Search results for: contextual meaning extraction

Authors: Ezzeldin M. T. Ali

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Arguably viewers hardly benefit from screen subtitles due to the inconsistency between scenarios and their subtitles. Research in this area will provide an understanding of the association between these scenarios and subtitles via context. It attempts to eliminate the inconsistency existing between contexts and screen subtitles providing insights into the problem. Specifically, the study aims at examining the extent to which the understanding of screen subtitles largely depends on the force of linguistic and situational contexts. This is because the context is assumed to have a powerful effect on the interpretation of the source text. Both descriptive and experimental methods were adopted for data collection. These included a test and paper-pencil-questionnaires where participants provided their impressions about the role of context in eliminating interpretation problems of screen subtitles. Participants developed a good background about screen subtitles watching films. Results showed that context forms a powerful element in understanding screen subtitles. Results also revealed that communicative translation fits well screen translation boosting the contextual meaning. The association of context and communicative translation makes subtitles globally more economical and intelligible. Context forms a central element for film language to be intelligible.

Keywords: communicative translation, context, scenario, powerful, intellgible

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Authors: Khaled Khaladi, Rafika Bibi, Hind Mokrane, Boubekeur Nadjemi

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Sorghum (Sorghum bicolor (L.) Moench) is an important cereal crop grown in the semi-arid tropics of Africa and Asia due to its drought tolerance. Sorghum grain has protein content varying from 6 to 18%, with an average of 11%, Sorghum proteins can be broadly classified into prolamin and non-prolamin proteins. Kafirins, the major storage proteins, are classified as prolamins, and as such, they contain high levels of proline and glutamine and are soluble in non-polar solvents such as aqueous alcohols. Kafirins account for 77 to 82% of the protein in the endosperm, whereas non-prolamin proteins (namely, albumins, globulins, and glutelins) make up about 30% of the proteins. To optimize the extraction of sorghum proteins, several variables were examined: detergent type and concentration, reducing agent type and concentration, and buffer pH and concentration. Samples were quantified and characterized by RP-HPLC.

Keywords: sorghum, protein extraction, detergent, food science

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

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In this paper, we propose a generic model of user profile integrating several elements that may positively impact the research process. We exploit the classical behavior of users and integrate a delimitation process of their research activities into several research sessions enriched with contextual and temporal information, which allows reflecting the current interests of these users in every period of time and infer data freshness. We argue that the annotation of resources gives more transparency on users' needs. It also strengthens social links among resources and users, and can so increase the scope of the user profile. Based on this idea, we integrate the social tagging practice in order to exploit the social users' behavior to enrich their profiles. These profiles are then integrated into a recommendation system in order to predict the interesting personalized items of users allowing to assist them in their researches and further enrich their profiles. In this recommendation, we provide users new research experiences.

Keywords: user profiles, topical ontology, contextual information, folksonomies, tags' clusters, data freshness, association rules, data recommendation

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Sharifa Alshahrani

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Comics is a multimodal text wherein meaning is created by taking in all modes of expression at once. It uses two different semiotic modes, the verbal and the visual modes, together to make meaning and these different semiotic modes can be socially and culturally shaped to give meaning. Therefore, comics translation cannot treat comics as a monomodal text by translating only the verbal mode inside or outside the speech balloons as the cultural differences are encoded in the visual mode as well. Due to the development of the internet and editing software, comics translation is not anymore confined to the publishing houses and official translation as scanlation, or the fan translation took the initiative in translating comics for being emotionally attracted to the culture and genre. Scanlation is carried out by volunteering fans who translate out of passion. However, quality is one of the debatable issues relating to scanlation and fan translation. This study will investigate how the dynamic multimodal relationship in comics is exploited and interpreted in the translation by exploring the translation strategies and procedures adopted by the publishing houses and scanlation in interpreting comics into Arabic using three analytical frameworks; cultural references model, multimodal relation model and translation strategies and procedures models.

Keywords: comics, multimodality, translation, scanlation

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Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

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With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

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Authors: Judyta Pawliszko

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The study draws on the theoretical framework of translanguaging. It investigates translanguaging patterns and how meaning-making processes among bilingual children in preschool are affected by using two different languages, 8 months of observation and 200 hours of vocal recordings of children (3-6 years old) provide data on bilingual children’s linguistic repertoire why children translanguage, and how they achieve understanding with the strategic use of the two languages. The data gathered point to translanguaging as a practice that maximizes meaning-making processes among preschool bilingual children.

