Search results for: mood classification

Authors: Muhammad Ameer Nawaz Akram

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The 21st century has been revealed that many individuals around the world are living in urban settlements than in rural zones. The evolution of numerous cities in emerging and newly developed countries is accompanied by the rise of slums. The precise definition of a slum varies countries to countries, but the universal harmony is that slums are dilapidated settlements facing severe poverty and have lacked access to sanitation, water, electricity, good living styles, and land tenure. The slum settlements always vary in unique patterns within and among the countries and cities. The core objective of this study is the spatial identification and classification of slums in Gujrat city Pakistan from very high-resolution GeoEye-1 (0.41m) satellite imagery. Slums were first identified using GPS for sample site identification and ground-truthing; through this process, 425 slums were identified. Then Object-Oriented Analysis (OOA) was applied to classify slums on digital image. Spatial analysis softwares, e.g., ArcGIS 10.3, Erdas Imagine 9.3, and Envi 5.1, were used for processing data and performing the analysis. Results show that OOA provides up to 90% accuracy for the identification of slums. Jalal Cheema and Allah Ho colonies are severely affected by slum settlements. The ratio of criminal activities is also higher here than in other areas. Slums are increasing with the passage of time in urban areas, and they will be like a hazardous problem in coming future. So now, the executive bodies need to make effective policies and move towards the amelioration process of the city.

Keywords: slums, GPS, satellite imagery, object oriented analysis, zonal change detection

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Authors: Pelin Sonmez

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Health services provided to refugees and asylum seekers are very important and of priority due to their physical damages during the war and conflict situation, possible diseases in migration journey and negative psychological mood. However, there are very poor international standards in regards to providing health services to these people, which in return cause each country to differ their regulations. United Nations Sustainable Development Goals that are in effect as of 2016 assure that attention should be provided to non-citizen vulnerable groups in terms of health policies and they should be included in the global development, thereby aims to decrease the problems arising from providing health services to refugees. Though, we should not forget that these are the recent and yet uncertain attempts, mostly, as a result of Syrian War's forced migration wave. As an attempt to reveal different attitudes of international actors, this study compares/analyzes health services provided to refugees and asylum seekers on the basis of Turkey-EU policy implementations. While doing so, two research data will be focused upon. In this globe, results of the focus group interviews and a field study in a specific work (from its health related section) which was done in 2017 to 5000 Syrian women living in Turkey and presented to Republic of Turkey Disaster and Emergency Management Presidency will be utilized.

Keywords: European Union, health policies, refugee, Syrian women, Turkey

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Authors: Devadrita Dey Sarkar

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Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

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Authors: Rika Uchida

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Claude Debussy's piano works can be divided into three categories in terms of style characteristics. The first category includes works which are strongly impressionistic, evoking a mood or an atmosphere, rather than making a direct, clear statement. These works often depict nature, and they are descriptive and sensitive in their character. Harmonic vocabulary is often complex, and the sense of tonality is often ambiguous in those works. Examples which belong to this category are ‘Clair de lune’ from Suite Bergamasque, Deux Arabesques, and ‘Reflets dans l'eau’ from Images Book 2. The second category shows little or no trace of impressionism. Works are not descriptive; rather, they are classical or absolute. Examples which belong to this category are Pour le Piano, ‘Hommage à Rameau’ and ‘Movement’ from Images Book 1 and Etudes. The third category can be called exotic. Debussy had a great interest in foreign lands such as the Far and Near East, and Spain. He employs pentatonic and quartal harmonies to describe the Orient, occasionally using the effect of the Javanese gamelan, which impressed him at the Paris Exhibition. His compositions in the Spanish style evoke the atmosphere of Spain. Though he borrowed some techniques from Spanish composers whom he knew, the tonal experimentation which occurs in these works sets them apart. Examples which belong to this category are ‘Pagodes’ and ‘la Soiree dans Grenade’ from Estampes, ‘la Puerta del Vino’ from Preludes Book 2.

