Search results for: similarity search

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

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

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

Procedia PDF Downloads 298

Authors: Sena Park

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Background: The concurrent presentation with colorectal cancer in the inguinal hernia has been extremely rare. Due to its rarity, its presentation may lead to diagnostic and therapeutic dilemmas. We aim to review all the reported cases on colorectal cancer incarcerated in the inguinal hernia in the last 20 years, and discuss the operative approaches. Methods: We identified all case reports on colorectal cancer within inguinal hernia using PUBMED (2002-2022) and MEDLINE (2002-2022). The search strategy included the following keywords: colorectal cancer (title/abstract) AND inguinal hernia (title/abstract) OR incarceration (title/abstract). The search did not include letters, book chapters, systemic reviews, meta-analysis and editorials. Results: In the last 20 years, a total of 19 cases on colorectal cancer within the inguinal hernia were identified. The age of the patients ranged between 48 and 89. Majority of the patients were male (95%). Most commonly involved part of the large intestine was sigmoid colon (79%). Of all the cases, 79 percent of patients received open procedure and 21 percent had laparoscopic procedure. Discussion: Inguinal hernias are common with an incidence of approximately 1.7 percent. Colorectal cancer is the one of the leading causes of cancer-related mortality worldwide. However, their concurrent presentation has been extremely rare. In the last 20 years, 19 cases on concurrent presentation of colorectal cancer and inguinal hernia have been reported. Most patients who had open procedures had two incisions of groin incision and a midline laparotomy. There were 4 cases where the oncological resection was performed laparoscopically. The advantages of laparoscopic resection include reduced blood lost, reduced post-operative pain, reduced length of hospital stay and similar number of lymph nodes taken. From the review of the cases in the last 20 years, both open and laparoscopic approaches seemed to be safe and achieve adequate oncological resections. Conclusion: This is a brief overview of reported cases of colorectal cancer presenting with inguinal hernia concurrently. Due to its rarity, there are no current guidelines on operative approach in clinical practice. The experience in the last 20 years supports both open and laparoscopic approach.

Keywords: colorectal cancer, inguinal hernia, incarceration, operative approach

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Authors: Masood Beheshtirad

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Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed.

Keywords: landslide, mapping, multiple model, regression

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Authors: Fátima Gonçalves, Joaquim Brigas, Jorge Gonçalves

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As a way of managing the increasing volume and complexity of information that circulates in the present time, graphical representations are increasingly used, which add meaning to the information presented in communication media, through an efficient communication design. The visual culture itself, driven by technological evolution, has been redefining the forms of communication, so that contemporary visual communication represents a major impact on society. This article presents the results and respective comparative analysis of four publications in the Iberian press, focusing on the formal aspects of newspapers and the space they dedicate to the various communication elements. Two Portuguese newspapers and two Spanish newspapers were selected for this purpose. The findings indicated that the newspapers show a similarity in the use of graphic solutions, which corroborate a visual trend in communication design. The results also reveal that Spanish newspapers are more meticulous with graphic consistency. This study intended to contribute to improving knowledge of the Iberian generalist press.

Keywords: communication design, graphic resources, Iberian press, visual journalism

Procedia PDF Downloads 237

Authors: Juntip Kanjanasilp, Ratree Sawangjit, Kanokporn Meelap, Kwanchanok Kruthakool

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Depression is a common mental health disorder. Antidepressants are effective pharmacological treatments, but most patients have low medication adherence. This study aims to systematic review and meta-analysis what method increase the antidepressants adherence efficiently and improve clinical outcome. Systematic review of articles of randomized controlled trials obtained by a computerized literature search of The Cochrane, Library, Pubmed, Embase, PsycINFO, CINAHL, Education search, Web of Science and ThaiLIS (28 December 2017). Twenty-three studies were included and assessed the quality of research by ROB 2.0. The results reported that printing media improved in number of people who had medication adherence statistical significantly (p= 0.018), but education, phone call, and program utilization were no different (p=0.172, p=0.127, p=0.659). There was no significant difference in pharmacist’s group, health care team’s group and physician’s group (p=0.329, p=0.070, p=0.040). Times of intervention at 1 month and 6 months improved medication adherence significantly (p= 0.0001, p=0.013). There was significantly improved adherence in single intervention (p=0.027) but no different in multiple interventions (p=0.154). When we analyzed medication adherence with the mean score, no improved adherence was found, not relevant with who gives the intervention and times to intervention. However, the multiple interventions group was statistically significant improved medication adherence (p=0.040). Phone call and the physician’s group were statistically significant improved clinical outcomes in number of improved patients (0.025 and 0.020, respectively). But in the pharmacist’s group and physician’s group were not found difference in the mean score of clinical outcomes (p=0.993, p=0.120, respectively). Times to intervention and number of intervention were not significant difference than usual care. The overall intervention can increase antidepressant adherence, especially the printing media, and the appropriate timing of the intervention is at least 6 months. For effective treatment, the provider should have experience and expert in caring for patients with depressive disorders, such as a psychiatrist. Medical personnel should have knowledge in caring for these patients also.

