacer grid, mixing vane, swirl flow, turbulent heat transfer, CFD

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Authors: Mamta M. Barapatre, V. N. Sahare

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Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

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Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

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We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

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Authors: Antonella Di Sotto, Cinzia Ingallina, Caterina Fraschetti, Simone Circi, Marcello Locatelli, Simone Carradori, Gabriela Mazzanti, Luisa Mannina, Silvia Di Giacomo

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Cannabis sativa L. is one of the oldest cultivated plant species known not only for its voluptuous use but also for the wide application in food, textile, and therapeutic industries. Recently, the progress of biotechnologies applied to medicinal plants has allowed to produce different hemp varieties with low content of psychotropic phytoconstituents (tetrahydrocannabinol < 0.2% w/v), thus leading to a renewed industrial and therapeutic interest for this plant. In this context, in order to discover new potential remedies of pharmaceutical and/or nutraceutical interest, the chemopreventive properties of different organic and hydroalcoholic extracts, obtained from the inflorescences of C. sativa L. var. USO31, collected in June and September harvesting, were assessed. Particularly, the antimutagenic activity towards the oxidative DNA-damage induced by tert-butyl hydroperoxide (t-BOOH) was evaluated, and the DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2'-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid) radical scavenging power of the samples were assessed as possible mechanisms of antimutagenicity. Furthermore, the ability of the extracts to inhibit the glucose-6-phosphate dehydrogenase (G6PD), whose overexpression has been found to play a critical role in neoplastic transformation and tumor progression, has been studied as a possible chemopreventive strategy. A careful phytochemical characterization of the extracts for phenolic and terpenoid composition has been obtained by high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS) methods. Under our experimental condition, all the extracts were found able to interfere with the tBOOH-induced mutagenicity in WP2uvrAR strain, although with different potency and effectiveness. The organic extracts from both the harvesting periods were found to be the main effective antimutagenic samples, reaching about a 55% inhibition of the tBOOH-mutagenicity at the highest concentration tested (250 μg/ml). All the extracts exhibited radical scavenger activity against DPPH and ABTS radicals, with a higher potency of the hydroalcoholic samples. The organic extracts were also able to inhibit the G6PD enzyme, being the samples from September harvesting the highly potent (about 50% inhibition respect to the vehicle). At the phytochemical analysis, all the extracts resulted to contain both polar and apolar phenolic compounds. The HPLC analysis revealed the presence of catechin and rutin as the major constituents of the hydroalcoholic extracts, with lower levels of quercetin and ferulic acid. The monoterpene carvacrol was found to be an ubiquitarian constituent. At GC-MS analysis, different terpenoids, among which caryophyllene sesquiterpenes, were identified. This evidence suggests a possible role of both polyphenols and terpenoids in the chemopreventive properties of the extracts from the inflorescences of C. sativa var. USO31. According to the literature, carvacrol and caryophyllene sesquiterpenes can contribute to the strong antimutagenicity although the role of all the hemp phytocomplex cannot be excluded. In conclusion, present results highlight a possible interest for the inflorescences of C. sativa var. USO31 as source of bioactive molecules and stimulate further studies in order to characterize its possible application for nutraceutical and pharmaceutical purposes.

Keywords: antimutagenicity, glucose-6-phosphate dehydrogenase, hemp inflorescences, nutraceuticals, sesquiterpenes

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Authors: Md. Mazharul Anwar, Md. Samim Hossain Molla, Md. Akkas Ali, Mian Sayeed Hassan

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After 68 years, the agreement between Bangladesh and India was ratified on 6 June 2015 and Bangladesh received 111 Indian enclaves. Millions of farm household lived in these previous enclaves, being detached from the mainland of the country, they were socially, economically and educationally deprived people in the world. This study was undertaken to compare of the Stochastic Frontier Analysis (SFA) and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models, based on a sample of 300 farms from the three largest enclaves of Bangladesh in 2017. However, the aim of the study was not only to compare estimates of technical efficiency obtained from the two approaches, but also to examine the determinants of inefficiency. The results from both the approaches indicated that there is a potential for increasing farm production through efficiency improvement and that farmers' age, educational level, new technology dissemination and training on crop production technology have a significant effect on efficiency. The detection and measurement of technical inefficiency and its determinants can be used as a basis of policy recommendations.