Keywords: music, piano, Debussy, style

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

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Authors: Ali Heyrani, Maryam Saidyousefi

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The aim of the present study was to investigate the relationship between emotional intelligence and Self-Efficacy of physical education teachers in Ilam province. The research method is descriptive correlational. The study participants were of 170 physical education teachers (90 males, 80 females) with an age range of 20 to 50 years, who were selected randomly. The instruments for data collection were Emotional Intelligence Questionnaire Bar-on (1997) to assess the Emotional Intelligence teachers and Self-Efficacy Questionnaire to measure their Self-Efficacy. The questionnaires used in the interior are reliable and valid. To analyze the data, descriptive statistics and inferential tests (Kolmogorov-Smirnov test, Pearson correlation and multiple regression) at a significance level of P <0/ 05 were used. The Results showed that there is a significant positive relationship between totall emotional intelligence and Self-Efficacy of teachers, so the more emotional intelligence of physical education teachers the better the extent of Self-Efficacy. Also, the results arising from regression analysis gradually showed that among components of emotional intelligence, three components, the General Mood, Adaptability, and Interpersonal Communication to Self-Efficacy are of a significant positive relationship and are able to predict the Self-Efficacy of physical education teachers. It seems the application of this study ҆s results can help to education authorities to promote the level of teachers’ emotional intelligence and therefore the improvement of their Self-Efficacy and success in learners’ teaching and training.

Keywords: emotional intelligence, self-efficacy, physical education teachers, Ilam province

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: M. Sanjarani, A. Danehkar, A. Mashincheyan, A. H. Javid, S. M. R. Fatemi

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The oil spill in marine water has direct impact on coastal resources and community. Environmental Sensitivity Index (ESI) map is the first step to assess the potential impact of an oil spill and minimize the damage of coastal resources. In order to create Environmental Sensitivity Maps for the Chabahar bay (Iran), information has been collected in three different layers (Shoreline Classification, Biological and Human- uses resources) by means of field observations and measurements of beach morphology, personal interviews with professionals of different areas and the collection of bibliographic information. In this paper an attempt made to prepare an ESI map for sensitivity to oil spills of Chabahar bay coast. The Chabahar bay is subjected to high threaten to oil spill because of port, dense mangrove forest,only coral spot in Oman Sea and many industrial activities. Mapping the coastal resources, shoreline and coastal structures was carried out using Satellite images and GIS technology. The coastal features classified into three major categories as: Shoreline Classification, Biological and Human uses resources. The important resources classified into mangrove, Exposed tidal flats, sandy beach, etc. The sensitivity of shore was ranked as low to high (1 = low sensitivity,10 = high sensitivity) based on geomorphology of Chabahar bay coast using NOAA standards (sensitivity to oil, ease of clean up, etc). Eight ESI types were found in the area namely; ESI 1A, 1C, 3A, 6B, 7, 8B,9A and 10D. Therefore, in the study area, 50% were defined as High sensitivity, less than 1% as Medium, and 49% as low sensitivity areas. The ESI maps are useful to the oil spill responders, coastal managers and contingency planners. The overall ESI mapping product can provide a valuable management tool not only for oil spill response but for better integrated coastal zone management.

Keywords: ESI, oil spill, GIS, Chabahar Bay, Iran

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Authors: Alexandra-Monica Toma

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As the internet became a ruling force of society, computer-mediated communication has enriched its methods to convey meaning by combining linguistic means to visual means of expressivity. One of the elements of cyberspace is what we call a meme, a succinct, visually engaging tool used to communicate ideas or emotions, usually in a funny or ironic manner. Coined by Richard Dawkings in the late 1970s to refer to cultural genes, this term now denominates a special type of vernacular language used to share content on the internet. This research aims to analyse the basic mechanism that stands at the basis of meme creation as a blend of innovation and imitation and will approach some of the most widely used image macros remixed to generate new content while also pointing out success strategies. Moreover, this paper discusses whether memes can transcend the light-hearted and playful mood they mirror and become biting and sharp cultural comments. The study also uses the concept of multimodality and stresses how the text interacts with image, discussing three types of relations between the two: symmetry, amplification, and contradiction. We will furthermore show that memes are cultural artifacts and virtual tropes highly dependent on context and societal issues by using a corpus of memes created related to the COVID-19 pandemic.