Keywords: translanguaging, bilingualism, preschool, polish-english bilingual children

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Authors: Deependra Prasad Sarraf, Ashish Shrestha, Mehul Rajesh Jaisani, Gajendra Prasad Rauniar

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Background: Honey is the worlds’ oldest known wound dressing. Its wound healing properties are not fully established till today. Concerns about antibiotic resistance, and a renewed interest in natural remedies have prompted the resurgence in the antimicrobial and wound healing properties of Honey. Evidence from animal studies and some trials has suggested that honey may accelerate wound healing in burns, infected wounds and open wounds. None of these reports have documented the effect of honey on the healing of socket after tooth extraction. Therefore, the present experimental study was planned to evaluate the efficacy of honey on the healing of socket after tooth extraction in rabbits. Materials and Methods: An experimental study was conducted in six New Zealand White rabbits. Extraction of first premolar tooth on both sides of the lower jaw was done under anesthesia produced by Ketamine and Xylazine followed by application of honey on one socket (test group) and normal saline (control group) in the opposite socket. The intervention was continued for two more days. On the 7th day, the biopsy was taken from the extraction site, and histopathological examination was done. Student’s t-test was used for comparison between the groups and differences were considered to be statistically significant at p-value less than 0.05. Results: There was a significant difference between control group and test group in terms of fibroblast proliferation (p = 0.0019) and bony trabeculae formation (p=0.0003). Inflammatory cells were also observed in both groups, and it was not significant (p=1.0). Overlying epithelium was hyperplastic in both the groups. Conclusion: The study showed that local application of honey promoted the rapid healing process particularly by increasing fibroblast proliferation and bony trabeculae.

Keywords: honey, extraction wound, Nepal, healing

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Authors: Teerapon Pirom, Ura Pancharoen

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Amoxicillin is an antibiotic which is widely used to treat various infections in both human beings and animals. However, when amoxicillin is released into the environment, it is a major problem. Amoxicillin causes bacterial resistance to these drugs and failure of treatment with antibiotics. Liquid membrane is of great interest as a promising method for the separation and recovery of the target ions from aqueous solutions due to the use of carriers for the transport mechanism, resulting in highly selectivity and rapid transportation of the desired metal ions. The simultaneous processes of extraction and stripping in a single unit operation of liquid membrane system are very interesting. Therefore, it is practical to apply liquid membrane, particularly the HFSLM for industrial applications as HFSLM is proved to be a separation process with lower capital and operating costs, low energy and extractant with long life time, high selectivity and high fluxes compared with solid membranes. It is a simple design amenable to scaling up for industrial applications. The extraction and recovery for (Amoxicillin) through the hollow fiber supported liquid membrane (HFSLM) using aliquat336 as a carrier were explored with the experimental data. The important variables affecting on transport of amoxicillin viz. extractant concentration and operating time were investigated. The highest AMOX- extraction percentages of 85.35 and Amoxicillin stripping of 80.04 were achieved with the best condition at 6 mmol/L [aliquat336] and operating time 100 min. The extraction reaction order (n) and the extraction reaction rate constant (kf) were found to be 1.00 and 0.0344 min-1, respectively.

