Search results for: canopy characters classification

Authors: Maryam Sadeghi

Abstract:

Civilization and industrialization are two important factors that make people believe they are just depriving of savagery and brutality. But practical studies show exactly something different. How groups of people behave, when they are put in extreme situations is the very unpleasant truth about the human being in general. Both novels deal with the fragility of human society, no matter the people who are playing a role are children or grown-ups, who by definition should know better. Both novels have got beautiful plots in which no one enforces rules and laws on the characters, so they begin to show their true nature. The present study is undertaken to investigate the process of a journey from lack of humanity to a sort of self-consciousness which happens at the end of both Blindness by Saramago and Lord of the Flies by Golding. In order to get the best result the two novels have been studied precisely and lots of different articles and critical essays have been analyzed, which shows people drift into cruelty and savagery easily but can also drift out of it. In blindness losing sight, and being apart from society in a deserted tropical island in Lord of the Flies causes limitation. Limitation in any form makes people rebel. Although in the process of both novels, any kind of savagery, brutality, filth, and social collapse can be observable and both writers believe that human being has the potential of being animal images, but they both also want to show that the very nature of human being is divine. Children’s weeping at the end Lord of the Flies and Doctor’s remark at the end of Blindness “I don’t think we did go blind, I think we are blind, blind but seeing, blind people who can see but do not see”, show exactly the matter of insight at the end of the novels. The fact that divinity exists in the very nature of human being is the indubitable aim that makes this research truly valuable.

Keywords: brutality, lack of humanity, savagery, Blindness

Procedia PDF Downloads 378

Authors: Iftikhar U. Sikder

Abstract:

This paper illustrates an application of granular computing approach, namely rough set theory in data mining. The paper outlines the formalism of granular computing and elucidates the mathematical underpinning of rough set theory, which has been widely used by the data mining and the machine learning community. A real-world application is illustrated, and the classification performance is compared with other contending machine learning algorithms. The predictive performance of the rough set rule induction model shows comparative success with respect to other contending algorithms.

Keywords: concept approximation, granular computing, reducts, rough set theory, rule induction

Procedia PDF Downloads 532

Authors: Mohmmad A. Obeidat, Amjed Al Fahoum, Ayman M. Mansour

Abstract:

The recognition of an abnormal activity of the brain functionality is a vital issue. To determine the type of the abnormal activity either a brain image or brain signal are usually considered. Imaging localizes the defect within the brain area and relates this area with somebody functionalities. However, some functions may be disturbed without affecting the brain as in epilepsy. In this case, imaging may not provide the symptoms of the problem. A cheaper yet efficient approach that can be utilized to detect abnormal activity is the measurement and analysis of the electroencephalogram (EEG) signals. The main goal of this work is to come up with a new method to facilitate the classification of the abnormal and disorder activities within the brain directly using EEG signal processing, which makes it possible to be applied in an on-line monitoring system.

Keywords: EEG, wavelet, epilepsy, detection

Procedia PDF Downloads 538

Authors: Siriporn Meenanan

Abstract:

The objective of this study is to study about the uses and gratification of the sample who use the website that named secret-thai.com which provides moral contents, inspires, and builds up the spirit. The study found that the samples mainly use this website to follow up on the dharma activities. They also use the space as the web board to discuss about dharma issues. Moreover, the contents help readers to relax and also provides the guidelines to deal with stress and uncomfortable situations properly. The samples found to be most satisfied. In other words, the samples found the contents of the website are complete, and can cover their needs. Moreover, they found that contents useful in their ways of living. In addition, they are satisfied with the beautiful and interesting design of the website and well classification of the contents that readers can easily find the information that they want.