Keywords: context, computer-mediated communication, memes, multimodality

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: Rajkumar Ghosh

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The Chaura Thrust, located in Himachal Pradesh, India, is a prominent geological feature that exhibits characteristics of an out-of-sequence thrust fault. This paper explores the geological setting of Himachal Pradesh, focusing on the Chaura Thrust's unique characteristics, its classification as an out-of-sequence thrust, and the implications of its presence in the region. The introduction provides background information on thrust faults and out-of-sequence thrusts, emphasizing their significance in understanding the tectonic history and deformation patterns of an area. It also outlines the objectives of the paper, which include examining the Chaura Thrust's geological features, discussing its classification as an out-of-sequence thrust, and assessing its implications for the region. The paper delves into the geological setting of Himachal Pradesh, describing the tectonic framework and providing insights into the formation of thrust faults in the region. Special attention is given to the Chaura Thrust, including its location, extent, and geometry, along with an overview of the associated rock formations and structural characteristics. The concept of out-of-sequence thrusts is introduced, defining their distinctive behavior and highlighting their importance in the understanding of geological processes. The Chaura Thrust is then analyzed in the context of an out-of-sequence thrust, examining the evidence and characteristics that support this classification. Factors contributing to the out-of-sequence behavior of the Chaura Thrust, such as stress interactions and fault interactions, are discussed. The geological implications and significance of the Chaura Thrust are explored, addressing its impact on the regional geology, tectonic evolution, and seismic hazard assessment. The paper also discusses the potential geological hazards associated with the Chaura Thrust and the need for effective mitigation strategies in the region. Future research directions and recommendations are provided, highlighting areas that warrant further investigation, such as detailed structural analyses, geodetic measurements, and geophysical surveys. The importance of continued research in understanding and managing geological hazards related to the Chaura Thrust is emphasized. In conclusion, the Chaura Thrust in Himachal Pradesh represents an out-of-sequence thrust fault that has significant implications for the region's geology and tectonic evolution. By studying the unique characteristics and behavior of the Chaura Thrust, researchers can gain valuable insights into the geological processes occurring in Himachal Pradesh and contribute to a better understanding and mitigation of seismic hazards in the area.

Keywords: chaura thrust, out-of-sequence thrust, himachal pradesh, geological setting, tectonic framework, rock formations, structural characteristics, stress interactions, fault interactions, geological implications, seismic hazard assessment, geological hazards, future research, mitigation strategies.

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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Authors: Kedar S. Prabhavalkar, Nimmy Baby Poovanpallil

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Lamotrigine is approved for maintenance treatment of bipolar I disorder. However, its role in the treatment of acute bipolar depression is not well clear. Its efficacy in the treatment of major depressive disorders including refractory unipolar depression suggested the use of lamotrigine as an augmentation drug for acute bipolar depression. The present study aims to evaluate and perform a comparative analysis of the therapeutic effects of lamotrigine, an epileptic mood stabilizer, when used alone and in combination with duloxetine in treating acute bipolar depression at different doses of lamotrigine. Male swiss albino mice were used. For evaluation of efficacy of combination, immobility period was analyzed 30 min after the treatment from forced swim and tail suspension tests. Further amount of sucrose consumed in sucrose preference test was estimated. The combination of duloxetine and lamotrigine showed potentiation of antidepressant activity in acute models. Decrease in immobility time and increase in the amount of sucrose consumption in stressed mice were higher in combined group compared to lamotrigine monotherapy group. Brain monoamine levels were also attenuated more with combination compared to monotherapy. Results of the present study suggest potential role of lamotrigine and duloxetine combination in the treatment of acute bipolar depression.

Keywords: lamotrigine, duloxetine, acute bipolar depression, augmentation

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Authors: Minakshi Jain, I. P. Singh

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Due to the era of outstanding technology and modern lifestyle, human beings are debasing their physical, psychological, and mental well-being. The effect of this leads to a trail of chronic diseases like anxiety, loneliness, and depression, especially in children and young adults. This is visible in individuals who suffer from clinical depression, which leads to impaired mood and distortion of cognition, particularly in children. The Members of the WHO European Region made a declaration to provisioning each child with access to healthy and safe environments by 2020, and the decision was taken at the Conference on Environment and Health in 2010 as an initiative to improve access to green spaces in cities which provides universal access for quality spaces for both social interaction and human well-being. In line with this, the paper aims to establish a prospective study on linking green spaces and CBT (Cognitive behavior therapy) in order to treat disorders with reference to children and young adults. A questionnaire was adopted to explore the possibility of green spaces as additive measures for the existing modes of therapy. The results adapted from the questionnaire show that certain species of vegetation have a significant effect in enhancing effective mental well-being.

