Search results for: text mining

Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Fiona Bei Na Tan, Glen Wen Kiat Ho, Ee Leen Liow, Li Yin Tan, Sean Wei Loong Ho

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Background: Shoulder arthroscopy is an increasingly common procedure. Pneumothorax post-shoulder arthroscopy is a rare complication. Objectives: Our aim is to highlight a case report of pneumothorax post shoulder arthroscopy and to conduct a literature review to evaluate the possible risk factors associated with developing a pneumothorax during or after shoulder arthroscopy. Case Report: We report the case of a 75-year-old male non-smoker who underwent left shoulder arthroscopy without regional anaesthesia and in the left lateral position. The general anaesthesia and surgery were uncomplicated. The patient was desaturated postoperatively and was found to have a pneumothorax on examination and chest X-ray. A chest tube drain was inserted promptly into the right chest. He had an uncomplicated postoperative course. Methods: PubMed Medline and Cochrane database search was carried out using the terms shoulder arthroplasty, pneumothorax, pneumomediastinum, and subcutaneous emphysema. We selected full-text articles written in English. Results: Thirty-two articles were identified and thoroughly reviewed. Based on our inclusion and exclusion criteria, 14 articles, which included 20 cases of pneumothorax during or after shoulder arthroscopy, were included. Eighty percent (16/20) of pneumothoraxes occurred postoperatively. In the articles that specify the side of pneumothorax, 91% (10/11) occur on the ipsilateral side of the arthroscopy. Eighty-eight percent (7/8) of pneumothoraxes occurred when subacromial decompression was performed. Fifty-six percent (9/16) occurred in patients placed in the lateral decubitus position. Only 30% (6/20) occurred in current or ex-smokers, and only 25% (5/20) had a pre-existing lung condition. Overall, of the articles that posit a mechanism, 75% (9/12) deem the pathogenesis to be multifactorial. Conclusion: The exact mechanism of pneumothorax is currently unknown. Awareness of this complication and timely recognition are important to prevent life-threatening sequelae. Surgeons should have a low threshold to obtain diagnostic plain radiographs in the event of clinical suspicion.

Keywords: rotator cuff repair, decompression, pressure, complication

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Authors: Comfort Adeoye, Anthony Eneji

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Lead pollution by mining, industrial dumping, and other anthropogenic uses are corroding the environment. Efforts being made to control it include physical, chemical and biological methods. The failure of the aforementioned methods are largely due to the fact that they are cumbersome, expensive, and not eco-friendly. Some plant species can be used for remediation of these pollutants. The objective of this work is to investigate the abilities of two native weed species to remediate two lead-polluted soils: a) Battery dumpsite and, (b) Naturally occurring lead mine. Soil samples were taken from the two sites: a) Kumapayi in Ibadan, a battery dumpsite, (b) Zamfara, a natural lead mine. Screen house experiment in Complete Randomized Design (CRD) replicated three times was carried out at I.I.T.A. Unpolluted soils were collected and polluted with various rates of lead concentrations of 0, 0.1, 0.2, and 0.5%. These were planted with weed species. Plant growth parameters were monitored for twelve weeks, after which the plants were harvested. Dry weight and plant uptake of the lead were taken. Analysis of data was carried out using, Genstat, Excel and descriptive statistics. Relative concentration of lead (Pb) in the above and below ground parts of Gomphrena celusoides revealed that a higher amount of Pb is taken up in the root compared with the shoots at different levels of Pb pollution. However, lead uptake at 0.5% > 0.2% > 0.1% > Control. In essence, phytoremediation of Gomphrena is highest at soil pollution of 0.5% and its retention is greater in the root than the shoot.In S. pyramidalis, soil retention ranges from 0.1% > 0.5% > 0.2% > control. Uptake is highest at 0.5% > 0.1% > 0.2 in stem. Uptake in leaves is highest at 0.2%, but none in the 0.5% pollution. Therefore, different plant species exhibited different accumulative mode probably due to their physiological and rooting systems. Gomphrena spp. rooting system is tap root,while that of S.pyramidalis is fibrous.