Keywords: aliquat336, amoxicillin, HFSLM, kinetic

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Authors: Cunyu Zhang

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Through literature review about studies related to tense, it is found that there exist disagreements on the definition and existence of Chinese tense. Influenced by some researches on English language which regard tense as a grammatical category based on the verbal inflections of English, some Chinese researchers claim that there is no tense in Chinese language as there are no verbal inflections involved. Meanwhile, other Chinese researchers hold that Chinese still has tense although its verbs are non-inflectional based on the fact that Chinese lexical expressions can imply temporal meaning. We assume that the reasons for the above disagreements in terms of Chinese tense lie in the fact that all the previous studies prefer to view language “from the below” which means expressions of tense are the core part of these studies. However, there are about 6,000 languages with distinct expressions all over the world. Hence, if the language studies only concentrate on expressions, it must become more difficult to understand the nature of language. By contrast, functions of languages are similar; otherwise, the human beings could not communicate with each other. Therefore, we believe that it is necessary for us to have a theoretical study on Chinese tense within the framework of SFL which holds that language is a system where meaning is the core part while form is just the realization of meaning. In addition, SFL is a general linguistic providing a universal framework for languages all over the world. Therefore, based on Systemic Functional Linguistics, the paper firstly redefines tense as a deictic semantic category for describing the speaker’s temporal location of processes and relevant temporal relations. With reference to this definition, this study explores the meaning system of tense. It is proposed that tense expresses four kinds of meaning, namely interpersonal, experiential, logical and textual meanings. From the interpersonal angle, tense helps to exchange temporal information between the speaker and the listener, and the temporal information refers to the anchoring of a concerned process in the past, present or future by the speaker. From the experiential angle, tense plays a role in the temporal locating of material, mental, relational, existential, behavioral and verbal processes by the speaker. From the logical angle, tense denotes the temporal relations at the two levels of clause and clause complex, and such relations fall into simultaneity, anteriority and posteriority. From the textual angle, tense refers to the temporal relations at the level of text, and the temporal relations in question concern linear serial relations and synchronous serial relations.

Keywords: Chinese, meaning system, Systemic Functional Linguistics, tense

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Authors: Freyedon Ahmadi

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Corporate citizenship is considered as one of the most discussed topics in the developed countries, in which a citizen considers a Corporate just like a usual citizen with every civil right as respectful for corporate as for actual citizens, and in return citizens expect that corporate would pay a reciprocal respect to them. The current study’s purpose is to identify the impact of the current state of corporate citizenship along effective factors on its condition on industrial producing units, in order to find an accession plane for corporate citizenship development. In this study corporate citizenship is studied in four dimensions like legal corporate, economical corporate, ethical corporate and voluntary corporate. Moreover, effective factors’ impact on corporate citizenship is explored based on threefold dimensional model: behavioral, structural, and content factors, as well. In this study, 50 corporate of Food industry and of petrochemical industry, along with 200 selected individuals from directors’ board on Tehran province’s scale with stratified random sampling method, are chosen as actuarial sample. If based on functional goal and compilation methods, the present study is a description of correlation type; questionnaire is used for accumulation of initial Data. For Instrument Validity expert’s opinion is used and structural equations and its reliability is qualified by using Cronbach Alpha. The results of this study indicate that close to 70 percent of under survey corporate have not a good condition in corporate citizenship. And all of structural factors, behavioral factors, contextual factors, have a great deal of impression and impact on the advent corporate citizenship behavior in the producing Units. Among the behavioral factors, social responsibility; among structural factors, organic structure and human centered orientation, medium size, high organizational capacity; and among the contextual factors, the clientele’s positive viewpoints toward corporate had the utmost importance in impression on under survey Producing units.

Keywords: corporate citizenship, structural factors, behavioral factors, contextual factors, producing units

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Authors: M. A. Marlow, R. Sørly, H. K. Kaatrakoski

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Social work practice produces and circulates dominant narratives of young women in residential care. These stories are characterised by negative descriptions and hopelessness while dismissing the capabilities of narrative practice. This paper gives an account of how young women with histories in residential care can resist the dominant narratives. The analysis is based on a study of five young women aged 17 to 26 years old with different backgrounds and experiences with Norwegian residential care. The meaning of the context is analysed based on two interviews that were completed and one that was cancelled in the field. The contextual narrative analysis was oriented around the understanding of stories as performances and provided insight into a possible future storytelling practice in social work. The first author’s field notes are included as part of the data material in the analysis and provide a picture of important knowledge development related to stories and the value of being able to tell one’s own experiences. Faced with the dominant narratives that define young women with negative experiences with residential care, we provide a more contextualised understanding of storytelling as a possibility for positive change. To allow young women to create new stories from their lives, we, as both social workers and researchers, must be aware of what kinds of stories we relate to our own practices.