Keywords: CBT, therapeutic gardens UCLA loneliness scale, anxiety, depression, green spaces, biophilia, environmental psychology

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Authors: Murat Mert, Yusuf Ozer, Fatih Kolay

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Behaviour of giving harm to the body in literature has been named as “self-injury”, “self-mutilation” ve “self-harm”. “Self-injury”, or “self-mutilation” is generally used for the same meaning and mentioned as an action which is committed to the body itself directly. As is seen that alcohol and drug users have injured their bodies because of deprivation, whereas behaviour of self-injury in some societies is accepted as religious and cultural, it has nevertheless been diagnosed in people who have a borderline personality disorder, histrionic personality disorder, psychotic personality disorder and mood disorder. There has not been any direct self-murder tendency in people having self-harmed. However, death cases can be seen together with loss of consciousness depending on loss of blood by exceeding the limit in the course of injury action. 34- year old – male person who was alcohol addicted, having had a psycological treatment beforehand, had mutilated his small intestine together with fatty tissue by cutting his body with a razor-blade at the thought of insects strolling around the body (delirium tremens) due to deprivation attack and had died in the result of various cuts. In this study, crime scene investigation and death mechanism of the person having had self-harmed in a result of abstinence syndrome will be explained. Relevant criteria which differentiate this case from homicide will be examined.

Keywords: self-injury, autopsy, abstinence syndrome, CSI

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Authors: Hukam Chand

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Over the past few years, the performance of Indian classical music has been improved a lot due to the technical inclusion of western instruments. Infect, the Indian classical music is all about raags which portray a mood and sentiments expressed through a microtonal scale based on natural harmonic series. And, most of the western instruments are not based on natural harmonic series and the tonal system is the only system which has considerable influence on the Indian classical music. However, the use of western instruments has been growing day by day in one way or the other by the Indian artists due to their quality of harmony. As a result of which, there are some common instruments such as harmonium, violin, guitar, saxophone, synthesizer which are being used commonly by Indian and western artists. On the other hand, a lot of fusion has taken place in the music of both sides due to the similar characteristics in their instruments. For example, harmonium which was originally the western instrument has now acquired an important position in Indian classical music to perform raags. Besides, a lot of suggestions for improving in the Indian music have been given by the artists for technical modification in the western instruments to cater the needs of Indian music through melody approach. Pt. Vishav Mohan Bhatt an Indian musician has developed Mohan Veena (called guitar) to perform raags. N. Rajam the Indian lady Violinist has made a remarkable work on Indian classical music by accompanied with vocal music. The purpose of the present research paper is to highlight the changes in Indian Classical Music through performance by using modified western music instruments.

Keywords: Indian classical music, Western instruments, harmonium, guitar, Violin and impact

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Rachid Mosbah, Aziez Chettoum, Zouhir Djerrou, Alberto Mantovani

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Selective serotonin reuptake inhibitors (SSRI) are a class of molecules used in treating depression, anxiety, and mood disorders. Paroxetine (PRT) is one of the mostly prescribed antidepressant which has attracted great attention regarding its side effects in recent years. This study was planned to assess the adverse effects of PRT on the biochemical parameters and reproductive system. Fourteen male Wistar rats were randomly allocated into two groups (7 rats or each): control and treated with PRT at dose of 5mg/kg.bw for two weeks. At the end of the experiment, blood was collected from retro orbital plexus for measuring the biochemical parameters, whereas the reproductive organs were removed for measuring semen quality and the histological investigations. Results showed that PRT induced significant changes in some biochemical parameters and alteration of semen quality including sperm count, spermatids number and sperm viability, motility, and abnormalities. The histopathological examinations of testis and epididymis revealed an alteration of spermatogenesis, cellular disorganization and vacuolization, enlargement of interstitial space, shrinkage and degenerative changes in the epithelium of seminiferous and epididymal tubules with few to nil numbers of spermatozoa in their lumen. In conclusion, PRT treatment caused changes in some biochemical parameters and sperm profile as well as histopathologic effects of reproductive organs.

Keywords: antidepressant, biochemical parameters, reproductive function, paroxetine

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: G. Martino, F. Silva, E. Marchal

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The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: clusterization and classification algorithms, integrated planning, mathematical modeling, optimization, penalty minimization

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Authors: Ingy Ibrahim El-Darwish, Neveen Youssef Azmy

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The endowment of a healthy environment can be implemented by endorsing sustainable fundamentals. Design of sustainable buildings through recycling of waste, can reduce health problems, provide good environments and contribute to the aesthetically pleasing entourage. Such environments can help in providing energy-saving alternatives to consolidate the principles of sustainability. The poor community awareness and the absence of laws and legislation in Egypt for waste management specifically in residential areas have led to an inability to provide an integrated system for waste management in urban and rural areas. Many problems and environmental challenges face the Egyptian urban environments. From these problems, is the lack of a cohesive vision for waste collection and recycling for energy-saving. The second problem is the lack public awareness of the short term and long term vision of waste management. Bad practices have adversely affected the efficiency of environmental management systems due to lack of urban legislations that codify collection and recycling of residential communities in Egyptian urban environments. Hence, this research tries to address residents on waste management matters to facilitate legislative process on waste collection and classification within residential units and outside them in a preparation phase for recycling in the Egyptian urban environments. In order to achieve this goal, one of the Egyptian communities has been addressed, analyzed and studied. Waste collection, classification, separation and access to recycling places in the urban city are proposed in preparation for a legislation ruling and regulating the process. Hence, sustainable principles are to be achieved.