Keywords: DEA approach, previous enclaves, SFA approach, technical inefficiency

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Authors: Bangoura Issa, Ji-Young Kang, M. T. H. Chowdhury, Ji-Eun Lee, Yong-Ki Hong

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Investigation was carried out for the production of value-added abalone Haliotis discus hannai containing bioactive phlorotannin by feeding phlorotannin-rich seaweed Eisenia bicyclis 2 weeks prior to harvesting. Accumulation of phlorotannins was proceded by feeding with E. bicyclis after 4 days of starvation. HPLC purification afforded two major phlorotannins. Mass spectrometry and 1H-nuclear magnetic resonance analysis clarified their structures to be as 7-phloroeckol and eckol. Throughout the feeding period of 20 days, 7-phloroeckolol was accumulated in the muscle (foot muscle tissue) up to 0.18±0.12 mg g-1 dry weight of tissue after 12 days. Eckol reached 0.21±0.03 mg g-1 dry weight of tissue after 18 days. By feeding Laminaria japonica as reference, abalone showed no detection of phlorotannins in the muscle tissue. Seaweed consumption and growth rate of abalone revealed almost similar when feed with E. bicyclis or L. japonicain 20 days. Phlorotannins reduction to half-maximal accumulation values took 1.0 day and 2.7 days for 7-phloroeckol and eckol respectively, after replacing the feed to L. japonica.

Keywords: abalone, accumulation, eisenia bicyclis, phlorotannins

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Zate Zewdneh Zana

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Coffea arabica (Arabica coffee), a cornerstone of the global beverage industry, necessitates rigorous genetic conservation due to its economic significance and genetic complexity. In this study, we performed whole-genome resequencing of wild species collected from its birthplace, Ethiopia. Advanced Illumina sequencing technology facilitated the mapping of a high percentage of clean reads to the C. arabica reference genome, revealing a substantial number of genetic variants, predominantly SNPs. Our comprehensive analysis not only uncovered a notable distribution of genomic variants across the coffee genome but also identified distinct genetic groups through phylogenetic and population structure analyses. This genomic study provides invaluable insights into the genetic diversity of C. arabica, highlighting the potential of identified SNPs and InDels in enhancing our understanding of key agronomic traits. The findings contribute significantly to genetic studies and support strategic breeding and conservation efforts essential for sustaining the global coffee industry.

Keywords: population genetics, wild species, evolutionary study, coffee plant

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Authors: Zakia Fatima, Liu Lu, Donghao Li