Keywords: grass, lead, phytoremediation, pollution

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Preet Gill, Danus Ravindran

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These The COVID-19 pandemic resulted in widespread implications for medical specialist training programs worldwide, including radiology. The objective of this study was to investigate the impact of COVID-19 on the Australian and New Zealand radiology trainee experience and well-being, as well as to compare the Australasian experience with that reported by other countries. An anonymised electronic online questionnaire was disseminated to all training members of the Royal Australian and New Zealand College of Radiologists who were radiology trainees during the 2020 – 2022 clinical years. Trainees were questioned about their experience from the beginning of the COVID-19 pandemic in Australasia (March 2020) to the time of survey completion. Participation was voluntary. Questions assessed the impact of the pandemic across multiple domains, including workload (inpatient/outpatient & individual modality volume), teaching, supervision, external learning opportunities, redeployment and trainee wellbeing. Survey responses were collated and compared with other peer reviewed publications. Answer options were primarily in categorical format (nominal and ordinal subtypes, as appropriate). An opportunity to provide free text answers to a minority of questions was provided. While our results mirror that of other countries, which demonstrated reduced case exposure and increased remote teaching and supervision, responses showed variation in the methods utilised by training sites during the height of the pandemic. A significant number of trainees were affected by examination cancellations/postponements and had subspecialty training rotations postponed. The majority of trainees felt that the pandemic had a negative effect on their training. In conclusion, the COVID-19 pandemic has had a significant impact on radiology trainees across Australia and New Zealand. The present study has highlighted the extent of these effects, with most aspects of training impacted. Opportunities exist to utilise this information to create robust workplace strategies to mitigate these negative effects should the need arise in the future.

Keywords: COVID-19, radiology, training, pandemic

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Authors: Calvin Stephen, Biswajit Basu, Aonghus McNabola

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Market liberalization in the power sector has led to the emergence of micro-hydropower schemes that are dependent on the use of pumps-as-turbines in applications that were not suitable as potential hydropower sites in earlier years. These applications include energy recovery in water supply networks, sewage systems, irrigation systems, alcohol breweries, underground mining and desalination plants. As a result, there has been an accelerated adoption of pumpsas-turbine technology due to the economic advantages it presents in comparison to the conventional turbines in the micro-hydropower space. The performance of this machines under cavitation conditions, however, is not well understood as there is a deficiency of knowledge in literature focused on their turbine mode of operation. In hydraulic machines, cavitation is a common occurrence which needs to be understood to safeguard them and prolong their operation life. The overall purpose of this study is to investigate the effects of cavitation on the performance of a pumps-as-turbine system over its entire operating range. At various operating speeds, the cavitating region is identified experimentally while monitoring the effects this has on the power produced by the machine. Initial results indicate occurrence of cavitation at higher flow rates for lower operating speeds and at lower flow rates at higher operating speeds. This implies that for cavitation free operation, low speed pumps-as-turbine must be used for low flow rate conditions whereas for sites with higher flow rate conditions high speed turbines should be adopted. Such a complete understanding of pumps-as-turbine suction performance can aid avoid cavitation induced failures hence improved reliability of the micro-hydropower plant.

Keywords: cavitation, micro-hydropower, pumps-as-turbine, system design

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Authors: Robin Ferguson

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The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

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Authors: Siti Dewi Aisyah

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The rise of the Internet in the late twentieth century rapidly gains information and understands the world through screens. The digital way of communication through the Internet becomes an ordinary daily pattern. In the digital era, Fashion has been tremendously shared on social media platform especially because of the emergence of #OOTD (Outfit of the Day). Fashion cannot survive without the media. The media have played a vital role in shaping fashion into the complex cultural phenomenon it has become, and fashion has become an intrinsic part of today’s visual culture, and vice versa. Islamic Muslim Fashion has become a trend in Indonesia. It is said that social media has a huge impact in its development. Indonesia is ranked among the most users of social media. That is why people who wear hijab also use social media for different purposes, one of this is to introduce hijab fashion. Consequently, they are becoming famous in social media. Social media has become a tool for communicating their beliefs as a Muslim as well as personal branding as a good hijabi yet with a fashionable style. This study will examine how social media especially Blog and Instagram can lead the movement of Islamic Modest Fashion in Indonesia, how it triggers the consumer culture to hijabi, how they visualize their style in their social media. This research had been conducted through in-depth interviews with several bloggers who created Hijabers Community who have made a new trend in Islamic fashion and also Instagrammers who made their feeds as a style inspiration. This research is based on empirical research with qualitative methods (text and picture analysis). The methodology used for this research is by analyzing Blog and Instagram through visual analysis on the social media especially about the Islamic Modest Fashion trend. This research also contains a literature review of a diverse group of works on topics related to the study. This research will be examined through several theoretical frameworks including the study of social media, visual analysis and consumer culture. Fashion and consumer culture are also two main topics because fashion furthermore leads to consumer culture. The benefit of this research is for gaining the insight how social media can visualize the trend in hijab fashion style of Indonesian people.