Keywords: depression, medication adherence, clinical outcomes, systematic review, meta-analysis

Procedia PDF Downloads 117

Authors: Yohannes Yirga, Daniel Tesfay

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The convective heat and mass transfer in nanofluid flow through a porous media due to a permeable stretching sheet with magnetic field, viscous dissipation, and chemical reaction and Soret effects are numerically investigated. Two types of nanofluids, namely Cu-water and Ag-water were studied. The governing boundary layer equations are formulated and reduced to a set of ordinary differential equations using similarity transformations and then solved numerically using the Keller box method. Numerical results are obtained for the skin friction coefficient, Nusselt number and Sherwood number as well as for the velocity, temperature and concentration profiles for selected values of the governing parameters. Excellent validation of the present numerical results has been achieved with the earlier linearly stretching sheet problems in the literature.

Keywords: heat and mass transfer, magnetohydrodynamics, nanofluid, fluid dynamics

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Authors: Renu Pattanshetty

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The aim of this narrative review is to highlight the impact of menopause on osteoporosis and weight gain. The review also aims to summarize physiotherapeutic strategies to combat the same.A thorough literature search was conducted using electronic databases like MEDline, PUBmed, Highwire Press, PUBmed Central for English language studies that included search terms like menopause, osteoporosis, obesity, weight gain, exercises, physical activity, physiotherapy strategies from the year 2000 till date. Out of 157 studies that included metanalyses, critical reviews and randomized clinical trials, a total of 84 were selected that met the inclusion criteria. Prevalence of obesity is increasing world - wide and is reaching epidemic proportions even in the menopausal women. Prevalence of abdominal obesity is almost double than that general obesity with rates in the US with 65.5% in women ages 40-59 years and 73.8 in women aged 60 years or more. Physical activities and exercises play a vital role in prevention and treatment of osteoporosis and weight gain related to menopause that aim to boost the general well-being and any symptoms brought about by natural body changes. Endurance exercises lasting about 30 minutes /day for 5 days/ week has shown to decrease weight and prevent weight gain. In addition, strength training with at least 8 exercises of 8-12 repetitions working for whole body and for large muscle groups has shown to result positive outcomes. Hot flashes can be combatted through yogic breathing and relaxation exercises. Prevention of fall strategies and resistance training are key to treat diagnosed cases of osteoporosis related to menopause. One to three sets with five to eight repetitions of four to six weight bearing exercises have shown positive results. Menopause marks an important time for women to evaluate their risk of obesity and osteoporosis. It is known fact that bone benefit from exercises are lost when training is stopped, hence, practicing bone smart habits and strict adherence to recommended physical activity programs are recommended which are enjoyable, safe and effective.

Keywords: menopause, osteoporosis, obesity, weight gain, exercises, physical activity, physiotherapy strategies

Procedia PDF Downloads 286

Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Rasaq A. Kareem, Sulyman O. Salawu

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The study of Soret and Dufour effect on variable viscosity and thermal conductivity of an inclined magnetic field with dissipation in non-Darcy porous medium over a continuously stretching sheet for power-law variation in the sheet temperature and concentration are investigated. The viscosity of the fluid flow and thermal conductivity are considered to vary as a function of temperature. The local similarity solutions for different values of the physical parameters are presented for velocity, temperature and concentration. The result shows that variational increase in the values of Soret and Dufour parameters increase the temperature and concentration distribution. Finally, the effects of skin friction, Nusselt and Sherwood numbers which are of physical and engineering interest are considered and discussed.