Keywords: recycling, residential buildings, sustainability, waste

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Authors: Marija Zulić, Vanda Hájková, Nina Brkić-Jovanović, Linda Rathousová, Sanja Tomić

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Cerebral palsy is primarily reflected in the disorder of the development of movement and posture, which may be accompanied by sensory disturbances, disturbances of perception, cognition and communication, behavioural disorders and epilepsy. According to current inclusive attitudes towards people with disabilities implies that full social participation of children with cerebral palsy means inclusion in all activities in family, peer, school and leisure environments in the same scope and to the same extent as is the case with the children of proper development and without physical difficulties. Due to the fact that it has been established that the quality of children's participation in primary school is directly related to their social inclusion in future life, the aim of the paper is to identify predictors of social participation, respectively, and in particular, factors that could to improve the quality of social participation of children with cerebral palsy, in the primary school environment in Czech Republic. The study includes children with cerebral palsy (n = 75) in the Czech Republic, aged between six and 12 years who attend mainstream or special primary schools to the sixth grade. The main instrument used was the first and third part of the School function assessment questionnaire. It will also take into account the type of damage assessed according to a scale the Gross motor function classification system, five–level classification system for cerebral palsy. The research results will provide detailed insight into the degree of social participation of children with cerebral palsy and the factors that would be a potential cause of their levels of participation, in regular and special primary schools, in different socioeconomic environments in Czech Republic.

Keywords: cerebral palsy, Czech republic, social participation, the school function assessment

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Authors: Sagheer Ahmad

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Teaching is a sacred profession whereby students are developed in their mental abilities to cope with the challenges of the remote world. Thinkers have developed plenty of interesting ways to make the learning process quick and absorbing for the students. However, third world countries are still lacking these remote facilities in the institutions, and therefore, teaching is totally dependent upon the skills of the teachers. Skillful teachers use self-devised and stimulating ideas to grab the attention of their students. Most of the time their ideas are based on local grounds with which the students are already familiar. This self-explanatory characteristic is the base of several local ideologies to disseminate scientific knowledge to new generations. Biology is such a subject which largely bases upon hypotheses, and teaching it in an interesting way is needful to create a friendly relationship between teacher and student, and to make a fantastic learning environment. Taxonomic classification if presented as it is, may not be attractive for the secondary school students who just start learning about biology at elementary levels. Presenting this hierarchy by exemplifying Kingdom, Phylum, Class, Order, family, genus and Species as comparatives of our division into continents, countries, cities, towns, villages, homes and finally individuals could be an attention-grabbing approach to make this concept get into bones of students. Similarly, many other interesting approaches have also been adopted to teach students in a fascinating way so that learning science subjects may not be boring for them. Discussing these appealing ways of teaching students can be a valuable stimulus to refine teaching methodologies about science, thereby promoting the concept of friendly learning.

Keywords: biology, innovative approaches, taxonomic classification, teaching

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Authors: Célia Barreto Carvalho, Carolina da Motta, Marina Sousa, Joana Cabral, Ana Luísa Carvalho, Ermelindo Peixoto

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The aim of the current study was to develop and validate a Response to Stressful Situations Scale (RSSS) for the Portuguese population. This scale assesses the degree of stress experienced in scenarios that can constitute positive, negative and more neutral stressors, and also describes the physiological, emotional and behavioral reactions to those events according to their intensity. These scenario include typical stressor scenarios relevant to patients with schizophrenia, which are currently absent from most scale, assessing specific risks that these stressors may bring on subjects, which may prove useful in non-clinical and clinical populations (i.e. patients with mood or anxiety disorders, schizophrenia). Results from Principal Components Analysis and Confirmatory Factor Analysis of on two adult samples from general population allowed to confirm a three-factor model with good fit indices: χ2 (144)= 370.211, p = 0.000; GFI = 0.928; CFI = 0.927; TLI = 0.914, RMSEA = 0.055, P( rmsea ≤ 0.005) = 0.096; PCFI = 0.781. Further data analysis on the scale revealed that RSSS is an adequate assessment tool of stress response in adults to be used in further research and clinical settings, with good psychometric characteristics, adequate divergent and convergent validity, good temporal stability and high internal consistency.