Keywords: blog, consumer culture, hijab fashion, instagram, style, visual analysis

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Authors: Metrek Almetrek, Naser Alqahtani, Eisa Ghazwani, Mona Asiri, Mohammed Alqahtani, Magboolah Balobaid

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Background: Advocacy of potential for community coalitions to positively address social determinants of health and quality of life, little is known about the views of stakeholders involved in such efforts. This study sought to assess the provinces leaders’ perspectives about social determinants related to the Health Neighborhood Initiative (HNI), a new county effort to support community coalitions. Method and Subjects: We used a descriptive, qualitative study using personal interviews in 2022. We conducted it in the community coalition's “main cities committees” set across service planning areas that serve vulnerable groups located in the seven registered healthy cities to WHO (Abha, Tareeb, Muhayel, Balqarn, Alharajah, Alamwah, and Bisha). We conducted key informant interviews with 76 governmental, profit, non-profit, and community leaders to understand their perspectives about the HNI. As part of a larger project, this study focused on leaders’ views about social determinants of health related to the HNI. All interviews were audio-recorded and transcribed. An inductive approach to coding was used, with text segments grouped by social determinant categories. Results: Provinces leaders described multiple social determinants of health and quality of life that were relevant to the HNI community coalitions: housing and safety, community violence, economic stability, city services coordination and employment and education. Leaders discussed how social determinants were interconnected with each other and the need for efforts to address multiple social determinants simultaneously to effectively improve health and quality of life. Conclusions: Community coalitions have an opportunity to address multiple social determinants of health and quality of life to meet the social needs of vulnerable groups. Future research should examine how community coalitions, like those in the HNI, can actively engage with community members to identify needs and then deliver evidence-based care.

Keywords: social determinants, health and quality of life, vulnerable groups, qualitative research

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Authors: Mehena Fedoul

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This paper examines the intersection of race, gender, and disability through a Critical disability race theory and black feminist disability perspective in Keah Brown's memoir, "The Pretty One." The background of the study highlights the significance of intersectionality in understanding the multifaceted experiences of individuals who navigate multiple marginalized identities. The study contributes to the underrepresented field of disability studies from a Critical race and black feminist perspectives, shedding light on the unique challenges and resilience of black disabled women. The study employs a qualitative analysis of Keah Brown's memoir as a primary text. Drawing on intersectionality theory and black feminist disability scholarship, the analysis focuses on how Brown's memoir illuminates the ways in which her race, gender, and disability intersect and shape her lived experiences. The analysis reveals how Brown's memoir challenges traditional notions of disability, beauty, and empowerment through her unapologetic celebration of her blackness, femaleness, and disability. The major findings of the study indicate that Brown's memoir provides a powerful narrative of the complexity, uniqueness and richness of the lived experiences of black disabled women. It demonstrates how the intersectionality of race, gender, and disability shapes Brown's identity, body image, relationships, and societal interactions. The paper also highlights how Brown's memoir emphasizes the importance of inclusivity and intersectionality in understanding and addressing the challenges faced by black disabled women. In conclusion, this study offers a critical analysis of the intersection of race, gender, and disability in Keah Brown's memoir, "The Pretty One," from a black feminist disability perspective. It contributes to the growing body of literature that recognizes the significance of intersectionality in understanding the experiences of marginalized individuals in the disability community. The study underscores the need for more inclusive and intersectional perspectives in disability studies and advocates for greater recognition of the voices and experiences of black disabled women in academic and societal discourse.