Keywords: uses and gratification, website, Secret-Thai.com, moral contents

Procedia PDF Downloads 235

Authors: Farnaz Alaeimoghadam, Farzad Alaeimoghadam

Abstract:

In low-lactose milk, due to lactose hydrolysis and its conversion to monosaccharides like glucose and galactose, the Maillard reaction (non-enzymatic browning) occurs more readily compared to non-hydrolyzed milk. This reaction incurs off-flavor and dark color, as well as a decrease in the nutritional value of milk. The target of this research was to evaluate the effect of natural antioxidants in diminishing the browning in low-lactose milk. In this research, three antioxidants, namely ascorbic acid, gallic acid, and pantothenic acid in the concentration range of 0-1 mM/L, either in combination with each other or separately, were added to low-lactose milk. After heat treatment (120 0C for 3 min.), milk samples incubated at 55 0C for one day and then stored at 4 0C for 9 days. Quality indices, including total phenol content, antioxidant activity, color indices, and sensory characters, were measured during intervals of 0, 2, 5, 7, and 9 days. Results of this research showed that the effect of storage time and adding antioxidants were significant on pH, antioxidant activity, total phenolic compounds either before or after heating, index L*, color change, and sensational characteristics (p < 0.05); however, acidity, a* and b* indices, chroma, and hue angle showed no significant changes (p > 0.05). The findings showed that the simultaneous application of gallic acid and ascorbic in the diminishing of non-enzymatic browning and color change, increasing pH, longevity, and antioxidant activity after heat treatment, and augmenting phenolic compounds before heat treatment was better than that of pantothenic acid.

Keywords: Maillard, low-lactose milk, non-enzymatic browning, natural antioxidant

Procedia PDF Downloads 139

Authors: Kalpana Jamdhade, Anita Chorey, Bharti Tijare, V. M. Bhale

Abstract:

A field experiment was conducted during summer season of 2011 at Agronomy research farm, Dr. PDKV, Akola, to study the effect of irrigation regime and nitrogen levels on growth and productivity of summer sesame. The experiment was laid out in split plot Design in which three irrigation scheduling on the basis of IW/CPE ratio viz., irrigation at 0.6, 0.8 and 1.0 IW/CPE ratios (I1, I2 and I3, respectively) and one irrigation scheduling based on critical growth stages of sesame (I4), in main plot and three nitrogen levels 0, 30 and 60 kg N ha-1 (N0, N1 and N2, respectively) in subplot. The result showed that plant height, number of leaves plant-1, leaf area and dry matter accumulation were maximum in irrigation scheduling at 1.0 IW/CPE ratio, which significantly superior over 0.6 IW/CPE ratio and irrigation at critical growth stages but were statistically at par with irrigation at 0.8 IW/CPE ratio. Nitrogen levels, application of 60 kg N ha-1 was recorded significantly superior all growth parameters over treatment 30 kg N ha-1 and 0 kg N ha-1. In case of yield attributes viz., No. of capsules plant-1, Test wt., grain yield and Stalk yield (qha-1) were maximum in irrigation scheduling at 1.0 IW/CPE ratio and were significantly superior over 0.8 IW/CPE ratio, 0.6 IW/CPE ratio and irrigation at critical growth stages. Application of 60 kg N ha-1 increased all yield attributing characters over application of 30 and 0 kg N ha-1. In case of economics of crop same trend was found and the highest B:C ration was obtained in irrigation scheduling at 1.0 IW/CPE ratio. Whereas, application of 30 kg N ha-1 was recorded highest B:C ration over application of 60 and 0 kg N ha-1. Interaction effect of irrigation and nitrogen levels were found to be non significant in summer season.

