Search results for: simultaneous sparse representation

Authors: Alkaben Patel

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The proposed RP-HPLC method is easy, rapid, economical, precise and accurate stability indicating RP-HPLC method for simultaneous estimation of Astorvastatin and Methylcobalamine in their combined dosage form has been developed.The separation was achieved by LC-20 AT C18(250mm*4.6mm*2.6mm)Colum and water (pH 3.5): methanol 70:30 as mobile phase, at a flow rate of 1ml/min. wavelength of this dosage form is 215nm.The drug is related to stress condition of hydrolysis, oxidation, photolysis and thermal degradation.

Keywords: RP- HPLC, atorvastatin, methylcobalamine, method, development, validation

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Authors: Brittany Joi B. Kirsch

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Textbooks carry a crucial role in imparting ideologies that stimulate inclusivity and social diversity. In the Philippines, a law on inclusive education (IE) for differently-abled learners has recently been signed in order to ensure their rights to quality and IE are protected and upheld (Republic Act No. 11650, 2022). With the presence of ableism in textbooks, the promotion of IE may be challenged. A considerable amount of research has been done on disability representation and ableism in foreign countries; however, none, to the extent of the researcher’s knowledge, has been conducted on ableist ideologies in primary education English language textbooks in the Philippines. Hence, this paper aims to investigate the negotiation of ableist ideologies in primary education English language textbooks in the Philippines. Utilizing Fairclough’s (1995) three-dimensional model of critical discourse analysis (CDA) as the framework, six prescribed primary education English language textbooks from different grade levels were analyzed to examine instances of ableism in the texts. To further support the analysis of the study, supplemental data were gathered from the accounts of six public elementary school English language teachers. Findings reveal that the textbooks contain ableist ideologies with a limited representation of differently-abled people; by disclosing them as (1) invisible, (2) equipped with negative abilities, and (3) plagued with delicate health. By identifying ableist ideologies in textbooks, educational institutions and publishers may benefit in assessing and reforming instructional materials to resolve the presence of such ideologies, thereby abiding by the country’s law on IE and strengthening its overall implementation.

Keywords: textbooks, ideologies, inclusive education, critical discourse analysis, ableism

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

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Authors: Nodi Islam

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This paper critically reads Rumi’s poems in The Masnavi (Book One) and the philosophy of master-disciple relationship, as reflected as a medium to attain the higher consciousness in the poems which is considered as spiritual by the Sufi practitioners. This paper further applies the concept of collective consciousness introduced by Durkheim, which stands for a set of beliefs, ideas, moral attitudes that operate as a unifying force in a certain society, in reading Rumi’s poems. According to Sufi philosophy, in order to reach to the beloved who is the Higher Being, a lover has to be a disciple of a master and dedicate himself completely even if it means to give up the earthly desires. When the process is completed, he achieves the divinity which is the utmost happiness to be one with the beloved. As this process is considered spiritual by the Sufi practitioners, this paper suggests that, apart from being spiritual, this is a reflection of collective consciousness also. This process plays a part to construct the collectivity as a means to create masters and disciples. Collective consciousness operates in this particular belief system of Sufis who tend to follow this phenomenon as a rule of obedience and accepts the rule because this is how their particular community proceeds on. This paper offers a view of Rumi’s poems which reflect such relationship and tends to offer a general discussion on the hegemonic approach of the Sufi society especially of the Mevlevi order. Finally, this paper offers a constructive representation of Mevlevi society based upon the idea of spirituality which could be an outcome of psychological and social issues and practices.

Keywords: collective consciousness, divinity, master-disciple relationship, Mevlevi order

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Authors: Rahul Malhotra, Anurag Sharma