Keywords: Intersectionality, black feminism, disability studies, keah brown

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Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes on the multi-criteria nature of the problem and on how decision makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of significant degree of ambiguity and indeterminacy observed in decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method to a real problem of academic personnel selection, having as main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherit ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: analytical hierarchy process, delphi method, multi-criteria decision maiking method, neutrosophic set theory, personnel recruitment

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Zerrin Akter Anni

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The media's role in shaping perceptions of violence against women (VAW) and their portrayal in news reporting significantly influences our understanding of this critical issue. My research delves into the portrayal of violence against women in mainstream media, using the prominent case of Dr. Rumana Manzur, a former UBC Fulbright Scholar from Bangladesh who suffered a brutal assault by her ex-husband in June 2011. Employing a qualitative research approach, this study uses an ethnographic media analysis method to scrutinize news reports of the aforementioned case from selected newspapers in Bangladesh. The primary objectives are to investigate how the popular news media in Bangladesh addresses the issue of violence against women and frames the victims of such violence. The findings of this research highlight that news media can perpetuate gender stereotypes and subtly shift blame onto the victim through various techniques, creating intricate interactions between the reader and the text. These techniques include sensationalized headlines, textual content, and graphic images. This victim-blaming process not only retraumatizes the survivor but also distorts the actual facts when presenting the case to a larger audience. Consequently, the representation of violence against women cases in media, particularly the portrayal of women as victims during reporting, significantly impacts our collective comprehension of this issue. In conclusion, this paper asserts that the Bangladeshi media, particularly news outlets, in conjunction with society, continue to follow a pattern of depicting gender-based violence in ways that devalue the image of women. This research underscores the need for critical analysis of media representations of violence against women cases, as they can perpetuate harmful stereotypes and hinder efforts to combat this pervasive problem. Therefore, the outcome of this research is to comprehend the complex dynamics between media and violence against women, which is essential for fostering a more empathetic and informed society that actively works towards eradicating this problem from our society.

Keywords: media representation, violence against women (vaw), ethnographic media analysis, victim-blaming, sensationalized headline

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Authors: Hicham Amar, Mustapha El Ghorfi, Yassine Taha, Abdellatif Elghali, Rachid Hakkou, Mostafa Benzaazoua

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Phosphate mine waste rock (PMWR) generated during ore extraction is continuously increasing, resulting in a significant environmental footprint. The main objectives of this study consist of i) elaboration of the sampling strategy of PMWR piles, ii) a mineralogical and chemical characterization of PMWR piles, and iii) 3D block model creation to evaluate the potential valorization of the existing PMWR. Destructive drilling using reverse circulation from 13 drills was used to collect samples for chemical (X-ray fluorescence analysis) and mineralogical assays. The 3D block model was created based on the data set, including chemical data of the realized drills using Datamine RM software. The optical microscopy observations showed that the sandy phosphate from drills in the PMWR piles is characterized by the abundance of carbonate fluorapatite with the presence of calcite, dolomite, and quartz. The mean grade of composite samples was around 19.5±2.7% for P₂O₅. The mean grade of P₂O₅ exhibited an increasing tendency by depth profile from bottom to top of PMWR piles. 3D block model generated with chemical data confirmed the tendency of the mean grades’ variation and may allow a potential selective extraction according to %P₂O₅. The 3D block model of P₂O₅ grade is an efficient sampling approach that confirmed the variation of P₂O₅ grade. This integrated approach for PMWR management will be a helpful tool for decision-making to recover the residual phosphate, adopting the circular economy and sustainability in the phosphate mining industry.

