Search results for: speech emotion classification

Authors: Patricia Sumod

Abstract:

There is a unique movement of fashion that features a trend around secondhand clothing. This is especially observed in the lifestyles of the millennials, where the concept of reusing apparel and accessories is noticeable and, therefore, slowly diminishing the high consumption of fast fashion and generating environmental awareness. This paper will focus on how this clothing trend influences and engages consumers in buying secondhand clothing and creating fashionable looks simultaneously. To further examine the millennials’ motivation towards consumption and using secondhand fashion, a concept as a trendsetter, this paper will take a closer look at their idea of concern for the environment. Considering second-hand clothing is a sustainable consumption practice, it will investigate the role of social influencers, trendsetters, and millennials in overall fashion consumption in this context. This study aims to understand how secondhand clothing and millennials differ from other consumers regarding the perception of fast-depleting natural resources, price sensitivity, vintage attachments, and psychographics. Secondly, the paper will also present the connection of emotion between millennials and secondhand clothing that may not be necessarily purchased but received. This study will reflect on the already identified influences in increased purchase behavior and an uncharted positive relationship between the consumer and the products. This behavior will further formulate into a habit by consumer segments, creating an expanded market for secondhand clothing. There is no definite indication that fast fashion will cease to exist, but slowing its rapid movement is an attempt to work toward a sustainable future. The conclusion will present possibilities for consumers to engage in C2C online interaction, thereby reinforcing a notable change in consumer behavior and attitude in contradiction to today’s extreme consumerism and willingness to be adaptable to a minimalist way of life. Fashion brands will then begin a new forecast to actively accommodate the new millennial concept of fashion that will advertise more concern than insatiability. The research will be with literature from various authors, insights provided by researchers on this new wave of consumers, and a qualitative approach with face-to-face interviews with a sample group who are in the practice of secondhand clothing consumption.

Keywords: second-hand clothing, millennials, sustainability, consumption practice, fashion environment.

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

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Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo

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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.

Keywords: digital terrain models, hydrology tools, strahler method, stream classification

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Authors: P. P. L. Kwan, D. K. S. Chan

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Organizations are constantly changing in today’s business environment. Research findings have revealed that overcoming resistance and getting employees ready for change is a crucial driver for organizational change success. Thus, change adaptability has become a more prominent selection criterion used in many organizations. Although change readiness could be situation-specific, employees’ personality, emotion, and cognition should also be crucial factors in shaping their readiness. However, relatively little research has focused on the roles of individual characteristics in organizational changes. The present study examines the relations between individual characteristics and change readiness with the aim to validate a model, which proposes three types of individual attributes as antecedents to change readiness. The three attributes considered are trait cynicism, positive affectivity, and personal valence covering personality, emotional, and cognitive aspects respectively. The model also hypothesizes that relations between the three antecedents and change readiness will be moderated by a positive mental resource known as psychological capital (PsyCap), which consists of hope, optimism, efficacy and resilience; and a learning culture within the organization. We are currently collecting data from a targeted sample size of 300 Hong Kong employees. Specifically, participants complete a questionnaire which was designed to measure their perceived change efficacy in response to three scenarios commonly happened in the workplace (i.e., business acquisition, team restructuring, and information system change) as a measure of change readiness, as well as the aforementioned individual characteristics. Preliminary analysis provides some support to the hypotheses. That is, employees who are less cynical in personality and more positive in their cognition and affectivity particularly welcome the potential changes in their organizations. Further data collection and analyses are continuously carried out for a more definitive conclusion. Our findings will shed light on employee selection; and on how strengthening positive psychological resources and promoting the culture of learning organization among employees may enhance the chance to succeed for organizations undergoing change.