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

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Authors: Saveria Capecchi

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In this paper, the results of qualitative content research on postfeminist female representation in contemporary Western media (advertising, television series, films, social media) are presented. Female role models spectacularized in media culture are an important part of the development of social identities and could inspire new generations. Postfeminist cultural texts have given rise to heated debate between gender and media studies scholars. There are those who claim they are commercial products seeking to sell feminism to women, a feminism whose political and subversive role is completely distorted and linked to the commercial interests of the cosmetics, fashion, fitness and cosmetic surgery industries, in which women’s ‘power’ lies mainly in their power to seduce. There are those who consider them feminist manifestos because they represent independent ‘modern women’ free from male control who aspire to achieve professionally and overcome gender stereotypes like that of the ‘housewife-mother’. Major findings of the research show that feminist principles have been gradually absorbed by the cultural industry and adapted to its commercial needs, resulting in the dissemination of contradictory values. On the one hand, in line with feminist arguments, patriarchal ideology is condemned and the concepts of equality and equal opportunity between men and women are promoted. On the other hand, feminist principles and demands are ascribed to individualism, which translates into the slogan: women are free to decide for themselves, even to objectify their own bodies. In particular, it is observed that femvertising trend in media industry is changing female representation moving away from classic stereotypes: the feminine beauty ideal of slenderness, emphasized in the media since the seventies, is ultimately challenged by the ‘curvy’ body model, which is considered to be more inclusive and based on the concept of ‘natural beauty’. Another aspect of change is the ‘anti-romantic’ revolution performed by some heroines, who are not in search of Prince Charming, in television drama and in the film industry. In conclusion, although femvertising tends to simplify and trivialize the concepts characterizing fourth-wave feminism (‘intersectionality’ and ‘inclusion’), it is also a tendency that enables the challenging of media imagery largely based on male viewpoints, interests and desires.

Keywords: feminine beauty ideal, femvertising, gender and media, postfeminism

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Mikyung Bak

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The dokkaebi, a beloved icon of Korean culture, is represented as an elf, goblin, monster, dwarf, or any similar creature in different media, such as animated shows, comics, soap operas, and movies. It is often described as a mythical creature with a horn or horns and long teeth, wearing tiger-skin pants or a grass skirt, and carrying a magic stick. Many Korean researchers agree on the similarity of the image of the Korean dokkaebi with that of the Japanese oni, a view that is regard as negative from an anti-colonial or nationalistic standpoint. They cite such similarity between the two mythical creatures as evidence that Japanese colonialism persists in Korea. The debate on the originality of dokkaebi’s visual representation is an issue that must be addressed urgently. This research demonstrates through a diagram the plurality of interpretations of dokkaebi’s visual representations in what are considered ‘authentic’ images of dokkaebi in Korean art and culture. This diagram presents the opinions of four major groups in the debate, namely, the scholars of Korean literature and folklore, art historians, authors, and artists. It also shows the creation of new dokkaebi visual representations in popular media, including those influenced by the debate. The diagram further proves that dokkaebi’s representations varied, which include the typical persons or invisible characters found in Korean literature, original Korean folk characters in traditional art, and even universal spirit characters. They are also visually represented by completely new creatures as well as oni-based mythical beings and the actual oni itself. The earlier dokkaebi representations were driven by the creation of a national ideology or national cultural paradigm and, thus, were more uniform and protected. In contrast, the more recent representations are influenced by the Korean industrial strategy of ‘cultural economics,’ which is concerned with the international rather than the domestic market. This recent Korean cultural strategy emphasizes diversity and commonality with the global culture rather than originality and locality. It employs traditional cultural resources to construct a global image. Consequently, dokkaebi’s recent representations have become more common and diverse, thereby incorporating even oni’s characteristics. This argument has rendered the grounds of the debate irrelevant. The dokkaebi has been used recently for tourist marketing purposes, particularly in revitalizing interest in regions considered the cradle of various traditional dokkaebi tales. These campaign strategies include the Jeju-do Dokkaebi Park, Koksung Dokkaebi Land, as well as the Taebaek and Sokri-san Dokkaebi Festivals. Almost dokkaebi characters are identical to the Japanese oni in tourist marketing. However, the pursuit for dokkaebi’s authentic visual representation is less interesting and fruitful than the appreciation of the entire spectrum of dokkaebi images that have been created. Thus, scholars and stakeholders must not exclude the possibilities for a variety of potentials within the visual culture. The same sentiment applies to traditional art and craft. This study aims to contribute to a new visualization of the dokkaebi that embraces the possibilities of both folk craft and art, which continue to be uncovered by diverse and careful researchers in a still-developing field.

Keywords: Dokkaebi, post-colonial period, representation, tourist marketing

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Authors: Zhifei Hu, Feng Xia

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In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Christopher Schwarz, Katrin Riegler, Erwin Zinser

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The management of outsourcing relationships between IT service providers and their customers proofs to be a critical issue that has to be stipulated by means of Service Level Agreements (SLAs). Since service requirements differ from customer to customer, SLA content and language structures vary largely, standardized SLA templates may not be used and an automated processing of SLA content is not possible. Hence, SLA management is usually a time-consuming and inefficient manual process. For overcoming these challenges, this paper presents an innovative and ITIL V3-conform approach for automated SLA design and management using controlled natural language in enterprise collaboration portals. The proposed novel concept is based on a self-developed controlled natural language that follows a subject-predicate-object approach to specify well-defined SLA content structures that act as templates for customized contracts and support automated SLA processing. The derived results eventually enable IT service providers to automate several SLA request, approval and negotiation processes by means of workflows and business rules within an enterprise collaboration portal. The illustrated prototypical realization gives evidence of the practical relevance in service-oriented scenarios as well as the high flexibility and adaptability of the presented model. Thus, the prototype enables the automated creation of well defined, customized SLA documents, providing a knowledge representation that is both human understandable and machine processable.