Keywords: 3D modelling, reverse circulation drilling, circular economy, phosphate mine waste rock, sampling

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Iris Sauerbrei, Jörg Trojan, Erich Lehner

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Introduction and significance of the study: This study examines if three-dimensional shapes elicit distinct patterns of perceptions. If so, it is relevant for all fields of design, especially for the design of the built environment. Description of basic methodologies: The five platonic solids are the geometrical base for all other three-dimensional shapes, among which tetrahedron and icosahedron provide the clearest representation of the qualities sharp and round. The component pair of attributes ‘sharp versus round’ has already been examined in various surveys in a psychology of perception and in neuroscience by means of graphics, images of products of daily use, as well as by photographs and walk-through-videos of landscapes and architecture. To verify a transfer of outcomes of the existing surveys to the perception of three-dimensional shapes, walk-in models (total height 2.2m) of tetrahedron and icosahedron were set up in a public park in Frankfurt am Main, Germany. Preferences of park visitors were tested by questionnaire; also they were asked to write down associations in a free text. In summer 2015, the tetrahedron was assembled eight times, the icosahedron seven times. In total 288 participants took part in the study; 116 rated the tetrahedron, 172 rated the icosahedron. Findings: Preliminary analyses of the collected data using Wilcoxon Rank-Sum tests show that the perceptions of the two solids differ in respect to several attributes and that each of the tested model show significance for specific attributes. Conclusion: These findings confirm the assumptions and provide first evidence that the perception of three-dimensional shapes are associated to characteristic attributes and to which. In order to enable conscious choices for spatial arrangements in design processes for the built environment, future studies should examine attributes for the other three basic bodies - Octahedron, Cube, and Dodecahedron. Additionally, similarities and differences between the perceptions of two- and three-dimensional shapes as well as shapes that are more complex need further research.

Keywords: 3D shapes, architecture, geometrical features, space perception, walk-in models

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Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

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Semi autogenous mills are designed for grinding or primary crushed ore, and are the most widely used in concentrators globally. Any defect occurrence in semi autogenous mills can stop the production line. A Gearbox is a significant part of a rotating machine or a mill, so, the gearbox monitoring is a necessary process to prevent the unwanted defects. When a defect happens in a gearbox bearing, this defect can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. Vibration analysis is one of the most effective and common ways to detect the bearing defects in the mills. Vibration signal in a mill can be made by different parts of the mill including electromotor, pinion girth gear, different rolling bearings, and tire. When a vibration signal, made by the aforementioned parts, is added to the gearbox vibration spectrum, an accurate and on time defect detection in the gearbox will be difficult. In this paper, a new method is proposed to detect the gearbox bearing defects in the semi autogenous mill on time and accurately, using the vibration signal analysis method. In this method, if the vibration values are increased in the vibration curve, the probability of defect occurrence is investigated by comparing the equipment vibration values and the standard ones. Then, all vibration frequencies are extracted from the vibration signal and the equipment defect is detected using the vibration spectrum curve. This method is implemented on the semi autogenous mills in the Golgohar mining and industrial company in Iran. The results show that the proposed method can detect the bearing looseness on time and accurately. After defect detection, the bearing is opened before the equipment failure and the predictive maintenance actions are implemented on it.

Keywords: condition monitoring, gearbox defects, predictive maintenance, vibration analysis

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Authors: Alexandre Chagnes

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Lithium-ion battery is the technology of choice in the development of electric vehicles. This technology is now mature, although there are still many challenges to increase their energy density while ensuring an irreproachable safety of use. For this goal, it is necessary to develop new cathodic materials that can be cycled at higher voltages and electrolytes compatible with these materials. But the challenge does not only concern the production of efficient batteries for the electrochemical storage of energy since lithium-ion battery technology relies on the use of critical and/or strategic value resources. It is, therefore, crucial to include Lithium-ion batteries development in a circular economy approach very early. In particular, optimized recycling and reuse of battery components must both minimize their impact on the environment and limit geopolitical issues related to tensions on the mineral resources necessary for lithium-ion battery production. Although recycling will never replace mining, it reduces resource dependence by ensuring the presence of exploitable resources in the territory, which is particularly important for countries like France, where exploited or exploitable resources are limited. This conference addresses the development of a new hydrometallurgical process combining leaching of cathodic material from spent lithium-ion battery in acidic chloride media and solvent extraction process. Most of recycling processes reported in the literature rely on the sulphate route, and a few studies investigate the potentialities of the chloride route despite many advantages and the possibility to develop new chemistry, which could get easier the metal separation. The leaching mechanisms and the solvent extraction equilibria will be presented in this conference. Based on the comprehension of the physicochemistry of leaching and solvent extraction, the present study will introduce a new hydrometallurgical process for the production of cobalt, nickel, manganese and lithium from spent cathodic materials.