Keywords: context analysis, narrative research, rejection, residential care, social work practice

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Authors: Nidal F. Shilbayeh, Remah W. Al-Khatib, Sameer A. Nooh

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Arabic offline handwriting recognition systems are considered as one of the most challenging topics. Arabic Handwritten Numeral Strings are used to automate systems that deal with numbers such as postal code, banking account numbers and numbers on car plates. Segmentation of connected numerals is the main bottleneck in the handwritten numeral recognition system.  This is in turn can increase the speed and efficiency of the recognition system. In this paper, we proposed algorithms for automatic segmentation and feature extraction of Arabic handwritten numeral strings based on Watershed approach. The algorithms have been designed and implemented to achieve the main goal of segmenting and extracting the string of numeral digits written by hand especially in a courtesy amount of bank checks. The segmentation algorithm partitions the string into multiple regions that can be associated with the properties of one or more criteria. The numeral extraction algorithm extracts the numeral string digits into separated individual digit. Both algorithms for segmentation and feature extraction have been tested successfully and efficiently for all types of numerals.

Keywords: handwritten numerals, segmentation, courtesy amount, feature extraction, numeral recognition

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: D. Pugazhendhi

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The ancient Greeks were forerunners in many fields than other societies. So, the Greeks were well connected with all the countries which were well developed during that time through trade route. In this connection, trading of goods from the ancient Greece to Tamil Nadu which is presently in India, though they are geographically far away, played an important role. In that way, the word and the goods related with kos and kare got exchanged between these two societies. So, it is necessary to compare the phonology and the morphological occurrences of these words that are found common both in the ancient Greek and Tamil literatures of the contemporary period. The results show that there were many words derived from the root kos with the basic meaning of ‘arrange’ in the ancient Greek language, but this is not the case in the usage of the word kare. In the ancient Tamil literature, the word ‘kos’ does not have any root and also had rare occurrences. But it was just the opposite in the case of the word ‘kare’. One of all the meanings of the word, which was derived from the root ‘kos’ in ancient Greek literature, is related with costly ornaments. This meaning seems to have close resemblance with the usage of word ‘kos’ in ancient Tamil literature. Also, the meaning of the word ‘kare’ in ancient Tamil literature is related with spices whereas, in the ancient Greek literature, its meaning is related to that of the cooking of meat using spices. Hence, the similarity seen in the meanings of these words ‘kos’ and ‘kare’ in both these languages provides lead for further study. More than that, the ancient literary resources which are available in both these languages ensure the export and import of gold and spices from the ancient Greek land to Tamil land.

Keywords: arrange, kare, Kos, ornament, Tamil

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Mingjun Xu, Man Pun Wan

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This study proposed an effective smoke control strategy for the large flat space with a low ceiling to achieve the requirement of perpetual tenability. For the large flat space with a low ceiling, the depth of the smoke reservoir is very shallow, and it is difficult to perpetually constrain the smoke within a limited space. A series of numerical tests were conducted to determine the smoke strategy. A zonal design i.e., the fire zone and two adjacent zones was proposed and validated to be effective in controlling smoke. Once a fire happens in a compartment space, the Engineered Smoke Control (ESC) system will be activated in three zones i.e., the fire zone, in which the fire happened, and two adjacent zones. The smoke can be perpetually constrained within the three smoke zones. To further improve the extraction efficiency, sequential activation of the ESC system within the 3 zones turned out to be more efficient than simultaneous activation. Additionally, the proposed zonal and sequential extraction design can reduce the mechanical extraction flow rate by up to 40.7 % as compared to the conventional method, which is much more economical than that of the conventional method.

Keywords: performance-based design, perpetual tenability, smoke control, fire plume

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Authors: Cristina Bahón Arnaiz

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Many Asian languages, such as Korean and Japanese, are well-known for their wide use of sound symbolic words or ideophones. This is a very particular characteristic which enriches its lexicon hugely. Ideophones are a class of sound symbolic words that utilize sound symbolism to express aspects, states, emotions, or conditions that can be experienced through the senses, such as shape, color, smell, action or movement. Ideophones have very particular characteristics in terms of sound symbolism and morphology, which distinguish them from other words. The phonological characteristics of ideophones are vowel ablaut or vowel gradation and consonant mutation. In the case of Korean, there are light vowels and dark vowels. Depending on the type of vowel that is used, the meaning will slightly change. Consonant mutation, also known as consonant ablaut, contributes to the level of intensity, emphasis, and volume of an expression. In addition to these phonological characteristics, there is one main morphological singularity, which is reduplication and it carries the meaning of continuity, repetition, intensity, emphasis, and plurality. All these characteristics play an important role in both linguistics and literature as they enhance the meaning of what is trying to be expressed with incredible semantic detail, expressiveness, and rhythm. The following study will analyze the ideophones used in a single paragraph of a Korean novel, which add incredible yet subtle detail to the meaning of the words, and advance the expressiveness and rhythm of the text. The results from analyzing one paragraph from a novel, after presenting the phonological and morphological characteristics of Korean ideophones, will evidence the important role that ideophones play in literature. 