Keywords: automated processing, controlled natural language, knowledge representation, information technology outsourcing, service level management

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Authors: Sahar Rasoulikolamaki

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ISIS (also known as DAASH) is an Islamic fundamentalist group that has been known as a global threat to the whole world for their radicalizing approach and application of online platforms as a tool to portray their activities, to disseminate their ideology, and to commit recruiting activities. This study is an attempt to carry out a critical discourse analysis on the argumentative devices by which ISIS legitimizes or delegitimizes positive or negative constructions of social practices in Dabiq. It tries to shed light on how texts in Dabiq as linguistic elements in the micro level of analysis relate to ISIS’ ideology as the higher-up macro level and in other words, how local structures contributed to the construction and transference of a global structure or ideology and vice versa. Therefore, following the relevant analytical frameworks, the study focuses on both micro-level of analysis of arguments (topoi) and macro-structure of legitimation and delegitimation in Dabiq. This purpose is nailed using the analytical categories and tools provided by Wodak’s Discourse Historical Approach (DHA) such as argumentation strategies (topoi), by which the coded language of legitimation/delegitimation and persuasion as used in Dabiq are explored. The ensuing findings demonstrate that Dabiq rigorously relies on the positive representation of the in-group course of actions and justifying its violence and, at the same time, the negative representation of the out-group behavior through implementing various topoi to achieve its desired outcome, which is the ideological manipulation and powerful self-depiction, as well as the supporter recruitment.

Keywords: argumentation, discourse-historical approach, ideology, legitimation and delegitimation, topoi

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Authors: Amin Khaksar

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The popular music scene is a highly speculative field of cultural production in which eroticism plays an essential role in attracting audiences. The juxtaposition of eroticism and cultural products possibly implies the importance of the representation of cultural values in popular music videos. As with norms in conservative societies, however, there are some types of inequalities, most of which are dominated by institutional inclinations as opposed to socio-cultural inclinations. This paper explores the challenges that increasing structural inequality poses to erotic representations, focusing on Iranian popular music videos. It outlines how eroticism is becoming a leading tool for circumventing institutional inequalities that affect some cultural values. Using the value-based approach, which draws on visual semiotics and content analysis of Iranian popular music videos compared to Western popular music videos, this study contends that the problematic nature of eroticism emerges when sexual representation takes on meaning beyond its commercial purpose. Indeed, erotica has more to say about freedom, social violence, gender discrimination, and, most importantly, values that can be shared and communicated. The concept of eroticism used in this study functions as a shared practice and can be perceived through symbols. Furthermore, the conclusions show that music artists (performers) use eroticism in three ways to represent cultural values: erotic performances, erotic qualities, and erotic narratives. The expected contribution highlights the role that eroticism can play in the encounter with institutional inequality and injustice. Consider a female celebrity whose erotic qualities help her body gain attention.

Keywords: inequality, value- based economics, eroticism, popular music video

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Authors: Itay Harlap

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Over the past decade, LGBT figures have become increasingly visible on Israeli television in its various channels and genres. In recent years, however, the representation of gays on Israeli television has undergone an interesting shift, whereby many television texts feature gay people as fathers. These texts, mostly news items and documentaries, usually present gay parenthood as a positive phenomenon. The question in paper is whether LGBT parenting (in reality and as representation) fated to be part of the homonormativity that characterizes the LGBT community in Israel, or can it be an alternative to the hegemonic discourse? This paper embraces a dialectical position and explores the tension between mainstream and radical, or homonormativity and queer politics in the specific Israeli Jewish context through a textual and discursive reading of a selection of television programs that revolve principally around gay parenting in Israel. The first part of this lecture addresses the cultural and social context that generated these representations, dealing with three key Israeli areas: The fertility cult, the evolution of the LGBT community, and the evolution of local television. The second part offers a queer reading of these ‘positive’ representations (mainly in special reports on the news and programs labeled as ‘documentaries’ by broadcasters) and highlight the possible price of the ‘bear hug’ given by Israeli media to gay parents. The last part focuses on a single case study, the TV serial drama Ima Veabaz, and suggests that this drama exposes the performative aspect of parenting and the connection between ethnicity and fertility, and offers an alternative to normative displays of gay parenting.