Keywords: lithium-ion battery, recycling, hydrometallurgy, leaching, solvent extraction

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Authors: El-Said. I. Shabana, Mohammad S. Tayeb, Maher M. T. Qutub, Abdulraheem A. Kinsara

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Usually, phosphate deposits contain ²³⁸U and ²³²Th in addition to their decay products. Due to their different pathways in the environment, the ²³⁸U/²³²Th activity concentration ratio usually found to be greater than unity in phosphate sediments. The presence of these radionuclides creates a potential need to control exposure of workers in the mining and processing activities of the phosphate minerals in accordance with IAEA safety standards. The greatest dose to workers comes from exposure to radon, especially ²²²Rn from the uranium series, and has to be controlled. In this regard, radon (²²²Rn) was measured in the atmosphere (indoor and outdoor) of Al-Jalamid phosphate-mines working area using a portable radon-measurement instrument RAD7, in a purpose of radiation protection. Radon was measured in 61 sites inside the open phosphate mines, the phosphate upgrading facility (offices and rooms of the workers, and in some open-air sites) and in the dwellings of the workers residence-village that lies at about 3 km from the mines working area. The obtained results indicated that the average indoor radon concentration was about 48.4 Bq/m³. Inside the upgrading facility, the average outdoor concentrations were 10.8 and 9.7 Bq/m³ in the concentrate piles and crushing areas, respectively. It was 12.3 Bq/m³ in the atmosphere of the open mines. These values are comparable with the global average values. Based on the average values, the annual effective dose due to radon inhalation was calculated and risk estimates have been done. The average annual effective dose to workers due to the radon inhalation was estimated by 1.32 mSv. The potential excess risk of lung cancer mortality that could be attributed to radon, when considering the lifetime exposure, was estimated by 53.0x10^-4. The results have been discussed in detail.

Keywords: dosimetry, environmental monitoring, phosphate deposits, radiation protection, radon

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Authors: Salha Mohamed Hussain

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As part of the review on the Malay Language curriculum and pedagogy in Singapore conducted in 2010, some recommendations were made to nurture active learners who are able to use the Malay Language efficiently in their daily lives. In response to the review, a new Malay Language teaching and learning package for primary school, called CEKAP (Cungkil – Elicit; Eksplorasi – Exploration; Komunikasi – Communication; Aplikasi – Application; Penilaian – Assessment), was developed from 2012 and implemented for Primary 1 in all primary schools from 2015. Resources developed in this package include the text book, activity book, teacher’s guide, big books, small readers, picture cards, flash cards, a game kit and Information and Communication Technology (ICT) resources. The development of the CEKAP package is continuous until 2020. This paper will look at a model incorporated in the development of the teaching materials in the new Malay Language Curriculum for Primary Schools and the rationale for each phase of development to ensure that the resources meet the needs of every pupil in the teaching and learning of Malay Language in the primary schools. This paper will also focus on the preliminary findings of the effectiveness of the model based on the feedback given by members of the working and steering committees. These members are academicians and educators who were appointed by the Ministry of Education to provide professional input on the soundness of pedagogical approach proposed in the revised syllabus and to make recommendations on the content of the new instructional materials. Quantitative data is derived from the interviews held with these members to gather their input on the model. Preliminary findings showed that the members provided positive feedback on the model and that the comprehensive process has helped to develop good and effective instructional materials for the schools. Some recommendations were also gathered from the interview sessions. This research hopes to provide useful information to those involved in the planning of materials development for teaching and learning.