Keywords: assessment, stress events, stress response, stress vulnerability

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Authors: Sirilak Areerachakul, Nat Ployong, Supayothin Na Songkla

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This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: artificial neural network, classification, students, e-learning

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Authors: Maximilian Elsen, Frank Tietze

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The development and diffusion of green technologies are crucial for achieving our ambitious climate targets. The Paris Agreement commits its members to develop strategies for achieving net zero greenhouse gas emissions by the second half of the century. Governments, executives, and academics are working on net-zero strategies and the business of rating organisations on their environmental, social and governance (ESG) performance has grown tremendously in its public interest. ESG data is now commonly integrated into traditional investment analysis and an important factor in investment decisions. Creating these metrics, however, is inherently challenging as environmental and social impacts are hard to measure and uniform requirements on ESG reporting are lacking. ESG metrics are often incomplete and inconsistent as they lack fully accepted reporting standards and are often of qualitative nature. This study explores the use of patent data for assessing the environmental performance of companies by focusing on their patented inventions in the space of climate change mitigation and adaptation technologies (CCMAT). The present study builds on the successful identification of CCMAT patents. In this context, the study adopts the Y02 patent classification, a fully cross-sectional tagging scheme that is fully incorporated in the Cooperative Patent Classification (CPC), to identify Climate Change Adaptation Technologies. The Y02 classification was jointly developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) and provides means to examine technologies in the field of mitigation and adaptation to climate change across relevant technologies. This paper develops sustainability-related metrics for firm-level patent portfolios. We do so by adopting a three-step approach. First, we identify relevant CCMAT patents based on their classification as Y02 CPC patents. Second, we examine the technological strength of the identified CCMAT patents by including more traditional metrics from the field of patent analytics while considering their relevance in the space of CCMAT. Such metrics include, among others, the number of forward citations a patent receives, as well as the backward citations and the size of the focal patent family. Third, we conduct our analysis on a firm level by sector for a sample of companies from different industries and compare the derived sustainability performance metrics with the firms’ environmental and financial performance based on carbon emissions and revenue data. The main outcome of this research is the development of sustainability-related metrics for firm-level environmental performance based on patent data. This research has the potential to complement existing ESG metrics from an innovation perspective by focusing on the environmental performance of companies and putting them into perspective to conventional financial performance metrics. We further provide insights into the environmental performance of companies on a sector level. This study has implications of both academic and practical nature. Academically, it contributes to the research on eco-innovation and the literature on innovation and intellectual property (IP). Practically, the study has implications for policymakers by deriving meaningful insights into the environmental performance from an innovation and IP perspective. Such metrics are further relevant for investors and potentially complement existing ESG data.

Keywords: climate change mitigation, innovation, patent portfolios, sustainability

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Authors: Néstor Iván Rojas, Wilson Medina Sierra

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Managing spatial information is described through a Geographic Information System (GIS), for some neighborhoods in the city of Tunja, in relation to the structural typology of the buildings. The use of GIS provides tools that facilitate the capture, processing, analysis and dissemination of cartographic information, product quality evaluation of the classification of buildings. Allows the development of a method that unifies and standardizes processes information. The project aims to generate a geographic database that is useful to the entities responsible for planning and disaster prevention and care for vulnerable populations, also seeks to be a basis for seismic vulnerability studies that can contribute in a study of urban seismic microzonation. The methodology consists in capturing the plat including road naming, neighborhoods, blocks and buildings, to which were added as attributes, the product of the evaluation of each of the housing data such as the number of inhabitants and classification, year of construction, the predominant structural systems, the type of mezzanine board and state of favorability, the presence of geo-technical problems, the type of cover, the use of each building, damage to structural and non-structural elements . The above data are tabulated in a spreadsheet that includes cadastral number, through which are systematically included in the respective building that also has that attribute. Geo-referenced data base is obtained, from which graphical outputs are generated, producing thematic maps for each evaluated data, which clearly show the spatial distribution of the information obtained. Using GIS offers important advantages for spatial information management and facilitates consultation and update. Usefulness of the project is recognized as a basis for studies on issues of planning and prevention.

Keywords: microzonation, buildings, geo-processing, cadastral number

Procedia PDF Downloads 317