Keywords: irrigation regimes, nitrogen levels, summer sesame, agricultural technology

Procedia PDF Downloads 367

Authors: Mary Ann L. Halliday, Zoengpari Gohain

Abstract:

The stigma associated with HIV-AIDS negatively affect mental health and ability to effectively manage the disease. While the number of People living with HIV/AIDS (PLHIV) has been increasing day by day in Mizoram (a small north-eastern state in India), research on HIV/AIDS stigma has so far been limited. Despite the potential significance of Internalized HIV Stigma (IHS) in the lives of PLHIV, there has been very limited research in this area. It was therefore, felt necessary to explore the internalized HIV stigma, mental health, coping and perceived social support of PLHIV in Aizawl District, Mizoram. The present study was designed with the objectives to determine the degree of IHS, to study the relationship between the socio-demographic characteristics and level of IHS, to highlight the mental health status, coping strategies and perceived social support of PLHIV and to elucidate the relationship between these psychosocial variables. In order to achieve the objectives of the study, six hypotheses were formulated and statistical analyses conducted accordingly. The sample consisted of 300 PLWHA from Aizawl District, 150 males and 150 females, of the age group 20 to 70 years. Two- way classification of “Gender” (male and female) and three-way classification of “Level of IHS” (High IHS, Moderate IHS, Low IHS) on the dependent variables was employed, to elucidate the relationship between Internalized HIV Stigma, mental health, coping and perceived social support of PLHIV. The overall analysis revealed moderate level of IHS (67.3%) among PLHIV in Aizawl District, with a small proportion of subjects reporting high level of IHS. IHS was found to be significantly different on the basis of disclosure status, with the disclosure status of PLHIV accounting for 9% variability in IHS.  Results also revealed more or less good mental health among the participants, which was assessed by minimal depression (50.3%) and minimal anxiety (45%), with females with high IHS scoring significantly higher in both depression and anxiety (p<.01). Examination of the coping strategies of PLHIV found that the most frequently used coping styles were Acceptance (91%), Religion (84.3%), Planning (74.7%), Active Coping (66%) and Emotional Support (52.7%). High perception of perceived social support (48%) was found in the present study. Correlation analysis revealed significant positive relationships between IHS and depression as well as anxiety (p<.01), thus revealing that IHS negatively affects the mental health of PLHIV. Results however revealed that this effect may be lessened by the use of various coping strategies by PLHIV as well as their perception of social support.

Keywords: Aizawl, anxiety, depression, internalized HIV stigma, HIV/AIDS, mental health, mizoram, perceived social support

Procedia PDF Downloads 262

Authors: I. Baddari, A. Riahla, M. Mezghich

Abstract:

Today in the literature, we discover a lot of routing algorithms which some have been the subject of normalization. Two great classes Routing algorithms are defined, the first is the class reactive algorithms and the second that of algorithms proactive. The aim of this work is to make a comparative study between some routing algorithms. Two comparisons are considered. The first will focus on the protocols of the same class and second class on algorithms of different classes (one reactive and the other proactive). Since they are not based on analytical models, the exact evaluation of some aspects of these protocols is challenging. Simulations have to be done in order to study their performances. Our simulation is performed in NS2 (Network Simulator 2). It identified a classification of the different routing algorithms studied in a metrics such as loss of message, the time transmission, mobility, etc.

Keywords: ad-hoc network routing protocol, simulation, NS2, delay, packet loss, wideband, mobility

Procedia PDF Downloads 401

Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

Abstract:

Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

Procedia PDF Downloads 61

Authors: Trupti Diwan

Abstract:

Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

Procedia PDF Downloads 423

Authors: Kexin Tan

Abstract:

The Silk Road is a concept idiosyncratic in nature. Western scholars co-created and conceptualized in its early days, transliterated into the countries along the Silk Road, redefined, reimagined, and reconfigured by the public in the second half of the twentieth century. Therefore, the image is not only a mirror of the discursive interactions between East and West but Self and Other. The travel narrative of Sven Hedin, through which the Silk Road was enriched in meanings and popularized, is the focus of this study. This article examines how the Silk Road was imagined in three key texts of Sven Hedin: The Silk Road, The Wandering Lake, and The Flight of “Big Horse”. Three recurring themes are extracted and analyzed: the Silk Road, the land of enigmas, the virgin land, and the reconnecting road. Ideas about ethnotypes and images drawn from theorists such as Joep Leerssen have been deployed in the analysis. This research tracks how the images were configured, concentrating on China’s ethnotypes, travel writing tropes, and the Silk Road discourse that preceded Sven Hedin. Hedin’s role in his expedition, his geopolitical viewpoints, and the commercial considerations of his books are also discussed in relation to the intellectual construct of the Silk Road. It is discovered that the images of the Silk Road and the discursive traditions behind it are mobile rather than static, inclusive than antithetical. The paradoxical characters of the Silk Road reveal the complexity of the socio-historical background of Hedin’s time, as well as the collision of discursive traditions and practical issues. While it is true that Hedin’s discursive construction of the Silk Road image embodies the bias of Self-West against Other-East, its characteristics such as fluidity and openness could probably offer a hint at its resurgence in the postcolonial era.

Keywords: the silk road, Sven Hedin, imagology, ethnotype, travelogue

Procedia PDF Downloads 194

Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

Abstract:

PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.

Keywords: mobile mapping, GNSS, IMU, similarity, classification

Procedia PDF Downloads 84

Authors: Nabil Shawkat, Jamil Saquer

Abstract:

Social media has accelerated our ability to engage with others and eliminated many communication barriers. On the other hand, the widespread use of social media resulted in an increase in online hate speech. This has drastic impacts on vulnerable individuals and societies. Therefore, it is critical to detect hate speech to prevent innocent users and vulnerable communities from becoming victims of hate speech. We investigate the performance of different deep learning and machine learning algorithms on three different datasets. Our results show that the BERT model gives the best performance among all the models by achieving an F1-score of 90.6% on one of the datasets and F1-scores of 89.7% and 88.2% on the other two datasets.

Keywords: hate speech, machine learning, deep learning, abusive words, social media, text classification

Procedia PDF Downloads 139

Authors: Saurabh Farkya, Govinda Surampudi

Abstract:

Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

Procedia PDF Downloads 501

Authors: Tamphasana Wairokpam

Abstract:

Inflammatory myopathies (IMs) have long been recognised as a heterogenous family of myopathies with acute, subacute, and sometimes chronic presentation and are potentially treatable. Necrotizing autoimmune myopathies (NAM) are a relatively new subset of myopathies. Patients generally present with subacute onset of proximal myopathy and significantly elevated creatinine kinase (CK) levels. It is being increasingly recognised that there are limitations to the independent diagnostic utility of muscle biopsy. Immunohistochemistry tests may reveal important information in these cases. The traditional classification of IMs failed to recognise NAM as a separate entity and did not adequately emphasize the diversity of IMs. This review and case report on NAM aims to highlight the heterogeneity of this entity and focus on the distinct clinical presentation, biopsy findings, specific auto-antibodies implicated, and available treatment options with prognosis. This article is a meta-analysis of literatures on NAM and a case report illustrating the clinical course, investigation and biopsy findings, antibodies implicated, and management of a patient with NAM. The main databases used for the search were Pubmed, Google Scholar, and Cochrane Library. Altogether, 67 publications have been taken as references. Two biomarkers, anti-signal recognition protein (SRP) and anti- hydroxyl methylglutaryl-coenzyme A reductase (HMGCR) Abs, have been found to have an association with NAM in about 2/3rd of cases. Interestingly, anti-SRP associated NAM appears to be more aggressive in its clinical course when compared to its anti-HMGCR associated counterpart. Biopsy shows muscle fibre necrosis without inflammation. There are reports of statin-induced NAM where progression of myopathy has been seen even after discontinuation of statins, pointing towards an underlying immune mechanism. Diagnosisng NAM is essential as it requires more aggressive immunotherapy than other types of IMs. Most cases are refractory to corticosteroid monotherapy. Immunosuppressive therapy with other immunotherapeutic agents such as IVIg, rituximab, mycophenolate mofetil, azathioprine has been explored and found to have a role in the treatment of NAM. In conclusion,given the heterogeneity of NAM, it appears that NAM is not just a single entity but consists of many different forms, despite the similarities in presentation and its classification remains an evolving field. A thorough understanding of underlying mechanism and the clinical correlation with antibodies associated with NAM is essential for efficacious management and disease prognostication.