Keywords: ideophones, mimetic words, phonomimes, phenomimes, psychomimes, sound symbolism

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Authors: Marina Stramarkou, Sofia Papadaki, Konstantina Kyriakopoulou, Magdalini Krokida

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Nowadays, microalgae represent the diverse branch of microorganism that is used not only in fish farming, but also in food, cosmetics, pharmaceuticals and biofuel production as they can produce a wide range of unique functional ingredients. In the present work, a remarkable microalga Chlorella vulgaris (CV) was selected as a raw material for the recovery of multifunctional extracts. First of all, the drying of raw biomass was examined with freeze-drying showing the best behavior. Ultrasonic-assisted extraction (UAE) using different solvents was applied under the specific optimized conditions. In case of raw biomass, ethanol was the suitable solvent, whereas on dried samples water performed better. The total carotenoid, β-carotene, chlorophyll and protein content in the raw materials, extracts and extraction residues was determined using UV-Vis spectrometry. The microalgae biomass and the extracts were evaluated regarding their antiradical activity using the DPPH method.

Keywords: antioxidant activity, pigments, proteins, ultrasound assisted extraction

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: A. Abdi, A. Barari, A. Hojatollah Nikbakht, Khosro Ebrahim

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Aim: The purpose of the current study was to investigate the effect of a high intensity treadmill running training (8 weeks) with or without aqueous extraction of Crataegus pentagyna on heart and plasma LDH and CK. Design: Thirty-two Wistar male rats (4-6 weeks old, 125-135 gr weight) were used. Animals were randomly assigned into training (n = 16) and control (n = 16) groups and further divided into saline-control (SC, n = 8), saline-training (ST, n = 8), red Crataegus pentagyna extraction -control (CPEC, n = 8), and red Crataegus pentagyna extraction -training (CPET, n = 8) groups. Training groups have performed a high-intensity running program 34 m/min on 0% grade, 60 min/day, 5 days/week) on a motor-driven treadmill for 8 weeks. Animals were fed orally with Crataegus extraction and saline solution (500mg/kg body weight/or 10ml/kg body weight) for last six weeks. Seventy- two hours after the last training session, rats were sacrificed; plasma and heart were excised and immediately frozen in liquid nitrogen. LDH and CK levels were measured by colorimetric method. Statistical analysis was performed using a one way analysis of variance and Tukey test. Significance was accepted at P = 0.05. Results: Result showed that consumption crataegus lowers LDH and CK in heart and plasma. Also the heart LDH and CK were lower in the CPET compared to the ST, while plasma LDH and CK in CPET was higher than the ST. The results of ANOVA showed that the due high-intensity exercise and consumption crataegus, there are significant differences between levels of hearth LDH (P < 0/001), plasma (P < 0/006) and hearth (P < 0/001) CK. Conclusion: It appears that high-intensity exercise led to increased tissue damage and inflammatory factors in plasma. In other hand, consumption aqueous extraction of Red Crataegus maybe inhibits these factors and prevents muscle and heart damage.

Keywords: LDH, CK, crataegus, intensity

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Authors: Park Jin Hee

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The purpose of this research is to analyze the meaning and essence of stress experiences school counselors experience while providing counseling. For this research, interviews were conducted with ten school counselors and analyze the interview findings by using phenomenological method of Colaizzi. As for the conclusion in this research, several of types of emotions and mindset of school counselors were examined, and the positive and negative effects of such emotions and mindset on counseling process were shown.