Keywords: learning organization, psychological capital, readiness for change, employee selection

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Annie Devault

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Mindfulness-based interventions (MBI) can be beneficial for the well-being of children. MBIs offered for children in contexts of vulnerability (poverty, neglect) report positive results in terms of emotion regulation and cognitive flexibility. Anxiety is a common issue for children living in a vulnerable context. It has a negative impact on children’s attention span, emotional regulation and self-esteem. The MBI (12 weeks) associated with this research has been developed for a total of 30 children suffering from anxiety (7 to 9 years old) and receiving services from a community center over the last seven years. The first objective is to describe in details the content of the mindfulness-based intervention. The second purpose is to document what helps and what hinders the practice of mindfulness for children living in a context of vulnerability. A special attention will be given to the importance of the way that the intervention is offered and the principles that are followed by the practitioners. Perceived effects of the intervention on children were collected through an individual semi-structured interview with each child at the end of the program. Parents were also interviewed to have their point of view on the effect of their children’s participation in the group. Anxiety was measure with the Beck youth pre-post and at follow up (2 months). Qualitative analysis of the interviews with children showed that most of them mentioned that the program helped them become calmer, more confident, less scared and more able to deal with difficult emotions. Almost all of them reported having used the material provided to them to practice at home. This result has been confirmed by parents. They reported that their child had gained confidence and were better at verbalizing emotions. Children also grew calmer, even though all anxiety was not gone. They would have liked more material to practice at home. The quantitative instrument used to measure anxiety did not corroborate the qualitative interviews about anxiety. Discussion will question the use of this questionnaire for children who have important cognitive limitations. Discussion will also report the importance of the personalized contact with children, along with other consideration, to enhance the adherence of children and parents. The MBI seems to have benefited children in different ways, which is corroborated by most parents. Since the sample was limited, we will need to continue documenting its effects with more children and parents. The major strength of this research is to have reported the subjective perspectives of children on their experience of mindfulness.

Keywords: anxiety, mindfulness, children, best practices

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Authors: Kamel Laidi, Khelifa Benmansour, Ouahid Bouchhida

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Neural networks-based approach for 2-cells serial converter has been developed and implemented. The approach is based on a behavioural description of the different operating modes of the converter. Each operating mode represents a well-defined configuration, and for which is matched an operating zone satisfying given invariance conditions, depending on the capacitors' voltages and the load current of the converter. For each mode, a control vector whose components are the control signals to be applied to the converter switches has been associated. Therefore, the problem is reduced to a classification task of the different operating modes of the converter. The artificial neural nets-based approach, which constitutes a powerful tool for this kind of task, has been adopted and implemented. The application to a 2-cells chopper has allowed ensuring efficient and robust control of the load current and a high capacitors voltages balancing.

Keywords: neural nets, control, multicellular converters, 2-cells chopper

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Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

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Authors: Oludare Olupemi Ezekiel

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This research examines the rhythmic structure of Sakara music by tracing its roots and analyzing the various rhythmic patterns of this neo-traditional genre, as well as the contributions of the major exponents and contemporary practitioners, using these as a model for understanding and establishing African rhythms. Biography of the major exponents and contemporary practitioners, interviews and participant observational methods were used to elicit information. Samples of the genre which were chosen at random were transcribed, notated and analyzed for academic use and documentation. The research affirmed that rhythms such as the Hemiola, Cross-rhythm, Clave or Bell rhythm, Percussive, Speech and Melodic rhythm and other relevant rhythmic theories were prevalent and applicable to Sakara music, while making important contributions to musical scholarship through its analysis of the music. The analysis and discussions carried out in the research pointed towards a conclusion that the Yoruba musicians are guided by some preconceptions and sound musical considerations in making their rhythmic patterns, used as compositional techniques and not mere incidental occurrence. These rhythmic patterns, with its consequential socio-cultural connotations, enhance musical values and national identity in Nigeria. The study concludes by recommending that musicologists need to carry out more research into this and other neo-traditional genres in order to advance the globalisation of African music.

Keywords: compositional techniques, globalisation, identity, neo-traditional, rhythmic theory, Sakara music