Keywords: fatherhood, heteronormativity, Israel, queer theory, television

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Authors: Makhlouf Sandy, Adem Ziad, Taher Fadia, Magnier Sylvie

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The electronic structure of 90ZrS has been investigated using Ab-initio methods based on Complete Active Space Self Consistent Field and Multi-reference Configuration Interaction (CASSCF/MRCI). The number of predicted states has been extended to 14 singlet and 12 triplet lowest-lying states situated below 36000cm-1. The equilibrium energies of these 26 lowest-lying electronic states have been calculated in the 2S+1Λ(±) representation. The potential energy curves have been plotted in function of the inter-nuclear distances in a range of 1.5 to 4.5Å. Spectroscopic constants, permanent electric dipole moments and transition dipole moments between the different electronic states have also been determined. A discrepancy error of utmost 5% for the majority of values shows a good agreement with available experimental data. The ground state is found to be of symmetry X1Σ+ with an equilibrium inter-nuclear distance Re= 2.16Å. However, the (1)3Δ is the closest state to X1Σ+ and is situated at 514 cm-1. To the best of our knowledge, this is the first time that the spin-orbit coupling has been investigated for all the predicted states of ZrS. 52 electronic components in the Ω(±) representation have been predicted. The energies of these components, the spectroscopic constants ωe, ωeχe, βe and the equilibrium inter-nuclear distances have been also obtained. The percentage composition of the Ω state wave-functions in terms of S-Λ states was calculated to identify their corresponding main parents. These (SOC) calculations have determined the shift between (1)3Δ1 and X1Σ+ states and confirmed the ground state type being 1Σ+.

Keywords: CASSCF/MRCI, electronic structure, spin-orbit effect, zirconium monosulfide

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Authors: Valeria Bondarenko

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In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates.

Keywords: fractional Brownian motion, Gausssian processes, approximation, time series, estimation of properties of the model

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Authors: Anurag Sharma, Dinesh Kumar, Rahul Malhotra, Manoj Kumar

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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Authors: Mohsen Maraoui

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In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

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Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

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Authors: Barbara Papp

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Purpose: This article aims to rethink the relationship between the trauma and the choice of professions. By studying a homogenous sample of respondents, it seeks answers to the following question: how did personal losses that were caused by historical upheavals motivate people to enter the helping professions. By becoming helping professionals, the respondents of the survey sought to handle both historical representation and self-representation. How did psychotherapists working in the second half of the 20th century (Kádár-era in Hungary) shape their course of life? How did their family members respond to their choice of career? What forces supported or hindered them? How did they become professional helpers? Methodology: When interviewing 40 psychotherapists, the interviewer used the oral history technique. In-depth interviews were made with a focus on motivation. First, the collected material was examined using traditional content analysis tools: searching for content patterns, applying a word frequency analysis, and identifying the connections between key events and key persons. Second, a narrative psychological content analysis (NarrCat) was made. Findings: Interconnections were established between attachment, family and historical traumas and career choices. The history of the mid-20th-century period was traumatic and full of losses for the families of most of the psychotherapists concerned. Those experiences may have considerably influenced their choice of career. Working as helping therapists, they could get the opportunity to revise their losses. Conclusion: The results revealed core components that play a role in the psychotherapists’ choice of career, and also emphasized the importance of post-traumatic growth.

Keywords: biography, identity, narrative psychological content analysis, psychotherapists, trauma

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Authors: Navdeep Goel, Salvador Gabarda

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Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4x4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4*4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4*4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: chirp signals, image multiplexing, image transformation, linear canonical transform, polynomial approximation

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Authors: Elena Ginghina

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There are two major categories of language acquisition: first and second language acquisition, which distinguish themselves in their learning process and in their ultimate attainment. However, in the case of a bilingual child, one of the languages he grows up with receives gradually the features of a second language. This phenomenon characterizes the successive first language acquisition, when the initial state of the child is already marked by another language. Nevertheless, the dominance of the languages can change throughout the life, if the exposure to language and the quality of the input are better in 2L1. Related to the exposure to language and the quality of the input, there are cases even at the simultaneous bilingualism, where the two languages although learned from birth one, differ from one another at some point. This paper aims to see, what makes a 2L1 to become a second language and under what circumstances can a L2 learner reach a native or a near native speaker level.