Keywords: Dufour, non-Darcy Flow, Soret, thermal conductivity, variable viscosity

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Authors: Hendri Purwadi, Christine McCloud

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Triage is a complex decision-making process that aims to categorize a victim’s level of acuity and the need for medical assistance. Two common triage systems have been widely used in Mass Casualty Incidents (MCIs) and disaster situation are START (Simple triage algorithm and rapid treatment) and SALT (sort, asses, lifesaving, intervention, and treatment/transport). There is currently controversy regarding the effectiveness of SALT over START triage system. This systematic review aims to investigate and compare the effectiveness between SALT and START triage system in disaster and MCIs setting. Literatures were searched via systematic search strategy from 2009 until 2019 in PubMed, Cochrane Library, CINAHL, Scopus, Science direct, Medlib, ProQuest. This review included simulated-based and medical record -based studies investigating the accuracy and applicability of SALT and START triage systems of adult and children population during MCIs and disaster. All type of studies were included. Joana Briggs institute critical appraisal tools were used to assess the quality of reviewed studies. As a result, 1450 articles identified in the search, 10 articles were included. Four themes were identified by review, they were accuracy, under-triage, over-triage and time to triage per individual victim. The START triage system has a wide range and inconsistent level of accuracy compared to SALT triage system (44% to 94. 2% of START compared to 70% to 83% of SALT). The under-triage error of START triage system ranged from 2.73% to 20%, slightly lower than SALT triage system (7.6 to 23.3%). The over-triage error of START triage system was slightly greater than SALT triage system (START ranged from 2% to 53% compared to 2% to 22% of SALT). The time for applying START triage system was faster than SALT triage system (START was 70-72.18 seconds compared to 78 second of SALT). Consequently; The START triage system has lower level of under-triage error and faster than SALT triage system in classifying victims of MCIs and disaster whereas SALT triage system is known slightly more accurate and lower level of over-triage. However, the magnitude of these differences is relatively small, and therefore the effect on the patient outcomes is not significance. Hence, regardless of the triage error, either START or SALT triage system is equally effective to triage victims of disaster and MCIs.

Keywords: disaster, effectiveness, mass casualty incidents, START triage system, SALT triage system

Procedia PDF Downloads 117

Authors: Baljeet Singh Saharan

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Bioremediation is the demand of the day. Tannery and textile effluents/waste waters have lots of pollution due to presence of hexavalent Chromium. Methodologies used in the present investigations include isolation, cultivation and purification of bacterial strain. Further characterization techniques and 16S rRNA sequencing were performed. Efficient bacterial strain capable of reducing hexavalent chromium was obtained. The strain can be used for bioremediation of industrial effluents containing hexavalent Cr. A gram negative, rod shaped and yellowish pigment producing bacterial strain from tannery effluent was isolated using nutrient agar. The 16S rRNA gene sequence similarity indicated that isolate SA13A is associated with genus Luteimonas (99%). This isolate has been found to reduce 100% of hexavalent chromium Cr (VI) (100 mg L-1) 100% in 16 h. Growth conditions were optimized for Cr (VI) reduction. Maximum reduction was observed at a temperature of 37 °C and pH 8.0. Additionally, Luteimonas aestuarii SA13A showed resistance against various heavy metals like Cr+6, Cr+3, Cu+2, Zn+2, Co+2, Ni+2 and Cd+2 . Hence, Luteimonas aestuarii SA13A could be used as potent Cr (VI) reducing strain as well as significant bioremediator in heavy metal contaminated sites.

Keywords: bioremediation, chromium, eco-friendly, heavy metals

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Authors: Natasha Petrovska, Mirjana Pavlovic, Maria M. Larrondo-Petrie

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Neural stem cells (NSCs) are multi-potent, self-renewing cells that generate new neurons. Three subtypes of NSCs can be separated regarding the stages of NSC lineage: quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs), but their gene expression signatures are not utterly understood yet. Single-cell examinations have started to elucidate the complex structure of NSC populations. Nevertheless, there is a lack of thorough molecular interpretation of the NSC lineage heterogeneity and an increasing need for tools to analyze and improve the efficiency and correctness of single-cell sequencing data. Feature selection and ordering can identify and classify the gene expression signatures of these subtypes and can discover novel subpopulations during the NSCs activation and differentiation processes. The aim here is to review the implementation of the feature selection technique on NSC subtypes and the classification techniques that have been used for the identification of gene expression signatures.