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Taylor La Carriere

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“What I had madly possessed was not she, but my own creation, another, fanciful Lolita perhaps, more real than Lolita; overlapping, encasing he and having no will, no consciousness indeed, no life of her own,” Vladimir Nabokov writes in his seminal work, Lolita. Throughout Nabokov’s novel, the eponymous character is rendered nonexistent through unreliable narrator Humbert Humbert’s impenetrable narrative, infused with lyrical rationalization. Instead, Lolita is “safely solipsised,” as Humbert muses, solidifying the potential for the erasure of Lolita’s agency and identity. In this literary work, Lolita’s voice is reduced to a nearly invisible presence, only seen through the eyes of her captor. However, in Stanley Kubrick’s film adaptation of Lolita (1962), the “nymphet,” as Nabokov coins, reemerges with a voice of her own, fueled by a lyric impulse, that displaces Humbert’s first-person narration. The lyric, as defined by Catherine Ing, is the voice of the invisible; it is also characterized by performance, the concentrated utterance of individual emotion, and the appearance of spontaneity. The novel’s lyricism is largely in the service of Humbert’s “seductive” voice, while the film reorients it more to Lolita’s subjectivity. Through a close analysis of Kubrick’s cinematic techniques, this paper examines the emergence and translation of Lolita’s voice in contrast with Humbert’s attempts to silence her in Nabokov’s Lolita, hypothesizing that Kubrick translates Lolita’s presence into a visual and aural voice with lyrical attributes, exemplified through the establishment of an altered power dynamic, Sue Lyon’s transformative performance as the titular character, Nelson Riddle and Bob Harris’ musical score, and the omission of Humbert’s first-person point-of-view. In doing so, the film reclaims Lolita’s agency by taking instances of Lolita’s voice in the novel as depicted in the last half of the work and expanding upon them in a way only cinematic depictions could allow. The results of this study suggest that Lolita’s voice in Kubrick’s adaptation functions without disrupting the lyricism present in Nabokov’s source text, materializing through the actions, expressions, and performance of Sue Lyon in the film. This voice, fueled by a lyric impulse of its own, refutes the silence bestowed upon the titular character and enables its ultimate reclamation upon the silver screen.

Keywords: cinema, adaptation, Lolita, lyric voice

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Chikae Isobe, Toshihiko Souma, Yoshiya Furukawa

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In Japan, an organization is sometimes asked for responsibility and apology toward the organization for the annoying behavior of employees, even though the behavior is not relevant to the organization. Our studies have repeatedly shown that it is important for organizational evaluation to organization propose compensatory behavior for such annoying behavior, even though the behavior is not relevant to the organization. In this study, it was examined how such an organizational response (apology) was likely to evaluate by members of the organization who were not related to the annoying behavior. Three independent variables were manipulated that is organization emotion (guilt and shame), compensation (proposal or not), and the relation between organization and the annoying behavior (relate or not). And the effects of organizational identity (high and low) were also examined. We conducted an online survey for 240 participants through a crowdsourcing company. Participants were asked to imagine a situation in which an incident in which some people in your company did not return an important document that they borrowed privately (vs. at work) became the topic of discussion, and the company responded. For the analysis,189 data (111 males and 78 females, mean age = 40.6) were selected. The results of ANOVA of 2 by2 on organizational appraisal, perceived organizational responsibility, and so on were conducted. Organization appraisal by members was also higher when the organization proposed compensatory behavior. In addition, when the annoying behavior was related to their work (than no related), for those who were high in organization identity (than low), organization appraisal was high. The interaction between relatedness and organizational identity was significant. Differences in relatedness between the organization and annoying behavior were significant in those with low organizational identity but not in those with high organizational identity. When the organization stated not taking compensatory action, members were more likely to perceive the organization as responsible for the annoying behavior. However, the interaction results indicated this tendency was limited to when the annoying behavior was not related to the organization. Furthermore, it tended to be perceived as responsible for the organization when the organization made a statement that felt shame for the annoying behavior not related to the organization and would compensate for the annoying behavior. These results indicate that even members of the organization do not consider the organization's compensatory actions to be unjustified. In addition, because those with high organizational identity perceived the organization to be responsible when it showed strong remorse (shame and compensation), they would be a tendency to make judgments that are consistent with organizational judgments. It would be considered that the Japanese have the norm that even if the organization is not at fault for a member's disruptive behavior, it should respond to it.

Keywords: appraisal for organization, annoying behavior, group shame and guilt, compensation, organizational apologies

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Authors: Vesna Pungercar, Florian Musso

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Identifying materials that can substitute rare or expensive natural resources is one of the key challenges for improving resource efficiency in the building sector. With a growing world population and rising living standards, more and more salt is produced as waste through seawater desalination and potash mining processes. Unfortunately, most of the salt is directly disposed of into nature, where it causes environmental pollution. On the other hand, salt is affordable, is used therapeutically in various respiratory treatments, and can store humidity and heat. It was, therefore, necessary to determine salt materials already in use in building construction and their hygrothermal properties. This research aims to identify salt materials from different scientific branches and historically, to investigate their properties and prioritize the most promising salt materials for indoor applications in a thermal envelope. This was realized through literature review and classification of salt materials into three groups (raw salt materials, composite salt materials, and processed salt materials). The outcome of this research shows that salt has already been used as a building material for centuries and has a potential for future applications due to its hygrothermal properties in a thermal envelope.