Keywords: Malay language, materials development, model, primary school

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Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

Procedia PDF Downloads 135

Authors: Oyuna Weina

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This study examines how musicians use visual and zoological metaphors for singing technique and voice quality in a genre of traditional music called urtiin duu (‘long song’) in Alshaa, Inner Mongolia, China. Previous studies have discussed melodic contour in Mongol music, but little study of the intersection of singing technique, visual and zoological metaphors has yet been undertaken. The purpose of this study is to address this lack by analysing urtiin duu itself, traditional pedagogy and performances, all of which have been inspired and are assessed by reference to nature and mobile pastoral herding practices. This study investigates the visual and zoological metaphors related to urtiin duu especially colour, the shape of the circle and animals in the Mongol community. Urtiin duu singing is associated with certain colours in song texts, in selection of repertoire and in the status of singers. Musicians also use colour to describe timbre. These colours in turn reference worship of nature, religions, and daily practices of most Mongols in Alshaa. Moreover, voice quality and singing technique are often related to the animals not only in song text but also in the approach to breathing and to melodic contour. Additionally, the concept of boronhoi (‘the shape of circle’), not only is applied to the melodic contour but also to the voice quality and singing technique. These three factors illustrate the connections among nature, spiritual world and everyday herding life of Mongols. These different connections provide evidence of multi-layered meanings. In contemporary Alshaa, urtiin duu singers received Western musical training from the city and returned to their homelands to perform urtiin duu. In doing so, they are also trying to reconnect with the history, nature and spiritual world in order to achieve their ideal sound. Within a multicultural society, singers negotiate amongst themselves, and with ethnic groups, audiences and government officials. The power of the metaphor therefore assists and reconnects the strength of regional identity and ethnic identity in Alshaa.

Keywords: Alshaa, urtiin duu, visual, zoological metaphors

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Authors: Abraham Addo-Bediako, Sophy Nukeri, Tebatso Mmako

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Many freshwater ecosystems have been subjected to prolonged and cumulative pollution as a result of human activities such as mining, agricultural, industrial and human settlements in their catchments. The objective of this study was to investigate spatial variability of heavy metal pollution of sediments and possible sources of pollutants in two streams of the Olifants River System, South Africa. Stream sediments were collected and analysed for Arsenic (As), Cadmium (Cd), Chromium (Cr), Copper (Cu), Lead (Pb), Nickel (Ni) and Zinc (Zn) concentrations using inductively coupled plasma-mass mass spectrometry (ICP-MS). In both rivers, As, Cd, Cu, Pb and Zn fell within the concentration ranges recommended by CCME and ANZECC, while the concentrations of Cr and Ni exceeded the standards; the results indicated that Cr and Ni in the sediments originated from human activities and not from natural geological background. The index of geo-accumulation (Igeo) was used to assess the degree of pollution. The results of the geo-accumulation index evaluation showed that Cr and Ni were present in the sediments of the rivers at moderately to extremely polluted levels, while As, Cd, Cu, Pb and Zn existed at unpolluted to moderately polluted levels. Generally, heavy metal concentrations increased along the gradient in the rivers. The high concentrations of Cr and Ni in both rivers are of great concern, as previously these two rivers were classified to be supplying the Olifants River with water of good quality. There is a critical need, therefore to monitor heavy metal concentrations and distributions, as well as a comprehensive plan to prevent health risks, especially those communities still reliant on untreated water from the rivers, as sediment pollution may pose a risk of secondary water pollution under sediment disturbance and/or changes in the geo-chemistry of sediments.

Keywords: geo-accumulation index, heavy metals, sediment pollution, water quality

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Authors: Shikhar Shrivastava, Varun Khare

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Background: We are confronted by a society that is becoming more complex, more mobile, and more dysfunctional. Teen pregnancy, suicide, elopement, and the perusal of dangerous drugs have become commonplace. In addition, children do not settle their disputes as they once did. Guns and knives are quotidian. Therefore, it has been an exigent to have a "Juvenile Code" that would provide specific substantive and procedural rules for juveniles in the justice system. However, until the twentieth century, there was little difference between how the justice system treated adults and children. Age was considered only in terms of appropriate punishment and juveniles were eligible for the same punishment as adults. Findings: The increased prevalence and legislative support for specialized courts, Juvenile Justice Boards, including juvenile drug, mental health and truancy court programs, as well as diversion programs and evidence-based approaches into the fabric of juvenile justice are just a few examples of recent advances. In India, various measures were taken to prosecute young offenders who committed violent crimes as adults. But it was argued that equating juveniles with adult criminals was neither scientifically correct nor normatively defensible. It would defeat the very purpose of the justice system. Methodology and Conclusion: This paper attempts to bring forth the results of analytical and descriptive research that examined changing trends in juvenile justice legislation. It covers the investigative and inspective practices of police, the various administrative agencies who have roles in implementing the legislation, the courts, and the detention centers. In this paper we shall discuss about how the juvenile justice system is the dumping ground for many of a youths’ problem. The changing notions of justice, from retributive to restorative and rehabilitative shall be discussed. A comparative study of the Juvenile act in India and that of the U.S has been discussed. Specific social institutions and forces that explain juvenile delinquency are identified. In addition, various influences on juvenile delinquency are noted, such as families, schools, peer groups and communities. The text concludes by addressing socialization, deterrence, imprisonments, alternatives, restitution and preventions.