Keywords: feature selection, feature similarity, neural stem cells, genes, feature selection methods

Procedia PDF Downloads 127

Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

Procedia PDF Downloads 432

Authors: Phakamas Rachamontree, Theerawut Phusantisampan, Natthakorn Woravutthikul, Peerapong Pornwongthong, Malinee Sriariyanun

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A total of 115 yeast strains isolated from local cassava processing wastes were measured for crude protein content. Among these strains, the strain MSY-2 possessed the highest protein concentration (>3.5 mg protein/mL). By using molecular identification tools, it was identified to be a strain of Pichia kudriavzevii based on similarity of D1/D2 domain of 26S rDNA region. In this study, to optimize the protein production by MSY-2 strain, Response Surface Methodology (RSM) was applied. The tested parameters were the carbon content, nitrogen content, and incubation time. Here, the value of regression coefficient (R2) = 0.7194 could be explained by the model, which is high to support the significance of the model. Under the optimal condition, the protein content was produced up to 3.77 g per L of the culture and MSY-2 strain contain 66.8 g protein per 100 g of cell dry weight. These results revealed the plausibility of applying the novel strain of yeast in single-cell protein production.

Keywords: single cell protein, response surface methodology, yeast, cassava processing waste

Procedia PDF Downloads 385

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Liana Lortkipanidze, Nino Amirezashvili, Nino Javashvili

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The purpose of the grammatical dictionary is to provide information on the morphological and syntactic characteristics of the basic word in the dictionary entry. The electronic grammatical dictionaries are used as a tool of automated morphological analysis for texts processing. The Georgian Grammatical Dictionary should contain grammatical information for each word: part of speech, type of declension/conjugation, grammatical forms of the word (paradigm), alternative variants of basic word/lemma. In this paper, we present the system for compiling the Georgian Grammatical Dictionary automatically. We propose dictionary-based methods for extending grammatical lexicons. The input lexicon contains only a few number of words with identical grammatical features. The extension is based on similarity measures between features of words; more precisely, we add words to the extended lexicons, which are similar to those, which are already in the grammatical dictionary. Our dictionaries are corpora-based, and for the compiling, we introduce the method for lemmatization of unknown words, i.e., words of which neither full form nor lemma is in the grammatical dictionary.

Keywords: acquisition of lexicon, Georgian grammatical dictionary, lemmatization rules, morphological processor

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Authors: N. Didiş Körhasan, D. Kaltakçı Gürel

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Many students have difficulty in learning physics from elementary to university level. In addition, students' expectancy, attitude, and motivation may be influenced negatively with their experience (failure) and prejudice about physics learning. For this reason, physics educators, who are also physics teachers, search for the best ways to make students' learning of physics easier by considering cognitive, affective, and psychomotor issues in learning. This research critically discusses the history of physics education, fundamental pedagogical approaches, and models to teach physics, and transformation of physics education with recent research.

Keywords: pedagogy, physics, physics education, science education

Procedia PDF Downloads 245

Authors: Abeer M. Algeblawi

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Fifteen isolates of Agrobacterium tumefaciens were obtained from crown gall samples collected from six locations (Tripoli, Alzahra, Ain-Zara, Alzawia, Alazezia in Libya) from Grape (Vitis vinifera L.), Pear (Pyrus communis L.), Peach (Prunus persica L.) and Alexandria in Egypt from Guava (Psidium guajava L.) trees, Artichoke (Cynara cardunculus L.) and Sugar beet (Beta vulgaris L.). Total DNA was extracted from the eight isolates as well as the identification of six isolates used into Polymerase Chain Reaction (PCR) analysis and Random Amplified Polymorphic DNA (RAPD) technique were used. High similarity (55.5%) was observed among the eight A. tumefaciens isolates (Agro1, Agro2, Agro3, Agro4, Agro5, Agro6, Agro7, and Agro8). The PCR amplification products were resulting from the use of two specific primers (virD2A-virD2C). Analysis induction six isolates of A. tumefaciens obtained from different hosts. A visible band was specific to A. tumefaciens of (220 bp, 224 bp) and 338 bp produced with total DNA extracted from bacterial cells.