Keywords: salt, building material, hygrothermal properties, environment

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Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

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Authors: Levent Basayigit, Mert Dedeoglu, Fadime Ozogul

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In this study, an application was carried out to determine the Volcanic Soils by using remote sensing.  The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models.

Keywords: Landsat 7, soil moisture index, temperature models, volcanic soils

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Authors: Wahab Ali, Oyebade K. Oyedotun, Adnan Khashman

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Breast cancer remains a threat to the woman’s world in view of survival rates, it early diagnosis and mortality statistics. So far, research has shown that many survivors of breast cancer cases are in the ones with early diagnosis. Breast cancer is usually categorized into stages which indicates its severity and corresponding survival rates for patients. Investigations show that the farther into the stages before diagnosis the lesser the chance of survival; hence the early diagnosis of breast cancer becomes imperative, and consequently the application of novel technologies to achieving this. Over the year, mammograms have used in the diagnosis of breast cancer, but the inconclusive deductions made from such scans lead to either false negative cases where cancer patients may be left untreated or false positive where unnecessary biopsies are carried out. This paper presents the application of artificial neural networks in the prediction of severity of breast tumour (whether benign or malignant) using mammography reports and other factors that are related to breast cancer.

Keywords: breast cancer, intelligent classification, neural networks, mammography

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Authors: Muhammad Farooq

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The present article explores the woman's consent as a paramount element in contracting a Muslim marriage. Also, whether permission of the wali (guardian) is a condition per se for a valid nikah (marriage deed) in the eye of law and Sharia. The researcher attempts to treat it through the related issues, inter alia; the marriage guardian, the women's legal capacity to give consent whether she is a virgin or nonvirgin and how that consent is to be given or may be understood. Does her laugh, tears or salience needs a legal interpretation as well as other female manifestations of emotion explained by the Muslim jurists? The silence of Muslim Family Law Ordinance 1961 (hereafter; MFLO 1961) in this regard and the likely reasons behind such silence is also inquired in brief. Germane to the theme, the various cases in which the true notion of woman's consent is interpreted by courts in Pakistan are also examined. In order to address the issue in hand, it is proposed to provide a brief overview of a few contemporary writers' opinions in which the real place of woman's consent in Muslim marriage is highlighted. Key to the idea of young Muslim woman's marriage, the doctrine of kafa'a (equality or suitability) between the man and woman is argued here to be grounded in the patriarchal and social norms. It is, therefore, concluded that such concept was the result of analogical reasoning and has less importance in the present time. As such it is not a valid factor in current scenarios to validate or invalidate marital bonds. A standard qualitative convention is used for this research. Among primary and secondary sources; for examples, Qur'an, Sunnah, Books, Scholarly articles, texts of law and case law is used to point out the researcher's view. In summation, the article is concluded with a bold statement that a young woman being a party to the contract, is absolutely entitled to 'full and free' consent for the Muslim marriage contract. It is the woman, an indispensable partaker and her consent (not the guardian' permission) that does validate or invalidate the said agreement in the eye of contemporary personal law and in Sharia.

Keywords: consent of woman, ejab (declaration), Nikah (marriage agreement), qabol (acceptance), sui juris (of age; independent), wali (guardian), wilayah (guardianship)

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Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

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Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Chialing Chang

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Language and culture are critical foundations of international mobility. However, the students who are limited to the local environment may affect their learning outcome and global perspective. Video Conferencing has been proven an economical way for students as a medium to communicate with international students around the world. In Taiwan, the National Development Commission advocated the development of bilingual national policies in 2030 to enhance national competitiveness and foster English proficiency and fully launched bilingual activation of the education system. Globalization is closely related to the development of Taiwan's education. Therefore, the teacher conducted an integrated lesson through interdisciplinary learning. This study aims to investigate how the teacher helps develop students' global and language core competencies in the international education class. The methodology comprises four stages, which are lesson planning, class observation, learning data collection, and speech analysis. The Grice's Conversational Maxims are adopted to analyze the students' conversation in the video conferencing course. It is the action research from the teacher's reflection on approaches to developing students' language learning skills. The study lays the foundation for mastering the teacher's international education professional development and improving teachers' teaching quality and teaching effectiveness as a reference for teachers' future instruction.