Keywords: inflammatory myopathies, necrotising autoimmune myopathies, anti-SRP antibody, anti-HMGCR antibody, statin induced myopathy

Procedia PDF Downloads 103

Authors: Khader Musbah Titi

Abstract:

In this era, traditional education systems do not meet the new challenges created by emerging technologies. On the other hand, eLearning offers all the necessary tools to meet these challenges. Using the Internet has brought numerous benefits to most educational institutions; it has also stretched traditional problems of plagiarism, cheating, stealing, vandalism, and spying into the cyberspace. This research discusses these issues in an eLearning environment. It attempts to provide suggestions and possible solutions to some of these issues. The main aim of this research is to conduct a survey at Irbid National University (INU), one of the oldest and biggest universities in Jordan, to study information related to moral and ethical issues in e-learning environment that affect the construction of the students’ characters in the future. The study will focus on student’s behavior and actions through the Internet using Learning Management System (LMS). Another aim of this research is to analyze the opinions of the instructors and last year students at INU about ethical behavior and interaction through LMS. The results show that educational institutes that use LMS should focus on student character development along with field knowledge. According to disadvantages, the results of the study showed that most of students behave unethically in their online activities (cheating, plagiarism, copy/paste etc.) while studying online courses through LMS. The result showed that instructors play a major role in the character development of students. The result also showed that academic institute must have variant mechanisms and strict policy in LMS to control unethical actions of students.

Keywords: LMS, cyber ethics, e-learning, IT ethics, students’ behaviors

Procedia PDF Downloads 243

Authors: Wenqi Liu, Reginald Bailey

Abstract:

This study proposes a comprehensive and effective approach to business-to-business (B2B) sales forecasting by integrating advanced machine learning models with a rule-based decision-making framework. The methodology addresses the critical challenge of optimizing sales pipeline performance and improving conversion rates through predictive analytics and actionable insights. The first component involves developing a classification model to predict the likelihood of conversion, aiming to outperform traditional methods such as logistic regression in terms of accuracy, precision, recall, and F1 score. Feature importance analysis highlights key predictive factors, such as client revenue size and sales velocity, providing valuable insights into conversion dynamics. The second component focuses on forecasting sales value using a regression model, designed to achieve superior performance compared to linear regression by minimizing mean absolute error (MAE), mean squared error (MSE), and maximizing R-squared metrics. The regression analysis identifies primary drivers of sales value, further informing data-driven strategies. To bridge the gap between predictive modeling and actionable outcomes, a rule-based decision framework is introduced. This model categorizes leads into high, medium, and low priorities based on thresholds for conversion probability and predicted sales value. By combining classification and regression outputs, this framework enables sales teams to allocate resources effectively, focus on high-value opportunities, and streamline lead management processes. The integrated approach significantly enhances lead prioritization, increases conversion rates, and drives revenue generation, offering a robust solution to the declining pipeline conversion rates faced by many B2B organizations. Our findings demonstrate the practical benefits of blending machine learning with decision-making frameworks, providing a scalable, data-driven solution for strategic sales optimization. This study underscores the potential of predictive analytics to transform B2B sales operations, enabling more informed decision-making and improved organizational outcomes in competitive markets.