Keywords: Agrobacterium tumefaciens, crown gall, identification, molecular characterization, PCR, RAPD

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

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Authors: A. Senthil Kumar, V. Murali Bhaskaran

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In the information technology ground, people are using various tools and software for their official use and personal reasons. Nowadays, people are worrying to choose data accessing and extraction tools at the time of buying and selling their products. In addition, worry about various quality factors such as price, durability, color, size, and availability of the product. The main purpose of the research study is to find solutions to these unsolved existing problems. The proposed algorithm is a Multidirectional Rank Prediction (MDRP) decision making algorithm in order to take an effective strategic decision at all the levels of data extraction, uses a real time textile dataset and analyzes the results. Finally, the results are obtained and compared with the existing measurement methods such as PCC, SLCF, and VSS. The result accuracy is higher than the existing rank prediction methods.

Keywords: Knowledge Discovery in Database (KDD), Multidirectional Rank Prediction (MDRP), Pearson’s Correlation Coefficient (PCC), VSS (Vector Space Similarity)

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Seda Birbilener, Semsettin Kulac, Zeki Severoglu

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In this study, we have performed genetic diversity analysis of Tilia tomentosa genotypes by using randomly amplified polymorphic DNA (RAPD) primers. A total of 28 genotypes, including 25 members from the urban ecosystem and 3 genotypes from forest ecosystem as outgroup were used. 8 RAPD primers produced a total of 53 bands, of which 48 (90.6 %) were polymorphic. Percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), Nei's (1973) gene diversity (h), and Shannon's information index (I) were found as 94.29 %, 1.94, 1.60, 0.34, and 0.50, respectively. The unweighted pair-group method with arithmetic average (UPGMA) cluster analysis revealed that two major groups were observed. The genotypes of urban and forest ecosystems showed a high genetic similarity between 28% and 92% and these genotypes did not separate from each other in UPGMA tree. Also, urban and forest genotypes clustered together in principal component analysis (PCA).

Keywords: Tilia tomentosa, genetic diversity, urban ecosystem, RAPD, UPGMA

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Authors: Roslinda Nazar, Ezad Hafidz Hafidzuddin, Norihan M. Arifin, Ioan Pop

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In this paper, the problem of steady laminar boundary layer flow and heat transfer over a permeable exponentially stretching/shrinking sheet with generalized slip velocity is considered. The similarity transformations are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary differential equations. The transformed equations are then solved numerically using the bvp4c function in MATLAB. Dual solutions are found for a certain range of the suction and stretching/shrinking parameters. The effects of the suction parameter, stretching/shrinking parameter, velocity slip parameter, critical shear rate, and Prandtl number on the skin friction and heat transfer coefficients as well as the velocity and temperature profiles are presented and discussed.

Keywords: boundary layer, exponentially stretching/shrinking sheet, generalized slip, heat transfer, numerical solutions

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Authors: Varong Pongsai

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The objective of this paper is introducing a new method of accounting posting which is called Matrix Method Posting. This method is based on the Matrix operation of pure Mathematics. Although, accounting field is classified as one of the social-science knowledge, many of accounting operations are placed by Mathematics sign and operation. Through the operation applying, it seems to be that the operations of Mathematics should be applied to accounting possibly. So, this paper tries to over-lap Mathematics logic to accounting logic smoothly. According to the context of discovery, deductive approach is employed to prove a simultaneously logical concept of both Mathematics and Accounting. The result proves that the Matrix can be placed to operate accounting perfectly, because Matrix and accounting logic also have a similarity concept which is balancing 2 sides during operations. Moreover, the Matrix posting also has a lot of benefit. It can help financial analyst calculating financial ratios comfortably. Furthermore, the matrix determinant which is a signature operation itself also helps auditors checking out the correction of clients’ recording. If the determinant is not equaled to 0, it will point out that the recording process of clients getting into the problem. Finally, the Matrix should be easily determining a concept of merger and consolidation far beyond the present day concept.

Keywords: matrix method posting, deductive approach, determinant, accounting application

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Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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Authors: Amal Khalifa, Nicolas Vana Santos

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Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: Jaewoo Choi, Ki-Tae Hwang, Eunyoung Ko

Abstract:

Backgrounds/Aims: Patients with breast cancer are currently classified according to TNM stage. Nevertheless, the actual volume would be mis-estimated, and it would bring on inappropriate diagnosis. Tridimensional volume-stage derived from the ellipsoid formula was presented as useful measure. Methods: The medical records of 480 consecutive breast cancer between January 2001 and March 2013 were retrospectively reviewed. All patients were divided into three groups according to tumor volume by receiver operating characteristic analysis, and the ranges of each volume-stage were that V1 was below 2.5 cc, V2 was exceeded 2.5 and below 10.9 cc, and V3 was exceeded 10.9 cc. We analyzed outcomes of volume-stage and compared disease-free survival (DFS) and overall survival (OS) between size-stage and volume-stage with variant intrinsic factor. Results: In the T2 stage, there were patients who had a smaller volume than 4.2 cc known as maximum value of T1. These findings presented that patients in T1c had poorer DFS than T2-lesser (mean of DFS 48.7 vs. 51.8, p = 0.011). Such is also the case in OS (mean of OS 51.1 vs. 55.3, p = 0.006). The cumulative survival curves for V1, V2 compared T1, T2 showed similarity in DFS (HR 1.9 vs. 1.9), and so did it for V3 compared T3 (HR 3.5 vs. 2.6) significantly. Conclusion: This study demonstrated that tumor volume had good feasibility on the prognosis of patients with breast cancer. We proposed that volume-stage should be considered for an additional stage indicator, particularly in early breast cancer.

Keywords: breast cancer, tridimensional volume of tumor, TNM stage, volume stage

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Authors: Abdelsabour G. A. Khaled, Galal A.R. El-Sherbeny, Ahmed M. Hassanein, Gameel M. G. Aly

Abstract:

Classical methods of identification, based on agronomical characterization, are not always the most accurate way due to the instability of these characteristics under the influence of the different environments. In order to estimate the genetic diversity, molecular markers provided excellent tools. In this study, Genetic variation of nine Egyptian jojoba shrubs was tested using ISSR (inter simple sequences repeats), RAPD (random amplified polymorphic DNA) markers and based on the morphological characterization. The average of the percentage of polymorphism (%P) ranged between 58.17% and 74.07% for ISSR and RAPD markers, respectively. The range of genetic similarity percents among shrubs based on ISSR and RAPD markers were from 82.9 to 97.9% and from 85.5 to 97.8%, respectively. The average of PIC (polymorphism information content) values were 0.19 (ISSR) and 0.24 (RAPD). In the present study, RAPD markers were more efficient than the ISSR markers. Where the RAPD technique exhibited higher marker index (MI) average (1.26) compared to ISSR one (1.11). There was an insignificant correlation between the ISSR and RAPD data (0.076, P > 0.05). The dendrogram constructed by the combined RAPD and ISSR data gave a relatively different clustering pattern.

Keywords: correlation, molecular markers, polymorphism, marker index

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Authors: Bintou Jobe

Abstract:

The construction sector, both in the United Kingdom (UK) and developing Anglophone West African countries, specifically The Gambia, is facing significant health and safety challenges. While the UK has established legislation and regulations to support Occupational Health and Safety (OHS) in the industry, the same level of support is lacking in developing countries. The significance of this review is to assess the extent and effectiveness of OHS legislation and regulatory reform in the construction industry, with a focus on understanding the challenges faced by both the UK and developing Anglophone West African countries. It aims to highlight the benefits of implementing an OHS management system, specifically ISO 45001. This study uses a literature review approach, synthesizing publications from the past decade and identifying common themes and best practices related to Occupational Health and Safety in the construction industry. Findings were analysed, compared, and conclusions and recommendations were drawn after developing research questions and addressing them. This comprehensive review of the literature allows for a detailed understanding of the challenges faced by the industry in both contexts. The findings of the study indicate that while the UK has established robust health and safety legislation, many UK construction companies have not fully met the standards outlined in ISO 45001. These challenges faced by the UK include poor data management, inadequate communication of best practices, insufficient training, and a lack of safety culture mirroring those observed in the developing Anglophone countries. Therefore, compliance with OHS management systems has been shown to yield benefits, including injury prevention and centralized health and safety documentation. In conclusion, the effectiveness of OHS legislation for developing Anglophone West African countries should consider the positive impact experienced by the UK. The implementation of ISO 45001 can serve as a benchmark standard and potentially inform recommendations for developing countries. The selection criteria for literature include search keywords and phrases, such as occupational health and safety challenges, The Gambia, developing countries management systems, ISO 45001, and impact and effectiveness of OHS legislation. The literature was sourced from Google Scholar, the UK Health and Safety Executive websites, and Google Advanced Search.

Keywords: ISO 45001, developing countries, occupational health and safety, UK

Procedia PDF Downloads 69