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The analysis of biological fluid metabolites holds significant importance in various areas, such as medical research, food science, and public health. Investigating the levels and distribution of nutrients and their metabolites in biological samples allows researchers and healthcare professionals to determine nutritional status, find hypovitaminosis or hypervitaminosis, and monitor the effectiveness of interventions such as dietary supplementation. Moreover, analysis of nutrient metabolites provides insight into their metabolism, bioavailability, and physiological processes, aiding in the clarification of their health roles. Hence, the exploration of a distinct, efficient, eco-friendly, and simpler methodology is of great importance to evaluate the metabolic content of complex biological samples. In this work, a green and rapid analytical method based on an automated online two-dimensional microscale carbon fiber/activated carbon fiber fractionation system and time-of-flight mass spectrometry (2DμCFs-TOF-MS) was used to evaluate metabolites of urine samples after oral administration of food supplements. The automated 2DμCFs instrument consisted of a microcolumn system with bare carbon fibers and modified carbon fiber coatings. Carbon fibers and modified carbon fibers exhibit different surface characteristics and retain different compounds accordingly. Three kinds of mobile-phase solvents were used to elute the compounds of varied chemical heterogeneities. The 2DμCFs separation system has the ability to effectively separate different compounds based on their polarity and solubility characteristics. No complicated sample preparation method was used prior to analysis, which makes the strategy more eco-friendly, practical, and faster than traditional analysis methods. For optimum analysis results, mobile phase composition, flow rate, and sample diluent were optimized. Water-soluble vitamins, fat-soluble vitamins, and amino acids, as well as 22 vitamin metabolites and 11 vitamin metabolic pathway-related metabolites, were found in urine samples. All water-soluble vitamins except vitamin B12 and vitamin B9 were detected in urine samples. However, no fat-soluble vitamin was detected, and only one metabolite of Vitamin A was found. The comparison with a blank urine sample showed a considerable difference in metabolite content. For example, vitamin metabolites and three related metabolites were not detected in blank urine. The complete single-run screening was carried out in 5.5 minutes with the minimum consumption of toxic organic solvent (0.5 ml). The analytical method was evaluated in terms of greenness, with an analytical greenness (AGREE) score of 0.72. The method’s practicality has been investigated using the Blue Applicability Grade Index (BAGI) tool, obtaining a score of 77. The findings in this work illustrated that the 2DµCFs-TOF-MS approach could emerge as a fast, sustainable, practical, high-throughput, and promising analytical tool for screening and accurate detection of various metabolites, pharmaceuticals, and ingredients in dietary supplements as well as biological fluids.

Keywords: metabolite analysis, sustainability, carbon fibers, urine.

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Authors: Spoorthi Sripad

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Rapid advancements in LiDAR (Light Detection and Ranging) technology, coupled with the synergy of remote sensing, have revolutionized Earth observation methodologies. This paper delves into the transformative impact of integrated LiDAR and remote sensing systems. Focusing on miniaturization, cost reduction, and improved resolution, the study explores the evolving landscape of terrestrial and aquatic environmental monitoring. The integration of multi-wavelength and dual-mode LiDAR systems, alongside collaborative efforts with other remote sensing technologies, presents a comprehensive approach. The paper highlights the pivotal role of LiDAR in environmental assessment, urban planning, and infrastructure development. As the amalgamation of LiDAR and remote sensing reshapes Earth observation, this research anticipates a paradigm shift in our understanding of dynamic planetary processes.

Keywords: LiDAR, remote sensing, earth observation, advancements, integration, environmental monitoring, multi-wavelength, dual-mode, technology, urban planning, infrastructure, resolution, miniaturization

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Authors: Geeta Sharma, Suma Chandra

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Sugarcane is one of the major commercial crop playing roles in agriculture and industrial economy of India. Globally sugarcane is affected by approximately 240 diseases caused by various plant pathogenic organisms. Among them, red rot disease caused by the fungus Colletotrichum falcatum, is one of the most important diseases. In the present investigation, one fungal bioagent of Trichoderma harzianum, Pant Bioagent 1 and one bacterial bioagent Pseudomonas fluorescence, Pant Bioagent 2 (PBAT 1 and PBAT 2, respectively) were tested by dual culture method against the pathogen under laboratory conditions. The effectiveness of biocontrol agents was observed against four isolates of C. falcatum. In the case of PBAT1 maximum percent inhibition of pathogen was recorded in isolated Cf 0238 (61.05%), followed by Cf 09 (60.62%) whereas, minimum percent inhibition was recorded in Cf 3220 (48.55%) and in case of PBAT2 maximum mycelial growth inhibition percent was recorded in Cf 767 (50.50%) followed by Cf 088230(48.83%), whereas minimum percent inhibition was recorded in Cf 08 (40.16%) followed by Cf 0238 (41.83%). The present study showed that these biocontrol agents have the potential of controlling the pathogen and can further be used for the management of red rot disease in field.

Keywords: biocontrol agents, Colletotrichum falcatum, isolates, sugarcane

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