Keywords: counseling stress experience, meaning, school counselors, phenomenological study

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Authors: Ine Huybrechts, Anja Declercq, Emily Verté, Peter Raeymaeckers, Sibyl Anthierens

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Goal-oriented care is a concept gaining increased interest as an approach to go towards more coordinated and integrated primary care. It places patients’ personal life goals at the core of health care support, hereby shifting the focus from “what’s the matter with this patient” to “what matters to this patient.” In Flanders/Belgium, various primary care providers, health and social care organizations and governmental bodies have picked up this concept and have initiated actions to facilitate this approach. The implementation of goal-oriented care not only happens on the micro-level, but it also requires efforts on the meso- and macro-level. Within implementation research, there is a growing recognition that the context in which an intervention takes place strongly relates to its implementation outcomes. However, when investigating contextual variables, the external context and its impact on implementation processes is often overlooked. This study aims to explore how we can better identify and understand the external context and how it relates to the mechanism of change within the implementation process of goal-oriented care in Flanders/Belgium. Results can be used to support and guide initiatives to introduce innovative approaches such as goal-oriented care inside an organization or in the broader primary care landscape. We have conducted qualitative research, performing in-depth interviews with n=23 respondents who have affinity with the implementation of goal-oriented care within their professional function. This lead to in-depth insights from a wide range of actors, with meso-level and/or macro-level perspectives on the implementation of goal-oriented care. This means that we have interviewed actors that are not only involved with initiatives to implement goal-oriented care, but also actors that actively give form to the external context in which goal-oriented care is implemented. Data were collected using a semi-structured interview guide, audio recorded, and analyzed first inductively and then deductively using various theories and concepts that derive from organizational research. Our preliminary findings suggest t Our findings can contribute to further define actions needed for sustainable implementation of goal-oriented primary care. It gives insights in the dynamics between contextual variables and implementation efforts, hereby indicating towards those contextual variables that can be further shaped to facilitate the implementation of an innovation such as goal-oriented care. hat organizational theories can help understand the mechanism of change of implementation processes with a macro-level perspective. Institutional theories, contingency theories, resources dependency theories and others can expose the mechanism of change for an innovation such as goal-oriented care. Our findings can contribute to further define actions needed for sustainable implementation of goal-oriented primary care. It gives insights in the dynamics between contextual variables and implementation efforts, hereby indicating towards those contextual variables that can be further shaped to facilitate the implementation of an innovation such as goal-oriented care.

Keywords: goal-oriented care, implementation processes, organizational theories, person-centered care, implementation research

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Authors: Mariam Shah

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The way the human mind interprets and comprehends the world it occupies has long been a topic of discussion amongst philosophers and phenomenologists. This paper will focus predominantly on the ideologies espoused by the phenomenologist Alfred Schutz and will investigate how we attribute meaning to an event through the process of typification, and the production and usage of ‘types' and ‘stereotypes.' This paper will then discuss how subjective ideologies innate within us result in unique and subjective decision outcomes, based on a phenomenologically influenced theoretical framework which will illustrate how we form ‘types’ in order to ‘typecast’ and form judgements of everything and everyone we experience. The framework used will be founded in theory espoused by Alfred Schutz, and will review the different types of knowledge we rely on innately to inform our judgements, the relevance we attribute to the information which we acquire, and how we consciously and unconsciously apply this framework to everyday situations. An assessment will then be made of the potential impact that these subjective meaning structures can present when dispensing justice in criminal courts. This paper will investigate how these subjective meaning structures can influence our consciousness on both a conscious and unconscious level, and how this could potentially result in bias judicial outcomes due to negative ‘types’ or ‘stereotypes.' This paper will ultimately illustrate that we unconsciously and unreflexively use pre-formed types and stereotypes to inform our judgements and give meaning to what we have just experienced.

Keywords: Alfred Schutz, criminal courts, decision making, judicial decision making, phenomenology, Schutzian stereotypes, types, typification

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Gamith Mendis

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Even though the doctors are knowledgeable, there's a gap between knowing and being ethical. This is a barrier to establish an ethical doctor-patient relationship. Current health system has oriented in a way that gives a meaning to both the doctor and the patient through intermediate entities. For the doctor, the meaning of the doctor-patient relationship is given through the financial benefits, promotions, and social status. For the patient, the meaning is given through curing of the disease. It is obvious that both are independent entities between the doctor and the patient. As the philosophers like Husserl and Heidegger have pointed out, our subjective world will give the immediate meaningfulness to us. We should seek this immediate meaningfulness of the doctor-patient relationship. The present research has used the existential methodology as guided self-reflections on the lived experiences of a doctor and his students. In this approach, two important aspects have been understood. The first is, establishing the fact that being ethical is itself giving meaningfulness to the doctor’s being without any mediate entities. Simply, it is enjoying being an honest being. The second is by being-with-the-patient while treating the disease; both the doctor and the patient can enjoy the meaningfulness of their human relationship. The medical students and the doctors should focus on this meaningfulness. For that, this discussion should be actively incorporated into the medical curriculum with programs of practical guidance to medical students and should be discussed in patient-care reviews in the health setting within a satisfactory framework.