Keywords: machine learning, XGBoost, regression, decision making framework, system engineering

Procedia PDF Downloads 25

Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

Abstract:

Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

Procedia PDF Downloads 173

Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

Abstract:

Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

Procedia PDF Downloads 119

Authors: Kothuri Sriraman, Mattupalli Komal Teja

Abstract:

In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

Procedia PDF Downloads 350

Authors: Slimane Mokrani, Nabti El hafid

Abstract:

Description of the subject: Currently, several efforts focus on the study of biodiversity, microbial biotechnology, and the use of ecological strategies. Objectives: The aim of this present work is to determine the functional diversity of bacteria in rhizospheric and non-rhizospheric soils of different plants. Methods: Bacteria were isolated from soil and identified based on physiological and biochemical characters and genotypic taxonomy performed by 16S rDNA and BOX-PCR. As well as the characterization of various PGPR traits. Then, they are tested for their effects on the stimulation of seed germination and the growth of Phaseolus vulgaris L. As well as their biological control activities with regard to the phytopathogenic bacterial isolate Xapf. Results and Discussion: The biochemical and physiological identification of 75 bacterial isolates made it possible to associate them with the two groups of fluorescent Pseudomonas (74.67%) and non-fluorescent Pseudomonas (25.33%). The identification by 16S rDNA of 27 strains made it possible to attribute the majority of the strains to the genus Pseudomonas (81.48%), Serratia (7.41%) and Bacillus (11.11%). The bacterial strains showed a high capacity to produce IAA, siderophores, HCN and to solubilize phosphate. A significant stimulation of germination and growth was observed by applying the Pseudomonas strains. Furthermore, significant reductions in the severity and intensity of the disease caused caused by Xapf were observed. Conclusion: The bacteria described in this present study endowed with different PGPR activities seem to be very promising for their uses as biological control agents and bio-fertilization.

Keywords: biofertilization, biological control, phaseolus vulgaris L, pseudomonas, Xanthomonas axonopodis pv. phaseoli var. fuscans and common blight

Procedia PDF Downloads 81

Authors: Abigail M. Csik, Gabriel A. Radvansky

Abstract:

As people read through event-based narratives, they construct an event model that captures information about the characters, goals, location, time, and causality. For many reasons, memory for such narratives is represented at different levels, namely, the surface form, textbase, and event model levels. Rereading has been shown to decrease surface form memory, while, at the same time, increasing textbase and event model memories. More generally, distributed practice has consistently shown memory benefits over massed practice for different types of materials, including texts. However, little research has investigated distributed practice of narratives at different inter-study intervals and these effects on these three levels of memory. Recent work in our lab has indicated that there may be dramatic changes in patterns of forgetting around one week, which may affect the three levels of memory. The present experiment aimed to determine the effects of rereading on the three levels of memory as a factor of whether the texts were reread before versus after one week. Participants (N = 42) read a set of stories, re-read them either before or after one week (with an inter-study interval of three days, seven days, or fourteen days), and then took a recognition test, from which the three levels of representation were derived. Signal detection results from this study reveal that differential patterns at the three levels as a factor of whether the narratives were re-read prior to one week or after one week. In particular, an ANOVA revealed that surface form memory was lower (p = .08) while textbase (p = .02) and event model memory (p = .04) were greater if narratives were re-read 14 days later compared to memory when narratives were re-read 3 days later. These results have implications for what type of memory benefits from distributed practice at various inter-study intervals.

Keywords: memory, event cognition, distributed practice, consolidation

Procedia PDF Downloads 226

Authors: Sami Mestiri, Abdeljelil Farhat

Abstract:

The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

Procedia PDF Downloads 542

Authors: Yating Mu

Abstract:

Young children acquire native language with amazing rapidity. After noticing this interesting phenomenon, lots of linguistics, as well as psychologists, devote themselves to exploring the best explanations. Thus researches on first language acquisition emerged. Early lexical development is an important branch of children’s FLA (first language acquisition). Verb, the most significant class of lexicon, the most grammatically complex syntactic category or word type, is not only the core of exploring syntactic structures of language but also plays a key role in analyzing semantic features. Obviously, early verb development must have great impacts on children’s early lexical acquisition. Most scholars conclude that verbs, in general, are very difficult to learn because the problem in verb learning might be more about mapping a specific verb onto an action or event than about learning the underlying relational concepts that the verb or relational term encodes. However, the previous researches on early verb development mainly focus on the argument about whether there is a noun-bias or verb-bias in children’s early productive vocabulary. There are few researches on general characteristics of children’s early verbs concerning both semantic and syntactic aspects, not mentioning a general survey on Chinese-speaking children’s verb acquisition. Therefore, the author attempts to examine the general conditions and characteristics of Chinese-speaking children’s early productive verbs, based on data from a longitudinal study on three Chinese-speaking children. In order to present an overall picture of Chinese verb development, both semantic and syntactic aspects will be focused in the present study. As for semantic analysis, a classification method is adopted first. Verb category is a sophisticated class in Mandarin, so it is quite necessary to divide it into small sub-types, thus making the research much easier. By making a reasonable classification of eight verb classes on basis of semantic features, the research aims at finding out whether there exist any universal rules in Chinese-speaking children’s verb development. With regard to the syntactic aspect of verb category, a debate between nativist account and usage-based approach has lasted for quite a long time. By analyzing the longitudinal Mandarin data, the author attempts to find out whether the usage-based theory can fully explain characteristics in Chinese verb development. To sum up, this thesis attempts to apply the descriptive research method to investigate the acquisition and the usage of Chinese-speaking children’s early verbs, on purpose of providing a new perspective in investigating semantic and syntactic features of early verb acquisition.

Keywords: Chinese-speaking children, early verb acquisition, verb classes, verb grammatical structures

Procedia PDF Downloads 367

Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

Procedia PDF Downloads 147

Authors: I. Fahi, T. Remmal, F. El Kamel, B. Ayoub

Abstract:

The treatment of the geotechnical database of the region of Casablanca was difficult to achieve due to the heterogeneity of the nomenclature of the lithological formations composing its soil. It appears necessary to harmonize the nomenclature of the facies and to produce cartographic documents useful for construction projects and studies before any investment program. To achieve this, more than 600 surveys made by the Public Laboratory for Testing and Studies (LPEE) in the agglomeration of Casablanca, were studied. Moreover, some local observations were made in different places of the metropolis. Each survey was the subject of a sheet containing lithological succession, macro and microscopic description of petrographic facies with photographic illustration, as well as measurements of geomechanical tests. In addition, an X-ray diffraction analysis was made in order to characterize the surficial formations of the region.

Keywords: Casablanca, guidebook, petrography, soil

Procedia PDF Downloads 302

Authors: R. Marhenke, M. Martini

Abstract:

The distraction of attentional resources after learning hinders long-term memory consolidation compared to several minutes of post-encoding inactivity in form of wakeful resting. We tested whether an 8-minute period of wakeful resting, compared to performing an adapted version of the d2 test of attention after learning, supports memory retention. Participants encoded and immediately recalled a word list followed by either an 8 minute period of wakeful resting (eyes closed, relaxed) or by performing an adapted version of the d2 test of attention (scanning and selecting specific characters while ignoring others). At the end of the experimental session (after 12-24 min) and again after 7 days, participants were required to complete a surprise free recall test of both word lists. Our results showed no significant difference in memory retention between the experimental conditions. However, we found that participants who completed the first lines of the d2 test in less than the given time limit of 20 seconds and thus had short unfilled intervals before switching to the next test line, remembered more words over the 12-24 minute and over the 7 days retention interval than participants who did not complete the first lines. This interaction occurred only for the first test lines, with the highest temporal proximity to the encoding task and not for later test lines. Differences in retention scores between groups (completed first line vs. did not complete) seem to be widely independent of the general performance in the d2 test. Implications and limitations of these exploratory findings are discussed.