Keywords: international education, language learning, Grice's conversational maxims, video conferencing course

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Authors: Yao-Hong Tsai

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This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: authentication, iris recognition, adaboost, local binary pattern

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Authors: Yulin Zhang, Kaixi Dong, Guozhen Zhao

Abstract:

Background: Different levels of life satisfaction are associated with some individual differences. Understanding the mechanism between them will help to enhance an individual’s well-being. On the one hand, traditional personality such as extraversion has been considered as the most stable and effective factor in predicting life satisfaction to the author’s best knowledge. On the other, individual emotional difference, such as alexithymia (difficulties identifying and describing one’s own feelings), is also closely related to life satisfaction. With the development of positive psychology, positive personalities such as virtues attract wide attention. And according to the broaden-and-build theory, social connectivity may mediate between emotion and life satisfaction. Therefore, the current study aims to explore the mediating role of social connectivity in the effect of positive personality and alexithymia on life satisfaction. Method: This study was conducted with 318 healthy Chinese college students whose age range from 18 to 30. Positive personality (including interpersonal, vitality, and cautiousness) was measured by the Chinese version of Values in Action Inventory of Strengths (VIA-IS). Alexithymia was measured by the Toronto Alexithymia Scale (TAS), and life satisfaction was measured by Satisfaction With Life Scale (SWLS). And social connectivity was measured by six items which have been used in previous studies. Each scale showed high reliability and validity. The mediating model was examined in Mplus 7.2 within a structural equation modeling (SEM) framework. Findings: The model fitted well and results revealed that both positive personality (95% confidence interval of indirect effect was [0.023, 0.097]) and alexithymia (95% confidence interval of indirect effect was [-0.270, -0.089]) predicted life satisfaction level significantly through social connectivity. Also, only positive personality significantly and directly predicted life satisfaction compared to alexithymia (95% confidence interval of direct effect was [0.109, 0.260]). Conclusion: Alexithymia predicts life satisfaction only through social connectivity, which emphasizes the importance of social bonding in enhancing the well-being of Chinese college students with alexithymia. And the positive personality can predict life satisfaction directly or through social connectivity, which provides implications for enhancing the well-being of Chinese college students by cultivating their virtue and positive psychological quality.

Keywords: alexithymia, life satisfaction, positive personality, social connectivity

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Authors: Omar Nouri, Wafa Mnejja, Fatma Dhouib, Syrine Zouari, Wicem Siala, Ilhem Charfeddine, Afef Khanfir, Leila Farhat, Nejla Fourati, Jamel Daoud