Keywords: juvenile, justice system, retributive, rehabilitative, delinquency

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Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

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In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

Procedia PDF Downloads 214

Authors: Mehena Fedoul

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This paper examines the intersection of race, gender, and disability through a Critical disability race theory and black feminist disability perspective in Keah Brown's memoir, "The Pretty One." The background of the study highlights the significance of intersectionality in understanding the multifaceted experiences of individuals who navigate multiple marginalized identities. The study contributes to the underrepresented field of disability studies from Critical race and black feminist perspectives, shedding light on the unique challenges and resilience of black disabled women. The study employs a qualitative analysis of Keah Brown's memoir as a primary text. Drawing on intersectionality theory and black feminist disability scholarship, the analysis focuses on how Brown's memoir illuminates the ways in which her race, gender, and disability intersect and shape her lived experiences. The analysis reveals how Brown's memoir challenges traditional notions of disability, beauty, and empowerment through the unapologetic celebration of her blackness, femaleness, and disability. The major findings of the study indicate that Brown's memoir provides a powerful narrative of the complexity, uniqueness and richness of the lived experiences of black disabled women. It demonstrates how the intersectionality of race, gender, and disability shapes Brown's identity, body image, relationships, and societal interactions. The paper also highlights how Brown's memoir emphasizes the importance of inclusivity and intersectionality in understanding and addressing the challenges faced by black disabled women. In conclusion, this study offers a critical analysis of the intersection of race, gender, and disability in Keah Brown's memoir, "The Pretty One," from a black feminist disability perspective. It contributes to the growing body of literature that recognizes the significance of intersectionality in understanding the experiences of marginalized individuals in the disability community. The study underscores the need for more inclusive and intersectional perspectives in disability studies and advocates for greater recognition of the voices and experiences of black disabled women in academic and societal discourse.

Keywords: disability studies, intersectionality, black feminism, Keah Brown

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Mir Md Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soils contaminated with metals, e.g., copper (Cu), zinc (Zn) and nickel (Ni) are one of the main global environmental problems. Zn is an important element for plant growth, but excess levels may become a threat to plant survival. Soils polluted with metals may also pose risks and hazards to human health. Afforestation based on short rotation Salix crops may be a good solution for the reduction of metals toxicity levels in the soil and in ecosystem restoration of severely polluted sites. In a greenhouse experiment, plant growth and zinc (Zn) uptake by four Salix cultivars grown in Zn contaminated soils collected from a mining area in Finland were tested to assess their suitability for phytoextraction. The sequential extraction technique and inductively coupled plasma‒mass spectrometry (ICP–MS) were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The cultivars displayed resistance to heavily polluted soils throughout the whole experiment. After uptake, the total mean Zn concentrations ranged from 776 to 1823 mg kg⁻¹. The average uptake percentage of Zn across all cultivars and treatments ranged from 97 to 223%. Lime and wood ash addition showed a significant effect on plant dry biomass growth and metal uptake percentage of Zn in most of the cultivars. The results revealed that Salix cultivars have the potential to accumulate and take up significant amounts of Zn. Ecological restoration of polluted soils could be environmentally favorable in conjunction with economically profitable practices, such as forestry and bioenergy production. As such, the utilization of Salix for phytoextraction and bioenergy purposes is of considerable interest.

Keywords: lime, phytoextraction, Salix, wood ash, zinc

Procedia PDF Downloads 134