Keywords: doctor-patient relationship, medical education, medical ethics, medical humanities, qualitative health research

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Authors: Amesh P, Suneesh A S, Venkatesan K A

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The magnetic solid-phase extraction is a relatively new method among the other solid-phase extraction techniques for the separating of metal ions from aqueous solutions, such as mine water and groundwater, contaminated wastes, etc. However, the bare magnetic particles (Fe3O4) exhibit poor selectivity due to the absence of target-specific functional groups for sequestering the metal ions. The selectivity of these magnetic particles can be remarkably improved by covalently tethering the task-specific ligands on magnetic surfaces. The magnetic particles offer a number of advantages such as quick phase separation aided by the external magnetic field. As a result, the solid adsorbent can be prepared with the particle size ranging from a few micrometers to the nanometer, which again offers the advantages such as enhanced kinetics of extraction, higher extraction capacity, etc. Conventionally, the magnetite (Fe3O4) particles were prepared by the hydrolysis and co-precipitation of ferrous and ferric salts in aqueous ammonia solution. Since the covalent linking of task-specific functionalities on Fe3O4 was difficult, and it is also susceptible to redox reaction in the presence of acid or alkali, it is necessary to modify the surface of Fe3O4 by silica coating. This silica coating is usually carried out by hydrolysis and condensation of tetraethyl orthosilicate over the surface of magnetite to yield a thin layer of silica-coated magnetite particles. Since the silica-coated magnetite particles amenable for further surface modification, it can be reacted with task-specific functional groups to obtain the functionalized magnetic particles. The surface area exhibited by such magnetic particles usually falls in the range of 50 to 150 m2.g-1, which offer advantage such as quick phase separation, as compared to the other solid-phase extraction systems. In addition, the magnetic (Fe3O4) particles covalently linked on mesoporous silica matrix (MCM-41) and task-specific ligands offer further advantages in terms of extraction kinetics, high stability, longer reusable cycles, and metal extraction capacity, due to the large surface area, ample porosity and enhanced number of functional groups per unit area on these adsorbents. In view of this, the present paper deals with the synthesis of uranium specific diethylenetriamine ligand (DETA) ligand anchored on silica-coated magnetite (Fe-DETA) as well as on magnetic mesoporous silica (MCM-Fe-DETA) and studies on the extraction of uranium from aqueous solution spiked with uranium to mimic the mine water or groundwater contaminated with uranium. The synthesized solid-phase adsorbents were characterized by FT-IR, Raman, TG-DTA, XRD, and SEM. The extraction behavior of uranium on the solid-phase was studied under several conditions like the effect of pH, initial concentration of uranium, rate of extraction and its variation with pH and initial concentration of uranium, effect of interference ions like CO32-, Na+, Fe+2, Ni+2, and Cr+3, etc. The maximum extraction capacity of 233 mg.g-1 was obtained for Fe-DETA, and a huge capacity of 1047 mg.g-1 was obtained for MCM-Fe-DETA. The mechanism of extraction, speciation of uranium, extraction studies, reusability, and the other results obtained in the present study suggests Fe-DETA and MCM-Fe-DETA are the potential candidates for the extraction of uranium from mine water, and groundwater.

Keywords: diethylenetriamine, magnetic mesoporous silica, magnetic solid-phase extraction, uranium extraction, wastewater treatment

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Authors: Radek Novotný, Martina Maněnová

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This article presents a summary of reviews on gender differences in perception of information and communication technology (ICT) by pupils in primary education. The article outlines the meaning of ICT in primary education then summarizes different studies of the use of ICT in primary education from the point of view of gender. The article also presents the specific differences of gender in the knowledge of modalities of use of specialized digital tools and the perception and value assigned to ICT, accordingly the article provides insight into the background of gender differences in performance in relation to ICT to determinate the complex meaning of pupils attitudes to the ICT.

Keywords: ICT in primary education, attitudes to ICT, gender differences, gender and ICT

Procedia PDF Downloads 448