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Purpose and Objective: Intensity modulated radiation (IMRT) technique, associated with induction chemotherapy (IC) and/or concomitant chemotherapy (CC), is actually the recommended treatment modality for nasopharyngeal carcinomas (NPC). The aim of this study was to evaluate the therapeutic results and the patterns of relapse with this treatment protocol. Material and methods: A retrospective monocentric study of 145 patients with NPC treated between June 2016 and July 2021. All patients received IMRT with integrated simultaneous boost (SIB) of 33 daily fractions at a dose of 69.96 Gy for high-risk volume, 60 Gy for intermediate risk volume and 54 Gy for low-risk volume. The high-risk volume dose was 66.5 Gy in children. Survival analysis was performed according to the Kaplan-Meier method, and the Log-rank test was used to compare factors that may influence survival. Results: Median age was 48 years (11-80) with a sex ratio of 2.9. One hundred-twenty tumors (82.7%) were classified as stages III-IV according to the 2017 UICC TNM classification. Ten patients (6.9%) were metastatic at diagnosis. One hundred-thirty-five patient (93.1%) received IC, 104 of which (77%) were TPF-based (taxanes, cisplatin and 5 fluoro-uracil). One hundred-thirty-eight patient (95.2%) received CC, mostly cisplatin in 134 cases (97%). After a median follow-up of 50 months [22-82], 46 patients (31.7%) had a relapse: 12 (8.2%) experienced local and/or regional relapse after a median of 18 months [6-43], 29 (20%) experienced distant relapse after a median of 9 months [2-24] and 5 patients (3.4%) had both. Thirty-five patients (24.1%) died, including 5 (3.4%) from a cause other than their cancer. Three-year overall survival (OS), cancer specific survival, disease free survival, metastasis free survival and loco-regional free survival were respectively 78.1%, 81.3%, 67.8%, 74.5% and 88.1%. Anatomo-clinic factors predicting OS were age > 50 years (88.7 vs. 70.5%; p=0.004), diabetes history (81.2 vs. 66.7%; p=0.027), UICC N classification (100 vs. 95 vs. 77.5 vs. 68.8% respectively for N0, N1, N2 and N3; p=0.008), the practice of a lymph node biopsy (84.2 vs. 57%; p=0.05), and UICC TNM stages III-IV (93.8 vs. 73.6% respectively for stage I-II vs. III-IV; p=0.044). Therapeutic factors predicting OS were a number of CC courses (less than 4 courses: 65.8 vs. 86%; p=0.03, less than 5 courses: 71.5 vs. 89%; p=0.041), a weight loss > 10% during treatment (84.1 vs. 60.9%; p=0.021) and a total cumulative cisplatin dose, including IC and CC, < 380 mg/m² (64.4 vs. 87.6%; p=0.003). Radiotherapy delay and total duration did not significantly affect OS. No grade 3-4 late side effects were noted in the evaluable 127 patients (87.6%). The most common toxicity was dry mouth which was grade 2 in 47 cases (37%) and grade 1 in 55 cases (43.3%).Conclusion: IMRT for nasopharyngeal carcinoma granted a high loco-regional control rate for patients during the last five years. However, distant relapses remain frequent and conditionate the prognosis. We identified many anatomo-clinic and therapeutic prognosis factors. Therefore, high-risk patients require a more aggressive therapeutic approach, such as radiotherapy dose escalation or adding adjuvant chemotherapy.

Keywords: therapeutic results, prognostic factors, intensity-modulated radiotherapy, nasopharyngeal carcinoma

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Authors: Suteera Pradubwong, Darawan Augsornwan, Pornpen Pathumwiwathana, Benjamas Prathanee, Bowornsilp Chowchuen

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Background: Cleft lip and palate (CLP) congenital anomalies have a high prevalence in the Northeast of Thailand. A care team’s understand of treatment plan would help to guide the family of patients with CLP to achieve the treatment. Objectives: To examine the impact of the empowering volunteer project, established in the northeast Thailand. Materials and Methods: The Empowering Volunteer project was conducted in 2008 under the Tawanchai Royal Granted project. The patients and family’s general information, treatment, the group brainstorming, and satisfaction with the project were analyzed. Results: Participants were 12 children with CLP, their families and five volunteers with CLP; the participating patients were predominantly females and the mean, age was 12.2 years. The treatment comprised of speech training, dental hygiene care, bone graft and orthodontic treatment. Four issues were addressed including: problems in taking care of breast feeding; instructions’ needs for care at birth; difficulty in access information and society impact; and needs in having a network of volunteers. Conclusions: Empowering volunteer is important for holistic care of patients with CLP which provides easy access and multiple channels for patients and their families. It should be developed as part of the self-help and family support group, the development of community based team and comprehensive CLP care program.

Keywords: self-help and family support group, community based model, volunteer, cleft lip-cleft palate

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Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

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Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

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Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

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Authors: Joy Aworookoroh

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Writing is one of the active skills in language learning. Students of English as a foreign language are expected to write efficiently and proficiently in the language; however, there are usually challenges to optimal performance and competence in writing. Errors, on the other hand, in a foreign language learning situation are more positive than negative as they provide the basis for solving the limitations of the students. This paper investigates the situation in the Department of English, Taraba State University Jalingo. Students are administered a descriptive writing test across different levels of study. The target students are multilingual with an L1 of either Kuteb, Hausa or Junkun languages. The essays are accessed to identify the different kinds of errors in them alongside the classification of the order. Errors of correctness, clarity, engagement, and delivery were identified. However, the study identified that the degree of errors reduces alongside the experience and exposure of the students to an EFL classroom.

Keywords: errors, writings, descriptive essay, multilingual

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Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 61