Keywords: bilingualism, first language acquisition, native speakers of German, second language acquisition

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Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: Haraz basin, change detection, land-use, satellite data

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Xiaohan Bookman, Xiaoyan Zhu

Abstract:

Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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Authors: Rafika Bibi, Khaled Khaladi, Hind Mokran, Mohamed Salah Boukhechem

Abstract:

A high performance liquid chromatographic method with ultraviolet detection at 264nm was developed and validate for quantitative determination and separation of cefazolin and cefotaxime in urine, the mobile phase consisted of acetonitrile and phosphate buffer pH4,2(15 :85) (v/v) pumped through ODB 250× 4,6 mm, 5um column at a flow rate of 1ml/min, loop of 20ul. In this condition, the validation of this technique showed that it is linear in a range of 0,01 to 10ug/ml with a good correlation coefficient ( R>0,9997), retention time of cefotaxime, cefazolin was 9.0, 10.1 respectively, the statistical evaluation of the method was examined by means of within day (n=6) and day to day (n=5) and was found to be satisfactory with high accuracy and precision.

Keywords: cefazolin, cefotaxime, HPLC, bioscience, biochemistry, pharmaceutical

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

Abstract:

The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: Nicole Merkle, Stefan Zander

Abstract:

Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Seba Mohanty, Jitendra Mahakud

Abstract:

Capital ratio is one of the major indicators of the stability of the commercial banks. Pertinent to its pervasive importance, over the years the regulators, policy makers focus on the maintenance of the particular level of capital ratio to minimize the solvency and liquidation risk. In this context, it is very much important to identify the relationship between capital and risk and find out the factors which determine the capital ratios of commercial banks. The study examines the relationship between capital and risk of the commercial banks operating in India. Other bank specific variables like bank size, deposit, profitability, non-performing assets, bank liquidity, net interest margin, loan loss reserves, deposits variability and regulatory pressure are also considered for the analysis. The period of study is 1997-2015 i.e. the period of post liberalization. To identify the impact of financial crisis and implementation of Basel II on capital ratio, we have divided the whole period into two sub-periods i.e. 1997-2008 and 2008-2015. This study considers all the three types of commercial banks, i.e. public sector, the private sector and foreign banks, which have continuous data for the whole period. The main sources of data are Prowess data base maintained by centre for monitoring Indian economy (CMIE) and Reserve Bank of India publications. We use simultaneous equation model and more specifically Two Stage Least Square method to find out the relationship between capital and risk. From the econometric analysis, we find that capital and risk affect each other simultaneously, and this is consistent across the time period and across the type of banks. Moreover, regulation has a positive significant impact on the ratio of capital to risk-weighted assets, but no significant impact on the banks risk taking behaviour. Our empirical findings also suggest that size has a negative impact on capital and risk, indicating that larger banks increase their capital less than the other banks supported by the too-big-to-fail hypothesis. This study contributes to the existing body of literature by predicting a strong relationship between capital and risk in an emerging economy, where banking sector plays a majority role for financial development. Further this study may be considered as a primary study to find out the macro economic factors which affecting risk and capital in India.

Keywords: capital, commercial bank, risk, simultaneous equation model

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Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

Abstract:

Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Anagha Pavithran Vattamparambil, Niranjana Regimon

Abstract:

Dalit and tribal communities in India have the largest suicide rate; however, the current literature does not reflect this reality. While existing research acknowledges socio-cultural risk factors, it fails to discuss structural issues pertaining to marginalized communities in India. Furthermore, the language is framed in an individualistic manner which denies room for recognizing systemic violence and injustice among causative agents of suicide. We aim to examine the representation of Dalit and tribal identities and their experiences of marginalisation as a contributive factor of suicide, as well as discuss the epistemic injustice involved in its exclusion. Electronic searches of PubMed, PsychInfo, and Web of Science databases will be carried out from inception till January 2023 to conduct a systematic scoping review of peer-reviewed articles; it will include all studies involving psychological autopsy in India. A narrative synthesis will be performed to gain insight into the inclusion of the experiences of Dalits and Tribals, the absence of which indicates a lacking understanding of suicide in India. It is also expected to highlight the alienation of lived experiences and narratives of marginalisation from mainstream discourse on suicide that constitutes epistemic injustice. There is a complex interplay of psychological, socio-cultural, economic, and political factors for suicide in the Indian setting. But, political and systemic issues are often downplayed in suicide etiology, including casteist assault, rape, violence, public humiliation, and discrimination which deserves more research attention.

Keywords: dalits, marginalisation, psychological autopsy, suicide, tribals

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