Keywords: long-term memory, retroactive interference, attention, forgetting

Procedia PDF Downloads 133

Authors: V. V. Lakshmi, Y. V. S. Annapurna

Abstract:

Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

Procedia PDF Downloads 421

Authors: Xu Lan, Zainor Izat Zainal

Abstract:

Human intervention in Earth’s macro system has ushered in the age of the Anthropocene, prompting introspection among humans, the action agent. This epoch demands a reawakening of human conscience and inner motivation to mitigate the irreversible trend so as to shape the trajectory of the Anthropocene. Environmental virtue ethics claims that the fundamental cause of environmental crisis lies in humans themselves. Rather than focusing more on what humans should do, environmental virtue ethics seeks to specify environmental virtues to appeal to what kind of person a human should be. Renowned Pulitzer Prize-winning author Barbara Kingsolver illustrates her contentions about environmental ethics through the narrative of Codi and her sister Hallie’s environmental choices and actions in Animal Dreams (1990). This study adopts a textual analysis approach of the character traits exhibited by Codi and Hallie that are constitutive of making them environmentally virtuous, exploring how emotions and inner motivations drive actions. This paper is informed by Ronald Sandler’s (2007) virtues of sustainability, virtues of communion with nature, and virtues of environmental stewardship and activism. It aims to examine how Codi and Hallie’s character traits are built around these virtues. Furthermore, this study underscores the importance of internalizing principles and cultivating virtues for the environment and humans’ flourishing in the Anthropocene. As a tentative practice in applying environmental virtue ethics to examine environmental virtues for the Anthropocene, this study reveals Kingsolver’s endeavor of setting environmental virtue exemplars from fictional characters to inspire humans’ long-term and stable contribution to a better future.

Keywords: anthopocene, environmental ethics, environmental virtues, virtue ethics

Procedia PDF Downloads 37

Authors: Evelyn Asante Yeboah, Kwabena O. Asubonteng, Justice Camillus Mensah, Christine Furst

Abstract:

Smallholder-dominated mosaic landscapes in rural Africa are relevant for food production, biodiversity conservation, and climate regulation. Land-use transitions threaten the multifunctionality of such landscapes, especially the production capacity of arable lands resulting in food security challenges. Using land-cover maps derived from maximum likelihood classification of Landsat satellite images for the years 2002, 2015, and 2020, post-classification change detection, landscape metrics, and key informant interviews, the study assessed the implications of rubber plantation expansion and oil business development on the food production capacity of Ahanta West District, Ghana. The analysis reveals that settlement and rubber areas expanded by 5.82% and 10.33% of the landscape area, respectively, between 2002 and 2020. This increase translates into over twice their initial sizes (144% in settlement change and 101% in rubber change). Rubber plantation spread dominates the north and southwestern areas, whereas settlement is widespread in the eastern parts of the landscape. Rubber and settlement expanded at the expense of cropland, palm, and shrublands. Land-use transitions between cropland, palm, and shrubland were targeting each other, but the net loss in shrubland was higher (-17.27%). Isolation, subdivision, connectedness, and patch adjacency indices showed patch consolidation in the landscape configuration from 2002 to 2015 and patch fragmentation from 2015 to 2020. The study also found patches with consistent increasing connectivity in settlement areas indicating the influence of oil discovery developments and fragmentation tendencies in rubber, shrubland, cropland, and palm, indicating springing up of smaller rubber farms, the disappearance of shrubland, and splitting up of cropland and palm areas respectively. The results revealed a trend in land-use transitions in favor of smallholder rubber plantation expansion and oil discovery developments, which suggest serious implications on food production systems and poses a risk for food security and landscape multifunctional characteristics. To ensure sustainability in land uses, this paper recommends the enforcement of legislative instruments governing spatial planning and land use in Ghana as embedded in the 2016 land-use and spatial planning act.

Keywords: food production systems, food security, Ghana’s west coast, land-use transitions, multifunctional rural landscapes

Procedia PDF Downloads 147